ihfft(a, n=None, axis=-1, norm=None)
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:
even: ihfft(hfft(a, 2*len(a) - 2)) == a
, within roundoff error,
odd: ihfft(hfft(a, 2*len(a) - 1)) == a
, within roundoff error.
Input array.
Length of the inverse FFT, the number of points along transformation axis in the input to use. 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 :None:None:`axis` is used.
Axis over which to compute the inverse FFT. If not given, the last axis is used.
Normalization mode (see numpy.fft
). Default is "backward". Indicates which direction of the forward/backward pair of transforms is scaled and with what normalization factor.
The "backward", "forward" values were added.
The truncated or zero-padded input, transformed along the axis indicated by :None:None:`axis`, or the last one if :None:None:`axis` is not specified. The length of the transformed axis is n//2 + 1
.
Compute the inverse FFT of a signal that has Hermitian symmetry.
>>> 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]) # may vary
>>> np.fft.ihfft(spectrum) array([ 1.-0.j, 2.-0.j, 3.-0.j, 4.-0.j]) # may varySee :
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.fft.hfft
numpy.fft.ihfft
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