chore: minor clean up

Author: Neerajpathak07

lib/node_modules/@stdlib/stats/base/dsnanmean/README.md

@@ -51,36 +51,33 @@ The [arithmetic mean][arithmetic-mean] is defined as
 var dsnanmean = require( '@stdlib/stats/base/dsnanmean' );
 ```
 
-#### dsnanmean( N, x, stride )
+#### dsnanmean( N, x, strideX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x`, ignoring `NaN` values, using extended accumulation, and returning an extended precision result.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 
 var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dsnanmean( N, x, 1 );
+var v = dsnanmean( x.length, x, 1 );
 // returns ~0.3333
 ```
 
 The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float32Array`][@stdlib/array/float32].
--   **stride**: index increment for `x`.
+-   **strideX**: index increment for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ] );
-var N = floor( x.length / 2 );
 
-var v = dsnanmean( N, x, 2 );
+var v = dsnanmean( 4, x, 2 );
 // returns 1.25
 ```
 
@@ -95,40 +92,35 @@ var floor = require( '@stdlib/math/base/special/floor' );
 var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
 var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = dsnanmean( N, x1, 2 );
+var v = dsnanmean( 4, x1, 2 );
 // returns 1.25
 ```
 
-#### dsnanmean.ndarray( N, x, stride, offset )
+#### dsnanmean.ndarray( N, x, strideX, offsetX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array, ignoring `NaN` values and using extended accumulation and alternative indexing semantics.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 
 var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dsnanmean.ndarray( N, x, 1, 0 );
+var v = dsnanmean.ndarray( x.length, x, 1, 0 );
 // returns ~0.33333
 ```
 
 The function has the following additional parameters:
 
--   **offset**: starting index for `x`.
+-   **offsetX**: starting index for `x`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
-var N = floor( x.length / 2 );
 
-var v = dsnanmean.ndarray( N, x, 2, 1 );
+var v = dsnanmean.ndarray( 4, x, 2, 1 );
 // returns 1.25
 ```
 
@@ -193,12 +185,12 @@ console.log( v );
 
 #### stdlib_strided_dsnanmean( N, \*X, strideX )
 
-Calculate the Arithmetic Mean value of a double-precision floating-point strided array, ignoring `NaN` values.
+Computes the Arithmetic Mean of a single-precision floating-point strided array `x`, ignoring `NaN` values, using extended accumulation, and returning an extended precision result.
 
 ```c
 const float x[] = { 1.0f, 2.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f, 4.0f, 5.0f, 6.0f, 0.0f/0.0f, 7.0f, 8.0f, 0.0f/0.0f };
 
-double v = stdlib_strided_dsnanmean( 5, x, 2 );
+double v = stdlib_strided_dsnanmean( 6, x, 2 );
 // returns 1.25
 ```
 
@@ -214,12 +206,12 @@ double stdlib_strided_dsnanmean( const CBLAS_INT N, const float *X, const CBLAS_
 
 #### stdlib_strided_dsnanmean_ndarray( N, \*X, strideX, offsetX )
 
-Computes the Arithmetic Mean value of a double-precision floating-point strided array, ignoring `NaN` values and using alternative indexing semantics.
+Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using extended accumulation and alternative indexing semantics.
 
 ```c
 const float x[] = { 1.0f, 2.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f, 4.0f, 5.0f, 6.0f, 0.0f/0.0f, 7.0f, 8.0f, 0.0f/0.0f };
 
-double v = stdlib_strided_dsnanmean_ndarray( 5, x, 2, 0 );
+double v = stdlib_strided_dsnanmean_ndarray( 6, x, 2, 0 );
 // returns 1.25
 ```
 
@@ -258,7 +250,7 @@ double stdlib_strided_dsnanmean_ndarray( const CBLAS_INT N, const float *X, cons
 
 int main( void ) {
     // Create a strided array:
-    const float x[] = { 1.0f, 2.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f, 4.0f, 5.0f, 6.0f,   0.0f/0.0f, 7.0f, 8.0f, 0.0f/0.0f };
+    const float x[] = { 1.0f, 2.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f, 4.0f, 5.0f, 6.0f, 0.0f/0.0f, 7.0f, 8.0f, 0.0f/0.0f };
 
     // Specify the number of elements:
     const int N = 6;

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

@@ -21,22 +21,29 @@
 // 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 dsnanmean = require( './../lib/dsnanmean.js' );
 
 
-// VARIABLES //
-
-var options = {
-	'dtype': 'float32'
-};
-
-
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @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 +52,7 @@ 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/dsnanmean/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 +37,22 @@ var dsnanmean = tryRequire( resolve( __dirname, './../lib/dsnanmean.native.js' )
 var opts = {
 	'skip': ( dsnanmean instanceof Error )
 };
-var options = {
-	'dtype': 'float32'
-};
 
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @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 +61,7 @@ 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/dsnanmean/benchmark/benchmark.ndarray.js

@@ -21,22 +21,29 @@
 // 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 dsnanmean = require( './../lib/ndarray.js' );
 
 
-// VARIABLES //
-
-var options = {
-	'dtype': 'float32'
-};
-
-
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @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 +52,7 @@ 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/dsnanmean/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 +37,22 @@ var dsnanmean = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) )
 var opts = {
 	'skip': ( dsnanmean instanceof Error )
 };
-var options = {
-	'dtype': 'float32'
-};
 
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @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 +61,7 @@ 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/dsnanmean/benchmark/c/benchmark.length.c

@@ -97,14 +97,14 @@ static float rand_float( void ) {
 static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	float x[ len ];
-	float v;
+	double v;
 	double t;
 	int i;
 
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = ( rand_float()*20000.0f ) - 10000.0f;
 	}
-	v = 0.0f;
+	v = 0.0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
 		// cppcheck-suppress uninitvar
@@ -131,14 +131,14 @@ static double benchmark1( int iterations, int len ) {
 static double benchmark2( int iterations, int len ) {
 	double elapsed;
 	float x[ len ];
-	float v;
+	double v;
 	double t;
 	int i;
 
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = ( rand_float()*20000.0f ) - 10000.0f;
 	}
-	v = 0.0f;
+	v = 0.0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
 		// cppcheck-suppress uninitvar