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262 changes: 262 additions & 0 deletions lib/node_modules/@stdlib/blas/ext/index-of/README.md
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<!--

@license Apache-2.0

Copyright (c) 2025 The Stdlib Authors.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

-->

# indexOf

> Return the first index of a specified search element along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.

<section class="usage">

## Usage

```javascript
var indexOf = require( '@stdlib/blas/ext/index-of' );
```

#### indexOf( x, searchElement\[, fromIndex]\[, options] )

Returns the first index of a specified search element along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.

```javascript
var array = require( '@stdlib/ndarray/array' );

// Create an input ndarray:
var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
// returns <ndarray>

// Find index:
var out = indexOf( x, 2.0 );
// returns <ndarray>

var idx = out.get();
// returns 1
```

The function has the following parameters:

- **x**: input [ndarray][@stdlib/ndarray/ctor].
- **searchElement**: element in an input [ndarray][@stdlib/ndarray/ctor] for which to find an index. May be either a scalar value or an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] same as the data type of the input [ndarray][@stdlib/ndarray/ctor]. If provided a scalar value, the value is cast to the data type of the input [ndarray][@stdlib/ndarray/ctor]. 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]`, the search element [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], the search element [ndarray][@stdlib/ndarray/ctor] must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor].
- **fromIndex**: index from which to begin searching (_optional_). May be either a scalar value or an [ndarray][@stdlib/ndarray/ctor] having an `integer` 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]`, an [ndarray][@stdlib/ndarray/ctor] containing the index from which to begin searching 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], an [ndarray][@stdlib/ndarray/ctor] containing the index from which to begin searching must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor]. By default, the the index from which to begin searching is `0`.
- **options**: function options (_optional_).

The function accepts the following options:

- **dtype**: output ndarray [data type][@stdlib/ndarray/dtypes]. Must be an "integer_index_and_generic" [data type][@stdlib/ndarray/dtypes].
- **dims**: list of dimensions over which to perform operation. If not provided, the function performs the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor].
- **keepdims**: boolean indicating whether the reduced dimensions should be included in the returned [ndarray][@stdlib/ndarray/ctor] as singleton dimensions. Default: `false`.

If the function is unable to find a search element, the function returns `-1`.

```javascript
var array = require( '@stdlib/ndarray/array' );

// Create an input ndarray:
var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
// returns <ndarray>

// Find index:
var out = indexOf( x, 10.0 );
// returns <ndarray>

var idx = out.get();
// returns -1
```

By default, the function uses `0` as the index from which to begin searching. To begin searching from a different index, provide the `fromIndex` argument.

```javascript
var array = require( '@stdlib/ndarray/array' );

// Create an input ndarray:
var x = array( [ 1.0, 2.0, 3.0, 4.0, 2.0, 6.0 ] );
// returns <ndarray>

// Find index:
var out = indexOf( x, 2.0, 2 );
// returns <ndarray>

var idx = out.get();
// returns 4
```

By default, the function performs the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform the operation over specific dimensions, provide a `dims` option.

```javascript
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var array = require( '@stdlib/ndarray/array' );

var x = array( [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] );

var out = indexOf( x, -3.0, {
'dims': [ 0 ]
});
// returns <ndarray>

var idx = ndarray2array( out );
// returns [ 1, -1 ]
```

By default, the function returns an [`ndarray`][@stdlib/ndarray/ctor] having a shape matching only the non-reduced dimensions of the input [`ndarray`][@stdlib/ndarray/ctor] (i.e., the reduced dimensions are dropped). To include the reduced dimensions as singleton dimensions in the output [`ndarray`][@stdlib/ndarray/ctor], set the `keepdims` option to `true`.

```javascript
var array = require( '@stdlib/ndarray/array' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );

// Create an input ndarray:
var x = array( [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] );
// returns <ndarray>

var opts = {
'dims': [ 0 ],
'keepdims': true
};

// Find index:
var out = indexOf( x, -3.0, opts );
// returns <ndarray>

var idx = ndarray2array( out );
// returns [ [ 1, -1 ] ]
```

By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] determined by the function's output data type [policy][@stdlib/ndarray/output-dtype-policies]. To override the default behavior, set the `dtype` option.

```javascript
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var dtype = require( '@stdlib/ndarray/dtype' );
var array = require( '@stdlib/ndarray/array' );

var x = array( [ 1.0, 2.0, 3.0, 4.0 ] );

var idx = indexOf( x, 2.0, {
'dtype': 'int32'
});
// returns <ndarray>

var dt = dtype( idx );
// returns 'int32'
```

