code: def MakeGaussianPmf(mu, sigma, num_sigmas, n=201):
      
      pmf = Pmf()
      low = mu - num_sigmas * sigma
      high = mu + num_sigmas * sigma
  
      for x in numpy.linspace(low, high, n):
          p = EvalGaussianPdf(x, mu, sigma)
          pmf.Set(x, p)
      pmf.Normalize()
      return pmf
docs: Makes a PMF discrete approx to a Gaussian distribution.
      
      mu: float mean
      sigma: float standard deviation
      num_sigmas: how many sigmas to extend in each direction
      n: number of values in the Pmf
  
      returns: normalized Pmf