parameters: (M, sym=True)
return_statement: return _truncate(w, needs_trunc)
docstring: Return a modified Bartlett-Hann window.
  
      Parameters
      ----------
      M : int
          Number of points in the output window. If zero or less, an empty
          array is returned.
      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 normalized to 1 (though the value 1
          does not appear if `M` is even and `sym` is True).
  
      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.barthann(51)
      >>> plt.plot(window)
      >>> plt.title("Bartlett-Hann window")
      >>> 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 Bartlett-Hann window")
      >>> plt.ylabel("Normalized magnitude [dB]")
      >>> plt.xlabel("Normalized frequency [cycles per sample]")
docstring_summary: Return a modified Bartlett-Hann window.
docstring_tokens: Return a modified Bartlett - Hann window .
function: def barthann(M, sym=True):
      """Return a modified Bartlett-Hann window.
  
      Parameters
      ----------
      M : int
          Number of points in the output window. If zero or less, an empty
          array is returned.
      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 normalized to 1 (though the value 1
          does not appear if `M` is even and `sym` is True).
  
      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.barthann(51)
      >>> plt.plot(window)
      >>> plt.title("Bartlett-Hann window")
      >>> 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 Bartlett-Hann window")
      >>> plt.ylabel("Normalized magnitude [dB]")
      >>> plt.xlabel("Normalized frequency [cycles per sample]")
  
      """
      if _len_guards(M):
          return np.ones(M)
      M, needs_trunc = _extend(M, sym)
  
      n = np.arange(0, M)
      fac = np.abs(n / (M - 1.0) - 0.5)
      w = 0.62 - 0.48 * fac + 0.38 * np.cos(2 * np.pi * fac)
  
      return _truncate(w, needs_trunc)
function_tokens: def barthann ( M , sym = True ) : if _len_guards ( M ) : return np . ones ( M ) M , needs_trunc = _extend ( M , sym ) n = np . arange ( 0 , M ) fac = np . abs ( n / ( M - 1.0 ) - 0.5 ) w = 0.62 - 0.48 * fac + 0.38 * np . cos ( 2 * np . pi * fac ) return _truncate ( w , needs_trunc )