jax.numpy.fft.ifft(a, n=None, axis=-1, norm=None)[source]#

Compute the one-dimensional inverse discrete Fourier Transform.

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

Original docstring below.

This function computes the inverse of the one-dimensional n-point discrete Fourier transform computed by fft. In other words, ifft(fft(a)) == a to within numerical accuracy. For a general description of the algorithm and definitions, see numpy.fft.

The input should be ordered in the same way as is returned by fft, i.e.,

  • a[0] should contain the zero frequency term,

  • a[1:n//2] should contain the positive-frequency terms,

  • a[n//2 + 1:] should contain the negative-frequency terms, in increasing order starting from the most negative frequency.

For an even number of input points, A[n//2] represents the sum of the values at the positive and negative Nyquist frequencies, as the two are aliased together. See numpy.fft for details.

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

  • n (int, optional) – Length of the transformed axis of the output. If n is smaller than the length of the input, the input is cropped. If it is larger, the input is padded with zeros. If n is not given, the length of the input along the axis specified by axis is used. See notes about padding issues.

  • axis (int, optional) – Axis over which to compute the inverse DFT. If not given, the last axis is used.

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


out – The truncated or zero-padded input, transformed along the axis indicated by axis, or the last one if axis is not specified.

Return type:

complex ndarray