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

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

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

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

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

RandomState.weibull(a, size=None) Draw samples from a Weibull distribution. Draw samples from a 1-parameter

RandomState.bytes(length) Return random bytes.

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

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

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