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+// Copyright 2019 Developers of the Rand project.
+//
+// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
+// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
+// <LICENSE-MIT or https://opensource.org/licenses/MIT>, 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)
+    }
+}