RandomState.random_sample(size=None) Return random floats in the half-open interval [0.0, 1.0). Results

numpy.random.logistic(loc=0.0, scale=1.0, size=None) Draw samples from a logistic distribution. Samples are drawn

numpy.random.standard_t(df, size=None) Draw samples from a standard Student?s t distribution with df degrees

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

RandomState.geometric(p, size=None) Draw samples from the geometric distribution. Bernoulli trials

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

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

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

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

RandomState.noncentral_chisquare(df, nonc, size=None) Draw samples from a noncentral chi-square