rust-average/tests/average.rs
2017-05-19 15:54:13 +02:00

58 lines
1.5 KiB
Rust

#[macro_use] extern crate average;
extern crate core;
extern crate rand;
use core::iter::Iterator;
use average::Average;
#[test]
fn trivial() {
let mut a = Average::new();
assert_eq!(a.len(), 0);
a.add(1.0);
assert_eq!(a.mean(), 1.0);
assert_eq!(a.len(), 1);
assert_eq!(a.sample_variance(), 0.0);
assert_eq!(a.population_variance(), 0.0);
assert_eq!(a.error(), 0.0);
a.add(1.0);
assert_eq!(a.mean(), 1.0);
assert_eq!(a.len(), 2);
assert_eq!(a.sample_variance(), 0.0);
assert_eq!(a.population_variance(), 0.0);
assert_eq!(a.error(), 0.0);
}
#[test]
fn simple() {
let a: Average = (1..6).map(f64::from).collect();
assert_eq!(a.mean(), 3.0);
assert_eq!(a.len(), 5);
assert_eq!(a.sample_variance(), 2.5);
assert_almost_eq!(a.error(), f64::sqrt(0.5), 1e-16);
}
#[test]
fn numerically_unstable() {
// The naive algorithm fails for this example due to cancelation.
let big = 1e9;
let sample = &[big + 4., big + 7., big + 13., big + 16.];
let a: Average = sample.iter().map(|x| *x).collect();
assert_eq!(a.sample_variance(), 30.);
}
#[test]
fn normal_distribution() {
use rand::distributions::{Normal, IndependentSample};
let normal = Normal::new(2.0, 3.0);
let mut a = Average::new();
for _ in 0..1_000_000 {
a.add(normal.ind_sample(&mut ::rand::thread_rng()));
}
assert_almost_eq!(a.mean(), 2.0, 1e-2);
assert_almost_eq!(a.sample_variance().sqrt(), 3.0, 1e-2);
}