code: def hann(M, sym=True):
      r"""
      Return a Hann window.
  
      The Hann window is a taper formed by using a raised cosine or sine-squared
      with ends that touch zero.
  
      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).
  
      Notes
      -----
      The Hann window is defined as
  
      .. math::  w(n) = 0.5 - 0.5 \cos\left(\frac{2\pi{n}}{M-1}\right)
                 \qquad 0 \leq n \leq M-1
  
      The window was named for Julius von Hann, an Austrian meteorologist. It is
      also known as the Cosine Bell. It is sometimes erroneously referred to as
      the "Hanning" window, from the use of "hann" as a verb in the original
      paper and confusion with the very similar Hamming window.
  
      Most references to the Hann window come from the signal processing
      literature, where it is used as one of many windowing functions for
      smoothing values.  It is also known as an apodization (which means
      "removing the foot", i.e. smoothing discontinuities at the beginning
      and end of the sampled signal) or tapering function.
  
      For more information, see [1]_, [2]_, [3]_, and [4]_
  
      References
      ----------
      .. [1] Blackman, R.B. and Tukey, J.W., (1958) The measurement of power
             spectra, Dover Publications, New York.
      .. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics",
             The University of Alberta Press, 1975, pp. 106-108.
      .. [3] Wikipedia, "Window function",
             https://en.wikipedia.org/wiki/Window_function
      .. [4] W.H. Press,  B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling,
             "Numerical Recipes", Cambridge University Press, 1986, page 425.
  
      Examples
      --------
      Plot the window and its frequency response:
  
      >>> import cupyx.scipy.signal.windows
      >>> import cupy as cp
      >>> from cupy.fft import fft, fftshift
      >>> import matplotlib.pyplot as plt
  
      >>> window = cupyx.scipy.signal.windows.hann(51)
      >>> plt.plot(cupy.asnumpy(window))
      >>> plt.title("Hann window")
      >>> plt.ylabel("Amplitude")
      >>> plt.xlabel("Sample")
  
      >>> plt.figure()
      >>> A = fft(window, 2048) / (len(window)/2.0)
      >>> freq = cupy.linspace(-0.5, 0.5, len(A))
      >>> response = cupy.abs(fftshift(A / cupy.abs(A).max()))
      >>> response = 20 * cupy.log10(np.maximum(response, 1e-10))
      >>> plt.plot(cupy.asnumpy(freq), cupy.asnumpy(response))
      >>> plt.axis([-0.5, 0.5, -120, 0])
      >>> plt.title("Frequency response of the Hann window")
      >>> plt.ylabel("Normalized magnitude [dB]")
      >>> plt.xlabel("Normalized frequency [cycles per sample]")
  
      """
      # Docstring adapted from NumPy's hanning function
      return general_hamming(M, 0.5, sym)
  
imports: import warnings
  from typing import Set
  import cupy
  import numpy
label_desc: Use image node_id 14 for calling a global function with example usage: hann(M, sym) and returns: general_hamming