From 4e98a1bc91be1b1a1b715ea7ac87284f80697a35 Mon Sep 17 00:00:00 2001
From: Gunj Joshi <gunjjoshi8372@gmail.com>
Date: Mon, 12 Oct 2026 23:47:12 +0530
Subject: [PATCH] feat: add fft/rfftf

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
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---
---
 lib/node_modules/@stdlib/fft/rfftf/README.md  | 186 ++++++
 .../fft/rfftf/benchmark/benchmark.assign.js   | 118 ++++
 .../@stdlib/fft/rfftf/benchmark/benchmark.js  | 107 ++++
 .../@stdlib/fft/rfftf/docs/repl.txt           |  90 +++
 .../@stdlib/fft/rfftf/docs/types/index.d.ts   | 187 ++++++
 .../@stdlib/fft/rfftf/docs/types/test.ts      | 182 ++++++
 .../@stdlib/fft/rfftf/examples/index.js       |  35 +
 .../@stdlib/fft/rfftf/lib/assign.js           | 178 ++++++
 .../@stdlib/fft/rfftf/lib/base.js             | 192 ++++++
 .../@stdlib/fft/rfftf/lib/index.js            |  98 +++
 .../@stdlib/fft/rfftf/lib/main.js             | 177 ++++++
 .../@stdlib/fft/rfftf/package.json            |  66 ++
 .../@stdlib/fft/rfftf/test/test.assign.js     | 598 ++++++++++++++++++
 .../@stdlib/fft/rfftf/test/test.js            |  39 ++
 .../@stdlib/fft/rfftf/test/test.main.js       | 444 +++++++++++++
 15 files changed, 2697 insertions(+)
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/README.md
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/benchmark/benchmark.assign.js
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/benchmark/benchmark.js
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/docs/repl.txt
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/docs/types/index.d.ts
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/docs/types/test.ts
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/examples/index.js
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/lib/assign.js
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/lib/base.js
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/lib/index.js
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/lib/main.js
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/package.json
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/test/test.assign.js
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/test/test.js
 create mode 100644 lib/node_modules/@stdlib/fft/rfftf/test/test.main.js

diff --git a/lib/node_modules/@stdlib/fft/rfftf/README.md b/lib/node_modules/@stdlib/fft/rfftf/README.md
new file mode 100644
index 000000000000..692078f12848
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/README.md
@@ -0,0 +1,186 @@
+<!--
+
+@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.
+
+-->
+
+# rfftf
+
+> Return a new [ndarray][@stdlib/ndarray/ctor] containing the one-dimensional discrete Fourier transform of a real-valued input [ndarray][@stdlib/ndarray/ctor].
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var rfftf = require( '@stdlib/fft/rfftf' );
+```
+
+#### rfftf( x\[, options] )
+
+Returns a new [ndarray][@stdlib/ndarray/ctor] containing the one-dimensional discrete Fourier transform of a real-valued input [ndarray][@stdlib/ndarray/ctor].
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ 1.0, 2.0, 3.0, 4.0 ] );
+
+var out = rfftf( x );
+// returns <ndarray>
+```
+
+The function has the following parameters:
+
+-   **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a real-valued or "generic" [data type][@stdlib/ndarray/dtypes].
+-   **options**: function options (_optional_).
+
+The function accepts the following options:
+
+-   **n**: number of points over which to compute the transform. If not provided, defaults to the length of the input [ndarray][@stdlib/ndarray/ctor]. If `n` is greater than the input length, the input is zero-padded. If `n` is less than the input length, the input is truncated.
+-   **normalize**: normalization mode. Must be one of the following: `'backward'` (default), `'ortho'`, or `'forward'`.
+
+The returned [ndarray][@stdlib/ndarray/ctor] has a complex-valued floating-point [data type][@stdlib/ndarray/dtypes] determined by the input [data type][@stdlib/ndarray/dtypes]. For example, `float64` maps to `complex128`. The returned [ndarray][@stdlib/ndarray/ctor] has a length of `floor(N/2) + 1`, where `N` is the length of the sequence to transform.
+
+By default, the number of transform points equals the length of the input [ndarray][@stdlib/ndarray/ctor]. To specify a different number of transform points, provide an `n` option.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ 1.0, 2.0, 3.0, 4.0 ] );
+
+var out = rfftf( x, {
+    'n': 8
+});
+// returns <ndarray>
+```
+
+By default, no normalization is applied to the transform result. To specify a normalization mode, provide a `normalize` option.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ 1.0, 2.0, 3.0, 4.0 ] );
+
+// Scale by 1/sqrt(N):
+var out = rfftf( x, {
+    'normalize': 'ortho'
+});
+// returns <ndarray>
+```
+
+The normalization modes are as follows:
+
+-   **backward**: no normalization (default).
+-   **ortho**: scale by `1/sqrt(N)`, making the transform orthonormal.
+-   **forward**: scale by `1/N`.
+
+#### rfftf.assign( x, out\[, options] )
+
+Computes the one-dimensional discrete Fourier transform of a real-valued input [ndarray][@stdlib/ndarray/ctor] and assigns the results to a provided output [ndarray][@stdlib/ndarray/ctor].
+
+```javascript
+var zeros = require( '@stdlib/ndarray/zeros' );
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ 1.0, 2.0, 3.0, 4.0 ] );
+var out = zeros( [ 3 ], {
+    'dtype': 'complex128'
+});
+
+var v = rfftf.assign( x, out );
+// returns <ndarray>
+
+var bool = ( v === out );
+// returns true
+```
+
+The function has the following parameters:
+
+-   **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a real-valued or "generic" [data type][@stdlib/ndarray/dtypes].
+-   **out**: output [ndarray][@stdlib/ndarray/ctor]. Must have a complex-valued floating-point [data type][@stdlib/ndarray/dtypes].
+-   **options**: function options (_optional_).
+
+The function accepts the following options:
+
+-   **n**: number of points over which to compute the transform. If not provided, defaults to the length of the input [ndarray][@stdlib/ndarray/ctor]. If `n` is greater than the input length, the input is zero-padded. If `n` is less than the input length, the input is truncated.
+-   **normalize**: normalization mode. Must be one of the following: `'backward'` (default), `'ortho'`, or `'forward'`.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   The function does **not** mutate the input [ndarray][@stdlib/ndarray/ctor].
+-   The output [ndarray][@stdlib/ndarray/ctor] contains only the non-negative frequency terms of the full DFT, exploiting the Hermitian symmetry of real-valued input. For an input of length `N`, the output has length `floor(N/2) + 1`.
+-   The output [ndarray][@stdlib/ndarray/ctor] has a complex-valued floating-point [data type][@stdlib/ndarray/dtypes] determined by the input [data type][@stdlib/ndarray/dtypes]. For example, `float64` input maps to `complex128` output.
+-   The DC component (index `0`) and, for even-length transforms, the Nyquist component (last index) are always purely real (i.e., have zero imaginary parts).
