code: def _kaiser(n, beta):
      
      from scipy.special import iv as besselI
      m = n - 1
      k = arange(0, m)
      k = 2. * beta / m * sqrt (k * (m - k))
      w = besselI (0, k) / besselI (0, beta)
      return w
docs: Independant Kaiser window
  
      For the definition of the Kaiser window, see A. V. Oppenheim & R. W. Schafer, "Discrete-Time Signal Processing".
  
      The continuous version of width n centered about x=0 is:
  
      .. note:: 2 times slower than scipy.kaiser