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

PR-URL: stdlib-js#4744
Reviewed-by: Athan Reines <[email protected]>

Author: anandkaranubc

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

@@ -22,8 +22,8 @@
 
 var bench = require( '@stdlib/bench' );
 var Float64Array = require( '@stdlib/array/float64' );
-var uniform = require( '@stdlib/random/array/uniform' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniformArray = require( '@stdlib/random/array/uniform' );
+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' );
@@ -44,9 +44,9 @@ bench( pkg, function benchmark( b ) {
 	min = new Float64Array( len );
 	max = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		x[ i ] = ( randu() * 20.0 ) - 10.0;
-		min[ i ] = ( randu() * 20.0 ) - 20.0;
-		max[ i ] = min[ i ] + ( randu() * 40.0 );
+		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();
@@ -75,7 +75,7 @@ bench( pkg+':factory', function benchmark( b ) {
 	min = -1.5;
 	max = 1.5;
 	mycdf = cdf.factory( min, max );
-	x = uniform( 100, -2.0, 2.0 );
+	x = uniformArray( 100, -2.0, 2.0 );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {

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

@@ -23,7 +23,7 @@
 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' );
 var pkg = require( './../package.json' ).name;
@@ -52,9 +52,9 @@ bench( pkg+'::native', opts, function benchmark( b ) {
 	min = new Float64Array( len );
 	max = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		x[ i ] = ( randu() * 20.0 ) - 10.0;
-		min[ i ] = ( randu() * 20.0 ) - 20.0;
-		max[ i ] = min[ i ] + ( randu() * 40.0 );
+		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();

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

@@ -22,6 +22,7 @@
 
 var bench = require( '@stdlib/bench' );
 var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
 var pkg = require( './../package.json' ).name;
@@ -38,8 +39,8 @@ bench( pkg+'::instantiation', function benchmark( bm ) {
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		a = ( randu() * 10.0 ) + EPS;
-		b = ( randu() * 10.0 ) + a + EPS;
+		a = uniform( EPS, 10.0 );
+		b = uniform( a + EPS, a + 10.0 + EPS );
 		dist = new Arcsine( a, b );
 		if ( !( dist instanceof Arcsine ) ) {
 			bm.fail( 'should return a distribution instance' );
@@ -92,7 +93,7 @@ bench( pkg+'::set:a', function benchmark( bm ) {
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		y = ( 100.0*randu() ) + EPS;
+		y = uniform( EPS, 100.0 + EPS );
 		dist.a = y;
 		if ( dist.a !== y ) {
 			bm.fail( 'should return set value' );
@@ -145,7 +146,7 @@ bench( pkg+'::set:b', function benchmark( bm ) {
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		y = ( 100.0*randu() ) + a + EPS;
+		y = uniform( a + EPS, a + 100.0 + EPS );
 		dist.b = y;
 		if ( dist.b !== y ) {
 			bm.fail( 'should return set value' );
@@ -172,7 +173,7 @@ bench( pkg+':entropy', function benchmark( bm ) {
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.a = ( 100.0*randu() ) + EPS;
+		dist.a = uniform( EPS, 100.0 + EPS );
 		y = dist.entropy;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -199,7 +200,7 @@ bench( pkg+':kurtosis', function benchmark( bm ) {
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.a = ( 100.0*randu() ) + EPS;
+		dist.a = uniform( EPS, 100.0 + EPS );
 		y = dist.kurtosis;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -226,7 +227,7 @@ bench( pkg+':mean', function benchmark( bm ) {
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.a = ( 100.0*randu() ) + EPS;
+		dist.a = uniform( EPS, 100.0 + EPS );
 		y = dist.mean;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -253,7 +254,7 @@ bench( pkg+':median', function benchmark( bm ) {
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.a = ( 100.0*randu() ) + EPS;
+		dist.a = uniform( EPS, 100.0 + EPS );
 		y = dist.median;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -280,7 +281,7 @@ bench( pkg+':mode', function benchmark( bm ) {
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.a = ( 100.0*randu() ) + 1.0 + EPS;
+		dist.a = uniform( 1.0 + EPS, 101.0 + EPS );
 		y = dist.mode;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -307,7 +308,7 @@ bench( pkg+':skewness', function benchmark( bm ) {
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.a = ( 100.0*randu() ) + EPS;
+		dist.a = uniform( EPS, 100.0 + EPS );
 		y = dist.skewness;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -334,7 +335,7 @@ bench( pkg+':stdev', function benchmark( bm ) {
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.a = ( 100.0*randu() ) + EPS;
+		dist.a = uniform( EPS, 100.0 + EPS );
 		y = dist.stdev;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -361,7 +362,7 @@ bench( pkg+':variance', function benchmark( bm ) {
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.a = ( 100.0*randu() ) + EPS;
+		dist.a = uniform( EPS, 100.0 + EPS );
 		y = dist.variance;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );

