Lock(...) |
Create a new lock object. |
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([size]) |
Return random floats in the half-open interval [0.0, 1.0). |
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). |
ranf([size]) |
Return random floats in the half-open interval [0.0, 1.0). |
rayleigh([scale, size]) |
Draw samples from a Rayleigh distribution. |
sample([size]) |
Return random floats in the half-open interval [0.0, 1.0). |
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. |
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. |