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‎CHANGELOG.md‎

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### Features
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- [`2c835da`](https://github.com/stdlib-js/stdlib/commit/2c835dabc4f37afb4f855dec66742d50d14adf32) - add `nansLike` to namespace
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- [`b9ecb29`](https://github.com/stdlib-js/stdlib/commit/b9ecb2970eedca271688dc7fc12ee2247a43cbf3) - add `ndarray/nans-like`
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- [`0d5b82a`](https://github.com/stdlib-js/stdlib/commit/0d5b82a1055d8a5fe51eae4011bedf64844fb48e) - add `onesLike` to namespace
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- [`64a9fda`](https://github.com/stdlib-js/stdlib/commit/64a9fda26a1e5411a439fbcff6b567e7ed1ea6b7) - add `ndarray/ones-like`
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- [`e38bbc8`](https://github.com/stdlib-js/stdlib/commit/e38bbc844b58b38ccb22be0ee62b0a42aa90fd75) - add `transpose` and `toTransposed` to namespace
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<details>
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- [`dfda2f7`](https://github.com/stdlib-js/stdlib/commit/dfda2f76fffbc7450ba3b7c943787de52c05e7b7) - **docs:** update ToC _(by Athan Reines)_
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- [`2c835da`](https://github.com/stdlib-js/stdlib/commit/2c835dabc4f37afb4f855dec66742d50d14adf32) - **feat:** add `nansLike` to namespace _(by Athan Reines)_
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- [`b9ecb29`](https://github.com/stdlib-js/stdlib/commit/b9ecb2970eedca271688dc7fc12ee2247a43cbf3) - **feat:** add `ndarray/nans-like` _(by Athan Reines)_
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- [`0d5b82a`](https://github.com/stdlib-js/stdlib/commit/0d5b82a1055d8a5fe51eae4011bedf64844fb48e) - **feat:** add `onesLike` to namespace _(by Athan Reines)_
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- [`64a9fda`](https://github.com/stdlib-js/stdlib/commit/64a9fda26a1e5411a439fbcff6b567e7ed1ea6b7) - **feat:** add `ndarray/ones-like` _(by Athan Reines)_
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- [`65f9d6f`](https://github.com/stdlib-js/stdlib/commit/65f9d6fd963809f82e54cdfd06ed15e15b51525e) - **refactor:** align `ndarray/*` errors and remove `namespace` self-ref [(#12102)](https://github.com/stdlib-js/stdlib/pull/12102) _(by Philipp Burckhardt)_

‎README.md‎

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The namespace exports the following functions to create multidimensional arrays:
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<!-- <toc pattern="+(array|copy|ctor|empty|empty-like|fancy|from-scalar|from-scalar-like|ndarraylike2ndarray|ones|ones-like|to-fancy|zeros|zeros-like)"> -->
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<!-- <toc pattern="+(array|copy|ctor|empty|empty-like|fancy|from-scalar|from-scalar-like|nans-like|ndarraylike2ndarray|ones|ones-like|to-fancy|zeros|zeros-like)"> -->
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<div class="namespace-toc">
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‎lib/index.js‎

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*/
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setReadOnly( ns, 'mostlySafeCasts', require( './../mostly-safe-casts' ) );
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/**
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* @name nansLike
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* @memberof ns
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* @readonly
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* @type {Function}
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* @see {@link module:@stdlib/ndarray/nans-like}
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*/
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setReadOnly( ns, 'nansLike', require( './../nans-like' ) );
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/**
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* @name ndarraylike2ndarray
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* @memberof ns

