bench: refactor random number generation in stats/base/dists/arcsine

PR-URL: stdlib-js#4798
Reviewed-by: Athan Reines <[email protected]>

Author: anandkaranubc

lib/node_modules/@stdlib/stats/base/dists/arcsine/ctor/benchmark/benchmark.js

@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+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;
@@ -32,16 +33,24 @@ var logcdf = require( './../lib' );
 bench( pkg, function benchmark( b ) {
 	var min;
 	var max;
+	var len;
 	var x;
 	var y;
 	var i;
 
+	len = 100;
+	x = new Float64Array( len );
+	min = new Float64Array( len );
+	max = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = uniform( -10.0, 10.0 );
+		min[ i ] = uniform( -20.0, 0.0 );
+		max[ i ] = uniform( min[ i ], min[ i ] + 40.0 );
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = uniform( -10.0, 10.0 );
-		min = uniform( -20.0, 0.0 );
-		max = uniform( min, min + 40.0 );
-		y = logcdf( x, min, max );
+		y = logcdf( x[ i % len ], min[ i % len ], max[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
@@ -58,18 +67,23 @@ bench( pkg+':factory', function benchmark( b ) {
 	var mylogcdf;
 	var min;
 	var max;
+	var len;
 	var x;
 	var y;
 	var i;
 
 	min = -1.5;
 	max = 1.5;
 	mylogcdf = logcdf.factory( min, max );
+	len = 100;
+	x = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = uniform( -2.0, 0.0 );
+	}
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = uniform( -2.0, 0.0 );
-		y = mylogcdf( x );
+		y = mylogcdf( x[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}

lib/node_modules/@stdlib/stats/base/dists/arcsine/logcdf/benchmark/benchmark.js

@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+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;
@@ -32,16 +33,24 @@ var logpdf = require( './../lib' );
 bench( pkg, function benchmark( b ) {
 	var min;
 	var max;
+	var len;
 	var x;
 	var y;
 	var i;
 
+	len = 100;
+	x = new Float64Array( len );
+	min = new Float64Array( len );
+	max = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = uniform( -10.0, 10.0 );
+		min[ i ] = uniform( -20.0, 0.0 );
+		max[ i ] = uniform( min[ i ], min[ i ] + 40.0 );
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = uniform( -10.0, 10.0 );
-		min = uniform( -20.0, 0.0 );
-		max = uniform( min, min + 40.0 );
-		y = logpdf( x, min, max );
+		y = logpdf( x[ i % len ], min[ i % len ], max[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
@@ -58,18 +67,23 @@ bench( pkg+':factory', function benchmark( b ) {
 	var mylogpdf;
 	var min;
 	var max;
+	var len;
 	var x;
 	var y;
 	var i;
 
 	min = -1.5;
 	max = 1.5;
 	mylogpdf = logpdf.factory( min, max );
+	len = 100;
+	x = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = uniform( -2.0, 0.0 );
+	}
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = uniform( -2.0, 0.0 );
-		y = mylogpdf( x );
+		y = mylogpdf( x[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}

lib/node_modules/@stdlib/stats/base/dists/arcsine/logpdf/benchmark/benchmark.js

@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+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;
@@ -32,14 +33,21 @@ var mean = require( './../lib' );
 bench( pkg, function benchmark( b ) {
 	var min;
 	var max;
+	var len;
 	var y;
 	var i;
 
+	len = 100;
+	min = new Float64Array( len );
+	max = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		min[ i ] = uniform( 0.0, 10.0 );
+		max[ i ] = uniform( min[ i ], min[ i ] + 10.0 );
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		min = uniform( 0.0, 10.0 );
-		max = uniform( min, min + 10.0 );
-		y = mean( min, max );
+		y = mean( min[ i % len ], max[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}

lib/node_modules/@stdlib/stats/base/dists/arcsine/mean/benchmark/benchmark.js

@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+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;
@@ -32,14 +33,21 @@ var median = require( './../lib' );
 bench( pkg, function benchmark( b ) {
 	var min;
 	var max;
+	var len;
 	var y;
 	var i;
 
