fft2(a, s=None, axes=(-2, -1), norm=None)
This function computes the n-dimensional discrete Fourier Transform over any axes in an M-dimensional array by means of the Fast Fourier Transform (FFT). By default, the transform is computed over the last two axes of the input array, i.e., a 2-dimensional FFT.
fft2
is just fftn
with a different default for :None:None:`axes`.
The output, analogously to fft
, contains the term for zero frequency in the low-order corner of the transformed 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 the axes, in order of decreasingly negative frequency.
See fftn
for details and a plotting example, and numpy.fft
for definitions and conventions used.
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 fft(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.
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 discrete Fourier Transform.
fft
The one-dimensional FFT.
fftn
The n-dimensional FFT.
fftshift
Shifts zero-frequency terms to the center of the array. For two-dimensional input, swaps first and third quadrants, and second and fourth quadrants.
ifft2
The inverse two-dimensional FFT.
numpy.fft
Overall view of discrete Fourier transforms, with definitions and conventions used.
>>> a = np.mgrid[:5, :5][0]See :
... np.fft.fft2(a) array([[ 50. +0.j , 0. +0.j , 0. +0.j , # may vary 0. +0.j , 0. +0.j ], [-12.5+17.20477401j, 0. +0.j , 0. +0.j , 0. +0.j , 0. +0.j ], [-12.5 +4.0614962j , 0. +0.j , 0. +0.j , 0. +0.j , 0. +0.j ], [-12.5 -4.0614962j , 0. +0.j , 0. +0.j , 0. +0.j , 0. +0.j ], [-12.5-17.20477401j, 0. +0.j , 0. +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.fftn
numpy.fft.fft2
numpy.fft.fft
numpy.fft.ifft2
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