numpy.random.RandomState
numpy.random.RandomState
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class numpy.random.RandomState
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Container for the Mersenne Twister pseudo-random number generator.
RandomState
exposes a number of methods for generating random numbers drawn from a variety of probability distributions. In addition to the distribution-specific arguments, each method takes a keyword argumentsize
that defaults toNone
. Ifsize
isNone
, then a single value is generated and returned. Ifsize
is an integer, then a 1-D array filled with generated values is returned. Ifsize
is a tuple, then an array with that shape is filled and returned.Parameters: seed : {None, int, array_like}, optional
Random seed initializing the pseudo-random number generator. Can be an integer, an array (or other sequence) of integers of any length, or
None
(the default). Ifseed
isNone
, thenRandomState
will try to read data from/dev/urandom
(or the Windows analogue) if available or seed from the clock otherwise.Notes
The Python stdlib module “random” also contains a Mersenne Twister pseudo-random number generator with a number of methods that are similar to the ones available in
RandomState
.RandomState
, besides being NumPy-aware, has the advantage that it provides a much larger number of probability distributions to choose from.Methods
beta
(a, b[, size])Draw samples from a Beta distribution. binomial
(n, p[, size])Draw samples from a binomial distribution. bytes
(length)Return random bytes. chisquare
(df[, size])Draw samples from a chi-square distribution. choice
(a[, size, replace, p])Generates a random sample from a given 1-D array dirichlet
(alpha[, size])Draw samples from the Dirichlet distribution. exponential
([scale, size])Draw samples from an exponential distribution. f
(dfnum, dfden[, size])Draw samples from an F distribution. gamma
(shape[, scale, size])Draw samples from a Gamma distribution. geometric
(p[, size])Draw samples from the geometric distribution. get_state
()Return a tuple representing the internal state of the generator. gumbel
([loc, scale, size])Draw samples from a Gumbel distribution. hypergeometric
(ngood, nbad, nsample[, size])Draw samples from a Hypergeometric distribution. laplace
([loc, scale, size])Draw samples from the Laplace or double exponential distribution with specified location (or mean) and scale (decay). logistic
([loc, scale, size])Draw samples from a logistic distribution. lognormal
([mean, sigma, size])Draw samples from a log-normal distribution. logseries
(p[, size])Draw samples from a logarithmic series distribution. multinomial
(n, pvals[, size])Draw samples from a multinomial distribution. multivariate_normal
(mean, cov[, size])Draw random samples from a multivariate normal distribution. negative_binomial
(n, p[, size])Draw samples from a negative binomial distribution. noncentral_chisquare
(df, nonc[, size])Draw samples from a noncentral chi-square distribution. noncentral_f
(dfnum, dfden, nonc[, size])Draw samples from the noncentral F distribution. normal
([loc, scale, size])Draw random samples from a normal (Gaussian) distribution. pareto
(a[, size])Draw samples from a Pareto II or Lomax distribution with specified shape. permutation
(x)Randomly permute a sequence, or return a permuted range. poisson
([lam, size])Draw samples from a Poisson distribution. power
(a[, size])Draws samples in [0, 1] from a power distribution with positive exponent a - 1. rand
(d0, d1, ..., dn)Random values in a given shape. randint
(low[, high, size])Return random integers from low
(inclusive) tohigh
(exclusive).randn
(d0, d1, ..., dn)Return a sample (or samples) from the “standard normal” distribution. random_integers
(low[, high, size])Return random integers between low
andhigh
, inclusive.random_sample
([size])Return random floats in the half-open interval [0.0, 1.0). rayleigh
([scale, size])Draw samples from a Rayleigh distribution. seed
([seed])Seed the generator. set_state
(state)Set the internal state of the generator from a tuple. shuffle
(x)Modify a sequence in-place by shuffling its contents. standard_cauchy
([size])Draw samples from a standard Cauchy distribution with mode = 0. standard_exponential
([size])Draw samples from the standard exponential distribution. standard_gamma
(shape[, size])Draw samples from a standard Gamma distribution. standard_normal
([size])Draw samples from a standard Normal distribution (mean=0, stdev=1). standard_t
(df[, size])Draw samples from a standard Student’s t distribution with df
degrees of freedom.tomaxint
([size])Random integers between 0 and sys.maxint
, inclusive.triangular
(left, mode, right[, size])Draw samples from the triangular distribution. uniform
([low, high, size])Draw samples from a uniform distribution. vonmises
(mu, kappa[, size])Draw samples from a von Mises distribution. wald
(mean, scale[, size])Draw samples from a Wald, or inverse Gaussian, distribution. weibull
(a[, size])Draw samples from a Weibull distribution. zipf
(a[, size])Draw samples from a Zipf distribution.
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Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.10.1/reference/generated/numpy.random.RandomState.html