+	len = 100;
+	min = new Float64Array( len );
+	max = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		min[ i ] = uniform( 0.0, 10.0 );
+		max[ i ] = uniform( min[ i ], min[ i ] + 10.0 );
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		min = uniform( 0.0, 10.0 );
-		max = uniform( min, min + 10.0 );
-		y = median( min, max );
+		y = median( min[ i % len ], max[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}

lib/node_modules/@stdlib/stats/base/dists/arcsine/median/benchmark/benchmark.js

@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+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;
@@ -32,14 +33,21 @@ var mode = require( './../lib' );
 bench( pkg, function benchmark( b ) {
 	var min;
 	var max;
+	var len;
 	var y;
 	var i;
 
+	len = 100;
+	min = new Float64Array( len );
+	max = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		min[ i ] = uniform( 0.0, 10.0 );
+		max[ i ] = uniform( min[ i ], min[ i ] + 10.0 );
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		min = uniform( 0.0, 10.0 );
-		max = uniform( min, min + 10.0 );
-		y = mode( min, max );
+		y = mode( min[ i % len ], max[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}

lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/benchmark.js

@@ -23,7 +23,6 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var Float64Array = require( '@stdlib/array/float64' );
-var randu = require( '@stdlib/random/base/randu' );
 var uniform = require( '@stdlib/random/base/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var tryRequire = require( '@stdlib/utils/try-require' );
@@ -51,7 +50,7 @@ bench( pkg+'::native', opts, function benchmark( b ) {
 	min = new Float64Array( len );
 	max = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		min[ i ] = ( randu()*10.0 );
+		min[ i ] = uniform( 0.0, 10.0 );
 		max[ i ] = uniform( min[ i ], min[ i ] + 10.0 );
 	}
 

lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/benchmark.native.js

@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+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;
@@ -32,16 +33,24 @@ var pdf = require( './../lib' );
 bench( pkg, function benchmark( b ) {
 	var min;
 	var max;
+	var len;
 	var x;
 	var y;
 	var i;
 
+	len = 100;
+	x = new Float64Array( len );
+	min = new Float64Array( len );
+	max = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = uniform( -10.0, 10.0 );
+		min[ i ] = uniform( -20.0, 0.0 );
+		max[ i ] = uniform( min[ i ], min[ i ] + 40.0 );
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = uniform( -10.0, 10.0 );
-		min = uniform( -20.0, 0.0 );
-		max = uniform( min, min + 40.0 );
-		y = pdf( x, min, max );
+		y = pdf( x[ i % len ], min[ i % len ], max[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
@@ -58,18 +67,23 @@ bench( pkg+':factory', function benchmark( b ) {
 	var mypdf;
 	var min;
 	var max;
+	var len;
 	var x;
 	var y;
 	var i;
 
 	min = -1.5;
 	max = 1.5;
 	mypdf = pdf.factory( min, max );
+	len = 100;
+	x = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = uniform( -2.0, 0.0 );
+	}
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = uniform( -2.0, 0.0 );
-		y = mypdf( x );
+		y = mypdf( x[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}

lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/benchmark/benchmark.js

@@ -21,7 +21,7 @@
 // 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;
@@ -33,16 +33,24 @@ var quantile = require( './../lib' );
 bench( pkg, function benchmark( b ) {
 	var min;
 	var max;
+	var len;
 	var p;
 	var y;
 	var i;
 
+	len = 100;
+	p = new Float64Array( len );
+	min = new Float64Array( len );
+	max = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		p[ i ] = uniform( 0.0, 1.0 );
+		min[ i ] = uniform( -20.0, 0.0 );
+		max[ i ] = uniform( min[ i ], min[ i ] + 40.0 );
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		p = randu();
-		min = uniform( -20.0, 0.0 );
-		max = uniform( min, min + 40.0 );
-		y = quantile( p, min, max );
+		y = quantile( p[ i % len ], min[ i % len ], max[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
@@ -59,18 +67,23 @@ bench( pkg+':factory', function benchmark( b ) {
 	var myquantile;
 	var min;
 	var max;
+	var len;
 	var p;
 	var y;
 	var i;
 
 	min = -1.5;
 	max = 1.5;
 	myquantile = quantile.factory( min, max );
+	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' );
 		}