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d5f5648b37
We use cargo vendor to generate a .cargo/config file and the vendor directory. Vendoring allows us to lock our dependencies and to modify them easily from the top level Cargo.toml. We vendor all dependencies, including the crates.io ones, which allows for network isolated builds. Signed-off-by: Samuel Ortiz <sameo@linux.intel.com>
68 lines
2.0 KiB
Rust
68 lines
2.0 KiB
Rust
// Copyright 2018 Developers of the Rand project.
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//
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// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
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// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
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// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
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// option. This file may not be copied, modified, or distributed
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// except according to those terms.
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#![cfg(feature = "std")]
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#[macro_use]
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extern crate average;
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extern crate rand;
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use std as core;
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use rand::FromEntropy;
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use rand::distributions::Distribution;
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use average::Histogram;
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const N_BINS: usize = 100;
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const N_SAMPLES: u32 = 1_000_000;
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const TOL: f64 = 1e-3;
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define_histogram!(hist, 100);
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use hist::Histogram as Histogram100;
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#[test]
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fn unit_sphere() {
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const N_DIM: usize = 3;
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let h = Histogram100::with_const_width(-1., 1.);
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let mut histograms = [h.clone(), h.clone(), h];
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let dist = rand::distributions::UnitSphereSurface::new();
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let mut rng = rand::rngs::SmallRng::from_entropy();
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for _ in 0..N_SAMPLES {
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let v = dist.sample(&mut rng);
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for i in 0..N_DIM {
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histograms[i].add(v[i]).map_err(
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|e| { println!("v: {}", v[i]); e }
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).unwrap();
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}
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}
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for h in &histograms {
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let sum: u64 = h.bins().iter().sum();
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println!("{:?}", h);
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for &b in h.bins() {
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let p = (b as f64) / (sum as f64);
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assert!((p - 1.0 / (N_BINS as f64)).abs() < TOL, "{}", p);
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}
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}
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}
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#[test]
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fn unit_circle() {
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use ::std::f64::consts::PI;
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let mut h = Histogram100::with_const_width(-PI, PI);
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let dist = rand::distributions::UnitCircle::new();
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let mut rng = rand::rngs::SmallRng::from_entropy();
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for _ in 0..N_SAMPLES {
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let v = dist.sample(&mut rng);
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h.add(v[0].atan2(v[1])).unwrap();
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}
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let sum: u64 = h.bins().iter().sum();
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println!("{:?}", h);
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for &b in h.bins() {
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let p = (b as f64) / (sum as f64);
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assert!((p - 1.0 / (N_BINS as f64)).abs() < TOL, "{}", p);
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}
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}
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