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feat: add ndarray/base/assign-scalar
PR-URL: #11029 Closes: stdlib-js/metr-issue-tracker#202 Co-authored-by: Athan Reines <kgryte@gmail.com> Reviewed-by: Athan Reines <kgryte@gmail.com>
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‎lib/node_modules/@stdlib/ndarray/base/assign-scalar/README.md‎

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

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

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

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