From ee5839904290a1be926cd938b20abc003dc38581 Mon Sep 17 00:00:00 2001
From: yuvi-mittal <yuvimittal2004@gmail.com>
Date: Sun, 2 Feb 2025 21:47:32 +0530
Subject: [PATCH] feat : Refactor random number generation in JS benchmarks

---
type: pre_push_report
description: Results of running various checks prior to pushing changes.
report:
  - task: run_javascript_examples
    status: na
  - task: run_c_examples
    status: na
  - task: run_cpp_examples
    status: na
  - task: run_javascript_readme_examples
    status: na
  - task: run_c_benchmarks
    status: na
  - task: run_cpp_benchmarks
    status: na
  - task: run_fortran_benchmarks
    status: na
  - task: run_javascript_benchmarks
    status: na
  - task: run_julia_benchmarks
    status: na
  - task: run_python_benchmarks
    status: na
  - task: run_r_benchmarks
    status: na
  - task: run_javascript_tests
    status: na
---
---
 .../kumaraswamy/ctor/benchmark/benchmark.js   | 388 +++++++++---------
 1 file changed, 194 insertions(+), 194 deletions(-)

diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/ctor/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/ctor/benchmark/benchmark.js
index 558002ea6bd5..5725c6f89a3e 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/ctor/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/ctor/benchmark/benchmark.js
@@ -31,34 +31,34 @@ var Kumaraswamy = require( './../lib' );
 
 // MAIN //
 
-bench( pkg+'::instantiation', function benchmark( b ) {
-	var alpha;
+bench( pkg+'::instantiation', function benchmark( bm ) {
 	var dist;
-	var beta;
 	var len;
+	var a;
+	var b;
 	var i;
 
 	len = 100;
-	alpha = new Float64Array( len );
-	beta = new Float64Array( len );
+	a = new Float64Array( len );
+	b = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		alpha[ i ] = uniform( EPS, 10.0 );
-		beta[ i ] = uniform( EPS, 10.0 );
+		a[ i ] = uniform( EPS, 10.0 );
+		b[ i ] = uniform( EPS, 10.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
-		dist = new Kumaraswamy( alpha[ i % len ], beta[ i % len ] );
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
+		dist = new Kumaraswamy( a[ i % len ], b[ i % len ] );
 		if ( !( dist instanceof Kumaraswamy ) ) {
-			b.fail( 'should return a distribution instance' );
+			bm.fail( 'should return a distribution instance' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( !( dist instanceof Kumaraswamy ) ) {
-		b.fail( 'should return a distribution instance' );
+		bm.fail( 'should return a distribution instance' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
 bench( pkg+'::get:a', function benchmark( bm ) {
@@ -87,36 +87,36 @@ bench( pkg+'::get:a', function benchmark( bm ) {
 	bm.end();
 });
 
-bench( pkg+'::set:alpha', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+'::set:a', function benchmark( bm ) {
 	var dist;
 	var len;
+	var a;
+	var b;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	y = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		y[ i ] = uniform( EPS, 100.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = y[ i % len ];
-		if ( dist.alpha !== y[i % len] ) {
-			b.fail( 'should return set value' );
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
+		dist.a = y[i % len];
+		if ( dist.a !== y[i % len] ) {
+			bm.fail( 'should return set value' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
 bench( pkg+'::get:b', function benchmark( bm ) {
@@ -145,403 +145,403 @@ bench( pkg+'::get:b', function benchmark( bm ) {
 	bm.end();
 });
 
