numpy.fft.ihfft(a, n=None, axis=-1, norm=None)
[source]
Compute the inverse FFT of a signal that has Hermitian symmetry.
Parameters: |
a : array_like Input array. n : int, optional Length of the inverse FFT, the number of points along transformation axis in the input to use. If axis : int, optional Axis over which to compute the inverse FFT. If not given, the last axis is used. norm : {None, “ortho”}, optional Normalization mode (see New in version 1.10.0. |
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Returns: |
out : complex ndarray The truncated or zero-padded input, transformed along the axis indicated by |
hfft
/ihfft
are a pair analogous to rfft
/irfft
, but for the opposite case: here the signal has Hermitian symmetry in the time domain and is real in the frequency domain. So here it’s hfft
for which you must supply the length of the result if it is to be odd:
ihfft(hfft(a, 2*len(a) - 2) == a
, within roundoff error,ihfft(hfft(a, 2*len(a) - 1) == a
, within roundoff error.>>> spectrum = np.array([ 15, -4, 0, -1, 0, -4]) >>> np.fft.ifft(spectrum) array([ 1.+0.j, 2.-0.j, 3.+0.j, 4.+0.j, 3.+0.j, 2.-0.j]) >>> np.fft.ihfft(spectrum) array([ 1.-0.j, 2.-0.j, 3.-0.j, 4.-0.j])
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https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.fft.ihfft.html