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feat: add blas/ext/unitspace
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‎lib/node_modules/@stdlib/blas/ext/unitspace/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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# unitspace
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> Return a new [ndarray][@stdlib/ndarray/ctor] filled with linearly spaced numeric elements which increment by `1` starting from a specified value along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.
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<section class="usage">
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## Usage
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```javascript
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var unitspace = require( '@stdlib/blas/ext/unitspace' );
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```
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#### unitspace( shape, start\[, options] )
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Returns a new [ndarray][@stdlib/ndarray/ctor] filled with linearly spaced numeric elements which increment by `1` starting from a specified value along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.
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```javascript
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var x = unitspace( [ 4 ], 1.0 );
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// returns <ndarray>[ 1.0, 2.0, 3.0, 4.0 ]
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```
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The function has the following parameters:
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- **shape**: array shape.
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- **start**: starting value. May be either a number, a complex number, or an [ndarray][@stdlib/ndarray/ctor] having a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. If provided an [ndarray][@stdlib/ndarray/ctor], the value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the complement of the shape defined by `options.dims`. For example, given the input shape `[2, 3, 4]` and `options.dims=[0]`, a start [ndarray][@stdlib/ndarray/ctor] must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the shape `[3, 4]`. Similarly, when performing the operation over all elements in a provided input shape, a start [ndarray][@stdlib/ndarray/ctor] must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor].
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- **options**: function options (_optional_).
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The function accepts the following options:
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- **dims**: list of dimensions over which to perform operation. If not provided, the function generates linearly spaced values along the last dimension. Default: `[-1]`.
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- **dtype**: output [ndarray][@stdlib/ndarray/ctor] [data type][@stdlib/ndarray/dtypes]. Must be a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. If a data type is provided, `start` is cast to the specified data type. If a data type is not provided, the default output array data type is the same as the data type of `start` (where number and complex number primitives are assumed to be `'float64'` and `'complex128'`, respectively).
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- **order**: specifies whether an [ndarray][@stdlib/ndarray/ctor] is `'row-major'` (C-style) or `'column-major'` (Fortran-style). If `start` is a scalar value, the default order is `'row-major'`. If `start` is an [ndarray][@stdlib/ndarray/ctor], the default order is the same as the memory layout of `start`.
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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 function recycles modes using modulo arithmetic. Default: `[ options.mode ]`.
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When provided a scalar or zero-dimensional [ndarray][@stdlib/ndarray/ctor] `start` argument, the value is broadcast across all elements in the shape defined by the complement of those dimensions specified by `options.dims`. To specify separate sub-array starting values, provide a non-zero-dimensional [ndarray][@stdlib/ndarray/ctor] argument.
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```javascript
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var array = require( '@stdlib/ndarray/array' );
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var start = array( [ 1.0, 5.0 ] );
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var x = unitspace( [ 2, 3 ], start );
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// returns <ndarray>[ [ 1.0, 2.0, 3.0 ], [ 5.0, 6.0, 7.0 ] ]
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```
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By default, the function generates linearly spaced values along the last dimension of an output [ndarray][@stdlib/ndarray/ctor]. To perform the operation over specific dimensions, provide a `dims` option.
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```javascript
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var x = unitspace( [ 2, 2 ], 1.0, {
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'dims': [ 0, 1 ]
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});
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// returns <ndarray>[ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]
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```
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To specify the output [ndarray][@stdlib/ndarray/ctor] [data type][@stdlib/ndarray/dtypes], provide a `dtype` option.
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```javascript
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var x = unitspace( [ 4 ], 1.0, {
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'dtype': 'float32'
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});
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// returns <ndarray>[ 1.0, 2.0, 3.0, 4.0 ]
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```
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#### unitspace.assign( x, start\[, options] )
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Fills an [ndarray][@stdlib/ndarray/ctor] with linearly spaced numeric elements which increment by `1` starting from a specified value along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.
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```javascript
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var zeros = require( '@stdlib/ndarray/zeros' );
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var x = zeros( [ 4 ] );
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// returns <ndarray>
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var out = unitspace.assign( x, 1.0 );
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// returns <ndarray>[ 1.0, 2.0, 3.0, 4.0 ]
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var bool = ( x === out );
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// returns true
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```
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The function has the following parameters:
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- **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a numeric or "generic" [data type][@stdlib/ndarray/dtypes].
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- **start**: starting value. May be either a number, a complex number, or an [ndarray][@stdlib/ndarray/ctor] having a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. If provided an [ndarray][@stdlib/ndarray/ctor], the value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the complement of the shape defined by `options.dims`. For example, given the input shape `[2, 3, 4]` and `options.dims=[0]`, a start [ndarray][@stdlib/ndarray/ctor] must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the shape `[3, 4]`. Similarly, when performing the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor], a start [ndarray][@stdlib/ndarray/ctor] must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor].
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- **options**: function options (_optional_).
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The function accepts the following options:
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- **dims**: list of dimensions over which to perform operation. If not provided, the function generates linearly spaced values along the last dimension. Default: `[-1]`.
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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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- When writing to a complex floating-point output [ndarray][@stdlib/ndarray/ctor], a real-valued `start` value is treated as a complex number having a real component equaling the provided value and having an imaginary component equaling zero.
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- The `start` argument is cast to the data type of the output [ndarray][@stdlib/ndarray/ctor].
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- The function iterates over [ndarray][@stdlib/ndarray/ctor] elements according to the memory layout of an output [ndarray][@stdlib/ndarray/ctor]. Accordingly, performance degradation is possible when operating over multiple dimensions of a large non-contiguous multi-dimensional output [ndarray][@stdlib/ndarray/ctor]. In such scenarios, one may want to copy an output [ndarray][@stdlib/ndarray/ctor] to contiguous memory before filling with linearly spaced values.
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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 ndarray2array = require( '@stdlib/ndarray/to-array' );
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var unitspace = require( '@stdlib/blas/ext/unitspace' );
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// Create a vector of starting values:
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var start = unitspace( [ 5 ], 1 );
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// Create a grid:
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var out = unitspace( [ 5, 5 ], start );
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console.log( ndarray2array( out ) );
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// Generate values over multiple dimensions:
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out = unitspace( [ 5, 5 ], 1, {
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'dims': [ 0, 1 ]
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});
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console.log( ndarray2array( out ) );
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// Generate values over multiple dimensions in column-major order:
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out = unitspace( [ 5, 5 ], 1, {
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'dims': [ 0, 1 ],
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'order': 'column-major'
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});
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console.log( ndarray2array( 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 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/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
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[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes
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[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes
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</section>
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<!-- /.links -->

