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Commit 50b84b5

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headlessNodekgryte
andauthored
feat: add ndarray/base/find
PR-URL: #7426 Ref: #2656 Co-authored-by: Athan Reines <kgryte@gmail.com> Reviewed-by: Athan Reines <kgryte@gmail.com>
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<!--
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@license Apache-2.0
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Copyright (c) 2025 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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# find
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> Return the first element in an ndarray which passes a test implemented by a predicate function.
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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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<!-- eslint-disable no-redeclare -->
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```javascript
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var find = require( '@stdlib/ndarray/base/find' );
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```
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<!-- eslint-enable no-redeclare -->
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#### find( arrays, predicate\[, thisArg] )
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Returns the first element in an ndarray which passes a test implemented by a predicate function.
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<!-- eslint-disable max-len -->
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```javascript
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var Float64Array = require( '@stdlib/array/float64' );
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function isEven( value ) {
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return value % 2.0 === 0.0;
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}
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// Create a data buffer:
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var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
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// Define the shape of the input array:
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var shape = [ 3, 1, 2 ];
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// Define the array strides:
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var sx = [ 4, 4, 1 ];
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// Define the index offset:
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var ox = 0;
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// Create the input ndarray-like object:
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var x = {
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'dtype': 'float64',
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'data': xbuf,
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'shape': shape,
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'strides': sx,
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'offset': ox,
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'order': 'row-major'
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};
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// Create an ndarray-like object containing a sentinel value:
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var sentinelValue = {
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'dtype': 'float64',
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'data': new Float64Array( [ NaN ] ),
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'shape': [],
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'strides': [ 0 ],
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'offset': 0,
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'order': 'row-major'
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};
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// Perform reduction:
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var out = find( [ x, sentinelValue ], isEven );
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// returns 2.0
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```
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The function accepts the following arguments:
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- **arrays**: array-like object containing an input ndarray and a zero-dimensional ndarray containing a sentinel value. The sentinel value is returned when no element in an input ndarray passes a test implemented by the predicate function.
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- **predicate**: predicate function.
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- **thisArg**: predicate function execution context (_optional_).
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Each provided ndarray 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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The predicate function is provided the following arguments:
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- **value**: current array element.
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- **indices**: current array element indices.
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- **arr**: the input ndarray.
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To set the predicate function execution context, provide a `thisArg`.
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<!-- eslint-disable no-invalid-this, max-len -->
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```javascript
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var Float64Array = require( '@stdlib/array/float64' );
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function isEven( value ) {
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this.count += 1;
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return value % 2.0 === 0.0;
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}
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// Create a data buffer:
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var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
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// Define the shape of the input array:
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var shape = [ 3, 1, 2 ];
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// Define the array strides:
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var sx = [ 4, 4, 1 ];
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// Define the index offset:
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var ox = 0;
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// Create the input ndarray-like object:
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var x = {
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'dtype': 'float64',
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'data': xbuf,
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'shape': shape,
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'strides': sx,
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'offset': ox,
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'order': 'row-major'
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};
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// Create an ndarray-like object containing a sentinel value:
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var sentinelValue = {
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'dtype': 'float64',
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'data': new Float64Array( [ NaN ] ),
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'shape': [],
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'strides': [ 0 ],
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'offset': 0,
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'order': 'row-major'
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};
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var ctx = {
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'count': 0
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};
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// Perform reduction:
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var out = find( [ x, sentinelValue ], isEven, ctx );
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// returns 2.0
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var count = ctx.count;
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// returns 2
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```
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</section>
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<!-- /.usage -->
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<section class="notes">
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## Notes
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- 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.
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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 discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var Float64Array = require( '@stdlib/array/float64' );
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var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
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var find = require( '@stdlib/ndarray/base/find' );
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function isEven( value ) {
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return value % 2.0 === 0.0;
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}
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var x = {
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'dtype': 'float64',
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'data': discreteUniform( 10, 0.0, 10.0, {
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'dtype': 'float64'
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}),
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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( x.data, x.shape, x.strides, x.offset, x.order ) );
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var sv = {
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'dtype': 'float64',
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'data': new Float64Array( [ NaN ] ),
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'shape': [],
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'strides': [ 0 ],
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'offset': 0,
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'order': x.order
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};
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console.log( 'Sentinel Value: %d', sv.data[ 0 ] );
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var out = find( [ x, sv ], isEven );
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console.log( out );
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```
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</section>
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<!-- /.examples -->
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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 class="links">
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<!-- <related-links> -->
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<!-- </related-links> -->
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</section>
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<!-- /.links -->
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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2025 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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/* eslint-disable stdlib/no-redeclare */
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// MODULES //
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var bench = require( '@stdlib/bench' );
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var isInteger = require( '@stdlib/math/base/assert/is-integer' );
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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 discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
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var pkg = require( './../package.json' ).name;
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var find = require( './../lib/10d.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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* Callback function.
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*
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* @param {*} value - ndarray element
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* @returns {boolean} result
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*/
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function clbk( value ) {
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return value < 0.0;
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}
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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 - ndarray data type
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len, shape, xtype ) {
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var x;
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x = discreteUniform( len, 1, 100, {
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'dtype': xtype
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});
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x = {
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'dtype': xtype,
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'data': x,
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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 out;
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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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out = find( x, NaN, clbk );
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if ( isInteger( out ) ) {
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b.fail( 'should not return an integer' );
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}
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}
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b.toc();
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if ( isInteger( out ) ) {
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b.fail( 'should not return an integer' );
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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 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 = 5; // 10^max
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for ( j = 0; j < types.length; j++ ) {
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t1 = 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 );
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bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, 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 );
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bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, 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 );
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bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f );
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}
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}
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}
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main();

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