Notes

For full details of the DCT types and normalization modes, as well as references, see dct .

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 :None:None:`axes` (see below) are None, s is x.shape ; if s is None but :None:None:`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 DCT 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 ~scipy.fft.fft for more details.

orthogonalize : bool, optional

Whether to use the orthogonalized DCT variant (see Notes). Defaults to True when norm=="ortho" and False otherwise.

versionadded

Returns

y : ndarray of real

The transformed input array.

Return multidimensional Discrete Cosine Transform along the specified axes.

See Also

idctn

Inverse multidimensional DCT

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

See :

Back References

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

scipy.fft._realtransforms.idctn

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