diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/README.md
index 66749944b1fe..c79cd338c809 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/README.md
+++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/README.md
@@ -160,9 +160,9 @@ console.log( v );
## See Also
- [`@stdlib/blas/ext/base/dapxsumkbn`][@stdlib/blas/ext/base/dapxsumkbn]: add a constant to each double-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm.
-- [`@stdlib/blas/ext/base/gapxsum`][@stdlib/blas/ext/base/gapxsum]: add a constant to each strided array element and compute the sum.
+- [`@stdlib/blas/ext/base/gapxsum`][@stdlib/blas/ext/base/gapxsum]: add a scalar constant to each strided array element and compute the sum.
- [`@stdlib/blas/ext/base/gsumkbn`][@stdlib/blas/ext/base/gsumkbn]: calculate the sum of strided array elements using an improved Kahan–Babuška algorithm.
-- [`@stdlib/blas/ext/base/sapxsumkbn`][@stdlib/blas/ext/base/sapxsumkbn]: add a constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm.
+- [`@stdlib/blas/ext/base/sapxsumkbn`][@stdlib/blas/ext/base/sapxsumkbn]: add a scalar constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm.
diff --git a/lib/node_modules/@stdlib/math/base/special/deg2radf/README.md b/lib/node_modules/@stdlib/math/base/special/deg2radf/README.md
index ed76dec7ec2c..de78b118cd3e 100644
--- a/lib/node_modules/@stdlib/math/base/special/deg2radf/README.md
+++ b/lib/node_modules/@stdlib/math/base/special/deg2radf/README.md
@@ -168,6 +168,7 @@ int main( void ) {
## See Also
- [`@stdlib/math/base/special/deg2rad`][@stdlib/math/base/special/deg2rad]: convert an angle from degrees to radians.
+- [`@stdlib/math/base/special/rad2degf`][@stdlib/math/base/special/rad2degf]: convert an angle from radians to degrees (single-precision).
@@ -181,6 +182,8 @@ int main( void ) {
[@stdlib/math/base/special/deg2rad]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/deg2rad
+[@stdlib/math/base/special/rad2degf]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/rad2degf
+
diff --git a/lib/node_modules/@stdlib/stats/base/dists/studentized-range/cdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/studentized-range/cdf/benchmark/benchmark.js
index 7c92ac233f56..41875a03cef5 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/studentized-range/cdf/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/studentized-range/cdf/benchmark/benchmark.js
@@ -21,7 +21,8 @@
// MODULES //
var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var Float64Array = require( '@stdlib/array/float64' );
+var uniform = require( '@stdlib/random/base/uniform' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pkg = require( './../package.json' ).name;
var cdf = require( './../lib' );
@@ -30,18 +31,26 @@ var cdf = require( './../lib' );
// MAIN //
bench( pkg, function benchmark( b ) {
+ var len;
var v;
var r;
var q;
var y;
var i;
+ len = 100;
+ q = new Float64Array( len );
+ r = new Float64Array( len );
+ v = new Float64Array( len );
+ for ( i = 0; i < len; i++ ) {
+ q[ i ] = uniform( 0, 12.0 );
+ r[ i ] = uniform( 2.0, 22.0 );
+ v[ i ] = uniform( 2.0, 22.0 );
+ }
+
b.tic();
for ( i = 0; i < b.iterations; i++ ) {
- q = randu() * 12.0;
- r = ( randu()*20.0 ) + 2.0;
- v = ( randu()*20.0 ) + 2.0;
- y = cdf( q, r, v );
+ y = cdf( q[ i % len ], r[ i % len ], v[ i % len ] );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
@@ -56,6 +65,7 @@ bench( pkg, function benchmark( b ) {
bench( pkg+':factory', function benchmark( b ) {
var mycdf;
+ var len;
var r;
var q;
var v;
@@ -65,11 +75,15 @@ bench( pkg+':factory', function benchmark( b ) {
v = 5.0;
r = 3.0;
mycdf = cdf.factory( v, r );
+ len = 100;
+ q = new Float64Array( len );
+ for ( i = 0; i < len; i++ ) {
+ q[ i ] = uniform( 0, 1.0 );
+ }
b.tic();
for ( i = 0; i < b.iterations; i++ ) {
- q = randu();
- y = mycdf( q );
+ y = mycdf( q[ i % len ] );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/studentized-range/quantile/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/studentized-range/quantile/benchmark/benchmark.js
index c43d8a244383..c8f072792e53 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/studentized-range/quantile/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/studentized-range/quantile/benchmark/benchmark.js
@@ -21,7 +21,8 @@
// MODULES //
var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var Float64Array = require( '@stdlib/array/float64' );
+var uniform = require( '@stdlib/random/base/uniform' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pkg = require( './../package.json' ).name;
var quantile = require( './../lib' );
@@ -30,18 +31,24 @@ var quantile = require( './../lib' );
// MAIN //
bench( pkg, function benchmark( b ) {
+ var len;
var v;
var r;
var p;
var y;
var i;
-
+ len = 100;
+ p = new Float64Array( len );
+ r = new Float64Array( len );
+ v = new Float64Array( len );
+ for ( i = 0; i < len; i++ ) {
+ p[ i ] = uniform( 0.0, 1.0 );
+ r[ i ] = uniform( 2.0, 22.0 );
+ v[ i ] = uniform( 2.0, 22.0 );
+ }
b.tic();
for ( i = 0; i < b.iterations; i++ ) {
- p = randu();
- r = ( randu()*20.0 ) + 2.0;
- v = ( randu()*20.0 ) + 2.0;
- y = quantile( p, r, v );
+ y = quantile( p[ i % len ], r[ i % len ], v[ i % len ] );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
@@ -56,6 +63,7 @@ bench( pkg, function benchmark( b ) {
bench( pkg+':factory', function benchmark( b ) {
var myquantile;
+ var len;
var r;
var p;
var v;
@@ -65,11 +73,14 @@ bench( pkg+':factory', function benchmark( b ) {
v = 5.0;
r = 3.0;
myquantile = quantile.factory( v, r );
-
+ len = 100;
+ p = new Float64Array( len );
+ for ( i = 0; i < len; i++ ) {
+ p[ i ] = uniform( 0.0, 1.0 );
+ }
b.tic();
for ( i = 0; i < b.iterations; i++ ) {
- p = randu();
- y = myquantile( p );
+ y = myquantile( p[ i % len ] );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}