‎lib/node_modules/@stdlib/blas/ext/unitspace/benchmark/benchmark.assign.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 zeros = require( '@stdlib/ndarray/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 assign = require( './../lib/assign.js' );
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// VARIABLES //
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var options = {
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'dtype': 'float64'
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};
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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 - array length
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
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var x = zeros( [ len ], options );
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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 o;
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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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o = assign( x, i );
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if ( typeof o !== 'object' ) {
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b.fail( 'should return an ndarray' );
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}
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}
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b.toc();
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if ( isnan( x.get( 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 f;
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var i;
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min = 1; // 10^min
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max = 6; // 10^max
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for ( i = min; i <= max; i++ ) {
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len = pow( 10, i );
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f = createBenchmark( len );
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bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f );
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}
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}
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main();

‎lib/node_modules/@stdlib/blas/ext/unitspace/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 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 format = require( '@stdlib/string/format' );
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var pkg = require( './../package.json' ).name;
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var unitspace = require( './../lib' );
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// VARIABLES //
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var options = {
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'dtype': 'float64'
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};
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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 - array length
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
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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 o;
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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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o = unitspace( [ len ], i, options );
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if ( typeof o !== 'object' ) {
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b.fail( 'should return an ndarray' );
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}
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}
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b.toc();
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if ( isnan( o.get( 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 f;
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var i;
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min = 1; // 10^min
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max = 6; // 10^max
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for ( i = min; i <= max; i++ ) {
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len = pow( 10, i );
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f = createBenchmark( len );
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bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f );
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}
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}
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main();

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