+-   This transform is unnormalized by default. A call to this function followed by a call performing a backward transform will multiply the input by `N`. To obtain an orthonormal transform, set the `normalize` option to `'ortho'`.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var uniform = require( '@stdlib/random/uniform' );
+var rfftf = require( '@stdlib/fft/rfftf' );
+
+// Generate an ndarray of random numbers:
+var x = uniform( [ 8 ], -10.0, 10.0, {
+    'dtype': 'float64'
+});
+console.log( ndarray2array( x ) );
+
+// Perform operation:
+var out = rfftf( x );
+
+// Print the results:
+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">
+
+[@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
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/fft/rfftf/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/fft/rfftf/benchmark/benchmark.assign.js
new file mode 100644
index 000000000000..8506cfe11814
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/benchmark/benchmark.assign.js
@@ -0,0 +1,118 @@
+/**
+* @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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var floor = require( '@stdlib/math/base/special/floor' );
+var uniform = require( '@stdlib/random/uniform' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var reinterpret128 = require( '@stdlib/strided/base/reinterpret-complex128' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var assign = require( './../lib/assign.js' );
+
+
+// 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 M;
+	var x;
+
+	M = floor( len/2 ) + 1;
+	x = uniform( [ len ], -50.0, 50.0, options );
+	out = zeros( [ M ], {
+		'dtype': 'complex128'
+	});
+
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var view;
+		var o;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			o = assign( x, out );
+			if ( typeof o !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		view = reinterpret128( getData( o ), 0 );
+		if ( isnan( view[ 0 ] ) ) {
+			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( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/fft/rfftf/benchmark/benchmark.js b/lib/node_modules/@stdlib/fft/rfftf/benchmark/benchmark.js
new file mode 100644
index 000000000000..45a168ebc790
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/benchmark/benchmark.js
@@ -0,0 +1,107 @@
+/**
+* @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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var uniform = require( '@stdlib/random/uniform' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var reinterpret128 = require( '@stdlib/strided/base/reinterpret-complex128' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var rfftf = 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 x = uniform( [ len ], -50.0, 50.0, options );
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var view;
+		var o;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			o = rfftf( x );
+			if ( typeof o !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		view = reinterpret128( getData( o ), 0 );
+		if ( isnan( view[ 0 ] ) ) {
+			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( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/fft/rfftf/docs/repl.txt b/lib/node_modules/@stdlib/fft/rfftf/docs/repl.txt
new file mode 100644
index 000000000000..cd954fc65176
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/docs/repl.txt
@@ -0,0 +1,90 @@
+
+{{alias}}( x[, options] )
+    Returns a new ndarray containing the one-dimensional discrete Fourier
+    transform of a real-valued input ndarray.
+
+    The returned ndarray has a complex-valued floating-point data type
+    determined by the input data type. For example, `float64` maps to
+    `complex128`.
+
+    The returned ndarray has a length of `floor(N/2) + 1`, where `N` is the
+    length of the sequence to transform.
+
+    Parameters
+    ----------
+    x: ndarray
+        Input array. Must have a real-valued or "generic" data type.
+
+    options: Object (optional)
+        Function options.
+
+    options.n: integer (optional)
+        Number of points over which to compute the transform. If not provided,
+        the number of points is equal to the length of the input array. If the
+        value is greater than the length of the input array, the input is
+        zero-padded. If the value is less than the length of the input array,
+        the input is truncated.
+
+    options.normalize: string (optional)
+        Normalization mode. Must be one of the following: 'backward' (default),
+        'ortho', or 'forward'. When set to 'backward', no normalization is
+        applied. When set to 'ortho', the result is scaled by `1/sqrt(n)`.
+        When set to 'forward', the result is scaled by `1/n`.
+
+    Returns
+    -------
+    out: ndarray
+        Output array.
+
+    Examples
+    --------
+    > var x = {{alias:@stdlib/ndarray/array}}( [ 1.0, 2.0, 3.0, 4.0 ] );
+    > var out = {{alias}}( x )
+    <ndarray>
+
+
+{{alias}}.assign( x, out[, options] )
+    Computes the one-dimensional discrete Fourier transform of a real-valued
+    input ndarray and assigns the results to a provided output ndarray.
+
+    Parameters
+    ----------
+    x: ndarray
+        Input array. Must have a real-valued or "generic" data type.
+
+    out: ndarray
+        Output array. Must have a complex-valued floating-point data type.
+
+    options: Object (optional)
+        Function options.
+
+    options.n: integer (optional)
+        Number of points over which to compute the transform. If not provided,
+        the number of points is equal to the length of the input array. If the
+        value is greater than the length of the input array, the input is
+        zero-padded. If the value is less than the length of the input array,
+        the input is truncated.
+
+    options.normalize: string (optional)
+        Normalization mode. Must be one of the following: 'backward' (default),
+        'ortho', or 'forward'. When set to 'backward', no normalization is
+        applied. When set to 'ortho', the result is scaled by `1/sqrt(n)`.
+        When set to 'forward', the result is scaled by `1/n`.
+
+    Returns
+    -------
+    out: ndarray
+        Output array.
+
+    Examples
+    --------
+    > var x = {{alias:@stdlib/ndarray/array}}( [ 1.0, 2.0, 3.0, 4.0 ] );
+    > var opts = { 'dtype': 'complex128' };
+    > var out = {{alias:@stdlib/ndarray/zeros}}( [ 3 ], opts );
+    > var v = {{alias}}.assign( x, out )
+    <ndarray>
+    > var bool = ( v === out )
+    true
+
+    See Also
+    --------
diff --git a/lib/node_modules/@stdlib/fft/rfftf/docs/types/index.d.ts b/lib/node_modules/@stdlib/fft/rfftf/docs/types/index.d.ts
new file mode 100644
index 000000000000..8ad97a723a13
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/docs/types/index.d.ts
@@ -0,0 +1,187 @@
+/*
+* @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 { realndarray, complexndarray, genericndarray } from '@stdlib/types/ndarray';
+
+/**
+* Input array.
+*/
+type InputArray = realndarray | genericndarray<number>;
+
+/**
+* Interface defining options.
+*/
+interface Options {
+	/**
+	* Number of points over which to compute the transform.
+	*/
+	n?: number;
+
+	/**
+	* Normalization mode.
+	*/
+	normalize?: 'backward' | 'ortho' | 'forward';
+}
+
+/**
+* Interface for computing the forward real FFT.
+*/
+interface Rfftf {
+	/**
+	* Returns a new ndarray containing the one-dimensional discrete Fourier transform of a real-valued input ndarray.
+	*
+	* @param x - input ndarray
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	* var ndarray = require( '@stdlib/ndarray/ctor' );
+	*
+	* // Create a data buffer:
+	* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	*
+	* // Define the shape of the input array:
+	* var sh = [ 4 ];
+	*
+	* // Define the array strides:
+	* var sx = [ 1 ];
+	*
+	* // Define the index offset:
+	* var ox = 0;
+	*
+	* // Create an input ndarray:
+	* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+	*
+	* // Perform operation:
+	* var out = rfftf( x );
+	* // returns <ndarray>[ <Complex128>[ 10.0, 0.0 ], <Complex128>[ -2.0, 2.0 ], <Complex128>[ -2.0, 0.0 ] ]
+	*/
+	( x: InputArray, options?: Options ): complexndarray;
+
+	/**
+	* Computes the one-dimensional discrete Fourier transform of a real-valued input ndarray and assigns the results to a provided output ndarray.
