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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)
-    }
-}