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

@@ -22,7 +22,7 @@
 
 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 pkg = require( './../package.json' ).name;
 var entropy = require( './../lib' );
@@ -41,8 +41,8 @@ bench( pkg, function benchmark( b ) {
 	min = new Float64Array( len );
 	max = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		min[ i ] = randu() * 20.0;
-		max[ i ] = ( randu() * 20.0 ) + min[ i ];
+		min[ i ] = uniform( 0.0, 20.0 );
+		max[ i ] = uniform( min[ i ], min[ i ] + 20.0 );
 	}
 
 	b.tic();

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

@@ -24,7 +24,7 @@ var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pkg = require( './../package.json' ).name;
 
@@ -50,8 +50,8 @@ bench( pkg+'::native', opts, function benchmark( b ) {
 	min = new Float64Array( len );
 	max = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		min[ i ] = randu() * 20.0;
-		max[ i ] = ( randu() * 20.0 ) + min[ i ];
+		min[ i ] = uniform( 0.0, 20.0 );
+		max[ i ] = uniform( min[ i ], min[ i ] + 20.0 );
 	}
 
 	b.tic();

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

@@ -22,7 +22,7 @@
 
 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 pkg = require( './../package.json' ).name;
 var kurtosis = require( './../lib' );
@@ -41,8 +41,8 @@ bench( pkg, function benchmark( b ) {
 	min = new Float64Array( len );
 	max = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		min[ i ] = randu() * 20.0;
-		max[ i ] = ( randu() * 20.0 ) + min[ i ];
+		min[ i ] = uniform( 0.0, 20.0 );
+		max[ i ] = uniform( min[ i ], min[ i ] + 20.0 );
 	}
 
 	b.tic();

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

@@ -24,7 +24,7 @@ var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pkg = require( './../package.json' ).name;
 
@@ -50,8 +50,8 @@ bench( pkg+'::native', opts, function benchmark( b ) {
 	min = new Float64Array( len );
 	max = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		min[ i ] = randu() * 20.0;
-		max[ i ] = ( randu() * 20.0 ) + min[ i ];
+		min[ i ] = uniform( 0.0, 20.0 );
+		max[ i ] = uniform( min[ i ], min[ i ] + 20.0 );
 	}
 
 	b.tic();

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

@@ -21,7 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pkg = require( './../package.json' ).name;
 var logcdf = require( './../lib' );
@@ -38,9 +38,9 @@ bench( pkg, function benchmark( b ) {
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = ( randu() * 20.0 ) - 10.0;
-		min = ( randu() * 20.0 ) - 20.0;
-		max = min + ( randu() * 40.0 );
+		x = uniform( -10.0, 10.0 );
+		min = uniform( -20.0, 0.0 );
+		max = uniform( min, min + 40.0 );
 		y = logcdf( x, min, max );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
@@ -68,7 +68,7 @@ bench( pkg+':factory', function benchmark( b ) {
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = ( randu()*2.0 ) - 2.0;
+		x = uniform( -2.0, 0.0 );
 		y = mylogcdf( x );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );

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

@@ -21,7 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pkg = require( './../package.json' ).name;
 var logpdf = require( './../lib' );
@@ -38,9 +38,9 @@ bench( pkg, function benchmark( b ) {
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = ( randu() * 20.0 ) - 10.0;
-		min = ( randu() * 20.0 ) - 20.0;
-		max = min + ( randu() * 40.0 );
+		x = uniform( -10.0, 10.0 );
+		min = uniform( -20.0, 0.0 );
+		max = uniform( min, min + 40.0 );
 		y = logpdf( x, min, max );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
@@ -68,7 +68,7 @@ bench( pkg+':factory', function benchmark( b ) {
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = ( randu()*2.0 ) - 2.0;
+		x = uniform( -2.0, 0.0 );
 		y = mylogpdf( x );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );

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

@@ -23,7 +23,7 @@
 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' );
 var pkg = require( './../package.json' ).name;
@@ -52,9 +52,9 @@ bench( pkg+'::native', opts, function benchmark( b ) {
 	min = new Float64Array( len );
 	max = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		x[ i ] = ( randu() * 20.0 ) - 10.0;
-		min[ i ] = ( randu() * 20.0 ) - 20.0;
-		max[ i ] = min[ i ] + ( randu() * 40.0 );
+		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();