Random sampling

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RandomState.seed()

RandomState.seed(seed=None) Seed the generator. This method is called when

2017-01-10 18:19:46

numpy.random.uniform()

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

2017-01-10 18:18:19

numpy.random.normal()

numpy.random.normal(loc=0.0, scale=1.0, size=None) Draw random samples from a normal (Gaussian) distribution. The

2017-01-10 18:18:08

RandomState.rand()

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

2017-01-10 18:19:43

RandomState.permutation()

RandomState.permutation(x) Randomly permute a sequence, or return a permuted range. If x

2017-01-10 18:19:42

numpy.random.bytes()

numpy.random.bytes(length) Return random bytes.

2017-01-10 18:17:59

numpy.random.multinomial()

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

2017-01-10 18:18:05

numpy.random.lognormal()

numpy.random.lognormal(mean=0.0, sigma=1.0, size=None) Draw samples from a log-normal distribution. Draw samples

2017-01-10 18:18:04

numpy.random.poisson()

numpy.random.poisson(lam=1.0, size=None) Draw samples from a Poisson distribution. The Poisson distribution is

2017-01-10 18:18:09

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