code: def MakeExponentialPmf(lam, high, n=200):
      
      pmf = Pmf()
      for x in numpy.linspace(0, high, n):
          p = EvalExponentialPdf(x, lam)
          pmf.Set(x, p)
      pmf.Normalize()
      return pmf
docs: Makes a PMF discrete approx to an exponential distribution.
  
      lam: parameter lambda in events per unit time
      high: upper bound
      n: number of values in the Pmf
  
      returns: normalized Pmf