diff --git a/lib/node_modules/@stdlib/stats/base/dnanmskmin/README.md b/lib/node_modules/@stdlib/stats/base/dnanmskmin/README.md
index 1b77cb867a41..548519394f0f 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmskmin/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dnanmskmin/README.md
@@ -18,6 +18,8 @@ limitations under the License.
-->
+
+
# dnanmskmin
> Calculate the minimum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.
@@ -38,7 +40,7 @@ var dnanmskmin = require( '@stdlib/stats/base/dnanmskmin' );
#### dnanmskmin( N, x, strideX, mask, strideMask )
-Computes the minimum value of a double-precision floating-point strided array `x` according to a `mask`, ignoring `NaN` values.
+Computes the minimum value of a double-precision floating-point strided array according to a `mask`, ignoring `NaN` values.
```javascript
var Float64Array = require( '@stdlib/array/float64' );
@@ -55,22 +57,20 @@ The function has the following parameters:
- **N**: number of indexed elements.
- **x**: input [`Float64Array`][@stdlib/array/float64].
-- **strideX**: index increment for `x`.
+- **strideX**: stride length for `x`.
- **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation.
-- **strideMask**: index increment for `mask`.
+- **strideMask**: stride length for `mask`.
-The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the minimum value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the minimum value of every other element in `x`,
```javascript
var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
var x = new Float64Array( [ 1.0, 2.0, 7.0, -2.0, -4.0, 3.0, -5.0, -6.0 ] );
var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
-var N = floor( x.length / 2 );
-var v = dnanmskmin( N, x, 2, mask, 2 );
+var v = dnanmskmin( 4, x, 2, mask, 2 );
// returns -4.0
```
@@ -81,7 +81,6 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t
```javascript
var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
@@ -89,9 +88,7 @@ var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd
var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-var N = floor( x0.length / 2 );
-
-var v = dnanmskmin( N, x1, 2, mask1, 2 );
+var v = dnanmskmin( 4, x1, 2, mask1, 2 );
// returns -2.0
```
@@ -115,18 +112,16 @@ The function has the following additional parameters:
- **offsetX**: starting index for `x`.
- **offsetMask**: starting index for `mask`.
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to calculate the minimum value for every other element in `x` starting from the second element
```javascript
var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
var x = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ] );
var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
-var N = floor( x.length / 2 );
-var v = dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 );
+var v = dnanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 );
// returns -2.0
```
@@ -151,31 +146,22 @@ var v = dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 );
```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
var dnanmskmin = require( '@stdlib/stats/base/dnanmskmin' );
-var mask;
-var x;
-var i;
-
-x = new Float64Array( 10 );
-mask = new Uint8Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
- if ( randu() < 0.2 ) {
- mask[ i ] = 1;
- } else {
- mask[ i ] = 0;
- }
- if ( randu() < 0.1 ) {
- x[ i ] = NaN;
- } else {
- x[ i ] = round( (randu()*100.0) - 50.0 );
+function rand() {
+ if ( bernoulli( 0.8 ) < 1 ) {
+ return NaN;
}
+ return uniform( -50.0, 50.0 );
}
+
+var x = filledarrayBy( 10, 'float64', rand );
console.log( x );
+
+var mask = filledarrayBy( x.length, 'uint8', bernoulli.factory( 0.2 ) );
console.log( mask );
var v = dnanmskmin( x.length, x, 1, mask, 1 );
@@ -186,6 +172,145 @@ console.log( v );
+
+
+* * *
+
+
+
+## C APIs
+
+
+
+
+
+
+
+
+
+
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dnanmskmin.h"
+```
+
+#### stdlib_strided_dnanmskmin( N, \*X, strideX, \*Mask, strideMask )
+
+Computes the minimum value of a double-precision floating-point strided array according to a `mask`, ignoring `NaN` values.
+
+```c
+#include
+
+const double x[] = { 1.0, -2.0, 4.0, 2.0, 0.0/0.0 };
+const uint8_t mask[] = { 0, 0, 1, 0, 0 };
+
+double v = stdlib_strided_dnanmskmin( 5, x, 1, mask, 1 );
+// returns -2.0
+```
+
+The function accepts the following arguments:
+
+- **N**: `[in] CBLAS_INT` number of indexed elements.
+- **X**: `[in] double*` input array.
+- **strideX**: `[in] CBLAS_INT` stride length for `X`.
+- **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation.
+- **strideMask**: `[in] CBLAS_INT` stride length for `Mask`.
+
+```c
+double stdlib_strided_dnanmskmin( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );
+```
+
+#### stdlib_strided_dnanmskmin_ndarray( N, \*X, strideX, offsetX, \*Mask, strideMask, offsetMask )
+
+Computes the minimum value of a double-precision floating-point strided array according to a `mask`, ignoring `NaN` values and using alternative indexing semantics.
+
+```c
+#include
+
+const double x[] = { 1.0, -2.0, 4.0, 2.0, 0.0/0.0 };
+const uint8_t mask[] = { 0, 0, 1, 0, 0 };
+
+double v = stdlib_strided_dnanmskmin_ndarray( 5, x, 1, 0, mask, 1, 0 );
+// returns -2.0
+```
+
+The function accepts the following arguments:
+
+- **N**: `[in] CBLAS_INT` number of indexed elements.
+- **X**: `[in] double*` input array.
+- **strideX**: `[in] CBLAS_INT` stride length for `X`.
+- **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+- **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation.
+- **strideMask**: `[in] CBLAS_INT` stride length for `Mask`.
+- **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`.
+
+```c
+double stdlib_strided_dnanmskmin_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dnanmskmin.h"
+#include
+#include
+
+int main( void ) {
+ // Create a strided array:
+ const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 0.0/0.0, 0.0/0.0 };
+
+ // Create a mask array:
+ const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
+
+ // Specify the number of elements:
+ const int N = 5;
+
+ // Specify the stride lengths:
+ const int strideX = 2;
+ const int strideMask = 2;
+
+ // Compute the minimum value:
+ double v = stdlib_strided_dnanmskmin( N, x, strideX, mask, strideMask );
+
+ // Print the result:
+ printf( "min: %lf\n", v );
+}
+```
+
+
+
+
+
+
+
+
+
+
+
+
+