# numpy.fft.ihfft¶

`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. 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`/`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

```>>> 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 vary
```

numpy.fft.hfft

#### Next topic

numpy.fft.fftfreq