RandomState.logseries(p, size=None) Draw samples from a logarithmic series distribution. Samples are

numpy.random.hypergeometric(ngood, nbad, nsample, size=None) Draw samples from a Hypergeometric distribution.

RandomState.binomial(n, p, size=None) Draw samples from a binomial distribution. Samples are drawn from

RandomState.weibull(a, size=None) Draw samples from a Weibull distribution. Draw samples from a 1-parameter

RandomState.get_state() Return a tuple representing the internal state of the generator. For more details

numpy.random.dirichlet(alpha, size=None) Draw samples from the Dirichlet distribution. Draw size

RandomState.exponential(scale=1.0, size=None) Draw samples from an exponential distribution. Its

RandomState.bytes(length) Return random bytes.

class numpy.random.RandomState Container for the Mersenne Twister pseudo-random number generator.

numpy.random.standard_cauchy(size=None) Draw samples from a standard Cauchy distribution with mode = 0. Also