Auto-generated commit

Author: stdlib-bot

CHANGELOG.md

@@ -4,14 +4,37 @@
 
 <section class="release" id="unreleased">
 
-## Unreleased (2025-07-01)
+## Unreleased (2025-07-05)
+
+<section class="features">
+
+### Features
+
+-   [`c72df63`](https://github.com/stdlib-js/stdlib/commit/c72df63c4127781fd86c0fb3073b01b3db272223) - add support for accessor arrays and refactor `stats/base/stdevwd` [(#6527)](https://github.com/stdlib-js/stdlib/pull/6527)
+
+</section>
+
+<!-- /.features -->
+
+<section class="issues">
+
+### Closed Issues
+
+This release closes the following issue:
+
+[#5685](https://github.com/stdlib-js/stdlib/issues/5685)
+
+</section>
+
+<!-- /.issues -->
 
 <section class="commits">
 
 ### Commits
 
 <details>
 
+-   [`c72df63`](https://github.com/stdlib-js/stdlib/commit/c72df63c4127781fd86c0fb3073b01b3db272223) - **feat:** add support for accessor arrays and refactor `stats/base/stdevwd` [(#6527)](https://github.com/stdlib-js/stdlib/pull/6527) _(by Arihant Pal, Athan Reines, stdlib-bot, Gururaj Gurram)_
 -   [`7088dfa`](https://github.com/stdlib-js/stdlib/commit/7088dfa1cab0860d25b5a0feb649ec572cbc1e98) - **refactor:** update paths _(by Gururaj Gurram)_
 -   [`6ff81eb`](https://github.com/stdlib-js/stdlib/commit/6ff81eb876b628462c4a029a0392fcf8e2aff2bf) - **refactor:** update paths _(by Aayush Khanna)_
 
@@ -25,9 +48,11 @@
 
 ### Contributors
 
-A total of 2 people contributed to this release. Thank you to the following contributors:
+A total of 4 people contributed to this release. Thank you to the following contributors:
 
 -   Aayush Khanna
+-   Arihant Pal
+-   Athan Reines
 -   Gururaj Gurram
 
 </section>

README.md

@@ -131,9 +131,9 @@ To view installation and usage instructions specific to each branch build, be su
 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 ];
@@ -147,17 +147,14 @@ 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] or [`typed array`][mdn-typed-array].
--   **stride**: index increment for `x`.
+-   **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
 ```
 
@@ -167,18 +164,15 @@ 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.
 
@@ -191,17 +185,14 @@ 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
 ```
 
@@ -215,6 +206,7 @@ var v = stdevwd.ndarray( N, 1, x, 2, 1 );
 
 -   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>
@@ -228,18 +220,12 @@ var v = stdevwd.ndarray( N, 1, x, 2, 1 );
 <!-- 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 );
@@ -359,6 +345,8 @@ Copyright &copy; 2016-2025. The Stdlib [Authors][stdlib-authors].
 
 [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/array-base-accessor
+
 [@welford:1962a]: https://doi.org/10.1080/00401706.1962.10490022
 
 [@vanreeken:1968a]: https://doi.org/10.1145/362929.362961

benchmark/benchmark.js

@@ -21,11 +21,18 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench-harness' );
-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' );
+var stdevwd = require( './../lib/main.js' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'generic'
+};
 
 
 // FUNCTIONS //
@@ -38,13 +45,7 @@ var stdevwd = require( './../lib/stdevwd.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = [];
-	for ( i = 0; i < len; i++ ) {
-		x.push( ( randu()*20.0 ) - 10.0 );
-	}
+	var x = uniform( len, -10, 10, options );
 	return benchmark;
 
 	function benchmark( b ) {

benchmark/benchmark.ndarray.js

@@ -21,13 +21,20 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench-harness' );
-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' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'generic'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var stdevwd = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = [];
-	for ( i = 0; i < len; i++ ) {
-		x.push( ( randu()*20.0 ) - 10.0 );
-	}
+	var x = uniform( len, -10, 10, options );
 	return benchmark;
 
 	function benchmark( b ) {