The mkl_random package provides interfaces that serve as drop-in replacements for equivalent functions in NumPy.

This interface is a drop-in replacement for the legacy portion of the numpy.random module and includes all classes and functions available there:

• random generator: RandomState.

• seeding and state functions: get_state, set_state, and seed.

• simple random data: rand, randn, randint, random_integers, random_sample, choice and bytes.

• permutations: shuffle and permutation

• distributions: beta, binomial, chisquare, dirichlet, exponential, f, gamma, geometric, gumbel, hypergeometric, laplace, logistic, lognormal, logseries, multinomial, multivariate_normal, negative_binomial, noncentral_chisquare, noncentral_f, normal, pareto, poisson, power, rayleigh, standard_cauchy, standard_exponential, standard_gamma, standard_normal, standard_t, triangular, uniform, vonmises, wald, weibull, and zipf.