code: def make_1D_gauss(n, m, s):
      
      x = np.arange(n, dtype=np.float64)
      h = np.exp(-(x - m)**2 / (2 * s**2))
      return h / h.sum()
docs: return a 1D histogram for a gaussian distribution (n bins, mean m and std s)
  
      Parameters
      ----------
  
      n : int
          number of bins in the histogram
      m : float
          mean value of the gaussian distribution
      s : float
          standard deviaton of the gaussian distribution
  
  
      Returns
      -------
      h : np.array (n,)
            1D histogram for a gaussian distribution