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:
- xarray_like
The input array.
- type{1, 2, 3, 4}, optional
Type of the DCT (see Notes). Default type is 2.
- nint, 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]
.- axisint, 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_xbool, optional
If True, the contents of x can be destroyed; the default is False.
- Returns:
- idctndarray 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 MATLABidct(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. IDCT of type 4 is the DCT of type 4. 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 >>> import numpy as np >>> 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.])