Rename rand::distributions -> rand::distr

Author: dhardy

README.md

@@ -17,7 +17,7 @@ A Rust library for random number generation, featuring:
     ([see the book](https://rust-random.github.io/book/crates.html))
 -   Fast implementations of the best-in-class [cryptographic](https://rust-random.github.io/book/guide-rngs.html#cryptographically-secure-pseudo-random-number-generators-csprngs) and
     [non-cryptographic](https://rust-random.github.io/book/guide-rngs.html#basic-pseudo-random-number-generators-prngs) generators
--   A flexible [`distributions`](https://docs.rs/rand/*/rand/distributions/index.html) module
+-   A flexible [`distributions`](https://docs.rs/rand/*/rand/distr/index.html) module
 -   Samplers for a large number of random number distributions via our own
     [`rand_distr`](https://docs.rs/rand_distr) and via
     the [`statrs`](https://docs.rs/statrs/0.13.0/statrs/)

benches/Cargo.toml

@@ -15,8 +15,8 @@ criterion = "0.5"
 criterion-cycles-per-byte = "0.6"
 
 [[bench]]
-name = "distributions"
-path = "src/distributions.rs"
+name = "distr"
+path = "src/distr.rs"
 harness = false
 
 [[bench]]

benches/benches/base_distributions.rs

@@ -16,8 +16,8 @@ extern crate test;
 
 const RAND_BENCH_N: u64 = 1000;
 
-use rand::distributions::{Alphanumeric, Open01, OpenClosed01, Standard, Uniform};
-use rand::distributions::uniform::{UniformInt, UniformSampler};
+use rand::distr::{Alphanumeric, Open01, OpenClosed01, Standard, Uniform};
+use rand::distr::uniform::{UniformInt, UniformSampler};
 use core::mem::size_of;
 use core::num::{NonZeroU128, NonZeroU16, NonZeroU32, NonZeroU64, NonZeroU8};
 use core::time::Duration;
@@ -253,7 +253,7 @@ gen_range_float!(gen_range_f32, f32, -20000.0f32, 100000.0);
 gen_range_float!(gen_range_f64, f64, 123.456f64, 7890.12);
 
 
-// In src/distributions/uniform.rs, we say:
+// In src/distr/uniform.rs, we say:
 // Implementation of [`uniform_single`] is optional, and is only useful when
 // the implementation can be faster than `Self::new(low, high).sample(rng)`.
 

benches/benches/misc.rs

@@ -14,7 +14,7 @@ const RAND_BENCH_N: u64 = 1000;
 
 use test::Bencher;
 
-use rand::distributions::{Bernoulli, Distribution, Standard};
+use rand::distr::{Bernoulli, Distribution, Standard};
 use rand::prelude::*;
 use rand_pcg::{Pcg32, Pcg64Mcg};
 

benches/benches/weighted.rs

@@ -10,7 +10,7 @@
 
 extern crate test;
 
-use rand::distributions::WeightedIndex;
+use rand::distr::WeightedIndex;
 use rand::Rng;
 use test::Bencher;
 

benches/src/distributions.rs renamed to benches/src/distr.rs

@@ -10,7 +10,7 @@
 
 use core::time::Duration;
 use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion};
-use rand::distributions::uniform::{SampleRange, Uniform};
+use rand::distr::uniform::{SampleRange, Uniform};
 use rand::prelude::*;
 use rand_chacha::ChaCha8Rng;
 use rand_pcg::{Pcg32, Pcg64};

benches/src/uniform.rs

@@ -14,7 +14,7 @@
 
 use core::time::Duration;
 use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion};
-use rand::distributions::uniform::{SampleUniform, Uniform, UniformSampler};
+use rand::distr::uniform::{SampleUniform, Uniform, UniformSampler};
 use rand::prelude::*;
 use rand_chacha::ChaCha8Rng;
 use rand_pcg::{Pcg32, Pcg64};

benches/src/uniform_float.rs

@@ -23,7 +23,7 @@
 //! We can use the above fact to estimate the value of π: pick many points in
 //! the square at random, calculate the fraction that fall within the circle,
 //! and multiply this fraction by 4.
-use rand::distributions::{Distribution, Uniform};
+use rand::distr::{Distribution, Uniform};
 
 fn main() {
     let range = Uniform::new(-1.0f64, 1.0).unwrap();

examples/monte-carlo.rs

@@ -26,7 +26,7 @@
 //!
 //! [Monty Hall Problem]: https://en.wikipedia.org/wiki/Monty_Hall_problem
 
-use rand::distributions::{Distribution, Uniform};
+use rand::distr::{Distribution, Uniform};
 use rand::Rng;
 
 struct SimulationResult {