ifft2(a, s=None, axes=(-2, -1), norm=None)
This function computes the inverse of the 2-dimensional discrete Fourier Transform over any number of axes in an M-dimensional array by means of the Fast Fourier Transform (FFT). In other words, ifft2(fft2(a)) == a
to within numerical accuracy. By default, the inverse transform is computed over the last two axes of the input array.
The input, analogously to ifft
, should be ordered in the same way as is returned by fft2
, i.e. it should have the term for zero frequency in the low-order corner of the two axes, the positive frequency terms in the first half of these axes, the term for the Nyquist frequency in the middle of the axes and the negative frequency terms in the second half of both axes, in order of decreasingly negative frequency.
ifft2
is just ifftn
with a different default for :None:None:`axes`.
See ifftn
for details and a plotting example, and numpy.fft
for definition and conventions used.
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 ifft2
is called.
Input array, can be complex.
Shape (length of each 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 each 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 FFT. If not given, the last two axes are used. A repeated index in :None:None:`axes` means the transform over that axis is performed multiple times. A one-element sequence means that a one-dimensional FFT is performed.
Normalization mode (see numpy.fft
). Default is "backward". Indicates which direction of the forward/backward pair of transforms is scaled and with what normalization factor.
The "backward", "forward" values were added.
If s and :None:None:`axes` have different length, or :None:None:`axes` not given and len(s) != 2
.
If an element of :None:None:`axes` is larger than than the number of axes of a.
The truncated or zero-padded input, transformed along the axes indicated by :None:None:`axes`, or the last two axes if :None:None:`axes` is not given.
Compute the 2-dimensional inverse discrete Fourier Transform.
fft
The one-dimensional FFT.
fft2
The forward 2-dimensional FFT, of which :None:None:`ifft2` is the inverse.
ifft
The one-dimensional inverse FFT.
ifftn
The inverse of the n-dimensional FFT.
numpy.fft
Overall view of discrete Fourier transforms, with definitions and conventions used.
>>> a = 4 * np.eye(4)See :
... np.fft.ifft2(a) array([[1.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], # may vary [0.+0.j, 0.+0.j, 0.+0.j, 1.+0.j], [0.+0.j, 0.+0.j, 1.+0.j, 0.+0.j], [0.+0.j, 1.+0.j, 0.+0.j, 0.+0.j]])
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.fft.fft2
numpy.fft.ifft
numpy.fft.ifft2
numpy.fft.ifftn
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