cupyx.scipy.fft.idct#
- cupyx.scipy.fft.idct(x, type=2, n=None, axis=-1, norm=None, overwrite_x=False)[source]#
Return the Inverse Discrete Cosine Transform of an array, x.
- Parameters
x (cupy.ndarray) – The input array.
type ({1, 2, 3, 4}, optional) – Type of the DCT (see Notes). Default type is 2.
n (int, optional) – Length of the transform. If
n < x.shape[axis]
, x is truncated. Ifn > x.shape[axis]
, x is zero-padded. The default results inn = x.shape[axis]
.axis (int, optional) – Axis along which the idct is computed; the default is over the last axis (i.e.,
axis=-1
).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.
- Returns
idct – The transformed input array.
- Return type
cupy.ndarray of real
See also
Notes
For a single dimension array x,
idct(x, norm='ortho')
is equal to MATLABidct(x)
.For
norm="ortho"
both the dct and idct are scaled by the same overall factor in both directions. By default, the transform is also orthogonalized which for types 1, 2 and 3 means the transform definition is modified to give orthogonality of the IDCT matrix (see dct for the full definitions).‘The’ IDCT is the IDCT-II, which is the same as the normalized DCT-III 1. See the
scipy.fft.dct()
documentation for a full description of each type. CuPy currently only supports DCT types 2 and 3.References
- 1
Wikipedia, “Discrete sine transform”, https://en.wikipedia.org/wiki/Discrete_sine_transform