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

PR-URL: stdlib-js#4955

Reviewed-by: Philipp Burckhardt <[email protected]>

Author: anandkaranubc

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

@@ -21,8 +21,9 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var round = require( '@stdlib/math/base/special/round' );
-var randu = require( '@stdlib/random/base/randu' );
+var Float64Array = require( '@stdlib/array/float64' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var discreteUniform = require( '@stdlib/random/base/discrete-uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pkg = require( './../package.json' ).name;
 var cdf = require( './../lib' );
@@ -31,20 +32,29 @@ var cdf = require( './../lib' );
 // MAIN //
 
 bench( pkg, function benchmark( b ) {
+	var len;
 	var N;
 	var K;
 	var n;
 	var x;
 	var y;
 	var i;
 
+	len = 100;
+	x = new Float64Array( len );
+	N = new Float64Array( len );
+	K = new Float64Array( len );
+	n = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = discreteUniform( 1, 50 );
+		N[ i ] = discreteUniform( 1, 100 );
+		K[ i ] = discreteUniform( 1, N[ i ] );
+		n[ i ] = discreteUniform( 1, N[ i ] );
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = round( randu()*50.0 );
-		N = round( randu()*100.0 );
-		K = round( randu()*N );
-		n = round( randu()*N );
-		y = cdf( x, N, K, n );
+		y = cdf( x[ i % len ], N[ i % len ], K[ i % len ], n[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
@@ -59,22 +69,27 @@ bench( pkg, function benchmark( b ) {
 
 bench( pkg+':factory', function benchmark( b ) {
 	var mycdf;
+	var len;
 	var N;
 	var K;
 	var n;
 	var x;
 	var y;
 	var i;
 
-	N = round( randu()*100.0 );
-	K = round( randu()*N );
-	n = round( randu()*N );
+	len = 100;
+	N = discreteUniform( 1, 100 );
+	K = discreteUniform( 1, N );
+	n = discreteUniform( 1, N );
 	mycdf = cdf.factory( N, K, n );
+	x = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = uniform( 0.0, 40.0 );
+	}
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = randu()*40.0;
-		y = mycdf( x );
+		y = mycdf( x[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}