class mars.tensor.random.RandomState(seed=None)[source]#



beta(a, b[, size, chunk_size, gpu, dtype])

Draw samples from a Beta distribution.

binomial(n, p[, size, chunk_size, gpu, dtype])

Draw samples from a binomial distribution.


Return random bytes.

chisquare(df[, size, chunk_size, gpu, dtype])

Draw samples from a chi-square distribution.

choice(a[, size, replace, p, chunk_size, gpu])

Generates a random sample from a given 1-D array

dirichlet(alpha[, size, chunk_size, gpu, dtype])

Draw samples from the Dirichlet distribution.

exponential([scale, size, chunk_size, gpu, ...])

Draw samples from an exponential distribution.

f(dfnum, dfden[, size, chunk_size, gpu, dtype])

Draw samples from an F distribution.


gamma(shape[, scale, size, chunk_size, gpu, ...])

Draw samples from a Gamma distribution.

geometric(p[, size, chunk_size, gpu, dtype])

Draw samples from the geometric distribution.

gumbel([loc, scale, size, chunk_size, gpu, ...])

Draw samples from a Gumbel distribution.

hypergeometric(ngood, nbad, nsample[, size, ...])

Draw samples from a Hypergeometric distribution.

laplace([loc, scale, size, chunk_size, gpu, ...])

Draw samples from the Laplace or double exponential distribution with specified location (or mean) and scale (decay).

logistic([loc, scale, size, chunk_size, ...])

Draw samples from a logistic distribution.

lognormal([mean, sigma, size, chunk_size, ...])

Draw samples from a log-normal distribution.

logseries(p[, size, chunk_size, gpu, dtype])

Draw samples from a logarithmic series distribution.

multinomial(n, pvals[, size, chunk_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, chunk_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, chunk_size, gpu, ...])

Draw random samples from a normal (Gaussian) distribution.

pareto(a[, size, chunk_size, gpu, dtype])

Draw samples from a Pareto II or Lomax distribution with specified shape.

permutation(x[, axis, chunk_size])

Randomly permute a sequence, or return a permuted range.

poisson([lam, size, chunk_size, gpu, dtype])

Draw samples from a Poisson distribution.

power(a[, size, chunk_size, gpu, dtype])

Draws samples in [0, 1] from a power distribution with positive exponent a - 1.

rand(*dn, **kw)

Random values in a given shape.

randint(low[, high, size, dtype, density, ...])

Return random integers from low (inclusive) to high (exclusive).

randn(*dn, **kw)

Return a sample (or samples) from the "standard normal" distribution.

random([size, chunk_size, gpu, dtype])

Return random floats in the half-open interval [0.0, 1.0).

random_integers(low[, high, size, ...])

Random integers of type between low and high, inclusive.

random_sample([size, chunk_size, gpu, dtype])

Return random floats in the half-open interval [0.0, 1.0).

ranf([size, chunk_size, gpu, dtype])

Return random floats in the half-open interval [0.0, 1.0).

rayleigh([scale, size, chunk_size, gpu, dtype])

Draw samples from a Rayleigh distribution.

sample([size, chunk_size, gpu, dtype])

Return random floats in the half-open interval [0.0, 1.0).


Seed the generator.

shuffle(x[, axis])

Modify a sequence in-place by shuffling its contents.

standard_cauchy([size, chunk_size, gpu, dtype])

Draw samples from a standard Cauchy distribution with mode = 0.

standard_exponential([size, chunk_size, ...])

Draw samples from the standard exponential distribution.

standard_gamma(shape[, size, chunk_size, ...])

Draw samples from a standard Gamma distribution.

standard_normal([size, chunk_size, gpu, dtype])

Draw samples from a standard Normal distribution (mean=0, stdev=1).

standard_t(df[, size, chunk_size, gpu, dtype])

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 over the interval [left, right].

uniform([low, high, size, chunk_size, gpu, ...])

Draw samples from a uniform distribution.

vonmises(mu, kappa[, size, chunk_size, gpu, ...])

Draw samples from a von Mises distribution.

wald(mean, scale[, size, chunk_size, gpu, dtype])

Draw samples from a Wald, or inverse Gaussian, distribution.

weibull(a[, size, chunk_size, gpu, dtype])

Draw samples from a Weibull distribution.

zipf(a[, size, chunk_size, gpu, dtype])

Draw samples from a Zipf distribution.