-bench( pkg+'::set:beta', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+'::set:b', function benchmark( bm ) {
 	var dist;
 	var len;
+	var a;
+	var b;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	y = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		y[ i ] = uniform( EPS, 100.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
-		dist.beta = y[ i % len ];
-		if ( dist.beta !== y[i % len ] ) {
-			b.fail( 'should return set value' );
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
+		dist.b = y[i % len];
+		if ( dist.b !== y[i % len] ) {
+			bm.fail( 'should return set value' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
-bench( pkg+':kurtosis', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+':kurtosis', function benchmark( bm ) {
 	var dist;
 	var len;
 	var x;
+	var a;
+	var b;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = uniform( EPS, 100.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
+		dist.a = x[ i % len ];
 		y = dist.kurtosis;
 		if ( isnan( y ) ) {
-			b.fail( 'should not return NaN' );
+			bm.fail( 'should not return NaN' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
-bench( pkg+':mean', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+':mean', function benchmark( bm ) {
 	var dist;
 	var len;
 	var x;
+	var a;
+	var b;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = uniform( EPS, 100.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
+		dist.a = x[ i % len ];
 		y = dist.mean;
 		if ( isnan( y ) ) {
-			b.fail( 'should not return NaN' );
+			bm.fail( 'should not return NaN' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
-bench( pkg+':mode', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+':mode', function benchmark( bm ) {
 	var dist;
 	var len;
 	var x;
+	var a;
+	var b;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = uniform( 1.0 + EPS, 100.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
+		dist.a = x[ i % len ];
 		y = dist.mode;
 		if ( isnan( y ) ) {
-			b.fail( 'should not return NaN' );
+			bm.fail( 'should not return NaN' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
-bench( pkg+':skewness', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+':skewness', function benchmark( bm ) {
 	var dist;
 	var len;
 	var x;
+	var a;
+	var b;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = uniform( EPS, 100.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
+		dist.a = x[ i % len ];
 		y = dist.skewness;
 		if ( isnan( y ) ) {
-			b.fail( 'should not return NaN' );
+			bm.fail( 'should not return NaN' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
-bench( pkg+':stdev', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+':stdev', function benchmark( bm ) {
 	var dist;
 	var len;
 	var x;
+	var a;
+	var b;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = uniform( EPS, 100.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
+		dist.a = x[ i % len ];
 		y = dist.stdev;
 		if ( isnan( y ) ) {
-			b.fail( 'should not return NaN' );
+			bm.fail( 'should not return NaN' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
-bench( pkg+':variance', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+':variance', function benchmark( bm ) {
 	var dist;
 	var len;
 	var x;
+	var a;
+	var b;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = uniform( EPS, 100.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
+		dist.a = x[ i % len ];
 		y = dist.variance;
 		if ( isnan( y ) ) {
-			b.fail( 'should not return NaN' );
+			bm.fail( 'should not return NaN' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
-bench( pkg+':cdf', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+':cdf', function benchmark( bm ) {
 	var dist;
 	var len;
+	var a;
+	var b;
 	var x;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = uniform( 0.0, 1.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
 		y = dist.cdf( x[ i % len ] );
 		if ( isnan( y ) ) {
-			b.fail( 'should not return NaN' );
+			bm.fail( 'should not return NaN' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
-bench( pkg+':logcdf', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+':logcdf', function benchmark( bm ) {
 	var dist;
 	var len;
+	var a;
+	var b;
 	var x;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = uniform( 0.0, 1.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
 		y = dist.logpdf( x[ i % len ] );
 		if ( isnan( y ) ) {
-			b.fail( 'should not return NaN' );
+			bm.fail( 'should not return NaN' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
-bench( pkg+':logpdf', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+':logpdf', function benchmark( bm ) {
 	var dist;
 	var len;
+	var a;
+	var b;
 	var x;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = uniform( 0.0, 1.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
 		y = dist.logpdf( x[ i % len ] );
 		if ( isnan( y ) ) {
-			b.fail( 'should not return NaN' );
+			bm.fail( 'should not return NaN' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
-bench( pkg+':pdf', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+':pdf', function benchmark( bm ) {
 	var dist;
 	var len;
+	var a;
+	var b;
 	var x;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = uniform( 0.0, 1.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
 		y = dist.pdf( x[ i % len ] );
 		if ( isnan( y ) ) {
-			b.fail( 'should not return NaN' );
+			bm.fail( 'should not return NaN' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });
 
-bench( pkg+':quantile', function benchmark( b ) {
-	var alpha;
-	var beta;
+bench( pkg+':quantile', function benchmark( bm ) {
 	var dist;
 	var len;
+	var a;
+	var b;
 	var x;
 	var y;
 	var i;
 
-	alpha = 100.56789;
-	beta = 55.54321;
-	dist = new Kumaraswamy( alpha, beta );
+	a = 100.56789;
+	b = 55.54321;
+	dist = new Kumaraswamy( a, b );
 	len = 100;
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = uniform( 0.0, 1.0 );
 	}
 
-	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
+	bm.tic();
+	for ( i = 0; i < bm.iterations; i++ ) {
 		y = dist.quantile( x[ i % len ] );
 		if ( isnan( y ) ) {
-			b.fail( 'should not return NaN' );
+			bm.fail( 'should not return NaN' );
 		}
 	}
-	b.toc();
+	bm.toc();
 	if ( isnan( y ) ) {
-		b.fail( 'should not return NaN' );
+		bm.fail( 'should not return NaN' );
 	}
-	b.pass( 'benchmark finished' );
-	b.end();
+	bm.pass( 'benchmark finished' );
+	bm.end();
 });