idct#
- scipy.fft.idct(x, type=2, n=None, axis=-1, norm=None, overwrite_x=False, workers=None, orthogonalize=None)[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{“backward”, “ortho”, “forward”}, optional
- Normalization mode (see Notes). Default is “backward”. 
- overwrite_xbool, optional
- If True, the contents of x can be destroyed; the default is False. 
- workersint, optional
- Maximum number of workers to use for parallel computation. If negative, the value wraps around from - os.cpu_count(). See- fftfor more details.
- orthogonalizebool, optional
- Whether to use the orthogonalized IDCT variant (see Notes). Defaults to - Truewhen- norm="ortho"and- Falseotherwise.- Added in version 1.8.0. 
 
- 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).- Warning - For - type in {1, 2, 3},- norm="ortho"breaks the direct correspondence with the inverse direct Fourier transform. To recover it you must specify- orthogonalize=False.- For - norm="ortho"both the- dctand- idctare 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- dctfor the full definitions).- ‘The’ IDCT is the IDCT-II, which is the same as the normalized DCT-III. - The IDCT is equivalent to a normal DCT except for the normalization and type. DCT type 1 and 4 are their own inverse and DCTs 2 and 3 are each other’s inverses. - 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.fft 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) array([ 4., 3., 5., 10.])