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' ); }