1 | // Copyright 2018 Developers of the Rand project. |
2 | // Copyright 2013-2017 The Rust Project Developers. |
3 | // |
4 | // Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or |
5 | // https://www.apache.org/licenses/LICENSE-2.0> or the MIT license |
6 | // <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your |
7 | // option. This file may not be copied, modified, or distributed |
8 | // except according to those terms. |
9 | |
10 | //! Distribution trait and associates |
11 | |
12 | use crate::Rng; |
13 | #[cfg (feature = "alloc" )] |
14 | use alloc::string::String; |
15 | use core::iter; |
16 | |
17 | /// Types (distributions) that can be used to create a random instance of `T`. |
18 | /// |
19 | /// It is possible to sample from a distribution through both the |
20 | /// `Distribution` and [`Rng`] traits, via `distr.sample(&mut rng)` and |
21 | /// `rng.sample(distr)`. They also both offer the [`sample_iter`] method, which |
22 | /// produces an iterator that samples from the distribution. |
23 | /// |
24 | /// All implementations are expected to be immutable; this has the significant |
25 | /// advantage of not needing to consider thread safety, and for most |
26 | /// distributions efficient state-less sampling algorithms are available. |
27 | /// |
28 | /// Implementations are typically expected to be portable with reproducible |
29 | /// results when used with a PRNG with fixed seed; see the |
30 | /// [portability chapter](https://rust-random.github.io/book/portability.html) |
31 | /// of The Rust Rand Book. In some cases this does not apply, e.g. the `usize` |
32 | /// type requires different sampling on 32-bit and 64-bit machines. |
33 | /// |
34 | /// [`sample_iter`]: Distribution::sample_iter |
35 | pub trait Distribution<T> { |
36 | /// Generate a random value of `T`, using `rng` as the source of randomness. |
37 | fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> T; |
38 | |
39 | /// Create an iterator that generates random values of `T`, using `rng` as |
40 | /// the source of randomness. |
41 | /// |
42 | /// Note that this function takes `self` by value. This works since |
43 | /// `Distribution<T>` is impl'd for `&D` where `D: Distribution<T>`, |
44 | /// however borrowing is not automatic hence `distr.sample_iter(...)` may |
45 | /// need to be replaced with `(&distr).sample_iter(...)` to borrow or |
46 | /// `(&*distr).sample_iter(...)` to reborrow an existing reference. |
47 | /// |
48 | /// # Example |
49 | /// |
50 | /// ``` |
51 | /// use rand::distr::{Distribution, Alphanumeric, Uniform, StandardUniform}; |
52 | /// |
53 | /// let mut rng = rand::rng(); |
54 | /// |
55 | /// // Vec of 16 x f32: |
56 | /// let v: Vec<f32> = StandardUniform.sample_iter(&mut rng).take(16).collect(); |
57 | /// |
58 | /// // String: |
59 | /// let s: String = Alphanumeric |
60 | /// .sample_iter(&mut rng) |
61 | /// .take(7) |
62 | /// .map(char::from) |
63 | /// .collect(); |
64 | /// |
65 | /// // Dice-rolling: |
66 | /// let die_range = Uniform::new_inclusive(1, 6).unwrap(); |
67 | /// let mut roll_die = die_range.sample_iter(&mut rng); |
68 | /// while roll_die.next().unwrap() != 6 { |
69 | /// println!("Not a 6; rolling again!" ); |
70 | /// } |
71 | /// ``` |
72 | fn sample_iter<R>(self, rng: R) -> Iter<Self, R, T> |
73 | where |
74 | R: Rng, |
75 | Self: Sized, |
76 | { |
77 | Iter { |
78 | distr: self, |
79 | rng, |
80 | phantom: core::marker::PhantomData, |
81 | } |
82 | } |
83 | |
84 | /// Map sampled values to type `S` |
85 | /// |
86 | /// # Example |
87 | /// |
88 | /// ``` |
89 | /// use rand::distr::{Distribution, Uniform}; |
90 | /// |
91 | /// let die = Uniform::new_inclusive(1, 6).unwrap(); |
92 | /// let even_number = die.map(|num| num % 2 == 0); |
93 | /// while !even_number.sample(&mut rand::rng()) { |
94 | /// println!("Still odd; rolling again!" ); |
95 | /// } |
96 | /// ``` |
97 | fn map<F, S>(self, func: F) -> Map<Self, F, T, S> |
98 | where |
99 | F: Fn(T) -> S, |
100 | Self: Sized, |
101 | { |
102 | Map { |
103 | distr: self, |
104 | func, |
105 | phantom: core::marker::PhantomData, |
106 | } |
107 | } |
108 | } |
109 | |
110 | impl<T, D: Distribution<T> + ?Sized> Distribution<T> for &D { |
111 | fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> T { |
112 | (*self).sample(rng) |
113 | } |
114 | } |
115 | |
116 | /// An iterator over a [`Distribution`] |
117 | /// |
118 | /// This iterator yields random values of type `T` with distribution `D` |
119 | /// from a random generator of type `R`. |
120 | /// |
121 | /// Construct this `struct` using [`Distribution::sample_iter`] or |
122 | /// [`Rng::sample_iter`]. It is also used by [`Rng::random_iter`] and |
