[SciPy-user] FFTN usage

Stefan van der Walt stefan@sun.ac...
Fri Feb 8 19:45:25 CST 2008

Hi Brad

On Fri, Feb 08, 2008 at 05:33:02PM -0800, Brad Malone wrote:
> So let's say I have a grid of values with [i,j,k] where i,j,k each go
> from 0 to 3. How do I compute the Fourier transform of this grid using
> fftn?  Is the first argument a 1D array that goes through my 3D array
> along some standard path (last column goes fastest, or something like
> this?), or is the first argument actually a 3D array itself?  I looked
> at the documentation but it wasn't clear to me.

I assume your values are packed into an array of shape (4,4,4).
`fftn` can be seen as the equivalent of running a one-dimensional FFT
along every axis of that array, i.e. along rows, columns and depth.
You can further adjust the working by specifying keywords:

np.fft.fftn(a, s=None, axes=None)
    fftn(a, s=None, axes=None)
    The n-dimensional fft of a. s is a sequence giving the shape of the input
    an result along the transformed axes, as n for fft. Results are packed
    analogously to fft: the term for zero frequency in all axes is in the
    low-order corner, while the term for the Nyquist frequency in all axes is
    in the middle.
    If neither s nor axes is specified, the transform is taken along all
    axes. If s is specified and axes is not, the last len(s) axes are used.
    If axes are specified and s is not, the input shape along the specified
    axes is used. If s and axes are both specified and are not the same
    length, an exception is raised.

Btw, this docstring was obtained by typing

  import numpy as np

in IPython.


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