scipy.fftpack.dctn(x, type=2, shape=None, axes=None, norm=None, overwrite_x=False)[source]#

Return multidimensional Discrete Cosine Transform along the specified axes.


The input array.

type{1, 2, 3, 4}, optional

Type of the DCT (see Notes). Default type is 2.

shapeint or array_like of ints or None, optional

The shape of the result. If both shape and axes (see below) are None, shape is x.shape; if shape is None but axes is not None, then shape is numpy.take(x.shape, axes, axis=0). If shape[i] > x.shape[i], the ith dimension is padded with zeros. If shape[i] < x.shape[i], the ith dimension is truncated to length shape[i]. If any element of shape is -1, the size of the corresponding dimension of x is used.

axesint or array_like of ints or None, optional

Axes along which the DCT is computed. The default is over all axes.

norm{None, ‘ortho’}, optional

Normalization mode (see Notes). Default is None.

overwrite_xbool, optional

If True, the contents of x can be destroyed; the default is False.

yndarray of real

The transformed input array.

See also


Inverse multidimensional DCT


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


>>> import numpy as np
>>> from scipy.fftpack import dctn, idctn
>>> rng = np.random.default_rng()
>>> y = rng.standard_normal((16, 16))
>>> np.allclose(y, idctn(dctn(y, norm='ortho'), norm='ortho'))