Random sampling (numpy.random)

Simple random data

rand (d0, d1, ..., dn) Random values in a given shape.
randn (d0, d1, ..., dn) Returns zero-mean, unit-variance Gaussian random numbers in an array of shape (d0, d1, ..., dn).
randint (low[, high, size]) Return random integers x such that low <= x < high.
random_integers (low[, high, size]) Return random integers x such that low <= x <= high.
random_sample ([size]) Return random floats in the half-open interval [0.0, 1.0).
bytes (length) Return random bytes.


shuffle (x) Modify a sequence in-place by shuffling its contents.
permutation (x) Randomly permute a sequence, or return a permuted range.


beta (a, b[, size]) The Beta distribution over [0, 1].
binomial (n, p[, size]) Draw samples from a binomial distribution.
chisquare (df[, size]) Draw samples from a chi-square distribution.
mtrand.dirichlet (alpha[, size]) Draw samples from the Dirichlet distribution.
exponential ([scale, size]) Exponential distribution.
f (dfnum, dfden[, size]) Draw samples from a F distribution.
gamma (shape[, scale, size]) Draw samples from a Gamma distribution.
geometric (p[, size]) Draw samples from the geometric distribution.
gumbel ([loc, scale, size]) Gumbel distribution.
hypergeometric (ngood, nbad, nsample[, size]) Draw samples from a Hypergeometric distribution.
laplace ([loc, scale, size]) Laplace or double exponential distribution.
logistic ([loc, scale, size]) Draw samples from a Logistic distribution.
lognormal ([mean, sigma, size]) Return samples drawn 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]) Negative Binomial distribution.
noncentral_chisquare (df, nonc[, size]) Draw samples from a noncentral chi-square distribution.
noncentral_f (dfnum, dfden, nonc[, size]) Noncentral F distribution.
normal ([loc, scale, size]) Draw random samples from a normal (Gaussian) distribution.
pareto (a[, size]) Draw samples from a Pareto distribution with specified shape.
poisson ([lam, size]) Poisson distribution.
power (a[, size]) Power distribution.
rayleigh ([scale, size]) Rayleigh distribution.
standard_cauchy ([size]) Standard Cauchy with mode=0.
standard_exponential ([size]) Standard exponential distribution (scale=1).
standard_gamma (shape[, size]) Standard Gamma distribution.
standard_normal ([size]) Standard Normal distribution (mean=0, stdev=1).
standard_t (df[, size]) Standard Student’s t distribution with df degrees of freedom.
triangular (left, mode, right[, size]) Triangular distribution starting at left, peaking at mode, and ending at right (left <= mode <= right).
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]) Wald (inverse Gaussian) distribution.
weibull (a[, size]) Weibull distribution.
zipf (a[, size]) Draw samples from a Zipf distribution.

Random generator

mtrand.RandomState ([seed]) Container for the Mersenne Twister PRNG.
seed ([seed]) Seed the generator.
get_state () Return a tuple representing the internal state of the generator:
set_state (state) Set the state from a tuple.