+	*
+	* @param x - input ndarray
+	* @param out - output ndarray
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	* var ndarray = require( '@stdlib/ndarray/ctor' );
+	* var zeros = require( '@stdlib/ndarray/zeros' );
+	*
+	* // Create a data buffer:
+	* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	*
+	* // Define the shape of the input array:
+	* var sh = [ 4 ];
+	*
+	* // Define the array strides:
+	* var sx = [ 1 ];
+	*
+	* // Define the index offset:
+	* var ox = 0;
+	*
+	* // Create an input ndarray:
+	* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+	*
+	* // Create an output ndarray:
+	* var out = zeros( [ 3 ], { 'dtype': 'complex128' } );
+	*
+	* // Perform operation:
+	* var v = rfftf.assign( x, out );
+	* // returns <ndarray>[ <Complex128>[ 10.0, 0.0 ], <Complex128>[ -2.0, 2.0 ], <Complex128>[ -2.0, 0.0 ] ]
+	*
+	* var bool = ( v === out );
+	* // returns true
+	*/
+	assign<T extends complexndarray>( x: InputArray, out: T, options?: Options ): T;
+}
+
+/**
+* Returns a new ndarray containing the one-dimensional discrete Fourier transform of a real-valued input ndarray.
+*
+* @param x - input ndarray
+* @param options - function options
+* @returns output ndarray
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 4 ];
+*
+* // Define the array strides:
+* var sx = [ 1 ];
+*
+* // Define the index offset:
+* var ox = 0;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Perform operation:
+* var out = rfftf( x );
+* // returns <ndarray>[ <Complex128>[ 10.0, 0.0 ], <Complex128>[ -2.0, 2.0 ], <Complex128>[ -2.0, 0.0 ] ]
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var zeros = require( '@stdlib/ndarray/zeros' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 4 ];
+*
+* // Define the array strides:
+* var sx = [ 1 ];
+*
+* // Define the index offset:
+* var ox = 0;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Create an output ndarray:
+* var out = zeros( [ 3 ], { 'dtype': 'complex128' } );
+*
+* // Perform operation:
+* var v = rfftf.assign( x, out );
+* // returns <ndarray>[ <Complex128>[ 10.0, 0.0 ], <Complex128>[ -2.0, 2.0 ], <Complex128>[ -2.0, 0.0 ] ]
+*
+* var bool = ( v === out );
+* // returns true
+*/
+declare const rfftf: Rfftf;
+
+
+// EXPORTS //
+
+export = rfftf;
diff --git a/lib/node_modules/@stdlib/fft/rfftf/docs/types/test.ts b/lib/node_modules/@stdlib/fft/rfftf/docs/types/test.ts
new file mode 100644
index 000000000000..7f8ffdfb3da9
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/docs/types/test.ts
@@ -0,0 +1,182 @@
+/*
+* @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.
+*/
+
+/* eslint-disable space-in-parens */
+
+/// <reference types="@stdlib/types"/>
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import rfftf = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+	const x = zeros( [ 4 ], {
+		'dtype': 'float64'
+	});
+
+	rfftf( x ); // $ExpectType complexndarray
+	rfftf( x, {} ); // $ExpectType complexndarray
+	rfftf( x, { 'n': 8 } ); // $ExpectType complexndarray
+	rfftf( x, { 'normalize': 'ortho' } ); // $ExpectType complexndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an ndarray...
+{
+	rfftf( '5' ); // $ExpectError
+	rfftf( 5 ); // $ExpectError
+	rfftf( true ); // $ExpectError
+	rfftf( false ); // $ExpectError
+	rfftf( null ); // $ExpectError
+	rfftf( void 0 ); // $ExpectError
+	rfftf( {} ); // $ExpectError
+	rfftf( ( x: number ): number => x ); // $ExpectError
+
+	rfftf( '5', {} ); // $ExpectError
+	rfftf( 5, {} ); // $ExpectError
+	rfftf( true, {} ); // $ExpectError
+	rfftf( false, {} ); // $ExpectError
+	rfftf( null, {} ); // $ExpectError
+	rfftf( void 0, {} ); // $ExpectError
+	rfftf( {}, {} ); // $ExpectError
+	rfftf( ( x: number ): number => x, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an options argument which is not an object...
+{
+	const x = zeros( [ 4 ], {
+		'dtype': 'float64'
+	});
+
+	rfftf( x, '5' ); // $ExpectError
+	rfftf( x, 5 ); // $ExpectError
+	rfftf( x, true ); // $ExpectError
+	rfftf( x, false ); // $ExpectError
+	rfftf( x, null ); // $ExpectError
+	rfftf( x, [] ); // $ExpectError
+	rfftf( x, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 4 ], {
+		'dtype': 'float64'
+	});
+
+	rfftf(); // $ExpectError
+	rfftf( x, {}, {} ); // $ExpectError
+}
+
+// Attached to the function is an `assign` method which returns an ndarray...
+{
+	const x = zeros( [ 4 ], {
+		'dtype': 'float64'
+	});
+	const out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	rfftf.assign( x, out ); // $ExpectType complex128ndarray
+	rfftf.assign( x, out, {} ); // $ExpectType complex128ndarray
+	rfftf.assign( x, out, { 'normalize': 'ortho' } ); // $ExpectType complex128ndarray
+	rfftf.assign( x, out, { 'n': 8 } ); // $ExpectType complex128ndarray
+}
+
+// The compiler throws an error if the `assign` method is provided a first argument which is not an ndarray...
+{
+	const out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	rfftf.assign( '5', out ); // $ExpectError
+	rfftf.assign( 5, out ); // $ExpectError
+	rfftf.assign( true, out ); // $ExpectError
+	rfftf.assign( false, out ); // $ExpectError
+	rfftf.assign( null, out ); // $ExpectError
+	rfftf.assign( void 0, out ); // $ExpectError
+	rfftf.assign( {}, out ); // $ExpectError
+	rfftf.assign( ( x: number ): number => x, out ); // $ExpectError
+
+	rfftf.assign( '5', out, {} ); // $ExpectError
+	rfftf.assign( 5, out, {} ); // $ExpectError
+	rfftf.assign( true, out, {} ); // $ExpectError
+	rfftf.assign( false, out, {} ); // $ExpectError
+	rfftf.assign( null, out, {} ); // $ExpectError
+	rfftf.assign( void 0, out, {} ); // $ExpectError
+	rfftf.assign( {}, out, {} ); // $ExpectError
+	rfftf.assign( ( x: number ): number => x, out, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided an output argument which is not an ndarray...
+{
+	const x = zeros( [ 4 ], {
+		'dtype': 'float64'
+	});
+
+	rfftf.assign( x, '5' ); // $ExpectError
+	rfftf.assign( x, 5 ); // $ExpectError
+	rfftf.assign( x, true ); // $ExpectError
+	rfftf.assign( x, false ); // $ExpectError
+	rfftf.assign( x, null ); // $ExpectError
+	rfftf.assign( x, void 0 ); // $ExpectError
+	rfftf.assign( x, {} ); // $ExpectError
+	rfftf.assign( x, ( x: number ): number => x ); // $ExpectError
+
+	rfftf.assign( x, '5', {} ); // $ExpectError
+	rfftf.assign( x, 5, {} ); // $ExpectError
+	rfftf.assign( x, true, {} ); // $ExpectError
+	rfftf.assign( x, false, {} ); // $ExpectError
+	rfftf.assign( x, null, {} ); // $ExpectError
+	rfftf.assign( x, void 0, {} ); // $ExpectError
+	rfftf.assign( x, {}, {} ); // $ExpectError
+	rfftf.assign( x, ( x: number ): number => x, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided an options argument which is not an object...
