scipy.fft.ihfftn¶
-
scipy.fft.
ihfftn
(x, s=None, axes=None, norm=None, overwrite_x=False, workers=None)[source]¶ Compute the N-dimensional inverse discrete Fourier Transform for a real spectrum.
This function computes the N-dimensional inverse discrete Fourier Transform over any number of axes in an M-dimensional 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
- xarray_like
Input array, taken to be real.
- ssequence 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.- axessequence 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{None, “ortho”}, optional
Normalization mode (see
fft
). Default is None.- overwrite_xbool, optional
If True, the contents of x can be destroyed; the default is False. See
fft
for more details.- workersint, optional
Maximum number of workers to use for parallel computation. If negative, the value wraps around from
os.cpu_count()
. Seefft
for more details.
- Returns
- outcomplex 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
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 byifftn
. The order of the output is the positive part of the Hermitian output signal, in the same format asrfft
.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]]])