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

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

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

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

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

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

numpy.random.pareto(a, size=None) Draw samples from a Pareto II or Lomax distribution with specified shape. The

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

RandomState.randn(d0, d1, ..., dn) Return a sample (or samples) from the ?standard normal? distribution. If

RandomState.multinomial(n, pvals, size=None) Draw samples from a multinomial distribution. The multinomial