+{
+	const x = zeros( [ 4 ], {
+		'dtype': 'float64'
+	});
+	const out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	rfftf.assign( x, out, '5' ); // $ExpectError
+	rfftf.assign( x, out, 5 ); // $ExpectError
+	rfftf.assign( x, out, true ); // $ExpectError
+	rfftf.assign( x, out, false ); // $ExpectError
+	rfftf.assign( x, out, null ); // $ExpectError
+	rfftf.assign( x, out, [] ); // $ExpectError
+	rfftf.assign( x, out, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 4 ], {
+		'dtype': 'float64'
+	});
+	const out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	rfftf.assign(); // $ExpectError
+	rfftf.assign( x ); // $ExpectError
+	rfftf.assign( x, out, {}, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/fft/rfftf/examples/index.js b/lib/node_modules/@stdlib/fft/rfftf/examples/index.js
new file mode 100644
index 000000000000..db3a363d7861
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/examples/index.js
@@ -0,0 +1,35 @@
+/**
+* @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';
+
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var uniform = require( '@stdlib/random/uniform' );
+var rfftf = require( './../lib' );
+
+// Generate an ndarray of random numbers:
+var x = uniform( [ 8 ], -10.0, 10.0, {
+	'dtype': 'float64'
+});
+console.log( ndarray2array( x ) );
+
+// Perform operation:
+var out = rfftf( x );
+
+// Print the results:
+console.log( ndarray2array( out ) );
diff --git a/lib/node_modules/@stdlib/fft/rfftf/lib/assign.js b/lib/node_modules/@stdlib/fft/rfftf/lib/assign.js
new file mode 100644
index 000000000000..705bf5e0ddc6
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/lib/assign.js
@@ -0,0 +1,178 @@
+/**
+* @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 hasOwnProp = require( '@stdlib/assert/has-own-property' );
+var isPlainObject = require( '@stdlib/assert/is-plain-object' );
+var isNonNegativeInteger = require( '@stdlib/assert/is-nonnegative-integer' ).isPrimitive;
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var floor = require( '@stdlib/math/base/special/floor' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var getShape = require( '@stdlib/ndarray/shape' );
+var getOrder = require( '@stdlib/ndarray/order' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var sliceTo = require( '@stdlib/ndarray/base/slice-to' );
+var gcopy = require( '@stdlib/blas/base/gcopy' ).ndarray;
+var baseZeros = require( '@stdlib/ndarray/base/zeros' );
+var reinterpret128 = require( '@stdlib/strided/base/reinterpret-complex128' );
+var reinterpret64 = require( '@stdlib/strided/base/reinterpret-complex64' );
+var gscal = require( '@stdlib/blas/base/gscal' ).ndarray;
+var contains = require( '@stdlib/array/base/assert/contains' );
+var join = require( '@stdlib/array/base/join' );
+var format = require( '@stdlib/string/format' );
+var base = require( './base.js' );
+
+
+// VARIABLES //
+
+var NORMS = [ 'backward', 'ortho', 'forward' ];
+
+
+// MAIN //
+
+/**
+* Computes the one-dimensional discrete Fourier transform of a real-valued input ndarray and assigns the result to a provided output ndarray.
+*
+* @param {ndarrayLike} x - input ndarray
+* @param {ndarrayLike} out - output ndarray
+* @param {Options} [options] - function options
+* @param {NonNegativeInteger} [options.n] - number of points over which to compute the transform
+* @param {string} [options.normalize='backward'] - normalization mode
+* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {TypeError} second argument must be an ndarray-like object
+* @throws {TypeError} options argument must be an object
+* @throws {Error} must provide valid options
+* @returns {ndarrayLike} output ndarray
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var zeros = require( '@stdlib/ndarray/zeros' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 4 ];
+*
+* // Define the array strides:
+* var sx = [ 1 ];
+*
+* // Define the index offset:
+* var ox = 0;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Create an output ndarray:
+* var out = zeros( [ 3 ], { 'dtype': 'complex128' } );
+*
+* // Perform operation:
+* var v = rfftf( x, out );
+* // returns <ndarray>[ <Complex128>[ 10.0, 0.0 ], <Complex128>[ -2.0, 2.0 ], <Complex128>[ -2.0, 0.0 ] ]
+*
+* var bool = ( v === out );
+* // returns true
+*/
+function rfftf( x, out ) {
+	var options;
+	var norm;
+	var view;
+	var xdt;
+	var odt;
+	var sh;
+	var M;
+	var N;
+	var n;
+	var y;
+	var s;
+
+	if ( !isndarrayLike( x ) ) {
+		throw new TypeError( format( 'invalid argument. First argument must be an ndarray-like object. Value: `%s`.', x ) );
+	}
+	if ( !isndarrayLike( out ) ) {
+		throw new TypeError( format( 'invalid argument. Second argument must be an ndarray-like object. Value: `%s`.', out ) );
+	}
+	norm = 'backward';
+	xdt = getDType( x );
+	odt = getDType( out );
+	sh = getShape( x );
+	N = sh[ 0 ];
+	n = N;
+	if ( arguments.length > 2 ) {
+		options = arguments[ 2 ];
+		if ( !isPlainObject( options ) ) {
+			throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', options ) );
+		}
+		if ( hasOwnProp( options, 'n' ) ) {
+			n = options.n;
+			if ( !isNonNegativeInteger( n ) ) {
+				throw new TypeError( format( 'invalid option. `%s` option must be a nonnegative integer. Option: `%s`.', 'n', n ) );
+			}
+		}
+		if ( hasOwnProp( options, 'normalize' ) ) {
+			norm = options.normalize;
+			if ( !contains( NORMS, norm ) ) {
+				throw new TypeError( format( 'invalid option. `%s` option must be one of the following: "%s". Option: `%s`.', 'normalize', join( NORMS, '", "' ), norm ) );
+			}
+		}
+	}
+	M = floor( n/2 ) + 1;
+
+	// When n differs from N, create a new input of length n:
+	if ( n !== N ) {
+		if ( n < N ) {
+			// Create a view of the first n elements:
+			x = sliceTo( x, [ n ], false, false );
+		} else {
+			// Create a new array of length n and copy the first N elements:
+			y = baseZeros( xdt, [ n ], getOrder( x ) );
+			gcopy( N, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), 1, 0 ); // eslint-disable-line max-len
+			x = y;
+		}
+	}
+	// Compute the forward FFT:
+	base( out, x );
+
+	// Apply normalization:
+	if ( norm !== 'backward' ) {
+		if ( odt === 'complex128' ) {
+			view = reinterpret128( getData( out ), 0 );
+		} else {
+			view = reinterpret64( getData( out ), 0 );
+		}
+		if ( norm === 'ortho' ) {
+			s = 1.0 / sqrt( n );
+		} else {
+			s = 1.0 / n;
+		}
+		gscal( 2*M, s, view, 1, 0 );
+	}
+	return out;
+}
+
+
+// EXPORTS //
+
+module.exports = rfftf;
diff --git a/lib/node_modules/@stdlib/fft/rfftf/lib/base.js b/lib/node_modules/@stdlib/fft/rfftf/lib/base.js
new file mode 100644
index 000000000000..3223f737b66e
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/lib/base.js
@@ -0,0 +1,192 @@
+/**
+* @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';
+
+/* eslint-disable vars-on-top */
+
+// MODULES //
+
+var dtypes = require( '@stdlib/ndarray/dtypes' );
+var factory = require( '@stdlib/ndarray/base/nullary-strided1d-dispatch-factory' );
+var isEven = require( '@stdlib/math/base/assert/is-even' );
+var floor = require( '@stdlib/math/base/special/floor' );
+var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var gcopy = require( '@stdlib/blas/base/gcopy' ).ndarray;
+var reinterpret = require( '@stdlib/strided/base/reinterpret-complex' );
+var reinterpret128 = require( '@stdlib/strided/base/reinterpret-complex128' );
+var reinterpret64 = require( '@stdlib/strided/base/reinterpret-complex64' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Float32Array = require( '@stdlib/array/float32' );
+var drffti = require( '@stdlib/fft/base/fftpack/float64/rffti' );
+var drfftf = require( '@stdlib/fft/base/fftpack/float64/rfftf' );
+var srffti = require( '@stdlib/fft/base/fftpack/float32/rffti' );
+var srfftf = require( '@stdlib/fft/base/fftpack/float32/rfftf' );
+var grffti = require( '@stdlib/fft/base/fftpack/generic/rffti' );
+var grfftf = require( '@stdlib/fft/base/fftpack/generic/rfftf' );
+
+
+// FUNCTIONS //
+
+/**
+* Computes the forward FFT and writes results to the output complex ndarray.
