This function computes the inverse of the N-D discrete Fourier Transform over any number of axes in an M-D array by means of the Fast Fourier Transform (FFT). In other words, ifftn(fftn(x)) == x
to within numerical accuracy.
The input, analogously to ifft
, should be ordered in the same way as is returned by fftn
, i.e., it should have the term for zero frequency in all axes in the low-order corner, the positive frequency terms in the first half of all axes, the term for the Nyquist frequency in the middle of all axes and the negative frequency terms in the second half of all axes, in order of decreasingly negative frequency.
Zero-padding, analogously with ifft
, is performed by appending zeros to the input along the specified dimension. Although this is the common approach, it might lead to surprising results. If another form of zero padding is desired, it must be performed before ifftn
is called.
Input array, can be complex.
Shape (length of each transformed axis) of the output ( s[0]
refers to axis 0, s[1]
to axis 1, etc.). This corresponds to n
for ifft(x, n)
. 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 :None:None:`axes` is used. See notes for issue on ifft
zero padding.
Axes over which to compute the IFFT. If not given, the last len(s)
axes are used, or all axes if s is also not specified.
Normalization mode (see fft
). Default is "backward".
If True, the contents of x can be destroyed; the default is False. See fft
for more details.
Maximum number of workers to use for parallel computation. If negative, the value wraps around from os.cpu_count()
. See ~scipy.fft.fft
for more details.
This argument is reserved for passing in a precomputed plan provided by downstream FFT vendors. It is currently not used in SciPy.
If s and :None:None:`axes` have different length.
If an element of :None:None:`axes` is larger than than the number of axes of x.
The truncated or zero-padded input, transformed along the axes indicated by :None:None:`axes`, or by a combination of s or x, as explained in the parameters section above.
Compute the N-D inverse discrete Fourier Transform.
fftn
The forward N-D FFT, of which :None:None:`ifftn` is the inverse.
ifft
The 1-D inverse FFT.
ifft2
The 2-D inverse FFT.
ifftshift
Undoes :None:None:`fftshift`, shifts zero-frequency terms to beginning of array.
>>> import scipy.fft
... x = np.eye(4)
... scipy.fft.ifftn(scipy.fft.fftn(x, axes=(0,)), axes=(1,)) array([[1.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], # may vary [0.+0.j, 1.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 1.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 1.+0.j]])
Create and plot an image with band-limited frequency content:
>>> import matplotlib.pyplot as plt
... rng = np.random.default_rng()
... n = np.zeros((200,200), dtype=complex)
... n[60:80, 20:40] = np.exp(1j*rng.uniform(0, 2*np.pi, (20, 20)))
... im = scipy.fft.ifftn(n).real
... plt.imshow(im) <matplotlib.image.AxesImage object at 0x...>
>>> plt.show()
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.fft._basic.irfftn
scipy.fft._basic.ifftn
scipy.fft._basic.ihfftn
scipy.fft._basic.fftn
scipy.fft._basic.ifft2
scipy.fft._basic.ifft
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