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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def MakeExponentialPmf(lam, high, n=200):
 """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 """

    pmf = Pmf()
    for x in numpy.linspace(0, high, n):
        p = EvalExponentialPdf(x, lam)
        pmf.Set(x, p)
    pmf.Normalize()
    return pmf