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bundles / scipy latest / scipy / fft / _basic / ihfftn

_Function

scipy.fft._basic:ihfftn

source: /scipy/fft/_basic.py :1529

Signature

def   ihfftn ( x s = None axes = None norm = None overwrite_x = False workers = None * plan = None )

Summary

Compute the N-D inverse discrete Fourier Transform for a real spectrum.

Extended Summary

This function computes the N-D inverse discrete Fourier Transform over any number of axes in an M-D real array by means of the Fast Fourier Transform (FFT). By default, all axes are transformed, with the real transform performed over the last axis, while the remaining transforms are complex.

Parameters

x : array_like

Input array, taken to be real.

s : sequence of ints, optional

Shape (length along each transformed axis) to use from the input. (s[0] refers to axis 0, s[1] to axis 1, etc.). Along any axis, if the given shape is smaller than that of the input, the input is cropped. If it is larger, the input is padded with zeros. if s is not given, the shape of the input along the axes specified by axes is used.

axes : sequence of ints, optional

Axes over which to compute the FFT. If not given, the last len(s) axes are used, or all axes if s is also not specified.

norm : {"backward", "ortho", "forward"}, optional

Normalization mode (see fft). Default is "backward".

overwrite_x : bool, optional

If True, the contents of x can be destroyed; the default is False. See fft for more details.

workers : int, optional

Maximum number of workers to use for parallel computation. If negative, the value wraps around from os.cpu_count(). See fft for more details.

plan : object, optional

This argument is reserved for passing in a precomputed plan provided by downstream FFT vendors. It is currently not used in SciPy.

Returns

out : complex ndarray

The truncated or zero-padded input, transformed along the axes indicated by axes, or by a combination of s and x, as explained in the parameters section above. The length of the last axis transformed will be s[-1]//2+1, while the remaining transformed axes will have lengths according to s, or unchanged from the input.

Raises

: ValueError

If s and axes have different length.

: IndexError

If an element of axes is larger than the number of axes of x.

Notes

The transform for real input is performed over the last transformation axis, as by ihfft, then the transform over the remaining axes is performed as by ifftn. The order of the output is the positive part of the Hermitian output signal, in the same format as rfft.

Array API Standard Support

ihfftn has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

====================  ====================  ====================
Library               CPU                   GPU
====================  ====================  ====================
NumPy                 ✅                     n/a                 
CuPy                  n/a                   ✅                   
PyTorch               ✅                     ✅                   
JAX                   ✅                     ✅                   
Dask                  ⚠️ computes graph     n/a                 
====================  ====================  ====================

See dev-arrayapi for more information.

Examples

import scipy.fft
import numpy as np
x = np.ones((2, 2, 2))
scipy.fft.ihfftn(x)
scipy.fft.ihfftn(x, axes=(2, 0))

See also

fft

The 1-D FFT, with definitions and conventions used.

fftn

The N-D FFT.

hfft

The 1-D FFT of Hermitian input.

hfft2

The 2-D FFT of Hermitian input.

hfftn

The forward N-D FFT of Hermitian input.

Aliases

  • scipy.fft.ihfftn