code: def idct(x, type=2, n=None, axis=-1, norm=None, overwrite_x=False):
      """
      Return the Inverse Discrete Cosine Transform of an arbitrary type sequence.
  
      Parameters
      ----------
      x : array_like
          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.  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. 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
      >>> 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.])
  
      """
      type = _inverse_typemap[type]
      return _pocketfft.dct(x, type, n, axis, norm, overwrite_x)
  
file_path: catboost/contrib/python/scipy/py3/scipy/fftpack/realtransforms.py
imports: from scipy.fft import _pocketfft
  from .helper import _good_shape
label_desc: Use image node_id 6 for calling a global function with example usage: idct(x, type, n, axis, norm, overwrite_x) and returns: _pocketfft