fix: implementation

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---

Author: gururaj1512

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

@@ -98,9 +98,9 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note,
 var stdevwd = require( '@stdlib/stats/base/stdevwd' );
 ```
 
-#### stdevwd( N, correction, x, stride )
+#### stdevwd( N, correction, x, strideX )
 
-Computes the [standard deviation][standard-deviation] of a strided array `x` using Welford's algorithm.
+Computes the [standard deviation][standard-deviation] of a strided array using Welford's algorithm.
 
 ```javascript
 var x = [ 1.0, -2.0, 2.0 ];
@@ -113,18 +113,15 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).
--   **x**: input [`Array`][mdn-array], [`typed array`][mdn-typed-array], or accessor array.
--   **stride**: index increment for `x`.
+-   **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
+-   **strideX**: stride length for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] 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 [standard deviation][standard-deviation] of every other element in `x`,
 
 ```javascript
-var floor = require( '@stdlib/math/base/special/floor' );
-
 var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ];
-var N = floor( x.length / 2 );
 
-var v = stdevwd( N, 1, x, 2 );
+var v = stdevwd( 4, 1, x, 2 );
 // returns 2.5
 ```
 
@@ -134,18 +131,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = stdevwd( N, 1, x1, 2 );
+var v = stdevwd( 4, 1, x1, 2 );
 // returns 2.5
 ```
 
-#### stdevwd.ndarray( N, correction, x, stride, offset )
+#### stdevwd.ndarray( N, correction, x, strideX, offsetX )
 
 Computes the [standard deviation][standard-deviation] of a strided array using Welford's algorithm and alternative indexing semantics.
 
@@ -158,37 +152,17 @@ var v = stdevwd.ndarray( x.length, 1, x, 1, 0 );
 
 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 [standard deviation][standard-deviation] 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 [standard deviation][standard-deviation] for every other element in the strided array starting from the second element
 
 ```javascript
-var floor = require( '@stdlib/math/base/special/floor' );
-
 var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
-var N = floor( x.length / 2 );
 
-var v = stdevwd.ndarray( N, 1, x, 2, 1 );
+var v = stdevwd.ndarray( 4, 1, x, 2, 1 );
 // returns 2.5
 ```
 
-```javascript
-var stdevwd = require( '@stdlib/stats/base/stdevwd' );
-
-var accessorArray = {
-    get(i) {
-        return [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ][i];
-    },
-    set(i, v) {
-        // No-op for this example
-    },
-    length: 8
-};
-
-var v = stdevwd.ndarray( 4, 1, accessorArray, 2, 1 );
-console.log( v );
-```
-
 </section>
 
 <!-- /.usage -->
@@ -199,6 +173,7 @@ console.log( v );
 
 -   If `N <= 0`, both functions return `NaN`.
 -   If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment), both functions return `NaN`.
+-   Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]).
 -   Depending on the environment, the typed versions ([`dstdevwd`][@stdlib/stats/strided/dstdevwd], [`sstdevwd`][@stdlib/stats/base/sstdevwd], etc.) are likely to be significantly more performant.
 
 </section>
@@ -212,43 +187,18 @@ console.log( v );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float64Array = require( '@stdlib/array/float64' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var stdevwd = require( '@stdlib/stats/base/stdevwd' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var x = discreteUniform( 10, -50, 50, {
+    'dtype': 'float64'
+});
 console.log( x );
 
 var v = stdevwd( x.length, 1, x, 1 );
 console.log( v );
 ```
 
-```javascript
-var stdevwd = require( '@stdlib/stats/base/stdevwd' );
-
-var accessorArray = {
-    get(i) {
-        return [ 1.0, -2.0, 3.0, -4.0, 5.0 ][i];
-    },
-    set(i, v) {
-        // No-op for this example
-    },
-    length: 5
-};
-
-var v = stdevwd( accessorArray.length, 1, accessorArray, 1 );
-console.log( v );
-```
-
--   The function supports accessor arrays, which provide an alternative way to define strided arrays using `get` and `set` methods for data access.
-
 </section>
 
 <!-- /.examples -->
@@ -294,6 +244,8 @@ console.log( v );
 
 [mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
 
+[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor
+
 [@welford:1962a]: https://doi.org/10.1080/00401706.1962.10490022
 
 [@vanreeken:1968a]: https://doi.org/10.1145/362929.362961

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

@@ -21,75 +21,31 @@
 // 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 pkg = require( './../package.json' ).name;
 var stdevwd = require( './../lib/stdevwd.js' );
 