#### indexOf.assign( x, searchElement\[, fromIndex], out\[, options] )

Returns the first index of a specified search element along one or more [ndarray][@stdlib/ndarray/ctor] dimensions and assigns results to a provided output [ndarray][@stdlib/ndarray/ctor].

```javascript
var array = require( '@stdlib/ndarray/array' );
var zeros = require( '@stdlib/ndarray/zeros' );

var x = array( [ 1.0, 2.0, 3.0, 4.0 ] );
var y = zeros( [], {
'dtype': 'int32'
});

var out = indexOf.assign( x, 3.0, y );
// returns <ndarray>

var idx = out.get();
// returns 2

var bool = ( out === y );
// returns true
```

The method has the following parameters:

- **x**: input [ndarray][@stdlib/ndarray/ctor].
- **searchElement**: element in an input [ndarray][@stdlib/ndarray/ctor] for which to find an index. May be either a scalar value or an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] same as the data type of the input [ndarray][@stdlib/ndarray/ctor]. If provided a scalar value, the value is cast to the data type of the input [ndarray][@stdlib/ndarray/ctor]. 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]`, the search element [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], an [ndarray][@stdlib/ndarray/ctor] initial value must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor].
- **fromIndex**: index from which to begin searching (_optional_). May be either a scalar value or an [ndarray][@stdlib/ndarray/ctor] having an `integer` 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]`, an [ndarray][@stdlib/ndarray/ctor] containing the index from which to begin searching 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], an [ndarray][@stdlib/ndarray/ctor] containing the index from which to begin searching must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor]. By default, the the index from which to begin searching is `0`.
- **out**: output [ndarray][@stdlib/ndarray/ctor]. Must have an `integer` or `generic` [data type][@stdlib/ndarray/dtypes].
- **options**: function options (_optional_).

The method accepts the following options:

- **dims**: list of dimensions over which to perform operation. If not provided, the function performs the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor].

</section>

<!-- /.usage -->

<section class="notes">

## Notes

- Both functions iterate over [ndarray][@stdlib/ndarray/ctor] elements according to the memory layout of the input [ndarray][@stdlib/ndarray/ctor]. Accordingly, performance degradation is possible when operating over multiple dimensions of a large non-contiguous multi-dimensional input [ndarray][@stdlib/ndarray/ctor]. In such scenarios, one may want to copy an input [ndarray][@stdlib/ndarray/ctor] to contiguous memory before computing the cumulative sum.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var ndarray = require( '@stdlib/ndarray/ctor' );
var indexOf = require( '@stdlib/blas/ext/index-of' );

// Generate an array of random numbers:
var xbuf = discreteUniform( 10, 0, 20, {
'dtype': 'float64'
});

// Wrap in an ndarray:
var x = new ndarray( 'float64', xbuf, [ 5, 2 ], [ 2, 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

// Find index:
var idx = indexOf( x, 10.0, {
'dims': [ 0 ]
});

// Print the results:
console.log( ndarray2array( idx ) );
```

</section>

<!-- /.examples -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

</section>

<!-- /.related -->

<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="links">

[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor

[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes

[@stdlib/ndarray/output-dtype-policies]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/output-dtype-policies

[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes

</section>

<!-- /.links -->
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/**
* @license Apache-2.0
*
* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

'use strict';

// MODULES //

var bench = require( '@stdlib/bench' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pow = require( '@stdlib/math/base/special/pow' );
var uniform = require( '@stdlib/random/array/uniform' );
var zeros = require( '@stdlib/ndarray/zeros' );
var ndarray = require( '@stdlib/ndarray/base/ctor' );
var pkg = require( './../package.json' ).name;
var indexOf = require( './../lib' );


// VARIABLES //

var options = {
'dtype': 'float64'
};


// FUNCTIONS //

/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} len - array length
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
var out;
var x;

x = uniform( len, -50.0, 50.0, options );
x = new ndarray( options.dtype, x, [ len ], [ 1 ], 0, 'row-major' );

out = zeros( [], {
'dtype': 'int32'
});

return benchmark;

/**
* Benchmark function.
*
* @private
* @param {Benchmark} b - benchmark instance
*/
function benchmark( b ) {
var o;
var i;

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
o = indexOf.assign( x, 10.0, out );
if ( typeof o !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( isnan( o.get() ) ) {
b.fail( 'should not return NaN' );
}
b.pass( 'benchmark finished' );
b.end();
}
}


// MAIN //

/**
* Main execution sequence.
*
* @private
*/
function main() {
var len;
var min;
var max;
var f;
var i;

min = 1; // 10^min
max = 6; // 10^max

for ( i = min; i <= max; i++ ) {
len = pow( 10, i );
f = createBenchmark( len );
bench( pkg+':assign:dtype='+options.dtype+',len='+len, f );
}
}

main();
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