RandomState.dirichlet(alpha, size=None) Draw samples from the Dirichlet distribution. Draw size
numpy.random.logseries(p, size=None) Draw samples from a logarithmic series distribution. Samples are drawn from
numpy.random.triangular(left, mode, right, size=None) Draw samples from the triangular distribution. The triangular
numpy.random.exponential(scale=1.0, size=None) Draw samples from an exponential distribution. Its probability
numpy.random.standard_cauchy(size=None) Draw samples from a standard Cauchy distribution with mode = 0. Also
RandomState.shuffle(x) Modify a sequence in-place by shuffling its contents.
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.get_state() Return a tuple representing the internal state of the generator. For more details
RandomState.triangular(left, mode, right, size=None) Draw samples from the triangular distribution. The
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