123 | /// [`crate::random_iter`]. |
124 | #[derive(Debug)] |
125 | pub struct Iter<D, R, T> { |
126 | distr: D, |
127 | rng: R, |
128 | phantom: core::marker::PhantomData<T>, |
129 | } |
130 | |
131 | impl<D, R, T> Iterator for Iter<D, R, T> |
132 | where |
133 | D: Distribution<T>, |
134 | R: Rng, |
135 | { |
136 | type Item = T; |
137 | |
138 | #[inline (always)] |
139 | fn next(&mut self) -> Option<T> { |
140 | // Here, self.rng may be a reference, but we must take &mut anyway. |
141 | // Even if sample could take an R: Rng by value, we would need to do this |
142 | // since Rng is not copyable and we cannot enforce that this is "reborrowable". |
143 | Some(self.distr.sample(&mut self.rng)) |
144 | } |
145 | |
146 | fn size_hint(&self) -> (usize, Option<usize>) { |
147 | (usize::MAX, None) |
148 | } |
149 | } |
150 | |
151 | impl<D, R, T> iter::FusedIterator for Iter<D, R, T> |
152 | where |
153 | D: Distribution<T>, |
154 | R: Rng, |
155 | { |
156 | } |
157 | |
158 | /// A [`Distribution`] which maps sampled values to type `S` |
159 | /// |
160 | /// This `struct` is created by the [`Distribution::map`] method. |
161 | /// See its documentation for more. |
162 | #[derive(Debug)] |
163 | pub struct Map<D, F, T, S> { |
164 | distr: D, |
165 | func: F, |
166 | phantom: core::marker::PhantomData<fn(T) -> S>, |
167 | } |
168 | |
169 | impl<D, F, T, S> Distribution<S> for Map<D, F, T, S> |
170 | where |
171 | D: Distribution<T>, |
172 | F: Fn(T) -> S, |
173 | { |
174 | fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> S { |
175 | (self.func)(self.distr.sample(rng)) |
176 | } |
177 | } |
178 | |
179 | /// Sample or extend a [`String`] |
180 | /// |
181 | /// Helper methods to extend a [`String`] or sample a new [`String`]. |
182 | #[cfg (feature = "alloc" )] |
183 | pub trait SampleString { |
184 | /// Append `len` random chars to `string` |
185 | /// |
186 | /// Note: implementations may leave `string` with excess capacity. If this |
187 | /// is undesirable, consider calling [`String::shrink_to_fit`] after this |
188 | /// method. |
189 | fn append_string<R: Rng + ?Sized>(&self, rng: &mut R, string: &mut String, len: usize); |
190 | |
191 | /// Generate a [`String`] of `len` random chars |
192 | /// |
193 | /// Note: implementations may leave the string with excess capacity. If this |
194 | /// is undesirable, consider calling [`String::shrink_to_fit`] after this |
195 | /// method. |
196 | #[inline ] |
197 | fn sample_string<R: Rng + ?Sized>(&self, rng: &mut R, len: usize) -> String { |
198 | let mut s = String::new(); |
199 | self.append_string(rng, &mut s, len); |
200 | s |
201 | } |
202 | } |
203 | |
204 | #[cfg (test)] |
205 | mod tests { |
206 | use crate::distr::{Distribution, Uniform}; |
207 | use crate::Rng; |
208 | |
209 | #[test] |
210 | fn test_distributions_iter() { |
211 | use crate::distr::Open01; |
212 | let mut rng = crate::test::rng(210); |
213 | let distr = Open01; |
214 | let mut iter = Distribution::<f32>::sample_iter(distr, &mut rng); |
215 | let mut sum: f32 = 0.; |
216 | for _ in 0..100 { |
217 | sum += iter.next().unwrap(); |
218 | } |
219 | assert!(0. < sum && sum < 100.); |
220 | } |
221 | |
222 | #[test] |
223 | fn test_distributions_map() { |
224 | let dist = Uniform::new_inclusive(0, 5).unwrap().map(|val| val + 15); |
225 | |
226 | let mut rng = crate::test::rng(212); |
227 | let val = dist.sample(&mut rng); |
228 | assert!((15..=20).contains(&val)); |
229 | } |
230 | |
231 | #[test] |
232 | fn test_make_an_iter() { |
233 | fn ten_dice_rolls_other_than_five<R: Rng>(rng: &mut R) -> impl Iterator<Item = i32> + '_ { |
234 | Uniform::new_inclusive(1, 6) |
235 | .unwrap() |
236 | .sample_iter(rng) |
237 | .filter(|x| *x != 5) |
238 | .take(10) |
239 | } |
240 | |
241 | let mut rng = crate::test::rng(211); |
242 | let mut count = 0; |
243 | for val in ten_dice_rolls_other_than_five(&mut rng) { |
244 | assert!((1..=6).contains(&val) && val != 5); |
245 | count += 1; |
246 | } |
247 | assert_eq!(count, 10); |
248 | } |
249 | |
250 | #[test] |
251 | #[cfg (feature = "alloc" )] |
252 | fn test_dist_string() { |
253 | use crate::distr::{Alphanumeric, SampleString, StandardUniform}; |
254 | use core::str; |
255 | let mut rng = crate::test::rng(213); |
256 | |
257 | let s1 = Alphanumeric.sample_string(&mut rng, 20); |
258 | assert_eq!(s1.len(), 20); |
259 | assert_eq!(str::from_utf8(s1.as_bytes()), Ok(s1.as_str())); |
260 | |
261 | let s2 = StandardUniform.sample_string(&mut rng, 20); |
262 | assert_eq!(s2.chars().count(), 20); |
263 | assert_eq!(str::from_utf8(s2.as_bytes()), Ok(s2.as_str())); |
264 | } |
265 | } |
266 | |