code: def slepian(M, width, sym=True):
      """Return a digital Slepian (DPSS) window.
  
      Used to maximize the energy concentration in the main lobe.  Also called
      the digital prolate spheroidal sequence (DPSS).
  
      .. note:: Deprecated in SciPy 1.1.
                `slepian` will be removed in a future version of SciPy, it is
                replaced by `dpss`, which uses the standard definition of a
                digital Slepian window.
  
      Parameters
      ----------
      M : int
          Number of points in the output window. If zero or less, an empty
          array is returned.
      width : float
          Bandwidth
      sym : bool, optional
          When True (default), generates a symmetric window, for use in filter
          design.
          When False, generates a periodic window, for use in spectral analysis.
  
      Returns
      -------
      w : ndarray
          The window, with the maximum value always normalized to 1
  
      See Also
      --------
      dpss
  
      References
      ----------
      .. [1] D. Slepian & H. O. Pollak: "Prolate spheroidal wave functions,
             Fourier analysis and uncertainty-I," Bell Syst. Tech. J., vol.40,
             pp.43-63, 1961. https://archive.org/details/bstj40-1-43
      .. [2] H. J. Landau & H. O. Pollak: "Prolate spheroidal wave functions,
             Fourier analysis and uncertainty-II," Bell Syst. Tech. J. , vol.40,
             pp.65-83, 1961. https://archive.org/details/bstj40-1-65
  
      Examples
      --------
      Plot the window and its frequency response:
  
      >>> from scipy import signal
      >>> from scipy.fftpack import fft, fftshift
      >>> import matplotlib.pyplot as plt
  
      >>> window = signal.slepian(51, width=0.3)
      >>> plt.plot(window)
      >>> plt.title("Slepian (DPSS) window (BW=0.3)")
      >>> plt.ylabel("Amplitude")
      >>> plt.xlabel("Sample")
  
      >>> plt.figure()
      >>> A = fft(window, 2048) / (len(window)/2.0)
      >>> freq = np.linspace(-0.5, 0.5, len(A))
      >>> response = 20 * np.log10(np.abs(fftshift(A / abs(A).max())))
      >>> plt.plot(freq, response)
      >>> plt.axis([-0.5, 0.5, -120, 0])
      >>> plt.title("Frequency response of the Slepian window (BW=0.3)")
      >>> plt.ylabel("Normalized magnitude [dB]")
      >>> plt.xlabel("Normalized frequency [cycles per sample]")
  
      """
      warnings.warn(
          "slepian is deprecated and will be removed in a future "
          "version, use dpss instead",
          DeprecationWarning,
      )
      if _len_guards(M):
          return np.ones(M)
      M, needs_trunc = _extend(M, sym)
  
      # our width is the full bandwidth
      width = width / 2
      # to match the old version
      width = width / 2
      m = np.arange(M, dtype="d")
      H = np.zeros((2, M))
      H[0, 1:] = m[1:] * (M - m[1:]) / 2
      H[1, :] = ((M - 1 - 2 * m) / 2) ** 2 * np.cos(2 * np.pi * width)
  
      _, win = linalg.eig_banded(
          H, select="i", select_range=(M - 1, M - 1)
      )
      win = win.ravel() / win.max()
  
      return _truncate(win, needs_trunc)
  
imports: from __future__ import division, print_function, absolute_import
  import operator
  import warnings
  import numpy
  from scipy import fftpack, linalg, special
  from scipy._lib.six import string_types
label_desc: Use image node_id 24 for calling a global function with example usage: slepian(M, width, sym) and returns: _truncate, np