scipy.fftpack.idct¶
- scipy.fftpack.idct(x, type=2, n=None, axis=-1, norm=None, overwrite_x=False)[source]¶
Return the Inverse Discrete Cosine Transform of an arbitrary type sequence.
Parameters: x : array_like
The input array.
type : {1, 2, 3}, 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. If n > x.shape[axis], x is zero-padded. The default results in n = 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 : {None, ‘ortho’}, optional
Normalization mode (see Notes). Default is None.
overwrite_x : bool, optional
If True, the contents of x can be destroyed; the default is False.
Returns: idct : ndarray of real
The transformed input array.
See also
- dct
- Forward DCT
Notes
For a single dimension array x, idct(x, norm='ortho') is equal to MATLAB idct(x).
‘The’ IDCT is the IDCT of type 2, which is the same as DCT of type 3.
IDCT of type 1 is the DCT of type 1, IDCT of type 2 is the DCT of type 3, and IDCT of type 3 is the DCT of type 2. For the definition of these types, see dct.
Examples
The Type 1 DCT is equivalent to the DFT for real, even-symmetrical inputs. The output is also real and even-symmetrical. Half of the IFFT input is used to generate half of the IFFT output:
>>> from scipy.fftpack import ifft, idct >>> ifft(np.array([ 30., -8., 6., -2., 6., -8.])).real array([ 4., 3., 5., 10., 5., 3.]) >>> idct(np.array([ 30., -8., 6., -2.]), 1) / 6 array([ 4., 3., 5., 10.])