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.

Parameters

x : array_like

The input array.

n : int, optional

Length of the transformed axis of the output. For n output points, n//2 + 1 input points are necessary. If the input is longer than this, it is cropped. If it is shorter than this, it is padded with zeros. If n is not given, it is taken to be 2*(m-1) , where m is the length of the input along the axis specified by :None:None:`axis`.

axis : int, optional

Axis over which to compute the FFT. If not given, the last axis is used.

norm : {"backward", "ortho", "forward"}, optional

Normalization mode (see fft ). Default is "backward".

overwrite_x : bool, optional

If True, the contents of x can be destroyed; the default is False. See fft for more details.

workers : int, optional

Maximum number of workers to use for parallel computation. If negative, the value wraps around from os.cpu_count() . See ~scipy.fft.fft for more details.

plan : object, optional

This argument is reserved for passing in a precomputed plan provided by downstream FFT vendors. It is currently not used in SciPy.

versionadded

Raises

IndexError

If :None:None:`axis` is larger than the last axis of a.

Returns

out : ndarray

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, or, if n is not given, 2*m - 2 , where m is the length of the transformed axis of the input. To get an odd number of output points, n must be specified, for instance, as 2*m - 1 in the typical case,

Compute the FFT of a signal that has Hermitian symmetry, i.e., a real spectrum.

See Also

hfftn

Compute the N-D FFT of a Hermitian signal.

ihfft

The inverse of :None:None:`hfft`.

rfft

Compute the 1-D FFT for real input.

Examples

>>> from scipy.fft import fft, hfft
... a = 2 * np.pi * np.arange(10) / 10
... signal = np.cos(a) + 3j * np.sin(3 * a)
... fft(signal).round(10)
array([ -0.+0.j,   5.+0.j,  -0.+0.j,  15.-0.j,   0.+0.j,   0.+0.j,
        -0.+0.j, -15.-0.j,   0.+0.j,   5.+0.j])

>>> hfft(signal[:6]).round(10) # Input first half of signal
array([  0.,   5.,   0.,  15.,  -0.,   0.,   0., -15.,  -0.,   5.])

>>> hfft(signal, 10)  # Input entire signal and truncate
array([  0.,   5.,   0.,  15.,  -0.,   0.,   0., -15.,  -0.,   5.])

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.fft._basic.ihfftn scipy.fft._basic.hfft scipy.fft._helper.next_fast_len scipy.fft._basic.ihfft

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

---

GitHub : /scipy/fft/_basic.py#467
type: <class 'uarray._Function'>
Commit: