Auto-generated commit

CHANGELOG.md

@@ -4,14 +4,25 @@
 
 <section class="release" id="unreleased">
 
-## Unreleased (2024-12-24)
+## Unreleased (2025-01-03)
+
+<section class="features">
+
+### Features
+
+-   [`2832442`](https://github.com/stdlib-js/stdlib/commit/28324425c1a630bd52cccc75d4f4a2a72bbc9e01) - add C `ndarray` interface and refactor implementation for `stats/base/dnanmeanwd` [(#4251)](https://github.com/stdlib-js/stdlib/pull/4251)
+
+</section>
+
+<!-- /.features -->
 
 <section class="commits">
 
 ### Commits
 
 <details>
 
+-   [`2832442`](https://github.com/stdlib-js/stdlib/commit/28324425c1a630bd52cccc75d4f4a2a72bbc9e01) - **feat:** add C `ndarray` interface and refactor implementation for `stats/base/dnanmeanwd` [(#4251)](https://github.com/stdlib-js/stdlib/pull/4251) _(by Neeraj Pathak, Athan Reines)_
 -   [`70dde47`](https://github.com/stdlib-js/stdlib/commit/70dde4759fdc94408dc4ee058cd83e6edf6ebda7) - **refactor:** update `stats/base/dnanmeanwd` native addon from C++ to C  [(#4157)](https://github.com/stdlib-js/stdlib/pull/4157) _(by Neeraj Pathak)_
 -   [`62364f6`](https://github.com/stdlib-js/stdlib/commit/62364f62ea823a3b52c2ad25660ecd80c71f8f36) - **style:** fix C comment alignment _(by Philipp Burckhardt)_
 -   [`9e689ff`](https://github.com/stdlib-js/stdlib/commit/9e689ffcb7c6223afc521f1e574b42f10921cf5e) - **chore:** fix indentation in manifest.json files _(by Philipp Burckhardt)_

CONTRIBUTORS

@@ -27,6 +27,7 @@ Daniel Killenberger <daniel.killenberger@gmail.com>
 Daniel Yu <40680511+Daniel777y@users.noreply.github.com>
 Debashis Maharana <debashismaharana7854@gmail.com>
 Desh Deepak Kant <118960904+DeshDeepakKant@users.noreply.github.com>
+Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
 Divyansh Seth <59174836+sethdivyansh@users.noreply.github.com>
 Dominic Lim <46486515+domlimm@users.noreply.github.com>
 Dominik Moritz <domoritz@gmail.com>

NOTICE

@@ -1 +1 @@
-Copyright (c) 2016-2024 The Stdlib Authors.
+Copyright (c) 2016-2025 The Stdlib Authors.

README.md

@@ -84,36 +84,33 @@ To view installation and usage instructions specific to each branch build, be su
 var dnanmeanwd = require( '@stdlib/stats-base-dnanmeanwd' );
 ```
 
-#### dnanmeanwd( N, x, stride )
+#### dnanmeanwd( N, x, strideX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array `x`, using Welford's algorithm and ignoring `NaN` values.
 
 ```javascript
 var Float64Array = require( '@stdlib/array-float64' );
 
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dnanmeanwd( N, x, 1 );
+var v = dnanmeanwd( x.length, x, 1 );
 // returns ~0.3333
 ```
 
 The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
--   **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 stride array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array-float64' );
-var floor = require( '@stdlib/math-base-special-floor' );
 
 var x = new Float64Array( [ 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 = dnanmeanwd( N, x, 2 );
+var v = dnanmeanwd( 4, x, 2 );
 // returns 1.25
 ```
 
@@ -123,45 +120,39 @@ 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, NaN ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = dnanmeanwd( N, x1, 2 );
+var v = dnanmeanwd( 4, x1, 2 );
 // returns 1.25
 ```
 
-#### dnanmeanwd.ndarray( N, x, stride, offset )
+#### dnanmeanwd.ndarray( N, x, strideX, offsetX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics.
 
 ```javascript
 var Float64Array = require( '@stdlib/array-float64' );
 
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dnanmeanwd.ndarray( N, x, 1, 0 );
+var v = dnanmeanwd.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 Float64Array = require( '@stdlib/array-float64' );
-var floor = require( '@stdlib/math-base-special-floor' );
 
 var x = new Float64Array( [ 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 = dnanmeanwd.ndarray( N, x, 2, 1 );
+var v = dnanmeanwd.ndarray( 4, x, 2, 1 );
 // returns 1.25
 ```
 
@@ -213,6 +204,123 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dnanmeanwd.h"
+```
+
+#### stdlib_strided_dnanmeanwd( N, \*X, strideX )
+
+Computes the arithmetic mean of a double-precision floating-point strided array `x`, using Welford's algorithm and ignoring `NaN` values.
+
+```c
+const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
+
+double v = stdlib_strided_dnanmeanwd( 6, x, 2 );
+// returns 1.25
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+double stdlib_strided_dnanmeanwd( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dnanmeanwd_ndarray( N, \*X, strideX, offsetX )
+
+Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
+
+double v = stdlib_strided_dnanmeanwd_ndarray( 6, x, 2, 0 );
+// returns 1.25
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+double stdlib_strided_dnanmeanwd_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dnanmeanwd.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
+
+    // Specify the number of elements:
+    const int N = 6;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the arithmetic mean:
+    double v = stdlib_strided_dnanmeanwd( N, x, strideX );
+
+    // Print the result:
+    printf( "mean: %lf\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 * * *
 
 <section class="references">
@@ -269,7 +377,7 @@ See [LICENSE][stdlib-license].
 
 ## Copyright
 
-Copyright &copy; 2016-2024. The Stdlib [Authors][stdlib-authors].
+Copyright &copy; 2016-2025. The Stdlib [Authors][stdlib-authors].
 
 </section>
 

benchmark/benchmark.js

@@ -21,16 +21,30 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench-harness' );
-var randu = require( '@stdlib/random-base-randu' );
+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 Float64Array = require( '@stdlib/array-float64' );
 var pkg = require( './../package.json' ).name;
 var dnanmeanwd = require( './../lib/dnanmeanwd.js' );
 
 
 // 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.
 *
@@ -39,17 +53,7 @@ var dnanmeanwd = require( './../lib/dnanmeanwd.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( 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 = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {

benchmark/benchmark.native.js

@@ -22,10 +22,11 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench-harness' );
-var randu = require( '@stdlib/random-base-randu' );
+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 Float64Array = require( '@stdlib/array-float64' );
 var tryRequire = require( '@stdlib/utils-try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -40,6 +41,19 @@ var opts = {
 
 // 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.
 *
@@ -48,17 +62,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( 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 = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {