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. If- n > x.shape[axis], x is zero-padded. The default results in- n = 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 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. 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.])