Implements a full suite of random number distribution sampling routines.
This crate is a superset of the rand::distributions module, including support for sampling from Beta, Binomial, Cauchy, ChiSquared, Dirichlet, Exponential, FisherF, Gamma, Geometric, Hypergeometric, InverseGaussian, LogNormal, Normal, Pareto, PERT, Poisson, StudentT, Triangular and Weibull distributions. Sampling from the unit ball, unit circle, unit disc and unit sphere surfaces is also supported.
It is worth mentioning the statrs crate which provides similar functionality along with various support functions, including PDF and CDF computation. In contrast, this rand_distr
crate focuses on sampling from distributions.
The floating point functions from num_traits
and libm
are used to support no_std
environments and ensure reproducibility. If the floating point functions from std
are preferred, which may provide better accuracy and performance but may produce different random values, the std_math
feature can be enabled.
std
(enabled by default): rand_distr
implements the Error
trait for its error types. Implies alloc
and rand/std
.alloc
(enabled by default): required for some distributions when not using std
(in particular, Dirichlet
and WeightedAliasIndex
).std_math
: see above on portability and libmserde1
: implement (de)seriaialization using serde
rand_distr
is distributed under the terms of both the MIT license and the Apache License (Version 2.0).
See LICENSE-APACHE and LICENSE-MIT, and COPYRIGHT for details.