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.
If the std
default feature is enabled, rand_distr
implements the Error
trait for its error types.
The default alloc
feature (which is implied by the std
feature) is required
for some distributions (in particular, Dirichlet
and WeightedAliasIndex
).
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.
Links:
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.