Random sampling (numpy.random)

Simple random data

rand (d0, d1, ..., dn) Random values in a given shape.
randn ([d1, ..., dn]) Return a sample (or samples) from the “standard normal” distribution.
randint (low[, high, size]) Return random integers from low (inclusive) to high (exclusive).
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).
bytes (length) Return random bytes.

Permutations

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

Distributions

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]) 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]) 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]) 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 distribution with specified shape.
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.
rayleigh ([scale, size]) Draw samples from a Rayleigh distribution.
standard_cauchy ([size]) 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]) Returns samples from a 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]) 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]) Weibull distribution.
zipf (a[, size]) Draw samples from a Zipf distribution.

Random generator

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

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