code: def dst(x, type=2, n=None, axis=-1, norm=None, overwrite_x=False):
      r"""
      Return the Discrete Sine Transform of arbitrary type sequence x.
  
      Parameters
      ----------
      x : array_like
          The input array.
      type : {1, 2, 3, 4}, optional
          Type of the DST (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 dst 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
      -------
      dst : ndarray of reals
          The transformed input array.
  
      See Also
      --------
      idst : Inverse DST
  
      Notes
      -----
      For a single dimension array ``x``.
  
      There are, theoretically, 8 types of the DST for different combinations of
      even/odd boundary conditions and boundary off sets [1]_, only the first
      4 types are implemented in scipy.
  
      **Type I**
  
      There are several definitions of the DST-I; we use the following
      for ``norm=None``. DST-I assumes the input is odd around `n=-1` and `n=N`.
  
      .. math::
  
          y_k = 2 \sum_{n=0}^{N-1} x_n \sin\left(\frac{\pi(k+1)(n+1)}{N+1}\right)
  
      Note that the DST-I is only supported for input size > 1.
      The (unnormalized) DST-I is its own inverse, up to a factor `2(N+1)`.
      The orthonormalized DST-I is exactly its own inverse.
  
      **Type II**
  
      There are several definitions of the DST-II; we use the following for
      ``norm=None``. DST-II assumes the input is odd around `n=-1/2` and
      `n=N-1/2`; the output is odd around :math:`k=-1` and even around `k=N-1`
  
      .. math::
  
          y_k = 2 \sum_{n=0}^{N-1} x_n \sin\left(\frac{\pi(k+1)(2n+1)}{2N}\right)
  
      if ``norm='ortho'``, ``y[k]`` is multiplied by a scaling factor ``f``
  
      .. math::
  
          f = \begin{cases}
          \sqrt{\frac{1}{4N}} & \text{if }k = 0, \\
          \sqrt{\frac{1}{2N}} & \text{otherwise} \end{cases}
  
      **Type III**
  
      There are several definitions of the DST-III, we use the following (for
      ``norm=None``). DST-III assumes the input is odd around `n=-1` and even
      around `n=N-1`
  
      .. math::
  
          y_k = (-1)^k x_{N-1} + 2 \sum_{n=0}^{N-2} x_n \sin\left(
          \frac{\pi(2k+1)(n+1)}{2N}\right)
  
      The (unnormalized) DST-III is the inverse of the (unnormalized) DST-II, up
      to a factor `2N`. The orthonormalized DST-III is exactly the inverse of the
      orthonormalized DST-II.
  
      .. versionadded:: 0.11.0
  
      **Type IV**
  
      There are several definitions of the DST-IV, we use the following (for
      ``norm=None``). DST-IV assumes the input is odd around `n=-0.5` and even
      around `n=N-0.5`
  
      .. math::
  
          y_k = 2 \sum_{n=0}^{N-1} x_n \sin\left(\frac{\pi(2k+1)(2n+1)}{4N}\right)
  
      The (unnormalized) DST-IV is its own inverse, up to a factor `2N`. The
      orthonormalized DST-IV is exactly its own inverse.
  
      .. versionadded:: 1.2.0
         Support for DST-IV.
  
      References
      ----------
      .. [1] Wikipedia, "Discrete sine transform",
             https://en.wikipedia.org/wiki/Discrete_sine_transform
  
      """
      return _pocketfft.dst(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 7 for calling a global function with example usage: dst(x, type, n, axis, norm, overwrite_x) and returns: _pocketfft