rust-average/tests/weighted_average.rs
Vinzent Steinberg a95ab05c10 Factor out calculation of average
Now it is possible to calculate the average without calculating the
error.
2017-05-24 11:33:15 +02:00

107 lines
4.1 KiB
Rust

#[macro_use] extern crate average;
extern crate core;
use core::iter::Iterator;
use average::WeightedAverageWithError;
#[test]
fn trivial() {
let mut a = WeightedAverageWithError::new();
assert_eq!(a.len(), 0);
assert_eq!(a.sum_weights(), 0.);
assert_eq!(a.sum_weights_sq(), 0.);
a.add(1.0, 1.0);
assert_eq!(a.len(), 1);
assert_eq!(a.weighted_mean(), 1.0);
assert_eq!(a.unweighted_mean(), 1.0);
assert_eq!(a.sum_weights(), 1.0);
assert_eq!(a.sum_weights_sq(), 1.0);
assert_eq!(a.population_variance(), 0.0);
assert_eq!(a.error(), 0.0);
a.add(1.0, 1.0);
assert_eq!(a.len(), 2);
assert_eq!(a.weighted_mean(), 1.0);
assert_eq!(a.unweighted_mean(), 1.0);
assert_eq!(a.sum_weights(), 2.0);
assert_eq!(a.sum_weights_sq(), 2.0);
assert_eq!(a.population_variance(), 0.0);
assert_eq!(a.error(), 0.0);
}
#[test]
fn simple() {
let a: WeightedAverageWithError = (1..6).map(|x| (f64::from(x), 1.0)).collect();
assert_eq!(a.len(), 5);
assert_eq!(a.weighted_mean(), 3.0);
assert_eq!(a.unweighted_mean(), 3.0);
assert_eq!(a.sum_weights(), 5.0);
assert_eq!(a.sample_variance(), 2.5);
assert_almost_eq!(a.error(), f64::sqrt(0.5), 1e-16);
}
#[test]
fn reference() {
// Example from http://www.analyticalgroup.com/download/WEIGHTED_MEAN.pdf.
let values = &[5., 5., 4., 4., 3., 4., 3., 2., 2., 1.];
let weights = &[1.23, 2.12, 1.23, 0.32, 1.53, 0.59, 0.94, 0.94, 0.84, 0.73];
let a: WeightedAverageWithError = values.iter().zip(weights.iter())
.map(|(x, w)| (*x, *w)).collect();
assert_almost_eq!(a.weighted_mean(), 3.53486, 1e-5);
assert_almost_eq!(a.sample_variance(), 1.7889, 1e-4);
assert_eq!(a.sum_weights(), 10.47);
assert_eq!(a.len(), 10);
assert_almost_eq!(a.effective_len(), 8.2315, 1e-4);
assert_almost_eq!(a.error(), f64::sqrt(0.2173), 1e-4);
}
#[test]
fn error_corner_case() {
let values = &[1., 2.];
let weights = &[0.5, 0.5];
let a: WeightedAverageWithError = values.iter().zip(weights.iter())
.map(|(x, w)| (*x, *w)).collect();
assert_eq!(a.error(), 0.5);
}
#[test]
fn merge_unweighted() {
let sequence: &[f64] = &[1., 2., 3., 4., 5., 6., 7., 8., 9.];
for mid in 0..sequence.len() {
let (left, right) = sequence.split_at(mid);
let avg_total: WeightedAverageWithError = sequence.iter().map(|x| (*x, 1.)).collect();
let mut avg_left: WeightedAverageWithError = left.iter().map(|x| (*x, 1.)).collect();
let avg_right: WeightedAverageWithError = right.iter().map(|x| (*x, 1.)).collect();
avg_left.merge(&avg_right);
assert_eq!(avg_total.sum_weights(), avg_left.sum_weights());
assert_eq!(avg_total.sum_weights_sq(), avg_left.sum_weights_sq());
assert_eq!(avg_total.len(), avg_left.len());
assert_eq!(avg_total.unweighted_mean(), avg_left.unweighted_mean());
assert_eq!(avg_total.weighted_mean(), avg_left.weighted_mean());
assert_eq!(avg_total.sample_variance(), avg_left.sample_variance());
}
}
#[test]
fn merge_weighted() {
let sequence: &[(f64, f64)] = &[
(1., 0.1), (2., 0.2), (3., 0.3), (4., 0.4), (5., 0.5),
(6., 0.6), (7., 0.7), (8., 0.8), (9., 0.)];
for mid in 0..sequence.len() {
let (left, right) = sequence.split_at(mid);
let avg_total: WeightedAverageWithError = sequence.iter().map(|&(x, w)| (x, w)).collect();
let mut avg_left: WeightedAverageWithError = left.iter().map(|&(x, w)| (x, w)).collect();
let avg_right: WeightedAverageWithError = right.iter().map(|&(x, w)| (x, w)).collect();
avg_left.merge(&avg_right);
assert_eq!(avg_total.len(), avg_left.len());
assert_almost_eq!(avg_total.sum_weights(), avg_left.sum_weights(), 1e-15);
assert_eq!(avg_total.sum_weights_sq(), avg_left.sum_weights_sq());
assert_almost_eq!(avg_total.weighted_mean(), avg_left.weighted_mean(), 1e-15);
assert_almost_eq!(avg_total.unweighted_mean(), avg_left.unweighted_mean(), 1e-15);
assert_almost_eq!(avg_total.sample_variance(), avg_left.sample_variance(), 1e-14);
}
}