diff options
Diffstat (limited to 'rand/tests/uniformity.rs')
-rw-r--r-- | rand/tests/uniformity.rs | 67 |
1 files changed, 67 insertions, 0 deletions
diff --git a/rand/tests/uniformity.rs b/rand/tests/uniformity.rs new file mode 100644 index 0000000..b8f74a6 --- /dev/null +++ b/rand/tests/uniformity.rs @@ -0,0 +1,67 @@ +// Copyright 2018 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. + +#![cfg(feature = "std")] + +#[macro_use] +extern crate average; +extern crate rand; + +use std as core; +use rand::FromEntropy; +use rand::distributions::Distribution; +use average::Histogram; + +const N_BINS: usize = 100; +const N_SAMPLES: u32 = 1_000_000; +const TOL: f64 = 1e-3; +define_histogram!(hist, 100); +use hist::Histogram as Histogram100; + +#[test] +fn unit_sphere() { + const N_DIM: usize = 3; + let h = Histogram100::with_const_width(-1., 1.); + let mut histograms = [h.clone(), h.clone(), h]; + let dist = rand::distributions::UnitSphereSurface::new(); + let mut rng = rand::rngs::SmallRng::from_entropy(); + for _ in 0..N_SAMPLES { + let v = dist.sample(&mut rng); + for i in 0..N_DIM { + histograms[i].add(v[i]).map_err( + |e| { println!("v: {}", v[i]); e } + ).unwrap(); + } + } + for h in &histograms { + let sum: u64 = h.bins().iter().sum(); + println!("{:?}", h); + for &b in h.bins() { + let p = (b as f64) / (sum as f64); + assert!((p - 1.0 / (N_BINS as f64)).abs() < TOL, "{}", p); + } + } +} + +#[test] +fn unit_circle() { + use ::std::f64::consts::PI; + let mut h = Histogram100::with_const_width(-PI, PI); + let dist = rand::distributions::UnitCircle::new(); + let mut rng = rand::rngs::SmallRng::from_entropy(); + for _ in 0..N_SAMPLES { + let v = dist.sample(&mut rng); + h.add(v[0].atan2(v[1])).unwrap(); + } + let sum: u64 = h.bins().iter().sum(); + println!("{:?}", h); + for &b in h.bins() { + let p = (b as f64) / (sum as f64); + assert!((p - 1.0 / (N_BINS as f64)).abs() < TOL, "{}", p); + } +} |