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133 changes: 133 additions & 0 deletions lib/node_modules/@stdlib/fft/base/fftpack/ndarray/cffti/README.md
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<!--

@license Apache-2.0

Copyright (c) 2026 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.

-->

# cffti

> Initialize a workspace array for performing a complex-valued Fourier transform on a one-dimensional ndarray.

<section class="intro">

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var cffti = require( '@stdlib/fft/base/fftpack/ndarray/cffti' );
```

#### cffti( arrays )

Initializes a workspace array for performing a complex-valued Fourier transform on a one-dimensional ndarray.

```javascript
var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var Slice = require( '@stdlib/slice/ctor' );
var slice = require( '@stdlib/ndarray/slice' );

var N = 8;
var len = scalar2ndarray( N, {
'dtype': 'int32'
});

var workspace = new Float64Vector( ( 4*N ) + 34 );

var out = cffti( [ workspace, len ] );
// returns <ndarray>

var bool = ( out === workspace );
// returns true

var twiddleFactors = slice( workspace, new Slice( 2*N, 4*N ) );
// returns <ndarray>[ 1, 0, ~0.707, ~0.707, ~0, 1, ~-0.707, ~0.707, 1, 0, 1, 0, 1, 0, ~0, -1 ]

var factors = slice( workspace, new Slice( 4*N, ( 4*N ) + 4 ) );
// returns <ndarray>[ 8, 2, 2, 4 ]
```

The function has the following parameters:

- **arrays**: array-like object containing the following ndarrays:

- a one-dimensional input ndarray.
- a zero-dimensional ndarray containing the length of the sequence to transform.

</section>

<!-- /.usage -->

<section class="notes">

## Notes

- If provided an empty one-dimensional input ndarray, the function returns the output ndarray unchanged.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var cffti = require( '@stdlib/fft/base/fftpack/ndarray/cffti' );

var N = 8;

var workspace = new Float64Vector( ( 4*N ) + 34 );
console.log( ndarray2array( workspace ) );

var len = scalar2ndarray( N, {
'dtype': 'int32'
});

var out = cffti( [ workspace, len ] );
console.log( ndarray2array( out ) );
```

</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">

</section>

<!-- /.links -->
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/**
* @license Apache-2.0
*
* Copyright (c) 2026 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 Float64Vector = require( '@stdlib/ndarray/vector/float64' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var format = require( '@stdlib/string/format' );
var pkg = require( './../package.json' ).name;
var cffti = require( './../lib' );


// FUNCTIONS //

/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} N - sequence length
* @returns {Function} benchmark function
*/
function createBenchmark( N ) {
var workspace = new Float64Vector( ( 4*N ) + 34 );
var len = scalar2ndarray( N, {
'dtype': 'int32'
});
return benchmark;

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

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
v = cffti( [ workspace, len ] );
if ( typeof v !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( isnan( v.get( 2*N ) ) ) {
b.fail( 'should not return NaN' );
}
b.pass( 'benchmark finished' );
b.end();
}
}


// MAIN //

/**
* Main execution sequence.
*
* @private
*/
function main() {
var lengths;
var N;
var f;
var i;

lengths = [
8,
16,
32,
64,
128,
256,
512,
1024
];

for ( i = 0; i < lengths.length; i++ ) {
N = lengths[ i ];
f = createBenchmark( N );
bench( format( '%s:N=%d', pkg, N ), f );
}
}

main();
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{{alias}}( arrays )
Initializes a workspace array for performing a complex-valued Fourier
transform on a one-dimensional ndarray.

If provided an empty input ndarray, the function returns the output ndarray
unchanged.

Parameters
----------
arrays: ArrayLikeObject<ndarray>
Array-like object containing the following ndarrays:

- a one-dimensional input ndarray.
- a zero-dimensional ndarray containing the length of the sequence to
transform.

Returns
-------
out: ndarray
Output ndarray.

Examples
--------
> var N = 8;
> var workspace = new {{alias:@stdlib/ndarray/vector/float64}}( ( 4*N ) + 34 );
> var len = {{alias:@stdlib/ndarray/from-scalar}}( N, { 'dtype': 'int32' });
> var out = {{alias}}( [ workspace, len ] )
<ndarray>
> var bool = ( out === workspace )
true
> var s = new {{alias:@stdlib/slice/ctor}}( 2*N, 4*N );
> var twiddleFactors = {{alias:@stdlib/ndarray/slice}}( workspace, s )
<ndarray>
Comment on lines +33 to +34

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I did not add the values present inside the ndarray, similar to the pattern that we used in fft/base/fftpack/cffti: https://github.com/stdlib-js/stdlib/blob/develop/lib/node_modules/%40stdlib/fft/base/fftpack/cffti/docs/repl.txt#L49.

This is because, the length of the output array was exceeding 80 characters. Here is the full output array:

<ndarray>[ 1, 0, ~0.707, ~0.707, ~0, 1, ~-0.707, ~0.707, 1, 0, 1, 0, 1, 0, ~0, -1 ]

> s = new {{alias:@stdlib/slice/ctor}}( 4*N, ( 4*N ) + 4 );
> var factors = {{alias:@stdlib/ndarray/slice}}( workspace, s )
<ndarray>[ 8, 2, 2, 4 ]

See Also
--------

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/*
* @license Apache-2.0
*
* Copyright (c) 2026 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.
*/

// TypeScript Version: 4.1

/// <reference types="@stdlib/types"/>

import { typedndarray, floatndarray, genericndarray } from '@stdlib/types/ndarray';

/**
* Input array.
*/
type InputArray = floatndarray | genericndarray<number>;

/**
* Initializes a workspace array for performing a complex-valued Fourier transform on a one-dimensional ndarray.
*
* ## Notes
*
* - The function expects the following ndarrays:
*
* - a one-dimensional input ndarray.
* - a zero-dimensional ndarray containing the length of the sequence to transform.
*
* @param arrays - array-like object containing ndarrays
* @returns output ndarray
*
* @example
* var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
* var Slice = require( '@stdlib/slice/ctor' );
* var slice = require( '@stdlib/ndarray/slice' );
*
* var N = 8;
* var len = scalar2ndarray( N, {
* 'dtype': 'int32'
* });
*
* var workspace = new Float64Vector( ( 4*N ) + 34 );
*
* var out = cffti( [ workspace, len ] );
* // returns <ndarray>
*
* var bool = ( out === workspace );
* // returns true
*
* var twiddleFactors = slice( workspace, new Slice( 2*N, 4*N ) );
* // returns <ndarray>[ 1, 0, ~0.707, ~0.707, ~0, 1, ~-0.707, ~0.707, 1, 0, 1, 0, 1, 0, ~0, -1 ]
*
* var factors = slice( workspace, new Slice( 4*N, ( 4*N ) + 4 ) );
* // returns <ndarray>[ 8, 2, 2, 4 ]
*/
declare function cffti<T extends InputArray = InputArray>( arrays: [ T, typedndarray<number> ] ): T;


// EXPORTS //

export = cffti;
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