code: def dstn(
      x, type=2, shape=None, axes=None, norm=None, overwrite_x=False
  ):
      """
      Return multidimensional Discrete Sine Transform along the specified axes.
  
      Parameters
      ----------
      x : array_like
          The input array.
      type : {1, 2, 3, 4}, optional
          Type of the DCT (see Notes). Default type is 2.
      shape : int or array_like of ints or None, optional
          The shape of the result.  If both `shape` and `axes` (see below) are
          None, `shape` is ``x.shape``; if `shape` is None but `axes` is
          not None, then `shape` is ``scipy.take(x.shape, axes, axis=0)``.
          If ``shape[i] > x.shape[i]``, the i-th dimension is padded with zeros.
          If ``shape[i] < x.shape[i]``, the i-th dimension is truncated to
          length ``shape[i]``.
          If any element of `shape` is -1, the size of the corresponding
          dimension of `x` is used.
      axes : int or array_like of ints or None, optional
          Axes along which the DCT is computed.
          The default is over all axes.
      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
      -------
      y : ndarray of real
          The transformed input array.
  
      See Also
      --------
      idstn : Inverse multidimensional DST
  
      Notes
      -----
      For full details of the DST types and normalization modes, as well as
      references, see `dst`.
  
      Examples
      --------
      >>> from scipy.fftpack import dstn, idstn
      >>> y = np.random.randn(16, 16)
      >>> np.allclose(y, idstn(dstn(y, norm='ortho'), norm='ortho'))
      True
  
      """
      x = np.asanyarray(x)
      shape, axes = _init_nd_shape_and_axes(x, shape, axes)
      for n, ax in zip(shape, axes):
          x = dst(
              x,
              type=type,
              n=n,
              axis=ax,
              norm=norm,
              overwrite_x=overwrite_x,
          )
      return x
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  from scipy.fftpack import _fftpack
  from scipy.fftpack.basic import _datacopied, _fix_shape, _asfarray
  from scipy.fftpack.helper import _init_nd_shape_and_axes
  import atexit
label_desc: Use image node_id 3 for calling a global function with example usage: dstn(x, type, shape, axes, norm, overwrite_x) and returns: x