vendor/rand-0.6.1/tests/uniformity.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 #![cfg(feature = "std")]
  10
  11 #[macro_use]
  12 extern crate average;
  13 extern crate rand;
  14
  15 use std as core;
  16 use rand::FromEntropy;
  17 use rand::distributions::Distribution;
  18 use average::Histogram;
  19
  20 const N_BINS: usize = 100;
  21 const N_SAMPLES: u32 = 1_000_000;
  22 const TOL: f64 = 1e-3;
  23 define_histogram!(hist, 100);
  24 use hist::Histogram as Histogram100;
  25
  26 #[test]
  27 fn unit_sphere() {
  28     const N_DIM: usize = 3;
  29     let h = Histogram100::with_const_width(-1., 1.);
  30     let mut histograms = [h.clone(), h.clone(), h];
  31     let dist = rand::distributions::UnitSphereSurface::new();
  32     let mut rng = rand::rngs::SmallRng::from_entropy();
  33     for _ in 0..N_SAMPLES {
  34         let v = dist.sample(&mut rng);
  35         for i in 0..N_DIM {
  36             histograms[i].add(v[i]).map_err(
  37                 |e| { println!("v: {}", v[i]); e }
  38             ).unwrap();
  39         }
  40     }
  41     for h in &histograms {
  42         let sum: u64 = h.bins().iter().sum();
  43         println!("{:?}", h);
  44         for &b in h.bins() {
  45             let p = (b as f64) / (sum as f64);
  46             assert!((p - 1.0 / (N_BINS as f64)).abs() < TOL, "{}", p);
  47         }
  48     }
  49 }
  50
  51 #[test]
  52 fn unit_circle() {
  53     use ::std::f64::consts::PI;
  54     let mut h = Histogram100::with_const_width(-PI, PI);
  55     let dist = rand::distributions::UnitCircle::new();
  56     let mut rng = rand::rngs::SmallRng::from_entropy();
  57     for _ in 0..N_SAMPLES {
  58         let v = dist.sample(&mut rng);
  59         h.add(v[0].atan2(v[1])).unwrap();
  60     }
  61     let sum: u64 = h.bins().iter().sum();
  62     println!("{:?}", h);
  63     for &b in h.bins() {
  64         let p = (b as f64) / (sum as f64);
  65         assert!((p - 1.0 / (N_BINS as f64)).abs() < TOL, "{}", p);
  66     }
  67 }