code: def smooth_hanning(x, size=11):
      
  
      if x.ndim != 1:
          raise ValueError, "smooth_hanning only accepts 1-D arrays."
      if x.size < size:
          raise ValueError, "Input vector needs to be bigger than window size."
      if size < 3:
          return x
  
      s = np.r_[x[size - 1:0:-1], x, x[-1:-size:-1]]
      w = np.hanning(size)
      y = np.convolve(w / w.sum(), s, mode='valid')
      return y
docs: smooth a 1D array using a hanning window with requested size.