Method expovariate

Lib/random.py:605–623

Exponential distribution. lambd is 1.0 divided by the desired mean. It should be nonzero. (The parameter would be called "lambda", but that is a reserved word in Python.) Returned values range from 0 to positive infinity if lambd is positive, and from negative

(self, lambd=1.0)

        return _exp(self.normalvariate(mu, sigma))

    def expovariate(self, lambd=1.0):
        """Exponential distribution.

        lambd is 1.0 divided by the desired mean.  It should be
        nonzero.  (The parameter would be called "lambda", but that is
        a reserved word in Python.)  Returned values range from 0 to
        positive infinity if lambd is positive, and from negative
        infinity to 0 if lambd is negative.

        The mean (expected value) and variance of the random variable are:

            E[X] = 1 / lambd
            Var[X] = 1 / lambd ** 2

        """
        # we use 1-random() instead of random() to preclude the
        # possibility of taking the log of zero.

        return -_log(1.0 - self.random()) / lambd

    def vonmisesvariate(self, mu, kappa):
        """Circular data distribution.