logaritmisk/trueskill-tt
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Added benchmark for Batch

Browse Source
This commit is contained in:
Anders Olsson
2022-12-19 07:42:08 +01:00
parent 2bdd3d9b89
commit 2b83ee5ef9
8 changed files with 131 additions and 66 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
src/agent.rs
View File

@@ -1,10 +1,10 @@
use crate::{gaussian::Gaussian, player::Player, N_INF};
#[derive(Debug)]
pub(crate) struct Agent {
pub(crate) player: Player,
pub(crate) message: Gaussian,
pub(crate) last_time: i64,
pub struct Agent {
pub player: Player,
pub message: Gaussian,
pub last_time: i64,
}
impl Agent {

11
src/batch.rs
View File

@@ -109,7 +109,7 @@ pub struct Batch {
}
impl Batch {
pub(crate) fn new(
pub fn new(
composition: Vec<Vec<Vec<Index>>>,
results: Vec<Vec<f64>>,
weights: Vec<Vec<Vec<f64>>>,
@@ -269,13 +269,6 @@ impl Batch {
self.iteration(from, agents);
}
// TODO(anders): Use Item::posterior() instead.
pub fn posterior(&self, agent: Index) -> Gaussian {
let skill = &self.skills[&agent];
skill.likelihood * skill.backward * skill.forward
}
pub(crate) fn posteriors(&self) -> HashMap<Index, Gaussian> {
self.skills
.iter()
@@ -283,7 +276,7 @@ impl Batch {
.collect::<HashMap<_, _>>()
}
pub(crate) fn iteration(&mut self, from: usize, agents: &HashMap<Index, Agent>) {
pub fn iteration(&mut self, from: usize, agents: &HashMap<Index, Agent>) {
for event in self.events.iter_mut().skip(from) {
let teams = event.within_priors(false, false, &self.skills, agents);
let result = event.outputs();

