feat: add ndarray/base/assign-scalar

lib/node_modules/@stdlib/ndarray/base/assign-scalar/README.md

@@ -0,0 +1,173 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2026 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# assignScalar
+
+> Assign a scalar value to every element of an output [ndarray][@stdlib/ndarray/base/ctor].
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var assignScalar = require( '@stdlib/ndarray/base/assign-scalar' );
+```
+
+#### assignScalar( arrays )
+
+Assigns a scalar value to every element of an output [ndarray][@stdlib/ndarray/base/ctor].
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var Float64Array = require( '@stdlib/array/float64' );
+
+// Create a zero-dimensional ndarray containing the scalar value:
+var x = scalar2ndarray( 5.0, {
+    'dtype': 'float64'
+});
+
+// Create a data buffer:
+var ybuf = new Float64Array( 6 );
+
+// Define the shape of the output array:
+var shape = [ 3, 1, 2 ];
+
+// Define the array strides:
+var sy = [ 2, 2, 1 ];
+
+// Define the index offset:
+var oy = 0;
+
+// Create the output ndarray-like object:
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': shape,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Assign the scalar value:
+assignScalar( [ x, y ] );
+
+console.log( y.data );
+// => <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]
+```
+
+The function accepts the following arguments:
+
+-   **arrays**: array-like object containing a zero-dimensional input [ndarray][@stdlib/ndarray/base/ctor] and an output [ndarray][@stdlib/ndarray/base/ctor].
+
+Each provided [ndarray][@stdlib/ndarray/base/ctor] should be an object with the following properties:
+
+-   **dtype**: data type.
+-   **data**: data buffer.
+-   **shape**: dimensions.
+-   **strides**: stride lengths.
+-   **offset**: index offset.
+-   **order**: specifies whether an ndarray is row-major (C-style) or column major (Fortran-style).
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before performing the operation in order to achieve better performance.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var filledarray = require( '@stdlib/array/filled' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var assignScalar = require( '@stdlib/ndarray/base/assign-scalar' );
+
+var x = scalar2ndarray( 10.0, {
+    'dtype': 'generic'
+});
+console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
+
+var y = {
+    'dtype': 'generic',
+    'data': filledarray( 0, 10, 'generic' ),
+    'shape': [ 5, 2 ],
+    'strides': [ 2, 1 ],
+    'offset': 0,
+    'order': 'row-major'
+};
+console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) );
+
+assignScalar( [ x, y ] );
+console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="references">
+
+</section>
+
+<!-- /.references -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[@stdlib/ndarray/base/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/ctor
+
+<!-- <related-links> -->
+
+<!-- </related-links> -->
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/ndarray/base/assign-scalar/benchmark/benchmark.10d_blocked_columnmajor.js

@@ -0,0 +1,145 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var floor = require( '@stdlib/math/base/special/floor' );
+var filledarray = require( '@stdlib/array/filled' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var assignScalar = require( './../lib/10d_blocked.js' );
+
+
+// VARIABLES //
+
+var types = [ 'float64' ];
+var order = 'column-major';
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - ndarray length
+* @param {NonNegativeIntegerArray} shape - ndarray shape
+* @param {string} xtype - input ndarray data type
+* @param {string} ytype - output ndarray data type
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len, shape, xtype, ytype ) {
+	var x;
+	var y;
+
+	y = filledarray( 0.0, len, ytype );
+	x = {
+		'dtype': xtype,
+		'data': [ 10.0 ],
+		'shape': [],
+		'strides': [ 0 ],
+		'offset': 0,
+		'order': order
+	};
+	y = {
+		'dtype': ytype,
+		'data': y,
+		'shape': shape,
+		'strides': shape2strides( shape, order ),
+		'offset': 0,
+		'order': order
+	};
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			assignScalar( x, y );
+			if ( isnan( y.data[ i%len ] ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( y.data[ i%len ] ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var sh;
+	var t1;
+	var t2;
+	var f;
+	var i;
+	var j;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( j = 0; j < types.length; j++ ) {
+		t1 = types[ j ];
+		t2 = types[ j ];
+		for ( i = min; i <= max; i++ ) {
+			len = pow( 10, i );
+
+			sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ];
+			f = createBenchmark( len, sh, t1, t2 );
+			bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,yorder=%s,xtype=%s,ytype=%s', pkg, sh.length, len, sh.join( ',' ), order, order, t1, t2 ), f );
+
+			sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ];
+			f = createBenchmark( len, sh, t1, t2 );
+			bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,yorder=%s,xtype=%s,ytype=%s', pkg, sh.length, len, sh.join( ',' ), order, order, t1, t2 ), f );
+
+			len = floor( pow( len, 1.0/10.0 ) );
+			sh = [ len, len, len, len, len, len, len, len, len, len ];
+			len *= pow( len, 9 );
+			f = createBenchmark( len, sh, t1, t2 );
+			bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,yorder=%s,xtype=%s,ytype=%s', pkg, sh.length, len, sh.join( ',' ), order, order, t1, t2 ), f );
+		}
+	}
+}
+
+main();