Auto-generated commit

CHANGELOG.md

@@ -4,7 +4,7 @@
 
 <section class="release" id="unreleased">
 
-## Unreleased (2024-08-18)
+## Unreleased (2024-09-02)
 
 <section class="packages">
 
@@ -62,10 +62,12 @@
 
 ### 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:
 
 -   Aman Bhansali
 -   Athan Reines
+-   Philipp Burckhardt
+-   yaswanth
 
 </section>
 
@@ -77,6 +79,8 @@ A total of 2 people contributed to this release. Thank you to the following cont
 
 <details>
 
+-   [`e9f4e07`](https://github.com/stdlib-js/stdlib/commit/e9f4e0759a14b8da93d4e0837b886d8ed56bc696) - **refactor:** update `blas/ext/base/dsnansumpw` to follow current conventions _(by yaswanth, Philipp Burckhardt)_
+-   [`e0cef99`](https://github.com/stdlib-js/stdlib/commit/e0cef995e884021db3001dc1a3cfef0ca7b368c2) - **style:** remove extra spaces for regular expressions in publish script _(by Philipp Burckhardt)_
 -   [`da12183`](https://github.com/stdlib-js/stdlib/commit/da121832eca80c36e1e32929e994fef44ca8a4cc) - **feat:** add `blas/base/dspr` [(#2794)](https://github.com/stdlib-js/stdlib/pull/2794) _(by Aman Bhansali, Athan Reines)_
 
 </details>

base/dgemm/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform the matrix-matrix operation `C = α*op(A)*op(B) + β*C` where `op(X)` is one of the `op(X) = X`, or `op(X) = X^T`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/dgemv/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform one of the matrix-vector operations `y = α*A*x + β*y` or `y = α*A**T*x + β*y`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/dspmv/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform the matrix-vector operation `y = α*A*x + β*y` where `α` and `β` are scalars, `x` and `y` are `N` element vectors and, `A` is an `N` by `N` symmetric matrix supplied in packed form.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/dspr/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform the symmetric rank 1 operation `A = α*x*x^T + A`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/dsymv/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform the matrix-vector operation `y = α*A*x + β*y` where `α` and `β` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/dsyr/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform the symmetric rank 1 operation `A = α*x*x^T + A`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/dsyr2/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform the symmetric rank 2 operation `A = α*x*y^T + α*y*x^T + A`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/dtrmv/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform one of the matrix-vector operations `x = A*x` or `x = A^T*x`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/dtrsv/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Solve one of the systems of equations `A*x = b` or `A^T*x = b`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/sgemm/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform the matrix-matrix operation `C = α*op(A)*op(B) + β*C` where `op(X)` is one of the `op(X) = X`, or `op(X) = X^T`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/sgemv/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform one of the matrix-vector operations `y = α*A*x + β*y` or `y = α*A^T*x + β*y`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/sspmv/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform the matrix-vector operation `y = α*A*x + β*y` where `α` and `β` are scalars, `x` and `y` are `N` element vectors and, `A` is an `N` by `N` symmetric matrix supplied in packed form.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/sspr/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform the symmetric rank 1 operation `A = α*x*x^T + A`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/ssymv/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform the matrix-vector operation `y = α*A*x + β*y` where `α` and `β` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/ssyr/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform the symmetric rank 1 operation `A = α*x*x**T + A`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/ssyr2/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform the symmetric rank 2 operation `A = α*x*y^T + α*y*x^T + A`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/strmv/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Perform one of the matrix-vector operations `x = A*x` or `x = A^T*x`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

base/strsv/README.md

@@ -22,7 +22,7 @@ limitations under the License.
 
 > Solve one of the systems of equations `A*x = b` or `A^T*x = b`.
 
-<section class = "usage">
+<section class="usage">
 
 ## Usage
 

ext/base/dsnansumpw/README.md

@@ -56,16 +56,14 @@ The function has the following parameters:
 -   **x**: input [`Float32Array`][@stdlib/array/float32].
 -   **stride**: index increment for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum 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 sum 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, NaN, -7.0, NaN, 3.0, 4.0, 2.0 ] );
-var N = floor( x.length / 2 );
 
-var v = dsnansumpw( N, x, 2 );
+var v = dsnansumpw( 4, x, 2 );
 // returns 5.0
 ```
 
@@ -75,14 +73,11 @@ 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, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = dsnansumpw( N, x1, 2 );
+var v = dsnansumpw( 4, x1, 2 );
 // returns 5.0
 ```
 
@@ -108,12 +103,10 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-var N = floor( x.length / 2 );
 
-var v = dsnansumpw.ndarray( N, x, 2, 1 );
+var v = dsnansumpw.ndarray( 4, x, 2, 1 );
 // returns 5.0
 ```
 
@@ -139,22 +132,19 @@ var v = dsnansumpw.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/base/discrete-uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var dsnansumpw = require( '@stdlib/blas/ext/base/dsnansumpw' );
 
-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 );
+function rand() {
+    if ( bernoulli( 0.8 ) > 0 ) {
+        return NaN;
     }
+    return discreteUniform( 0, 100 );
 }
+
+var x = filledarrayBy( 10, 'float32', rand );
 console.log( x );
 
 var v = dsnansumpw( x.length, x, 1 );

ext/base/dsnansumpw/benchmark/benchmark.js

@@ -21,10 +21,11 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-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 Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var dsnansumpw = require( './../lib/dsnansumpw.js' );
 
@@ -39,18 +40,15 @@ var dsnansumpw = require( './../lib/dsnansumpw.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
+	var x = filledarrayBy( len, 'float32', rand );
+	return benchmark;
 
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*10.0 ) - 20.0;
+	function rand() {
+		if ( bernoulli( 0.8 ) > 0 ) {
+			return NaN;
 		}
+		return uniform( -10, 10 );
 	}
-	return benchmark;
 
 	function benchmark( b ) {
 		var v;

ext/base/dsnansumpw/benchmark/benchmark.native.js

@@ -22,10 +22,11 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-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 Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -48,18 +49,15 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
+	var x = filledarrayBy( len, 'float32', rand );
+	return benchmark;
 
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*10.0 ) - 20.0;
+	function rand() {
+		if ( bernoulli( 0.8 ) > 0 ) {
+			return NaN;
 		}
+		return uniform( -10, 10 );
 	}
-	return benchmark;
 
 	function benchmark( b ) {
 		var v;

ext/base/dsnansumpw/benchmark/benchmark.ndarray.js

@@ -21,10 +21,11 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-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 Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var dsnansumpw = require( './../lib/ndarray.js' );
 
@@ -39,18 +40,15 @@ var dsnansumpw = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
+	var x = filledarrayBy( len, 'float32', rand );
+	return benchmark;
 
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*10.0 ) - 20.0;
+	function rand() {
+		if ( bernoulli( 0.8 ) > 0 ) {
+			return NaN;
 		}
+		return uniform( -10, 10 );
 	}
-	return benchmark;
 
 	function benchmark( b ) {
 		var v;