# Random Sampling¶

## Sample random data¶

 mars.tensor.random.rand Random values in a given shape. mars.tensor.random.randn Return a sample (or samples) from the “standard normal” distribution. mars.tensor.random.randint Return random integers from low (inclusive) to high (exclusive). mars.tensor.random.random_integers Random integers of type mt.int between low and high, inclusive. mars.tensor.random.random_sample Return random floats in the half-open interval [0.0, 1.0). mars.tensor.random.random Return random floats in the half-open interval [0.0, 1.0). mars.tensor.random.ranf Return random floats in the half-open interval [0.0, 1.0). mars.tensor.random.sample Return random floats in the half-open interval [0.0, 1.0). mars.tensor.random.choice Generates a random sample from a given 1-D array mars.tensor.random.bytes Return random bytes.

## Distributions¶

 mars.tensor.random.beta Draw samples from a Beta distribution. mars.tensor.random.binomial Draw samples from a binomial distribution. mars.tensor.random.chisquare Draw samples from a chi-square distribution. mars.tensor.random.dirichlet Draw samples from the Dirichlet distribution. mars.tensor.random.exponential Draw samples from an exponential distribution. mars.tensor.random.f Draw samples from an F distribution. mars.tensor.random.gamma Draw samples from a Gamma distribution. mars.tensor.random.geometric Draw samples from the geometric distribution. mars.tensor.random.gumbel Draw samples from a Gumbel distribution. mars.tensor.random.hypergeometric Draw samples from a Hypergeometric distribution. mars.tensor.random.laplace Draw samples from the Laplace or double exponential distribution with specified location (or mean) and scale (decay). mars.tensor.random.lognormal Draw samples from a log-normal distribution. mars.tensor.random.logseries Draw samples from a logarithmic series distribution. mars.tensor.random.multinomial Draw samples from a multinomial distribution. mars.tensor.random.multivariate_normal Draw random samples from a multivariate normal distribution. mars.tensor.random.negative_binomial Draw samples from a negative binomial distribution. mars.tensor.random.noncentral_chisquare Draw samples from a noncentral chi-square distribution. mars.tensor.random.noncentral_f Draw samples from the noncentral F distribution. mars.tensor.random.normal Draw random samples from a normal (Gaussian) distribution. mars.tensor.random.pareto Draw samples from a Pareto II or Lomax distribution with specified shape. mars.tensor.random.poisson Draw samples from a Poisson distribution. mars.tensor.random.power Draws samples in [0, 1] from a power distribution with positive exponent a - 1. mars.tensor.random.rayleigh Draw samples from a Rayleigh distribution. mars.tensor.random.standard_cauchy Draw samples from a standard Cauchy distribution with mode = 0. mars.tensor.random.standard_exponential Draw samples from the standard exponential distribution. mars.tensor.random.standard_gamma Draw samples from a standard Gamma distribution. mars.tensor.random.standard_normal Draw samples from a standard Normal distribution (mean=0, stdev=1). mars.tensor.random.standard_t Draw samples from a standard Student’s t distribution with df degrees of freedom. mars.tensor.random.triangular Draw samples from the triangular distribution over the interval [left, right]. mars.tensor.random.uniform Draw samples from a uniform distribution. mars.tensor.random.vonmises Draw samples from a von Mises distribution. mars.tensor.random.wald Draw samples from a Wald, or inverse Gaussian, distribution. mars.tensor.random.weibull Draw samples from a Weibull distribution. mars.tensor.random.zipf Draw samples from a Zipf distribution.

## Random number generator¶

 mars.tensor.random.seed Seed the generator. mars.tensor.random.RandomState