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

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

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

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

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

numpy.random.rand(d0, d1, ..., dn) Random values in a given shape. Create an array of the given shape and populate

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

RandomState.shuffle(x) Modify a sequence in-place by shuffling its contents.

RandomState.standard_normal(size=None) Draw samples from a standard Normal distribution (mean=0, stdev=1)

numpy.random.triangular(left, mode, right, size=None) Draw samples from the triangular distribution. The triangular