numpy.random.standard_gamma(shape, size=None) Draw samples from a standard Gamma distribution. Samples are

RandomState.rayleigh(scale=1.0, size=None) Draw samples from a Rayleigh distribution. The

numpy.random.get_state() Return a tuple representing the internal state of the generator. For more details, see

RandomState.random_integers(low, high=None, size=None) Random integers of type np.int between low

numpy.random.standard_exponential(size=None) Draw samples from the standard exponential distribution.

numpy.random.geometric(p, size=None) Draw samples from the geometric distribution. Bernoulli trials are experiments

RandomState.choice(a, size=None, replace=True, p=None) Generates a random sample from a given 1-D array

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

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.