vendor/rand-0.7.3/src/distributions/unit_circle.rs

   1 // Copyright 2018 Developers of the Rand project.
   2 //
   3 // Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
   4 // https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
   5 // <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
   6 // option. This file may not be copied, modified, or distributed
   7 // except according to those terms.
   8
   9 #![allow(deprecated)]
  10 #![allow(clippy::all)]
  11
  12 use crate::distributions::{Distribution, Uniform};
  13 use crate::Rng;
  14
  15 /// Samples uniformly from the edge of the unit circle in two dimensions.
  16 ///
  17 /// Implemented via a method by von Neumann[^1].
  18 ///
  19 /// [^1]: von Neumann, J. (1951) [*Various Techniques Used in Connection with
  20 ///       Random Digits.*](https://mcnp.lanl.gov/pdf_files/nbs_vonneumann.pdf)
  21 ///       NBS Appl. Math. Ser., No. 12. Washington, DC: U.S. Government Printing
  22 ///       Office, pp. 36-38.
  23 #[deprecated(since = "0.7.0", note = "moved to rand_distr crate")]
  24 #[derive(Clone, Copy, Debug)]
  25 pub struct UnitCircle;
  26
  27 impl UnitCircle {
  28     /// Construct a new `UnitCircle` distribution.
  29     #[inline]
  30     pub fn new() -> UnitCircle {
  31         UnitCircle
  32     }
  33 }
  34
  35 impl Distribution<[f64; 2]> for UnitCircle {
  36     #[inline]
  37     fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> [f64; 2] {
  38         let uniform = Uniform::new(-1., 1.);
  39         let mut x1;
  40         let mut x2;
  41         let mut sum;
  42         loop {
  43             x1 = uniform.sample(rng);
  44             x2 = uniform.sample(rng);
  45             sum = x1 * x1 + x2 * x2;
  46             if sum < 1. {
  47                 break;
  48             }
  49         }
  50         let diff = x1 * x1 - x2 * x2;
  51         [diff / sum, 2. * x1 * x2 / sum]
  52     }
  53 }
  54
  55 #[cfg(test)]
  56 mod tests {
  57     use super::UnitCircle;
  58     use crate::distributions::Distribution;
  59
  60     /// Assert that two numbers are almost equal to each other.
  61     ///
  62     /// On panic, this macro will print the values of the expressions with their
  63     /// debug representations.
  64     macro_rules! assert_almost_eq {
  65         ($a:expr, $b:expr, $prec:expr) => {
  66             let diff = ($a - $b).abs();
  67             if diff > $prec {
  68                 panic!(format!(
  69                     "assertion failed: `abs(left - right) = {:.1e} < {:e}`, \
  70                      (left: `{}`, right: `{}`)",
  71                     diff, $prec, $a, $b
  72                 ));
  73             }
  74         };
  75     }
  76
  77     #[test]
  78     fn norm() {
  79         let mut rng = crate::test::rng(1);
  80         let dist = UnitCircle::new();
  81         for _ in 0..1000 {
  82             let x = dist.sample(&mut rng);
  83             assert_almost_eq!(x[0] * x[0] + x[1] * x[1], 1., 1e-15);
  84         }
  85     }
  86
  87     #[test]
  88     fn value_stability() {
  89         let mut rng = crate::test::rng(2);
  90         let expected = [
  91             [-0.9965658683520504, -0.08280380447614634],
  92             [-0.9790853270389644, -0.20345004884984505],
  93             [-0.8449189758898707, 0.5348943112253227],
  94         ];
  95         let samples = [
  96             UnitCircle.sample(&mut rng),
  97             UnitCircle.sample(&mut rng),
  98             UnitCircle.sample(&mut rng),
  99         ];
 100         assert_eq!(samples, expected);
 101     }
 102 }