Wrapping of numpy.fft.fft2

The axis along which the FFT is applied must have only one chunk. To change the array’s chunking use dask.Array.rechunk.

The numpy.fft.fft2 docstring follows below:

Compute the 2-dimensional discrete Fourier Transform.

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
aarray_like

Input array, can be complex

ssequence of ints, optional

Shape (length of each transformed axis) of the output (`s` refers to axis 0, `s` 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 axes is used.

axessequence of ints, optional

Axes over which to compute the FFT. If not given, the last two axes are used. A repeated index in axes means the transform over that axis is performed multiple times. A one-element sequence means that a one-dimensional FFT is performed.

norm{“backward”, “ortho”, “forward”}, optional

New in version 1.10.0.

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.

New in version 1.20.0: The “backward”, “forward” values were added.

Returns
outcomplex ndarray

The truncated or zero-padded input, transformed along the axes indicated by axes, or the last two axes if axes is not given.

Raises
ValueError

If s and axes have different length, or axes not given and `len(s) != 2`.

IndexError

If an element of axes is larger than than the number of axes of a.

`numpy.fft`

Overall view of discrete Fourier transforms, with definitions and conventions used.

`ifft2`

The inverse two-dimensional FFT.

`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.

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

```>>> a = np.mgrid[:5, :5]
>>> 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        ]])
```