chore: minor clean up

Author: Neerajpathak07

lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.js

@@ -21,22 +21,30 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var uniform = require( '@stdlib/random/array/uniform' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
 var dsmeanors = require( './../lib/dsmeanors.js' );
 
 
-// VARIABLES //
-
-var options = {
-	'dtype': 'float32'
-};
-
-
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.2 ) ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -45,7 +53,7 @@ var options = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x = uniform( len, -10.0, 10.0, options );
+	var x = filledarrayBy( len, 'float32', rand );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.native.js

@@ -22,7 +22,9 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var uniform = require( '@stdlib/random/array/uniform' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var tryRequire = require( '@stdlib/utils/try-require' );
@@ -35,13 +37,23 @@ var dsmeanors = tryRequire( resolve( __dirname, './../lib/dsmeanors.native.js' )
 var opts = {
 	'skip': ( dsmeanors instanceof Error )
 };
-var options = {
-	'dtype': 'float32'
-};
 
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.2 ) ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -50,7 +62,7 @@ var options = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x = uniform( len, -10.0, 10.0, options );
+	var x = filledarrayBy( len, 'float32', rand );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.ndarray.js

@@ -21,22 +21,30 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var uniform = require( '@stdlib/random/array/uniform' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
 var dsmeanors = require( './../lib/ndarray.js' );
 
 
-// VARIABLES //
-
-var options = {
-	'dtype': 'float32'
-};
-
-
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.2 ) ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -45,7 +53,7 @@ var options = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x = uniform( len, -10.0, 10.0, options );
+	var x = filledarrayBy( len, 'float32', rand );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.ndarray.native.js

@@ -22,7 +22,9 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var uniform = require( '@stdlib/random/array/uniform' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var tryRequire = require( '@stdlib/utils/try-require' );
@@ -35,13 +37,23 @@ var dsmeanors = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) )
 var opts = {
 	'skip': ( dsmeanors instanceof Error )
 };
-var options = {
-	'dtype': 'float32'
-};
 
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.2 ) ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -50,7 +62,7 @@ var options = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x = uniform( len, -10.0, 10.0, options );
+	var x = filledarrayBy( len, 'float32', rand );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/dsmeanors/examples/index.js

@@ -18,12 +18,18 @@
 
 'use strict';
 
-var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var randu = require( '@stdlib/random/base/randu' );
+var round = require( '@stdlib/math/base/special/round' );
+var Float32Array = require( '@stdlib/array/float32' );
 var dsmeanors = require( './../lib' );
 
-var x = discreteUniform( 10, -50, 50, {
-	'dtype': 'float32'
-});
+var x;
+var i;
+
+x = new Float32Array( 10 );
+for ( i = 0; i < x.length; i++ ) {
+    x[ i ] = round( (randu()*100.0) - 50.0 );
+}
 console.log( x );
 
 var v = dsmeanors( x.length, x, 1 );

lib/node_modules/@stdlib/stats/base/dsmeanors/src/main.c

@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
@@ -49,7 +49,7 @@ double API_SUFFIX(stdlib_strided_dsmeanors_ndarray)( const CBLAS_INT N, const fl
 		return 0.0 / 0.0; // NaN
 	}
 	if ( N == 1 || strideX == 0 ) {
-		return X[ 0 ];
+		return X[ offsetX ];
 	}
 	return stdlib_strided_dssumors( N, X, strideX ) / (double)N;
 }