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_likeInput array, taken to be real.
s: sequence of ints, optionalShape (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. ifsis not given, the shape of the input along the axes specified byaxesis used.axes: sequence of ints, optionalAxes over which to compute the FFT. If not given, the last
len(s)axes are used, or all axes ifsis also not specified.norm: {"backward", "ortho", "forward"}, optionalNormalization mode (see fft). Default is "backward".
overwrite_x: bool, optionalIf True, the contents of
xcan be destroyed; the default is False. See fft for more details.workers: int, optionalMaximum 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, optionalThis argument is reserved for passing in a precomputed plan provided by downstream FFT vendors. It is currently not used in SciPy.
Returns
out: complex ndarrayThe truncated or zero-padded input, transformed along the axes indicated by
axes, or by a combination ofsandx, as explained in the parameters section above. The length of the last axis transformed will bes[-1]//2+1, while the remaining transformed axes will have lengths according tos, or unchanged from the input.
Raises
: ValueErrorIf
sandaxeshave different length.: IndexErrorIf an element of
axesis larger than the number of axes ofx.
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-arrayapifor 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