From d0d9683df8398696147e7ee1fcffb2e4e957008c Mon Sep 17 00:00:00 2001 From: Daniel Mueller Date: Sat, 4 Apr 2020 14:39:19 -0700 Subject: Remove vendored dependencies While it appears that by now we actually can get successful builds without Cargo insisting on Internet access by virtue of using the --frozen flag, maintaining vendored dependencies is somewhat of a pain point. This state will also get worse with upcoming changes that replace argparse in favor of structopt and pull in a slew of new dependencies by doing so. Then there is also the repository structure aspect, which is non-standard due to the way we vendor dependencies and a potential source of confusion. In order to fix these problems, this change removes all the vendored dependencies we have. Delete subrepo argparse/:argparse Delete subrepo base32/:base32 Delete subrepo cc/:cc Delete subrepo cfg-if/:cfg-if Delete subrepo getrandom/:getrandom Delete subrepo lazy-static/:lazy-static Delete subrepo libc/:libc Delete subrepo nitrokey-sys/:nitrokey-sys Delete subrepo nitrokey/:nitrokey Delete subrepo rand/:rand --- rand/rand_distr/src/lib.rs | 134 --------------------------------------------- 1 file changed, 134 deletions(-) delete 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 deleted file mode 100644 index baf65ed..0000000 --- a/rand/rand_distr/src/lib.rs +++ /dev/null @@ -1,134 +0,0 @@ -// 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