+*
+* @private
+* @param {Function} reinterpret - complex-to-real reinterpret function
+* @param {Function} rffti - workspace initialization function
+* @param {Function} rfftf - forward FFT function
+* @param {Function} Workspace - typed array constructor for workspace
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing ndarrays
+* @returns {void}
+*/
+function kernel( reinterpret, rffti, rfftf, Workspace, arrays ) {
+	var view;
+	var out;
+	var M;
+	var N;
+	var w;
+	var x;
+
+	out = arrays[ 0 ];
+	x = arrays[ 1 ];
+	N = numelDimension( x, 0 );
+	M = floor( N/2 ) + 1;
+	view = reinterpret( getData( out ), 0 );
+
+	if ( N === 0 ) {
+		return;
+	}
+	// Copy the input into the output buffer at offset 1:
+	gcopy( N, getData( x ), getStride( x, 0 ), getOffset( x ), view, 1, 1 );
+
+	// Initialize the workspace and compute the forward FFT in-place:
+	w = new Workspace( ( 2*N ) + 34 );
+	rffti( N, w, 1, 0 );
+	rfftf( N, view, 1, 1, w, 1, 0 );
+
+	// Move the DC component from the imaginary slot to the real slot of the first complex element and zero out the imaginary part:
+	view[ 0 ] = view[ 1 ];
+	view[ 1 ] = 0.0;
+
+	// For even-length sequences, zero out the imaginary part of the Nyquist component:
+	if ( isEven( N ) ) {
+		view[ ( 2*M ) - 1 ] = 0.0;
+	}
+}
+
+/**
+* Computes the forward FFT of a real-valued input.
+*
+* @private
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing ndarrays
+* @returns {void}
+*/
+function gkernel( arrays ) {
+	kernel( reinterpret, grffti, grfftf, Float64Array, arrays );
+}
+
+/**
+* Computes the forward FFT of a real-valued double-precision input.
+*
+* @private
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing ndarrays
+* @returns {void}
+*/
+function dkernel( arrays ) {
+	kernel( reinterpret128, drffti, drfftf, Float64Array, arrays );
+}
+
+/**
+* Computes the forward FFT of a real-valued single-precision input.
+*
+* @private
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing ndarrays
+* @returns {void}
+*/
+function skernel( arrays ) {
+	kernel( reinterpret64, srffti, srfftf, Float32Array, arrays );
+}
+
+
+// VARIABLES //
+
+var idtypes = dtypes( 'real_and_generic' );
+var odtypes = dtypes( 'complex_floating_point' );
+var table = {
+	'types': [
+		'complex128',
+		'complex64'
+	],
+	'fcns': [
+		dkernel,
+		skernel
+	],
+	'default': gkernel
+};
+
+
+// MAIN //
+
+/**
+* Computes the one-dimensional discrete Fourier transform of a real-valued input ndarray and assigns the results to a provided output ndarray.
+*
+* @private
+* @name rfftf
+* @type {Function}
+* @param {ndarray} out - output ndarray
+* @param {ndarray} x - input ndarray
+* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {TypeError} second argument must be an ndarray-like object
+* @returns {ndarray} output ndarray
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var Complex128Array = require( '@stdlib/array/complex128' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 4 ];
+*
+* // Define the array strides:
+* var sx = [ 1 ];
+*
+* // Define the index offset:
+* var ox = 0;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Create an output ndarray:
+* var out = new ndarray( 'complex128', new Complex128Array( 3 ), [ 3 ], [ 1 ], 0, 'row-major' );
+*
+* // Perform operation:
+* var v = rfftf( out, x );
+* // returns <ndarray>[ <Complex128>[ 10.0, 0.0 ], <Complex128>[ -2.0, 2.0 ], <Complex128>[ -2.0, 0.0 ] ]
+*/
+var rfftf = factory( table, [ idtypes ], odtypes );
+
+
+// EXPORTS //
+
+module.exports = rfftf;
diff --git a/lib/node_modules/@stdlib/fft/rfftf/lib/index.js b/lib/node_modules/@stdlib/fft/rfftf/lib/index.js
new file mode 100644
index 000000000000..56d823be6d8f
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/lib/index.js
@@ -0,0 +1,98 @@
+/**
+* @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';
+
+/**
+* Return a new ndarray containing the one-dimensional discrete Fourier transform of a real-valued input ndarray.
+*
+* @module @stdlib/fft/rfftf
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var rfftf = require( '@stdlib/fft/rfftf' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 4 ];
+*
+* // Define the array strides:
+* var sx = [ 1 ];
+*
+* // Define the index offset:
+* var ox = 0;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Perform operation:
+* var out = rfftf( x );
+* // returns <ndarray>[ <Complex128>[ 10.0, 0.0 ], <Complex128>[ -2.0, 2.0 ], <Complex128>[ -2.0, 0.0 ] ]
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var zeros = require( '@stdlib/ndarray/zeros' );
+* var rfftf = require( '@stdlib/fft/rfftf' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 4 ];
+*
+* // Define the array strides:
+* var sx = [ 1 ];
+*
+* // Define the index offset:
+* var ox = 0;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Create an output ndarray:
+* var out = zeros( [ 3 ], { 'dtype': 'complex128' } );
+*
+* // Perform operation:
+* var v = rfftf.assign( x, out );
+* // returns <ndarray>[ <Complex128>[ 10.0, 0.0 ], <Complex128>[ -2.0, 2.0 ], <Complex128>[ -2.0, 0.0 ] ]
+*
+* var bool = ( v === out );
+* // returns true
+*/
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var main = require( './main.js' );
+var assign = require( './assign.js' );
+
+
+// MAIN //
+
+setReadOnly( main, 'assign', assign );
+
+
+// EXPORTS //
+
+module.exports = main;
+
+// exports: { "assign": "main.assign" }
diff --git a/lib/node_modules/@stdlib/fft/rfftf/lib/main.js b/lib/node_modules/@stdlib/fft/rfftf/lib/main.js
new file mode 100644
index 000000000000..8bdc39e1de11
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/lib/main.js
@@ -0,0 +1,177 @@
+/**
+* @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 hasOwnProp = require( '@stdlib/assert/has-own-property' );
+var isPlainObject = require( '@stdlib/assert/is-plain-object' );
+var isNonNegativeInteger = require( '@stdlib/assert/is-nonnegative-integer' ).isPrimitive;
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var floor = require( '@stdlib/math/base/special/floor' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var unaryOutputDataType = require( '@stdlib/ndarray/base/unary-output-dtype' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var getShape = require( '@stdlib/ndarray/shape' );
+var getOrder = require( '@stdlib/ndarray/order' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var sliceTo = require( '@stdlib/ndarray/base/slice-to' );
+var gcopy = require( '@stdlib/blas/base/gcopy' ).ndarray;
+var empty = require( '@stdlib/ndarray/empty' );
+var baseZeros = require( '@stdlib/ndarray/base/zeros' );
+var reinterpret128 = require( '@stdlib/strided/base/reinterpret-complex128' );
+var reinterpret64 = require( '@stdlib/strided/base/reinterpret-complex64' );
+var gscal = require( '@stdlib/blas/base/gscal' ).ndarray;
+var contains = require( '@stdlib/array/base/assert/contains' );
+var join = require( '@stdlib/array/base/join' );
+var format = require( '@stdlib/string/format' );
+var base = require( './base.js' );
+
+
+// VARIABLES //
+
+var NORMS = [ 'backward', 'ortho', 'forward' ];
+
+
+// MAIN //
+
+/**
+* Returns a new ndarray containing the one-dimensional discrete Fourier transform of a real-valued input ndarray.
