Legacy random generation — NumPy v2.6.dev0 Manual

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Seeding and state#

get_state([legacy]) Return a tuple representing the internal state of the generator. set_state(state) Set the internal state of the generator from a tuple. seed([seed]) Reseed a legacy MT19937 BitGenerator

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numpy.random.RandomState.get_state

numpy.random.RandomState.set_state

numpy.random.RandomState.seed

numpy.random.RandomState.rand

numpy.random.RandomState.randn

numpy.random.RandomState.randint

numpy.random.RandomState.random_integers

numpy.random.RandomState.random_sample

numpy.random.RandomState.choice

numpy.random.RandomState.bytes

numpy.random.RandomState.shuffle

numpy.random.RandomState.permutation

numpy.random.RandomState.beta

numpy.random.RandomState.binomial

numpy.random.RandomState.chisquare

numpy.random.RandomState.dirichlet

numpy.random.RandomState.exponential

numpy.random.RandomState.f

numpy.random.RandomState.gamma

numpy.random.RandomState.geometric

numpy.random.RandomState.gumbel

numpy.random.RandomState.hypergeometric

numpy.random.RandomState.laplace

numpy.random.RandomState.logistic

numpy.random.RandomState.lognormal

numpy.random.RandomState.logseries

numpy.random.RandomState.multinomial

numpy.random.RandomState.multivariate_normal

numpy.random.RandomState.negative_binomial

numpy.random.RandomState.noncentral_chisquare