mars.tensor.random.RandomState#
- class mars.tensor.random.RandomState(seed=None)[source]#
-
Methods
__init__([seed])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.
bytes(length)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.
from_numpy(np_random_state)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 mt.int 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([seed])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.
to_numpy()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.