Implement merging of averages
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42
src/lib.rs
42
src/lib.rs
@ -39,6 +39,9 @@ impl Average {
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/// Add a number to the sequence of which the average is calculated.
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pub fn add(&mut self, x: f64) {
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// This algorithm introduced by Welford in 1962 trades numerical
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// stability for a division inside the loop.
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//
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// See https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance.
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self.n += 1;
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let delta = x - self.avg;
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@ -83,6 +86,25 @@ impl Average {
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}
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(self.sample_variance() / f64::approx_from(self.n).unwrap()).sqrt()
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}
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/// Merge the average of another sequence into this one.
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pub fn merge(&mut self, other: &Average) {
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// This algorithm was proposed by Chan et al. in 1979.
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//
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// See https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance.
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let delta = other.avg - self.avg;
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let len_self = f64::approx_from(self.n).unwrap();
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let len_other = f64::approx_from(other.n).unwrap();
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let len_total = len_self + len_other;
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self.n += other.n;
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self.avg = (len_self * self.avg + len_other * other.avg) / len_total;
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// Chan et al. use
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//
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// self.avg += delta * len_other / len_total;
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//
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// instead but this results in cancellation if the number of samples are similar.
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self.v += other.v + delta*delta * len_self * len_other / len_total;
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}
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}
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impl core::default::Default for Average {
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@ -118,10 +140,9 @@ macro_rules! assert_almost_eq {
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mod tests {
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use super::*;
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use core::iter::Iterator;
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use std::vec::Vec;
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use ::conv::ConvAsUtil;
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#[test]
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fn average_trivial() {
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let mut a = Average::new();
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@ -135,7 +156,7 @@ mod tests {
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#[test]
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fn average_simple() {
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let a: Average = (1..6).map(|x| x.approx().unwrap()).collect();
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let a: Average = (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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@ -154,6 +175,21 @@ mod tests {
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assert_almost_eq!(a.sample_variance().sqrt(), 3.0, 1e-2);
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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: Average = sequence.iter().map(|x| *x).collect();
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let mut avg_left: Average = left.iter().map(|x| *x).collect();
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let avg_right: Average = right.iter().map(|x| *x).collect();
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avg_left.merge(&avg_right);
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assert_eq!(avg_total.n, avg_left.n);
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assert_eq!(avg_total.avg, avg_left.avg);
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assert_eq!(avg_total.v, avg_left.v);
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}
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}
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fn initialize_vec() -> Vec<f64> {
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use rand::distributions::{Normal, IndependentSample};
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use rand::{XorShiftRng, SeedableRng};
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