+*
+* @param {ndarrayLike} x - input ndarray
+* @param {Options} [options] - function options
+* @param {NonNegativeInteger} [options.n] - number of points over which to compute the transform
+* @param {string} [options.normalize='backward'] - normalization mode
+* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {TypeError} options argument must be an object
+* @throws {Error} must provide valid options
+* @returns {ndarray} output ndarray
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 4 ];
+*
+* // Define the array strides:
+* var sx = [ 1 ];
+*
+* // Define the index offset:
+* var ox = 0;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Perform operation:
+* var out = rfftf( x );
+* // returns <ndarray>[ <Complex128>[ 10.0, 0.0 ], <Complex128>[ -2.0, 2.0 ], <Complex128>[ -2.0, 0.0 ] ]
+*/
+function rfftf( x ) {
+	var options;
+	var norm;
+	var view;
+	var xdt;
+	var odt;
+	var sh;
+	var M;
+	var N;
+	var n;
+	var o;
+	var y;
+	var s;
+
+	if ( !isndarrayLike( x ) ) {
+		throw new TypeError( format( 'invalid argument. First argument must be an ndarray-like object. Value: `%s`.', x ) );
+	}
+	norm = 'backward';
+	xdt = getDType( x );
+	sh = getShape( x );
+	N = sh[ 0 ];
+	n = N;
+	if ( arguments.length > 1 ) {
+		options = arguments[ 1 ];
+		if ( !isPlainObject( options ) ) {
+			throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', options ) );
+		}
+		if ( hasOwnProp( options, 'n' ) ) {
+			n = options.n;
+			if ( !isNonNegativeInteger( n ) ) {
+				throw new TypeError( format( 'invalid option. `%s` option must be a nonnegative integer. Option: `%s`.', 'n', n ) );
+			}
+		}
+		if ( hasOwnProp( options, 'normalize' ) ) {
+			norm = options.normalize;
+			if ( !contains( NORMS, norm ) ) {
+				throw new TypeError( format( 'invalid option. `%s` option must be one of the following: "%s". Option: `%s`.', 'normalize', join( NORMS, '", "' ), norm ) );
+			}
+		}
+	}
+	M = floor( n/2 ) + 1;
+
+	// Resolve the output complex data type:
+	odt = unaryOutputDataType( xdt, 'complex_floating_point' );
+
+	// Create the output ndarray:
+	o = empty( [ M ], {
+		'dtype': odt,
+		'order': getOrder( x )
+	});
+
+	// When n differs from N, create a new input of length n:
+	if ( n !== N ) {
+		if ( n < N ) {
+			// Create a view of the first n elements:
+			x = sliceTo( x, [ n ], false, false );
+		} else {
+			// Create a new array of length n and copy the first N elements:
+			y = baseZeros( getDType( x ), [ n ], getOrder( x ) );
+			gcopy( N, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), 1, 0 ); // eslint-disable-line max-len
+			x = y;
+		}
+	}
+	// Compute the forward FFT:
+	base( o, x );
+
+	// Apply normalization:
+	if ( norm !== 'backward' ) {
+		if ( odt === 'complex128' ) {
+			view = reinterpret128( getData( o ), 0 );
+		} else {
+			view = reinterpret64( getData( o ), 0 );
+		}
+		if ( norm === 'ortho' ) {
+			s = 1.0 / sqrt( n );
+		} else {
+			s = 1.0 / n;
+		}
+		gscal( 2*M, s, view, 1, 0 );
+	}
+	return o;
+}
+
+
+// EXPORTS //
+
+module.exports = rfftf;
diff --git a/lib/node_modules/@stdlib/fft/rfftf/package.json b/lib/node_modules/@stdlib/fft/rfftf/package.json
new file mode 100644
index 000000000000..5dd00368632a
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/package.json
@@ -0,0 +1,66 @@
+{
+  "name": "@stdlib/fft/rfftf",
+  "version": "0.0.0",
+  "description": "Return a new ndarray containing the one-dimensional discrete Fourier transform of a real-valued input ndarray.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "mathematics",
+    "math",
+    "fft",
+    "fourier",
+    "transform",
+    "forward",
+    "real",
+    "rfft",
+    "dft",
+    "ndarray"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/fft/rfftf/test/test.assign.js b/lib/node_modules/@stdlib/fft/rfftf/test/test.assign.js
new file mode 100644
index 000000000000..9053adfabc41
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/test/test.assign.js
@@ -0,0 +1,598 @@
+/**
+* @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 tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var getShape = require( '@stdlib/ndarray/shape' );
+var getData = require( '@stdlib/ndarray/data-buffer' );
+var reinterpret128 = require( '@stdlib/strided/base/reinterpret-complex128' );
+var reinterpret64 = require( '@stdlib/strided/base/reinterpret-complex64' );
+var isAlmostSameValue = require( '@stdlib/number/float64/base/assert/is-almost-same-value' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var assign = require( './../lib/assign.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof assign, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object', function test( t ) {
+	var values;
+	var out;
+	var i;
+
+	out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, out );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (options)', function test( t ) {
+	var values;
+	var out;
+	var i;
+
+	out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, out, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not an ndarray-like object', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 4 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not an ndarray-like object (options)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 4 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, value, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument which is not an object', function test( t ) {
+	var values;
+	var out;
+	var x;
+	var i;
+
+	x = zeros( [ 4 ], {
+		'dtype': 'float64'
+	});
+	out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, out, value );
+		};
+	}
+});
+
+tape( 'the function computes the FFT and assigns results to an output ndarray (float64, row-major)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+	var v;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+	out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	v = assign( x, out );
+	view = reinterpret128( getData( v ), 0 );
+
+	t.strictEqual( v, out, 'returns expected value' );
+	t.strictEqual( getDType( v ), 'complex128', 'returns expected value' );
+	t.deepEqual( getShape( v ), [ 3 ], 'returns expected value' );
+
+	// Expected: (10+0i), (-2+2i), (-2+0i):
+	expected = new Float64Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function computes the FFT and assigns results to an output ndarray (float64, column-major)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+	var v;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'column-major' );
+	out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	v = assign( x, out );
+	view = reinterpret128( getData( v ), 0 );
+
+	t.strictEqual( v, out, 'returns expected value' );
+	t.strictEqual( getDType( v ), 'complex128', 'returns expected value' );
+	t.deepEqual( getShape( v ), [ 3 ], 'returns expected value' );
+
+	expected = new Float64Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function computes the FFT and assigns results to an output ndarray (float32, row-major)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+	var v;
+
+	xbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+	out = zeros( [ 3 ], {
+		'dtype': 'complex64'
+	});
+
+	v = assign( x, out );
+	view = reinterpret64( getData( v ), 0 );
+
+	t.strictEqual( v, out, 'returns expected value' );
+	t.strictEqual( getDType( v ), 'complex64', 'returns expected value' );
+	t.deepEqual( getShape( v ), [ 3 ], 'returns expected value' );
+
