bundles / numpy 2.5.0.dev0+git20251130.2de293a / numpy / fft / ihfft
_ArrayFunctionDispatcher
numpy.fft:ihfft
source: build-install/usr/lib/python3.14/site-packages/numpy/fft/_pocketfft.py :632
Signature
def ihfft ( a , n = None , axis = -1 , norm = None , out = None ) Summary
Compute the inverse FFT of a signal that has Hermitian symmetry.
Parameters
a: array_likeInput array.
n: int, optionalLength of the inverse FFT, the number of points along transformation axis in the input to use. If
nis smaller than the length of the input, the input is cropped. If it is larger, the input is padded with zeros. Ifnis not given, the length of the input along the axis specified byaxisis used.axis: int, optionalAxis over which to compute the inverse FFT. If not given, the last axis is used.
norm: {"backward", "ortho", "forward"}, optionalNormalization mode (see numpy.fft). Default is "backward". Indicates which direction of the forward/backward pair of transforms is scaled and with what normalization factor.
out: complex ndarray, optionalIf provided, the result will be placed in this array. It should be of the appropriate shape and dtype.
Returns
out: complex ndarrayThe truncated or zero-padded input, transformed along the axis indicated by
axis, or the last one ifaxisis not specified. The length of the transformed axis isn//2 + 1.
Notes
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.
Examples
import numpy as np spectrum = np.array([ 15, -4, 0, -1, 0, -4])✓
np.fft.ifft(spectrum) np.fft.ihfft(spectrum)✗
See also
Aliases
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numpy.fft.ihfft