numpy.fft.ihfft¶
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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 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. 
- 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 - numpy.fft). Default is None.- New in version 1.10.0. 
 - Returns: - out : complex ndarray
- The truncated or zero-padded input, transformed along the axis indicated by axis, or the last one if axis is not specified. The length of the transformed axis is - n//2 + 1.
 - Notes - hfft/- ihfftare 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- hfftfor 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.
 - Examples - >>> 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]) 