‎nans-like/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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# nansLike
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> Create a NaN-filled [ndarray][@stdlib/ndarray/ctor] having the same shape and [data type][@stdlib/ndarray/dtypes] as a provided ndarray.
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<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
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<section class="intro">
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</section>
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<!-- /.intro -->
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<!-- Package usage documentation. -->
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<section class="usage">
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## Usage
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```javascript
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var nansLike = require( '@stdlib/ndarray/nans-like' );
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```
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#### nansLike( x\[, options] )
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Creates a NaN-filled [ndarray][@stdlib/ndarray/ctor] having the same shape and [data type][@stdlib/ndarray/dtypes] as a provided ndarray.
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```javascript
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var getShape = require( '@stdlib/ndarray/shape' );
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var getDType = require( '@stdlib/ndarray/dtype' );
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var zeros = require( '@stdlib/ndarray/zeros' );
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var x = zeros( [ 2, 2 ] );
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// returns <ndarray>[ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]
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var y = nansLike( x );
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// returns <ndarray>[ [ NaN, NaN ], [ NaN, NaN ] ]
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var sh = getShape( y );
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// returns [ 2, 2 ]
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var dt = String( getDType( y ) );
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// returns 'float64'
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```
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The function supports the following options:
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- **dtype**: output [ndarray][@stdlib/ndarray/ctor] [data type][@stdlib/ndarray/dtypes]. Must be a floating-point or "generic" [data type][@stdlib/ndarray/dtypes]. Overrides the input ndarray's inferred [data type][@stdlib/ndarray/dtypes].
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- **shape**: output [ndarray][@stdlib/ndarray/ctor] shape. Overrides the input ndarray's inferred shape.
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- **order**: specifies whether the output [ndarray][@stdlib/ndarray/ctor] should be `'row-major'` (C-style) or `'column-major'` (Fortran-style). Overrides the input ndarray's inferred order.
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- **mode**: specifies how to handle indices which exceed array dimensions (see [ndarray][@stdlib/ndarray/ctor]). Default: `'throw'`.
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- **submode**: a mode array which specifies for each dimension how to handle subscripts which exceed array dimensions (see [ndarray][@stdlib/ndarray/ctor]). If provided fewer modes than dimensions, the constructor recycles modes using modulo arithmetic. Default: `[ options.mode ]`.
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- **readonly**: boolean indicating whether an array should be **read-only**. Default: `false`.
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To override either the `dtype`, `shape`, or `order`, specify the corresponding option. For example, to override the inferred [data type][@stdlib/ndarray/dtypes],
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```javascript
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var getShape = require( '@stdlib/ndarray/shape' );
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var getDType = require( '@stdlib/ndarray/dtype' );
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var zeros = require( '@stdlib/ndarray/zeros' );
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var x = zeros( [ 2, 2 ] );
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// returns <ndarray>[ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]
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var dt = String( getDType( x ) );
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// returns 'float64'
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var y = nansLike( x, {
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'dtype': 'float32'
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});
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// returns <ndarray>[ [ NaN, NaN ], [ NaN, NaN ] ]
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var sh = getShape( y );
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// returns [ 2, 2 ]
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dt = String( getDType( y ) );
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// returns 'float32'
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```
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</section>
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<!-- /.usage -->
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<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
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<section class="notes">
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</section>
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<!-- /.notes -->
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<!-- Package usage examples. -->
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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 zeros = require( '@stdlib/ndarray/zeros' );
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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var nansLike = require( '@stdlib/ndarray/nans-like' );
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// Specify a list of data types:
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var dt = [
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'float64',
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'float32',
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'complex128',
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'complex64',
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'generic'
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];
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// Generate NaN-filled arrays...
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var x;
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var y;
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var i;
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for ( i = 0; i < dt.length; i++ ) {
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x = zeros( [ 2, 2 ], {
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'dtype': dt[ i ]
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});
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y = nansLike( x );
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console.log( ndarray2array( y ) );
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}
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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/ctor]: https://github.com/stdlib-js/ndarray/tree/main/ctor
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[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/ndarray/tree/main/dtypes
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</section>
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<!-- /.links -->

‎nans-like/benchmark/benchmark.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 isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
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var zeros = require( './../../zeros' );
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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 nansLike = require( './../lib' );
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// MAIN //
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bench( format( '%s:dtype=float64', pkg ), function benchmark( b ) {
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var x;
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var y;
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var i;
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x = zeros( [ 0 ], {
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'dtype': 'float64'
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});
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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y = nansLike( x );
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if ( y.length !== 0 ) {
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b.fail( 'should have length 0' );
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}
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}
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b.toc();
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if ( !isndarrayLike( y ) ) {
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b.fail( 'should return an ndarray' );
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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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bench( format( '%s:dtype=float32', pkg ), function benchmark( b ) {
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var x;
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var y;
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var i;
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x = zeros( [ 0 ], {
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'dtype': 'float32'
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});
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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y = nansLike( x );
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if ( y.length !== 0 ) {
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b.fail( 'should have length 0' );
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}
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}
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b.toc();
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if ( !isndarrayLike( y ) ) {
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b.fail( 'should return an ndarray' );
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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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bench( format( '%s:dtype=complex128', pkg ), function benchmark( b ) {
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var x;
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var y;
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var i;
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x = zeros( [ 0 ], {
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'dtype': 'complex128'
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});
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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y = nansLike( x );
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if ( y.length !== 0 ) {
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b.fail( 'should have length 0' );
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}
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}
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b.toc();
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if ( !isndarrayLike( y ) ) {
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b.fail( 'should return an ndarray' );
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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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bench( format( '%s:dtype=complex64', pkg ), function benchmark( b ) {
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var x;
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var y;
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var i;
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x = zeros( [ 0 ], {
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'dtype': 'complex64'
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});
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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y = nansLike( x );
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if ( y.length !== 0 ) {
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b.fail( 'should have length 0' );
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}
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}
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b.toc();
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if ( !isndarrayLike( y ) ) {
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b.fail( 'should return an ndarray' );
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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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bench( format( '%s:dtype=generic', pkg ), function benchmark( b ) {
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var x;
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var y;
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var i;
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x = zeros( [ 0 ], {
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'dtype': 'generic'
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});
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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y = nansLike( x );
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if ( y.length !== 0 ) {
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b.fail( 'should have length 0' );
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}
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}
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b.toc();
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if ( !isndarrayLike( y ) ) {
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b.fail( 'should return an ndarray' );
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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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