Module « scipy.fft »
Signature de la fonction idctn
def idctn(x, type=2, s=None, axes=None, norm=None, overwrite_x=False, workers=None)
Description
idctn.__doc__
Return multidimensional Discrete Cosine Transform along the specified axes.
Parameters
----------
x : array_like
The input array.
type : {1, 2, 3, 4}, optional
Type of the DCT (see Notes). Default type is 2.
s : int or array_like of ints or None, optional
The shape of the result. If both `s` and `axes` (see below) are
None, `s` is ``x.shape``; if `s` is None but `axes` is
not None, then `s` is ``numpy.take(x.shape, axes, axis=0)``.
If ``s[i] > x.shape[i]``, the ith dimension is padded with zeros.
If ``s[i] < x.shape[i]``, the ith dimension is truncated to length
``s[i]``.
If any element of `s` is -1, the size of the corresponding dimension of
`x` is used.
axes : int or array_like of ints or None, optional
Axes over which the IDCT is computed. If not given, the last ``len(s)``
axes are used, or all axes if `s` is also not specified.
norm : {"backward", "ortho", "forward"}, optional
Normalization mode (see Notes). Default is "backward".
overwrite_x : bool, optional
If True, the contents of `x` can be destroyed; the default is False.
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.
Returns
-------
y : ndarray of real
The transformed input array.
See Also
--------
dctn : multidimensional DCT
Notes
-----
For full details of the IDCT types and normalization modes, as well as
references, see `idct`.
Examples
--------
>>> from scipy.fft import dctn, idctn
>>> rng = np.random.default_rng()
>>> y = rng.standard_normal((16, 16))
>>> np.allclose(y, idctn(dctn(y)))
True
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