bundles / numpy 2.4.3 / numpy / fft / fft2
_ArrayFunctionDispatcher
numpy.fft:fft2
source: /numpy/fft/_pocketfft.py :1019
Signature
def fft2 ( a , s = None , axes = (-2, -1) , norm = None , out = None ) Summary
Compute the 2-dimensional discrete Fourier Transform.
Extended Summary
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.
Parameters
a: array_likeInput array, can be complex
s: sequence of ints, optionalShape (length of each transformed axis) of the output (
s[0]refers to axis 0,s[1]to axis 1, etc.). This corresponds tonforfft(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
sis not given, the shape of the input along the axes specified byaxesis used.axes: sequence of ints, optionalAxes over which to compute the FFT. If not given, the last two axes are used. A repeated index in
axesmeans the transform over that axis is performed multiple times. A one-element sequence means that a one-dimensional FFT is performed. Default:(-2, -1).norm: {"backward", "ortho", "forward"}, optionalNormalization mode (see numpy.fft). Default is "backward". Indicates which direction of the forward/backward pair of transforms is scaled and with what normalization factor.
out: complex ndarray, optionalIf provided, the result will be placed in this array. It should be of the appropriate shape and dtype for all axes (and hence only the last axis can have
snot equal to the shape at that axis).
Returns
out: complex ndarrayThe truncated or zero-padded input, transformed along the axes indicated by
axes, or the last two axes ifaxesis not given.
Raises
: ValueErrorIf
sandaxeshave different length, oraxesnot given andlen(s) != 2.: IndexErrorIf an element of
axesis larger than than the number of axes ofa.
Notes
fft2 is just fftn with a different default for 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.
Examples
import numpy as np a = np.mgrid[:5, :5][0]✓
np.fft.fft2(a)
✗See also
- 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.
Aliases
-
numpy.fft.fft2