+	expected = new Float32Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function computes the FFT and assigns results to an output ndarray (float32, column-major)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+	var v;
+
+	xbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'column-major' );
+	out = zeros( [ 3 ], {
+		'dtype': 'complex64'
+	});
+
+	v = assign( x, out );
+	view = reinterpret64( getData( v ), 0 );
+
+	t.strictEqual( v, out, 'returns expected value' );
+	t.strictEqual( getDType( v ), 'complex64', 'returns expected value' );
+	t.deepEqual( getShape( v ), [ 3 ], 'returns expected value' );
+
+	expected = new Float32Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function computes the FFT of an odd-length input', function test( t ) {
+	var view;
+	var xbuf;
+	var out;
+	var x;
+	var v;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 5 ], [ 1 ], 0, 'row-major' );
+	out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	v = assign( x, out );
+	view = reinterpret128( getData( v ), 0 );
+
+	t.strictEqual( v, out, 'returns expected value' );
+	t.strictEqual( getDType( v ), 'complex128', 'returns expected value' );
+	t.deepEqual( getShape( v ), [ 3 ], 'returns expected value' );
+
+	// DC component:
+	t.strictEqual( view[ 0 ], 15.0, 'returns expected value' );
+	t.strictEqual( view[ 1 ], 0.0, 'returns expected value' );
+
+	// No Nyquist component for odd N:
+	t.strictEqual( out.length, 3, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function computes the FFT of a length-1 input (DC only)', function test( t ) {
+	var view;
+	var xbuf;
+	var out;
+	var x;
+	var v;
+
+	xbuf = new Float64Array( [ 7.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 1 ], [ 1 ], 0, 'row-major' );
+	out = zeros( [ 1 ], {
+		'dtype': 'complex128'
+	});
+
+	v = assign( x, out );
+	view = reinterpret128( getData( v ), 0 );
+
+	t.strictEqual( v, out, 'returns expected value' );
+	t.deepEqual( getShape( v ), [ 1 ], 'returns expected value' );
+	t.strictEqual( view[ 0 ], 7.0, 'returns expected value' );
+	t.strictEqual( view[ 1 ], 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports the `n` option for zero-padding (n > N)', function test( t ) {
+	var view;
+	var xbuf;
+	var out;
+	var x;
+	var v;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+	out = zeros( [ 5 ], {
+		'dtype': 'complex128'
+	});
+
+	v = assign( x, out, {
+		'n': 8
+	});
+	view = reinterpret128( getData( v ), 0 );
+
+	t.strictEqual( v, out, 'returns expected value' );
+	t.deepEqual( getShape( v ), [ 5 ], 'returns expected value' );
+
+	// DC component: sum of [ 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] = 10.0:
+	t.strictEqual( view[ 0 ], 10.0, 'returns expected value' );
+	t.strictEqual( view[ 1 ], 0.0, 'returns expected value' );
+
+	// Nyquist component (even n=8):
+	t.strictEqual( view[ 9 ], 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports the `n` option for truncation (n < N)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+	var v;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+	out = zeros( [ 2 ], {
+		'dtype': 'complex128'
+	});
+
+	v = assign( x, out, {
+		'n': 2
+	});
+	view = reinterpret128( getData( v ), 0 );
+
+	t.strictEqual( v, out, 'returns expected value' );
+	t.deepEqual( getShape( v ), [ 2 ], 'returns expected value' );
+
+	expected = new Float64Array( [ 3.0, 0.0, -1.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports the `normalize` option (ortho)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+	out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	assign( x, out, {
+		'normalize': 'ortho'
+	});
+	view = reinterpret128( getData( out ), 0 );
+
+	// Ortho = backward / sqrt(N) = [ 10, -2+2i, -2 ] / 2 = [ 5, -1+1i, -1 ]:
+	expected = new Float64Array( [ 5.0, 0.0, -1.0, 1.0, -1.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports the `normalize` option (forward)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+	out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	assign( x, out, {
+		'normalize': 'forward'
+	});
+	view = reinterpret128( getData( out ), 0 );
+
+	// Forward = backward / N = [ 10, -2+2i, -2 ] / 4 = [ 2.5, -0.5+0.5i, -0.5 ]:
+	expected = new Float64Array( [ 2.5, 0.0, -0.5, 0.5, -0.5, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports `n` and `normalize` options together', function test( t ) {
+	var xbuf;
+	var view;
+	var out;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+	out = zeros( [ 5 ], {
+		'dtype': 'complex128'
+	});
+
+	assign( x, out, {
+		'n': 8,
+		'normalize': 'ortho'
+	});
+	view = reinterpret128( getData( out ), 0 );
+
+	t.deepEqual( getShape( out ), [ 5 ], 'returns expected value' );
+
+	// DC component: 10 / sqrt(8):
+	t.strictEqual( isAlmostSameValue( view[ 0 ], 10.0 / sqrt( 8 ), 1 ), true, 'returns expected value' );
+	t.strictEqual( view[ 1 ], 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports strided input', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+	var v;
+
+	xbuf = new Float64Array([
+		1.0, // 0
+		99.0,
+		2.0, // 1
+		99.0,
+		3.0, // 2
+		99.0,
+		4.0, // 3
+		99.0
+	]);
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 2 ], 0, 'row-major' );
+	out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	v = assign( x, out );
+	view = reinterpret128( getData( v ), 0 );
+
+	t.strictEqual( v, out, 'returns expected value' );
+	expected = new Float64Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports input with an offset', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+	var v;
+
+	xbuf = new Float64Array([
+		99.0,
+		99.0,
+		1.0, // 0
+		2.0, // 1
+		3.0, // 2
+		4.0  // 3
+	]);
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 2, 'row-major' );
+	out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	v = assign( x, out );
+	view = reinterpret128( getData( v ), 0 );
+
+	t.strictEqual( v, out, 'returns expected value' );
+	expected = new Float64Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function computes the FFT of a generic input', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+	var v;
+
+	xbuf = [ 1.0, 2.0, 3.0, 4.0 ];
+	x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+	out = zeros( [ 3 ], {
+		'dtype': 'complex128'
+	});
+
+	v = assign( x, out );
+	view = reinterpret128( getData( v ), 0 );
+
+	t.strictEqual( v, out, 'returns expected value' );
+	t.strictEqual( getDType( v ), 'complex128', 'returns expected value' );
+	expected = new Float64Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/fft/rfftf/test/test.js b/lib/node_modules/@stdlib/fft/rfftf/test/test.js
new file mode 100644
index 000000000000..5490119e64e4
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/test/test.js
@@ -0,0 +1,39 @@
+/**
+* @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 tape = require( 'tape' );
+var isMethod = require( '@stdlib/assert/is-method' );
+var rfftf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof rfftf, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'attached to the main export is an `assign` method', function test( t ) {
+	t.strictEqual( isMethod( rfftf, 'assign' ), true, 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/fft/rfftf/test/test.main.js b/lib/node_modules/@stdlib/fft/rfftf/test/test.main.js
new file mode 100644
index 000000000000..c8dc996270e4
--- /dev/null
+++ b/lib/node_modules/@stdlib/fft/rfftf/test/test.main.js
@@ -0,0 +1,444 @@
+/**
