class numpy.random.RandomState
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 argument size
that defaults to None
. If size
is None
, then a single value is generated and returned. If size
is an integer, then a 1-D array filled with generated values is returned. If size
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 |
---|
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.
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) to high (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 and high , 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