jax.numpy.fft.fftn

jax.numpy.fft.fftn(a, s=None, axes=None, norm=None)

Compute the N-dimensional discrete Fourier Transform.

LAX-backend implementation of numpy.fft.fftn().

Original docstring below.

This function computes the N-dimensional discrete Fourier Transform over any number of axes in an M-dimensional array by means of the Fast Fourier Transform (FFT).

Parameters:

• a (array_like) – Input array, can be complex.

• s (sequence of ints, optional) – 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 any 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.

• axes (sequence of ints, optional) – Axes over which to compute the FFT. If not given, the last len(s) axes are used, or all axes if s is also not specified. Repeated indices in axes means that the transform over that axis is performed multiple times.

• norm ({"backward", "ortho", "forward"}, optional)

Returns:

out – The truncated or zero-padded input, transformed along the axes indicated by axes, or by a combination of s and a, as explained in the parameters section above.

Return type:

complex ndarray