 
-// FUNCTIONS //
+// VARIABLES //
 
-/**
-* Creates a benchmark function for a native array.
-*
-* @private
-* @param {PositiveInteger} len - array length
-* @returns {Function} benchmark function
-*/
-function createNativeBenchmark( len ) {
-	var x;
-	var i;
+var options = {
+	'dtype': 'generic'
+};
 
-	x = new Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
-	return benchmark;
-
-	function benchmark( b ) {
-		var v;
-		var i;
 
-		b.tic();
-		for ( i = 0; i < b.iterations; i++ ) {
-			v = stdevwd( x.length, 1, x, 1 );
-			if ( isnan( v ) ) {
-				b.fail( 'should not return NaN' );
-			}
-		}
-		b.toc();
-		if ( isnan( v ) ) {
-			b.fail( 'should not return NaN' );
-		}
-		b.pass( 'benchmark finished' );
-		b.end();
-	}
-}
+// FUNCTIONS //
 
 /**
-* Creates a benchmark function for an accessor array.
+* Creates a benchmark function.
 *
 * @private
 * @param {PositiveInteger} len - array length
 * @returns {Function} benchmark function
 */
-function createAccessorBenchmark( len ) {
-	var data;
-	var x;
-	var i;
-
-	data = new Array( len );
-	for ( i = 0; i < len; i++ ) {
-		data[ i ] = ( randu()*20.0 ) - 10.0;
-	}
-	x = {
-		'get': function get( i ) {
-			return data[ i ];
-		},
-		'set': function set() {},
-		'length': data.length
-	};
+function createBenchmark( len ) {
+	var x = uniform( len, -10, 10, options );
 	return benchmark;
 
 	function benchmark( b ) {
@@ -132,11 +88,9 @@ function main() {
 
 	for ( i = min; i <= max; i++ ) {
 		len = pow( 10, i );
-		f = createNativeBenchmark( len );
-		bench( pkg+':native:len='+len, f );
-		f = createAccessorBenchmark( len );
-		bench( pkg+':accessors:len='+len, f );
+		f = createBenchmark( len );
+		bench( pkg+':len='+len, f );
 	}
 }
 
-main();
+main();

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

@@ -21,75 +21,31 @@
 // 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 pkg = require( './../package.json' ).name;
 var stdevwd = require( './../lib/ndarray.js' );
 
 
-// FUNCTIONS //
+// VARIABLES //
 
-/**
-* Creates a benchmark function for a native array.
-*
-* @private
-* @param {PositiveInteger} len - array length
-* @returns {Function} benchmark function
-*/
-function createNativeBenchmark( len ) {
-	var x;
-	var i;
+var options = {
+	'dtype': 'generic'
+};
 
-	x = new Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
-	return benchmark;
-
-	function benchmark( b ) {
-		var v;
-		var i;
 
-		b.tic();
-		for ( i = 0; i < b.iterations; i++ ) {
-			v = stdevwd( x.length, 1, x, 1, 0 );
-			if ( isnan( v ) ) {
-				b.fail( 'should not return NaN' );
-			}
-		}
-		b.toc();
-		if ( isnan( v ) ) {
-			b.fail( 'should not return NaN' );
-		}
-		b.pass( 'benchmark finished' );
-		b.end();
-	}
-}
+// FUNCTIONS //
 
 /**
-* Creates a benchmark function for an accessor array.
+* Creates a benchmark function.
 *
 * @private
 * @param {PositiveInteger} len - array length
 * @returns {Function} benchmark function
 */
-function createAccessorBenchmark( len ) {
-	var data;
-	var x;
-	var i;
-
-	data = new Array( len );
-	for ( i = 0; i < len; i++ ) {
-		data[ i ] = ( randu()*20.0 ) - 10.0;
-	}
-	x = {
-		'get': function get( i ) {
-			return data[ i ];
-		},
-		'set': function set() {},
-		'length': data.length
-	};
+function createBenchmark( len ) {
+	var x = uniform( len, -10, 10, options );
 	return benchmark;
 
 	function benchmark( b ) {
@@ -132,11 +88,9 @@ function main() {
 
 	for ( i = min; i <= max; i++ ) {
 		len = pow( 10, i );
-		f = createNativeBenchmark( len );
-		bench( pkg+':ndarray:native:len='+len, f );
-		f = createAccessorBenchmark( len );
-		bench( pkg+':ndarray:accessors:len='+len, f );
+		f = createBenchmark( len );
+		bench( pkg+':ndarray:len='+len, f );
 	}
 }
 
-main();
+main();