From fd091b04316db9dc5fafadbd6bdbe60b127408a9 Mon Sep 17 00:00:00 2001 From: Daniel Mueller Date: Thu, 2 Jan 2020 08:32:06 -0800 Subject: Update nitrokey crate to 0.4.0 This change finally updates the version of the nitrokey crate that we consume to 0.4.0. Along with that we update rand_core, one of its dependencies, to 0.5.1. Further more we add cfg-if in version 0.1.10 and getrandom in version 0.1.13, both of which are now new (non-development) dependencies. Import subrepo nitrokey/:nitrokey at e81057037e9b4f370b64c0a030a725bc6bdfb870 Import subrepo cfg-if/:cfg-if at 4484a6faf816ff8058088ad857b0c6bb2f4b02b2 Import subrepo getrandom/:getrandom at d661aa7e1b8cc80b47dabe3d2135b3b47d2858af Import subrepo rand/:rand at d877ed528248b52d947e0484364a4e1ae59ca502 --- rand/rand_distr/src/lib.rs | 134 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 134 insertions(+) create mode 100644 rand/rand_distr/src/lib.rs (limited to 'rand/rand_distr/src/lib.rs') diff --git a/rand/rand_distr/src/lib.rs b/rand/rand_distr/src/lib.rs new file mode 100644 index 0000000..baf65ed --- /dev/null +++ b/rand/rand_distr/src/lib.rs @@ -0,0 +1,134 @@ +// Copyright 2019 Developers of the Rand project. +// +// Licensed under the Apache License, Version 2.0 or the MIT license +// , at your +// option. This file may not be copied, modified, or distributed +// except according to those terms. + +#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png", + html_favicon_url = "https://www.rust-lang.org/favicon.ico", + html_root_url = "https://rust-random.github.io/rand/")] + +#![deny(missing_docs)] +#![deny(missing_debug_implementations)] + +#![allow(clippy::excessive_precision, clippy::float_cmp, clippy::unreadable_literal)] +#![allow(clippy::neg_cmp_op_on_partial_ord)] // suggested fix too verbose + +//! Generating random samples from probability distributions. +//! +//! ## Re-exports +//! +//! This crate is a super-set of the [`rand::distributions`] module. See the +//! [`rand::distributions`] module documentation for an overview of the core +//! [`Distribution`] trait and implementations. +//! +//! The following are re-exported: +//! +//! - The [`Distribution`] trait and [`DistIter`] helper type +//! - The [`Standard`], [`Alphanumeric`], [`Uniform`], [`OpenClosed01`], [`Open01`] and [`Bernoulli`] distributions +//! - The [`weighted`] sub-module +//! +//! ## Distributions +//! +//! This crate provides the following probability distributions: +//! +//! - Related to real-valued quantities that grow linearly +//! (e.g. errors, offsets): +//! - [`Normal`] distribution, and [`StandardNormal`] as a primitive +//! - [`Cauchy`] distribution +//! - Related to Bernoulli trials (yes/no events, with a given probability): +//! - [`Binomial`] distribution +//! - Related to positive real-valued quantities that grow exponentially +//! (e.g. prices, incomes, populations): +//! - [`LogNormal`] distribution +//! - Related to the occurrence of independent events at a given rate: +//! - [`Pareto`] distribution +//! - [`Poisson`] distribution +//! - [`Exp`]onential distribution, and [`Exp1`] as a primitive +//! - [`Weibull`] distribution +//! - Gamma and derived distributions: +//! - [`Gamma`] distribution +//! - [`ChiSquared`] distribution +//! - [`StudentT`] distribution +//! - [`FisherF`] distribution +//! - Triangular distribution: +//! - [`Beta`] distribution +//! - [`Triangular`] distribution +//! - Multivariate probability distributions +//! - [`Dirichlet`] distribution +//! - [`UnitSphere`] distribution +//! - [`UnitBall`] distribution +//! - [`UnitCircle`] distribution +//! - [`UnitDisc`] distribution + +pub use rand::distributions::{Distribution, DistIter, Standard, + Alphanumeric, Uniform, OpenClosed01, Open01, Bernoulli, uniform, weighted}; + +pub use self::unit_sphere::UnitSphere; +pub use self::unit_ball::UnitBall; +pub use self::unit_circle::UnitCircle; +pub use self::unit_disc::UnitDisc; +pub use self::gamma::{Gamma, Error as GammaError, ChiSquared, ChiSquaredError, + FisherF, FisherFError, StudentT, Beta, BetaError}; +pub use self::normal::{Normal, Error as NormalError, LogNormal, StandardNormal}; +pub use self::exponential::{Exp, Error as ExpError, Exp1}; +pub use self::pareto::{Pareto, Error as ParetoError}; +pub use self::pert::{Pert, PertError}; +pub use self::poisson::{Poisson, Error as PoissonError}; +pub use self::binomial::{Binomial, Error as BinomialError}; +pub use self::cauchy::{Cauchy, Error as CauchyError}; +pub use self::dirichlet::{Dirichlet, Error as DirichletError}; +pub use self::triangular::{Triangular, TriangularError}; +pub use self::weibull::{Weibull, Error as WeibullError}; +pub use self::utils::Float; + +mod unit_sphere; +mod unit_ball; +mod unit_circle; +mod unit_disc; +mod gamma; +mod normal; +mod exponential; +mod pareto; +mod pert; +mod poisson; +mod binomial; +mod cauchy; +mod dirichlet; +mod triangular; +mod weibull; +mod utils; +mod ziggurat_tables; + +#[cfg(test)] +mod test { + // Notes on testing + // + // Testing random number distributions correctly is hard. The following + // testing is desired: + // + // - Construction: test initialisation with a few valid parameter sets. + // - Erroneous usage: test that incorrect usage generates an error. + // - Vector: test that usage with fixed inputs (including RNG) generates a + // fixed output sequence on all platforms. + // - Correctness at fixed points (optional): using a specific mock RNG, + // check that specific values are sampled (e.g. end-points and median of + // distribution). + // - Correctness of PDF (extra): generate a histogram of samples within a + // certain range, and check this approximates the PDF. These tests are + // expected to be expensive, and should be behind a feature-gate. + // + // TODO: Vector and correctness tests are largely absent so far. + // NOTE: Some distributions have tests checking only that samples can be + // generated. This is redundant with vector and correctness tests. + + /// Construct a deterministic RNG with the given seed + pub fn rng(seed: u64) -> impl rand::RngCore { + // For tests, we want a statistically good, fast, reproducible RNG. + // PCG32 will do fine, and will be easy to embed if we ever need to. + const INC: u64 = 11634580027462260723; + rand_pcg::Pcg32::new(seed, INC) + } +} -- cgit v1.2.1