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

RandomState.gumbel(loc=0.0, scale=1.0, size=None) Draw samples from a Gumbel distribution. Draw samples

numpy.random.noncentral_f(dfnum, dfden, nonc, size=None) Draw samples from the noncentral F distribution. Samples

numpy.random.power(a, size=None) Draws samples in [0, 1] from a power distribution with positive exponent a - 1. Also

RandomState.randint(low, high=None, size=None, dtype='l') Return random integers from low (inclusive)

numpy.random.sample(size=None) Return random floats in the half-open interval [0.0, 1.0). Results are from the

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

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

RandomState.uniform(low=0.0, high=1.0, size=None) Draw samples from a uniform distribution. Samples are

RandomState.multivariate_normal(mean, cov[, size]) Draw random samples from a multivariate normal