75 lines
2.2 KiB
Rust
75 lines
2.2 KiB
Rust
#[macro_use] extern crate average;
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extern crate core;
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extern crate rand;
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use core::iter::Iterator;
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use average::AverageWithError;
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#[test]
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fn trivial() {
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let mut a = AverageWithError::new();
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assert_eq!(a.len(), 0);
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a.add(1.0);
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assert_eq!(a.mean(), 1.0);
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assert_eq!(a.len(), 1);
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assert_eq!(a.sample_variance(), 0.0);
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assert_eq!(a.population_variance(), 0.0);
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assert_eq!(a.error(), 0.0);
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a.add(1.0);
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assert_eq!(a.mean(), 1.0);
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assert_eq!(a.len(), 2);
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assert_eq!(a.sample_variance(), 0.0);
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assert_eq!(a.population_variance(), 0.0);
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assert_eq!(a.error(), 0.0);
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}
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#[test]
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fn simple() {
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let a: AverageWithError = (1..6).map(f64::from).collect();
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assert_eq!(a.mean(), 3.0);
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assert_eq!(a.len(), 5);
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assert_eq!(a.sample_variance(), 2.5);
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assert_almost_eq!(a.error(), f64::sqrt(0.5), 1e-16);
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}
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#[test]
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fn numerically_unstable() {
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// The naive algorithm fails for this example due to cancelation.
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let big = 1e9;
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let sample = &[big + 4., big + 7., big + 13., big + 16.];
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let a: AverageWithError = sample.iter().map(|x| *x).collect();
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assert_eq!(a.sample_variance(), 30.);
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}
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#[test]
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fn merge() {
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let sequence: &[f64] = &[1., 2., 3., 4., 5., 6., 7., 8., 9.];
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for mid in 0..sequence.len() {
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let (left, right) = sequence.split_at(mid);
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let avg_total: AverageWithError = sequence.iter().map(|x| *x).collect();
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let mut avg_left: AverageWithError = left.iter().map(|x| *x).collect();
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let avg_right: AverageWithError = right.iter().map(|x| *x).collect();
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avg_left.merge(&avg_right);
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assert_eq!(avg_total.len(), avg_left.len());
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assert_eq!(avg_total.mean(), avg_left.mean());
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assert_eq!(avg_total.sample_variance(), avg_left.sample_variance());
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}
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}
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#[test]
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fn normal_distribution() {
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use rand::distributions::{Normal, IndependentSample};
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let normal = Normal::new(2.0, 3.0);
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let mut a = AverageWithError::new();
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for _ in 0..1_000_000 {
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a.add(normal.ind_sample(&mut ::rand::thread_rng()));
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}
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assert_almost_eq!(a.mean(), 2.0, 1e-2);
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assert_almost_eq!(a.sample_variance().sqrt(), 3.0, 1e-2);
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assert_almost_eq!(a.population_variance().sqrt(), 3.0, 1e-2);
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assert_almost_eq!(a.error(), 0.0, 1e-2);
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}
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