98
src/history.rs
View File

@@ -460,7 +460,7 @@ mod tests {
assert_ulps_eq!(observed, expected, epsilon = 0.000001);
let observed = h.batches[1].posterior(a);
let observed = h.batches[1].skills[&a].posterior();
let p = Game::new(
h.batches[1].events[0].within_priors(false, false, &h.batches[1].skills, &h.agents),
@@ -508,12 +508,12 @@ mod tests {
h1.add_events_with_prior(composition, results, times, vec![], priors);
assert_ulps_eq!(
h1.batches[0].posterior(a),
h1.batches[0].skills[&a].posterior(),
Gaussian::new(22.904409, 6.010330),
epsilon = 1e-6
);
assert_ulps_eq!(
h1.batches[0].posterior(c),
h1.batches[0].skills[&c].posterior(),
Gaussian::new(25.110318, 5.866311),
epsilon = 1e-6
);
@@ -521,12 +521,12 @@ mod tests {
h1.convergence(ITERATIONS, EPSILON, false);
assert_ulps_eq!(
h1.batches[0].posterior(a),
h1.batches[0].skills[&a].posterior(),
Gaussian::new(25.000000, 5.419212),
epsilon = 1e-6
);
assert_ulps_eq!(
h1.batches[0].posterior(c),
h1.batches[0].skills[&c].posterior(),
Gaussian::new(25.000000, 5.419212),
epsilon = 1e-6
);
@@ -553,12 +553,12 @@ mod tests {
h2.add_events_with_prior(composition, results, times, vec![], priors);
assert_ulps_eq!(
h2.batches[2].posterior(a),
h2.batches[2].skills[&a].posterior(),
Gaussian::new(22.903522, 6.011017),
epsilon = 1e-6
);
assert_ulps_eq!(
h2.batches[2].posterior(c),
h2.batches[2].skills[&c].posterior(),
Gaussian::new(25.110702, 5.866811),
epsilon = 1e-6
);
@@ -566,12 +566,12 @@ mod tests {
h2.convergence(ITERATIONS, EPSILON, false);
assert_ulps_eq!(
h2.batches[2].posterior(a),
h2.batches[2].skills[&a].posterior(),
Gaussian::new(24.998668, 5.420053),
epsilon = 1e-6
);
assert_ulps_eq!(
h2.batches[2].posterior(c),
h2.batches[2].skills[&c].posterior(),
Gaussian::new(25.000532, 5.419827),
epsilon = 1e-6
);
@@ -658,17 +658,17 @@ mod tests {
assert_eq!(h.batches[2].skills[&c].elapsed, 1);
assert_ulps_eq!(
h.batches[0].posterior(a),
h.batches[0].skills[&a].posterior(),
Gaussian::new(25.000267, 5.419381),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[0].posterior(b),
h.batches[0].skills[&b].posterior(),
Gaussian::new(24.999465, 5.419425),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[2].posterior(b),
h.batches[2].skills[&b].posterior(),
Gaussian::new(25.000532, 5.419696),
epsilon = 1e-6
);
@@ -712,8 +712,8 @@ mod tests {
);
assert_ulps_eq!(
h.batches[0].posterior(b).mu,
-1.0 * h.batches[0].posterior(c).mu,
h.batches[0].skills[&b].posterior().mu,
-1.0 * h.batches[0].skills[&c].posterior().mu,
epsilon = 1e-6
);
@@ -732,33 +732,33 @@ mod tests {
assert_ulps_eq!(p_d_m_hat, 0.172432, epsilon = 1e-6);
assert_ulps_eq!(
h.batches[0].posterior(a),
h.batches[0].posterior(b),
h.batches[0].skills[&a].posterior(),
h.batches[0].skills[&b].posterior(),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[0].posterior(c),
h.batches[0].posterior(d),
h.batches[0].skills[&c].posterior(),
h.batches[0].skills[&d].posterior(),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[1].posterior(e),
h.batches[1].posterior(f),
h.batches[1].skills[&e].posterior(),
h.batches[1].skills[&f].posterior(),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[0].posterior(a),
h.batches[0].skills[&a].posterior(),
Gaussian::new(4.084902, 5.106919),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[0].posterior(c),
h.batches[0].skills[&c].posterior(),
Gaussian::new(-0.533029, 5.106919),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[2].posterior(e),
h.batches[2].skills[&e].posterior(),
Gaussian::new(-3.551872, 5.154569),
epsilon = 1e-6
);
@@ -795,17 +795,17 @@ mod tests {
assert_eq!(h.batches[2].skills[&c].elapsed, 1);
assert_ulps_eq!(
h.batches[0].posterior(a),
h.batches[0].skills[&a].posterior(),
Gaussian::new(0.000000, 1.300610),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[0].posterior(b),
h.batches[0].skills[&b].posterior(),
Gaussian::new(0.000000, 1.300610),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[2].posterior(b),
h.batches[2].skills[&b].posterior(),
Gaussian::new(0.000000, 1.300610),
epsilon = 1e-6
);
@@ -832,22 +832,22 @@ mod tests {
h.convergence(ITERATIONS, EPSILON, false);
assert_ulps_eq!(
h.batches[0].posterior(a),
h.batches[0].skills[&a].posterior(),
Gaussian::new(0.000000, 0.931236),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[3].posterior(a),
h.batches[3].skills[&a].posterior(),
Gaussian::new(0.000000, 0.931236),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[3].posterior(b),
h.batches[3].skills[&b].posterior(),
Gaussian::new(0.000000, 0.931236),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[5].posterior(b),
h.batches[5].skills[&b].posterior(),
Gaussian::new(0.000000, 0.931236),
epsilon = 1e-6
);
@@ -884,17 +884,17 @@ mod tests {
assert_eq!(h.batches[2].skills[&c].elapsed, 1);
assert_ulps_eq!(
h.batches[0].posterior(a),
h.batches[0].skills[&a].posterior(),
Gaussian::new(0.000000, 1.300610),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[0].posterior(b),
h.batches[0].skills[&b].posterior(),
Gaussian::new(0.000000, 1.300610),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[2].posterior(b),
h.batches[2].skills[&b].posterior(),
Gaussian::new(0.000000, 1.300610),
epsilon = 1e-6
);
@@ -921,22 +921,22 @@ mod tests {
h.convergence(ITERATIONS, EPSILON, false);
assert_ulps_eq!(
h.batches[0].posterior(a),
h.batches[0].skills[&a].posterior(),
Gaussian::new(0.000000, 0.931236),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[3].posterior(a),
h.batches[3].skills[&a].posterior(),
Gaussian::new(0.000000, 0.931236),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[3].posterior(b),
h.batches[3].skills[&b].posterior(),
Gaussian::new(0.000000, 0.931236),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[5].posterior(b),
h.batches[5].skills[&b].posterior(),
Gaussian::new(0.000000, 0.931236),
epsilon = 1e-6
);
@@ -1084,20 +1084,20 @@ mod tests {
h.convergence(ITERATIONS, EPSILON, false);
assert_ulps_eq!(
h.batches[0].posterior(b),
h.batches[end].posterior(b),
h.batches[0].skills[&b].posterior(),
h.batches[end].skills[&b].posterior(),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[0].posterior(c),
h.batches[end].posterior(c),
h.batches[0].skills[&c].posterior(),
h.batches[end].skills[&c].posterior(),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[0].posterior(c),
h.batches[0].posterior(b),
h.batches[0].skills[&c].posterior(),
h.batches[0].skills[&b].posterior(),
epsilon = 1e-6
);
@@ -1172,20 +1172,20 @@ mod tests {
h.convergence(ITERATIONS, EPSILON, false);
assert_ulps_eq!(
h.batches[0].posterior(b),
h.batches[end].posterior(b),
h.batches[0].skills[&b].posterior(),
h.batches[end].skills[&b].posterior(),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[0].posterior(c),
h.batches[end].posterior(c),
h.batches[0].skills[&c].posterior(),
h.batches[end].skills[&c].posterior(),
epsilon = 1e-6
);
assert_ulps_eq!(
h.batches[0].posterior(c),
h.batches[0].posterior(b),
h.batches[0].skills[&c].posterior(),
h.batches[0].skills[&b].posterior(),
epsilon = 1e-6
);
}

8
src/lib.rs
View File

@@ -4,15 +4,15 @@ use std::collections::HashMap;
use std::f64::consts::{FRAC_1_SQRT_2, FRAC_2_SQRT_PI, SQRT_2};
use std::hash::Hash;
mod agent;
pub mod agent;
#[cfg(feature = "approx")]
mod approx;
mod batch;
pub mod batch;
mod game;
mod gaussian;
pub mod gaussian;
mod history;
mod message;
mod player;
pub mod player;
pub use game::Game;
pub use gaussian::Gaussian;