refactor: refactored benchmarks, tests and docs

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stdlib-js · Jan 13, 2025 · 05492cd · 05492cd
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diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/README.md b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/README.md
@@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as
 var sdsnanmeanors = require( '@stdlib/stats/base/sdsnanmeanors' );
 ```
 
-#### sdsnanmeanors( N, x, stride )
+#### sdsnanmeanors( N, x, strideX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x`, ignoring `NaN` values and using ordinary recursive summation with extended accumulation.
 
@@ -69,18 +69,16 @@ 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 = sdsnanmeanors( N, x, 2 );
+var v = sdsnanmeanors( 4, x, 2 );
 // returns 1.25
 ```
 
@@ -90,45 +88,39 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-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 = sdsnanmeanors( N, x1, 2 );
+var v = sdsnanmeanors( 4, x1, 2 );
 // returns 1.25
 ```
 
-#### sdsnanmeanors.ndarray( N, x, stride, offset )
+#### sdsnanmeanors.ndarray( N, x, strideX, offsetX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation with 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 = sdsnanmeanors.ndarray( N, x, 1, 0 );
+var v = sdsnanmeanors.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 = sdsnanmeanors.ndarray( N, x, 2, 1 );
+var v = sdsnanmeanors.ndarray( 4, x, 2, 1 );
 // returns 1.25
 ```
 
@@ -155,22 +147,12 @@ var v = sdsnanmeanors.ndarray( N, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float32Array = require( '@stdlib/array/float32' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var sdsnanmeanors = require( '@stdlib/stats/base/sdsnanmeanors' );
 
-var x;
-var i;
-
-x = new Float32Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    if ( randu() < 0.2 ) {
-        x[ i ] = NaN;
-    } else {
-        x[ i ] = round( (randu()*100.0) - 50.0 );
-    }
-}
+var x = discreteUniform( 10, -50, 50, {
+    'dtype': 'float32'
+});
 console.log( x );
 
 var v = sdsnanmeanors( x.length, x, 1 );
@@ -198,7 +180,7 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p
 ```c
 const float x[] = { 1.0, -2.0, 0.0/0.0, 2.0 };
 
-double v = stdlib_strided_sdsnanmeanors( 4, x, 1 );
+double v = stdlib_strided_sdsnanmeanors( x.length, x, 1 );
 // returns ~0.3333
 ```
 
@@ -219,7 +201,7 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p
 ```c
 const float x[] = { 1.0, -2.0, 0.0/0.0, 2.0 };
 
-double v = stdlib_strided_sdsnanmeanors_ndarray( 4, x, 1, 0 );
+double v = stdlib_strided_sdsnanmeanors_ndarray( x.length, x, 1, 0 );
 // returns ~0.3333
 ```
 

diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/benchmark/benchmark.js
@@ -21,14 +21,20 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var sdsnanmeanors = require( './../lib/sdsnanmeanors.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,17 +45,7 @@ var sdsnanmeanors = require( './../lib/sdsnanmeanors.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*20.0 ) - 10.0;
-		}
-	}
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {

diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/benchmark/benchmark.native.js
@@ -22,10 +22,9 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -36,6 +35,9 @@ var sdsnanmeanors = tryRequire( resolve( __dirname, './../lib/sdsnanmeanors.nati
 var opts = {
 	'skip': ( sdsnanmeanors instanceof Error )
 };
+var options = {
+	'dtype': 'float32'
+};
 
 
 // FUNCTIONS //
@@ -48,17 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*20.0 ) - 10.0;
-		}
-	}
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {

diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/benchmark/benchmark.ndarray.js
@@ -21,14 +21,20 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var sdsnanmeanors = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,17 +45,7 @@ var sdsnanmeanors = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*20.0 ) - 10.0;
-		}
-	}
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {

diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/benchmark/benchmark.ndarray.native.js
@@ -22,10 +22,9 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -36,6 +35,9 @@ var sdsnanmeanors = tryRequire( resolve( __dirname, './../lib/ndarray.native.js'
 var opts = {
 	'skip': ( sdsnanmeanors instanceof Error )
 };
+var options = {
+	'dtype': 'float32'
+};
 
 
 // FUNCTIONS //
@@ -48,17 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*20.0 ) - 10.0;
-		}
-	}
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {

diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/docs/repl.txt
@@ -1,11 +1,11 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the arithmetic mean of a single-precision floating-point strided
     array, ignoring `NaN` values and using ordinary recursive summation with
     extended accumulation.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -22,8 +22,8 @@
     x: Float32Array
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
     Returns
     -------
@@ -37,22 +37,19 @@
     > {{alias}}( x.length, x, 1 )
     ~0.3333
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{alias}}( 3, x, 2 )
     ~0.3333
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );
     > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 3, x1, 2 )
     ~-0.3333
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the arithmetic mean of a single-precision floating-point strided
     array, ignoring `NaN` values and using ordinary recursive summation with
     extended accumulation and alternative indexing semantics.
@@ -69,10 +66,10 @@
     x: Float32Array
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -89,8 +86,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1 )
     ~-0.3333
 
     See Also