Module « scipy.fft »
Signature de la fonction ihfftn
def ihfftn(x, s=None, axes=None, norm=None, overwrite_x=False, workers=None, *, plan=None)
Description
ihfftn.__doc__
Compute the N-D inverse discrete Fourier Transform for a real
spectrum.
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 :func:`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 :func:`~scipy.fft.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.
.. versionadded:: 1.5.0
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 than the number of axes of `x`.
See Also
--------
hfftn : The forward N-D FFT of Hermitian input.
hfft : The 1-D FFT of Hermitian input.
fft : The 1-D FFT, with definitions and conventions used.
fftn : The N-D FFT.
hfft2 : The 2-D FFT of Hermitian input.
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`.
Examples
--------
>>> import scipy.fft
>>> x = np.ones((2, 2, 2))
>>> scipy.fft.ihfftn(x)
array([[[1.+0.j, 0.+0.j], # may vary
[0.+0.j, 0.+0.j]],
[[0.+0.j, 0.+0.j],
[0.+0.j, 0.+0.j]]])
>>> scipy.fft.ihfftn(x, axes=(2, 0))
array([[[1.+0.j, 0.+0.j], # may vary
[1.+0.j, 0.+0.j]],
[[0.+0.j, 0.+0.j],
[0.+0.j, 0.+0.j]]])
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