Compute the 2dimensional discrete Fourier Transform
This function computes the ndimensional discrete Fourier Transform over any axes in an Mdimensional 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 2dimensional FFT.
Parameters :  a : array_like
s : sequence of ints, optional
axes : sequence of ints, optional


Returns :  out : complex ndarray

Raises :  ValueError :
IndexError :

See also
Notes
fft2 is just fftn with a different default for axes.
The output, analogously to fft, contains the term for zero frequency in the loworder 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][0]
>>> np.fft.fft2(a)
array([[ 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 5.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 10.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 15.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 20.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])