Module « scipy.fft »
Signature de la fonction hfft
def hfft(x, n=None, axis=-1, norm=None, overwrite_x=False, workers=None, *, plan=None)
Description
hfft.__doc__
Compute the FFT of a signal that has Hermitian symmetry, i.e., a real
spectrum.
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
`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 :func:`~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:: 1.5.0
Returns
-------
out : 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`, 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,
Raises
------
IndexError
If `axis` is larger than the last axis of `a`.
See Also
--------
rfft : Compute the 1-D FFT for real input.
ihfft : The inverse of `hfft`.
hfftn : Compute the N-D FFT of a Hermitian signal.
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
--------
>>> 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.])
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