+* @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 tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var getShape = require( '@stdlib/ndarray/shape' );
+var getData = require( '@stdlib/ndarray/data-buffer' );
+var reinterpret128 = require( '@stdlib/strided/base/reinterpret-complex128' );
+var reinterpret64 = require( '@stdlib/strided/base/reinterpret-complex64' );
+var isAlmostSameValue = require( '@stdlib/number/float64/base/assert/is-almost-same-value' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var rfftf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof rfftf, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			rfftf( value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			rfftf( value, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument which is not an object', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 4 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			rfftf( x, value );
+		};
+	}
+});
+
+tape( 'the function computes the FFT of a real-valued input (float64, row-major)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+	out = rfftf( x );
+	view = reinterpret128( getData( out ), 0 );
+
+	t.strictEqual( getDType( out ), 'complex128', 'returns expected value' );
+	t.deepEqual( getShape( out ), [ 3 ], 'returns expected value' );
+
+	// Expected: (10+0i), (-2+2i), (-2+0i):
+	expected = new Float64Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function computes the FFT of a real-valued input (float64, column-major)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'column-major' );
+	out = rfftf( x );
+	view = reinterpret128( getData( out ), 0 );
+
+	t.strictEqual( getDType( out ), 'complex128', 'returns expected value' );
+	t.deepEqual( getShape( out ), [ 3 ], 'returns expected value' );
+
+	expected = new Float64Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function computes the FFT of a real-valued input (float32, row-major)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+	out = rfftf( x );
+	view = reinterpret64( getData( out ), 0 );
+
+	t.strictEqual( getDType( out ), 'complex64', 'returns expected value' );
+	t.deepEqual( getShape( out ), [ 3 ], 'returns expected value' );
+
+	expected = new Float32Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function computes the FFT of a real-valued input (float32, column-major)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'column-major' );
+	out = rfftf( x );
+	view = reinterpret64( getData( out ), 0 );
+
+	t.strictEqual( getDType( out ), 'complex64', 'returns expected value' );
+	t.deepEqual( getShape( out ), [ 3 ], 'returns expected value' );
+
+	expected = new Float32Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function computes the FFT of an odd-length input', function test( t ) {
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 5 ], [ 1 ], 0, 'row-major' );
+	out = rfftf( x );
+	view = reinterpret128( getData( out ), 0 );
+
+	t.strictEqual( getDType( out ), 'complex128', 'returns expected value' );
+	t.deepEqual( getShape( out ), [ 3 ], 'returns expected value' );
+
+	// DC component:
+	t.strictEqual( view[ 0 ], 15.0, 'returns expected value' );
+	t.strictEqual( view[ 1 ], 0.0, 'returns expected value' );
+
+	// No Nyquist component for odd N:
+	t.strictEqual( out.length, 3, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function computes the FFT of a length-1 input (DC only)', function test( t ) {
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float64Array( [ 7.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 1 ], [ 1 ], 0, 'row-major' );
+	out = rfftf( x );
+	view = reinterpret128( getData( out ), 0 );
+
+	t.deepEqual( getShape( out ), [ 1 ], 'returns expected value' );
+	t.strictEqual( view[ 0 ], 7.0, 'returns expected value' );
+	t.strictEqual( view[ 1 ], 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports the `n` option for zero-padding (n > N)', function test( t ) {
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+	out = rfftf( x, {
+		'n': 8
+	});
+	view = reinterpret128( getData( out ), 0 );
+
+	t.deepEqual( getShape( out ), [ 5 ], 'returns expected value' );
+
+	// DC component: sum of [ 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] = 10.0:
+	t.strictEqual( view[ 0 ], 10.0, 'returns expected value' );
+	t.strictEqual( view[ 1 ], 0.0, 'returns expected value' );
+
+	// Nyquist component (even n=8):
+	t.strictEqual( view[ 9 ], 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports the `n` option for truncation (n < N)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+	out = rfftf( x, {
+		'n': 2
+	});
+	view = reinterpret128( getData( out ), 0 );
+
+	t.deepEqual( getShape( out ), [ 2 ], 'returns expected value' );
+	expected = new Float64Array( [ 3.0, 0.0, -1.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports the `normalize` option (ortho)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+	out = rfftf( x, {
+		'normalize': 'ortho'
+	});
+	view = reinterpret128( getData( out ), 0 );
+
+	// Ortho = backward / sqrt(N) = [ 10, -2+2i, -2 ] / 2 = [ 5, -1+1i, -1 ]:
+	expected = new Float64Array( [ 5.0, 0.0, -1.0, 1.0, -1.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports the `normalize` option (forward)', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+	out = rfftf( x, {
+		'normalize': 'forward'
+	});
+	view = reinterpret128( getData( out ), 0 );
+
+	// Forward = backward / N = [ 10, -2+2i, -2 ] / 4 = [ 2.5, -0.5+0.5i, -0.5 ]:
+	expected = new Float64Array( [ 2.5, 0.0, -0.5, 0.5, -0.5, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports `n` and `normalize` options together', function test( t ) {
+	var xbuf;
+	var view;
+	var out;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+	out = rfftf( x, {
+		'n': 8,
+		'normalize': 'ortho'
+	});
+	view = reinterpret128( getData( out ), 0 );
+
+	t.deepEqual( getShape( out ), [ 5 ], 'returns expected value' );
+
+	// DC component: 10 / sqrt(8):
+	t.strictEqual( isAlmostSameValue( view[ 0 ], 10.0 / sqrt( 8 ), 1 ), true, 'returns expected value' );
+	t.strictEqual( view[ 1 ], 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports strided input', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float64Array([
+		1.0, // 0
+		99.0,
+		2.0, // 1
+		99.0,
+		3.0, // 2
+		99.0,
+		4.0, // 3
+		99.0
+	]);
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 2 ], 0, 'row-major' );
+	out = rfftf( x );
+	view = reinterpret128( getData( out ), 0 );
+
+	expected = new Float64Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports input with an offset', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = new Float64Array([
+		99.0,
+		99.0,
+		1.0, // 0
+		2.0, // 1
+		3.0, // 2
+		4.0  // 3
+	]);
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 2, 'row-major' );
+	out = rfftf( x );
+	view = reinterpret128( getData( out ), 0 );
+
+	expected = new Float64Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function computes the FFT of a generic input', function test( t ) {
+	var expected;
+	var view;
+	var xbuf;
+	var out;
+	var x;
+
+	xbuf = [ 1.0, 2.0, 3.0, 4.0 ];
+	x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+	out = rfftf( x );
+	view = reinterpret128( getData( out ), 0 );
+
+	t.strictEqual( getDType( out ), 'complex128', 'returns expected value' );
+	expected = new Float64Array( [ 10.0, 0.0, -2.0, 2.0, -2.0, 0.0 ] );
+	t.deepEqual( view, expected, 'returns expected value' );
+
+	t.end();
+});