From c23d929aa6be6304496ef4613285163728efb265 Mon Sep 17 00:00:00 2001
From: hrshya <harshyadav6078@gmail.com>
Date: Tue, 13 Jan 2026 18:45:40 +0530
Subject: [PATCH] bench: update random value generation

---
 .../invgamma/ctor/benchmark/benchmark.js      | 205 +++++++++---------
 1 file changed, 101 insertions(+), 104 deletions(-)

diff --git a/lib/node_modules/@stdlib/stats/base/dists/invgamma/ctor/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/invgamma/ctor/benchmark/benchmark.js
index f284010ffcf3..296ca2b33c8e 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/invgamma/ctor/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/invgamma/ctor/benchmark/benchmark.js
@@ -21,8 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var Float64Array = require( '@stdlib/array/float64' );
-var uniform = require( '@stdlib/random/base/uniform' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
 var pkg = require( './../package.json' ).name;
@@ -35,20 +34,18 @@ bench( pkg+'::instantiation', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var i;
 
-	len = 100;
-	alpha = new Float64Array( len );
-	beta = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		alpha[ i ] = uniform( EPS, 10.0 );
-		beta[ i ] = uniform( EPS, 10.0 );
-	}
+	opts = {
+		'dtype': 'float64'
+	};
+	alpha = uniform( 100, EPS, 10.0, opts );
+	beta = uniform( 100, EPS, 10.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		dist = new InvGamma( alpha[ i % len ], beta[ i % len ] );
+		dist = new InvGamma( alpha[ i % alpha.length ], beta[ i % beta.length ] );
 		if ( !( dist instanceof InvGamma ) ) {
 			b.fail( 'should return a distribution instance' );
 		}
@@ -91,23 +88,23 @@ bench( pkg+'::set:alpha', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	y = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		y[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	y = uniform( 100, EPS, 100.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = y[ i % len ];
-		if ( dist.alpha !== y[ i % len ] ) {
+		dist.alpha = y[ i % y.length ];
+		if ( dist.alpha !== y[ i % y.length ] ) {
 			b.fail( 'should return set value' );
 		}
 	}
@@ -149,23 +146,23 @@ bench( pkg+'::set:beta', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	y = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		y[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	y = uniform( 100, EPS, 100.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		dist.beta = y[ i % len ];
-		if ( dist.beta !== y[ i % len ] ) {
+		dist.beta = y[ i % y.length ];
+		if ( dist.beta !== y[ i % y.length ] ) {
 			b.fail( 'should return set value' );
 		}
 	}
@@ -181,23 +178,23 @@ bench( pkg+':entropy', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var x;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS, 100.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+		dist.alpha = x[ i % x.length ];
 		y = dist.entropy;
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
@@ -215,23 +212,23 @@ bench( pkg+':kurtosis', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var x;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( 4.0 + EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS + 4.0, 100.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+		dist.alpha = x[ i % x.length ];
 		y = dist.kurtosis;
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
@@ -249,23 +246,23 @@ bench( pkg+':mean', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var x;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( 1.0 + EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS + 1.0, 100.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+		dist.alpha = x[ i % x.length ];
 		y = dist.mean;
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
@@ -283,23 +280,23 @@ bench( pkg+':mode', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var x;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS, 100.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+		dist.alpha = x[ i % x.length ];
 		y = dist.mode;
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
@@ -317,23 +314,23 @@ bench( pkg+':skewness', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var x;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( 3.0 + EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS + 3.0, 100.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+		dist.alpha = x[ i % x.length ];
 		y = dist.skewness;
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
@@ -351,23 +348,23 @@ bench( pkg+':stdev', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var x;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( 2.0 + EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS + 2.0, 100.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+		dist.alpha = x[ i % x.length ];
 		y = dist.stdev;
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
@@ -385,23 +382,23 @@ bench( pkg+':variance', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var x;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( 2.0 + EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS + 2.0, 100.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		dist.alpha = x[ i % len ];
+		dist.alpha = x[ i % x.length ];
 		y = dist.variance;
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
@@ -419,23 +416,23 @@ bench( pkg+':cdf', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var x;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( 0.0, 1.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, 0.0, 1.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		y = dist.cdf( x[ i % len ] );
+		y = dist.cdf( x[ i % x.length ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
@@ -452,23 +449,23 @@ bench( pkg+':logpdf', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var x;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( 0.0, 1.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, 0.0, 1.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		y = dist.logpdf( x[ i % len ] );
+		y = dist.logpdf( x[ i % x.length ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
@@ -485,23 +482,23 @@ bench( pkg+':pdf', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var x;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( 0.0, 1.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, 0.0, 1.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		y = dist.pdf( x[ i % len ] );
+		y = dist.pdf( x[ i % x.length ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
@@ -518,23 +515,23 @@ bench( pkg+':quantile', function benchmark( b ) {
 	var alpha;
 	var beta;
 	var dist;
-	var len;
+	var opts;
 	var x;
 	var y;
 	var i;
 
 	alpha = 10.332;
 	beta = 15.54321;
-	len = 100;
 	dist = new InvGamma( alpha, beta );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( 0.0, 1.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, 0.0, 1.0, opts );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		y = dist.quantile( x[ i % len ] );
+		y = dist.quantile( x[ i % x.length ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}