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

Use and Index struct instead of str and String for player id

Browse Source
This commit is contained in:
Anders Olsson
2022-06-27 10:16:12 +02:00
parent d52895f804
commit cd1079a811
4 changed files with 514 additions and 455 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
README.md
View File

@@ -12,7 +12,7 @@ Rust port of [TrueSkillThroughTime.py](https://github.com/glandfried/TrueSkillTh
## Todo
- [x] Implement approx for Gaussian
- [ ] Add more tests from `TrueSkillThroughTime.jl`
- [x] Add more tests from `TrueSkillThroughTime.jl`
- [ ] Time needs to be an enum so we can have multiple states (see `batch::compute_elapsed()`)
- [ ] Add examples (use same TrueSkillThroughTime.(py|jl))
- [ ] Add Observer (see [argmin](https://docs.rs/argmin/latest/argmin/core/trait.Observe.html) for inspiration)

237
src/batch.rs
View File

@@ -1,7 +1,7 @@
use std::collections::{HashMap, HashSet};
use crate::{
agent::Agent, game::Game, gaussian::Gaussian, player::Player, tuple_gt, tuple_max, N_INF,
agent::Agent, game::Game, gaussian::Gaussian, player::Player, tuple_gt, tuple_max, Index, N_INF,
};
#[derive(Debug)]
@@ -27,7 +27,7 @@ impl Default for Skill {
#[derive(Debug)]
struct Item {
agent: String,
agent: Index,
likelihood: Gaussian,
}
@@ -56,19 +56,19 @@ impl Event {
#[derive(Debug)]
pub struct Batch {
pub(crate) events: Vec<Event>,
pub(crate) skills: HashMap<String, Skill>,
pub(crate) skills: HashMap<Index, Skill>,
pub(crate) time: u64,
p_draw: f64,
}
impl Batch {
pub(crate) fn new(
composition: Vec<Vec<Vec<&str>>>,
composition: Vec<Vec<Vec<Index>>>,
results: Vec<Vec<f64>>,
weights: Vec<Vec<Vec<f64>>>,
time: u64,
p_draw: f64,
agents: &mut HashMap<String, Agent>,
agents: &mut HashMap<Index, Agent>,
) -> Self {
assert!(
results.is_empty() || results.len() == composition.len(),
@@ -88,17 +88,17 @@ impl Batch {
let elapsed = this_agent
.iter()
.map(|&a| (a, compute_elapsed(agents[a].last_time, time)))
.map(|&idx| (idx, compute_elapsed(agents[&idx].last_time, time)))
.collect::<HashMap<_, _>>();
let skills = this_agent
.iter()
.map(|&a| {
.map(|&idx| {
(
a.to_string(),
idx,
Skill {
forward: agents[a].receive(elapsed[a]),
elapsed: elapsed[a],
forward: agents[&idx].receive(elapsed[&idx]),
elapsed: elapsed[&idx],
..Default::default()
},
)
@@ -111,7 +111,7 @@ impl Batch {
.map(|t| {
let items = (0..composition[e][t].len())
.map(|a| Item {
agent: composition[e][t][a].to_string(),
agent: composition[e][t][a],
likelihood: N_INF,
})
.collect::<Vec<_>>();
@@ -153,10 +153,10 @@ impl Batch {
pub(crate) fn add_events(
&mut self,
composition: Vec<Vec<Vec<&str>>>,
composition: Vec<Vec<Vec<Index>>>,
results: Vec<Vec<f64>>,
weights: Vec<Vec<Vec<f64>>>,
agents: &mut HashMap<String, Agent>,
agents: &mut HashMap<Index, Agent>,
) {
let this_agent = composition
.iter()
@@ -165,17 +165,17 @@ impl Batch {
.cloned()
.collect::<HashSet<_>>();
for a in this_agent {
let elapsed = compute_elapsed(agents[a].last_time, self.time);
for idx in this_agent {
let elapsed = compute_elapsed(agents[&idx].last_time, self.time);
if let Some(skill) = self.skills.get_mut(a) {
if let Some(skill) = self.skills.get_mut(&idx) {
skill.elapsed = elapsed;
skill.forward = agents[a].receive(elapsed);
skill.forward = agents[&idx].receive(elapsed);
} else {
self.skills.insert(
a.to_string(),
idx,
Skill {
forward: agents[a].receive(elapsed),
forward: agents[&idx].receive(elapsed),
elapsed,
..Default::default()
},
@@ -190,7 +190,7 @@ impl Batch {
.map(|t| {
let items = (0..composition[e][t].len())
.map(|a| Item {
agent: composition[e][t][a].to_string(),
agent: composition[e][t][a],
likelihood: N_INF,
})
.collect::<Vec<_>>();
@@ -222,16 +222,16 @@ impl Batch {
self.iteration(from, agents);
}
pub fn posterior(&self, agent: &str) -> Gaussian {
let skill = &self.skills[agent];
pub fn posterior(&self, agent: Index) -> Gaussian {
let skill = &self.skills[&agent];
skill.likelihood * skill.backward * skill.forward
}
pub(crate) fn posteriors(&self) -> HashMap<String, Gaussian> {
pub(crate) fn posteriors(&self) -> HashMap<Index, Gaussian> {
self.skills
.keys()
.map(|a| (a.to_string(), self.posterior(a)))
.map(|&idx| (idx, self.posterior(idx)))
.collect::<HashMap<_, _>>()
}
@@ -240,7 +240,7 @@ impl Batch {
item: &Item,
online: bool,
forward: bool,
agents: &mut HashMap<String, Agent>,
agents: &mut HashMap<Index, Agent>,
) -> Player {
let r = &agents[&item.agent].player;
@@ -249,7 +249,7 @@ impl Batch {
} else if forward {
Player::new(self.skills[&item.agent].forward, r.beta, r.gamma)
} else {
let wp = self.posterior(&item.agent) / item.likelihood;
let wp = self.posterior(item.agent) / item.likelihood;
Player::new(wp, r.beta, r.gamma)
}
@@ -260,7 +260,7 @@ impl Batch {
event: usize,
online: bool,
forward: bool,
agents: &mut HashMap<String, Agent>,
agents: &mut HashMap<Index, Agent>,
) -> Vec<Vec<Player>> {
self.events[event]
.teams
@@ -274,7 +274,7 @@ impl Batch {
.collect::<Vec<_>>()
}
pub(crate) fn iteration(&mut self, from: usize, agents: &mut HashMap<String, Agent>) {
pub(crate) fn iteration(&mut self, from: usize, agents: &mut HashMap<Index, Agent>) {
for e in from..self.events.len() {
let teams = self.within_priors(e, false, false, agents);
let result = self.events[e].outputs();
@@ -295,7 +295,7 @@ impl Batch {
}
}
pub(crate) fn convergence(&mut self, agents: &mut HashMap<String, Agent>) -> usize {
pub(crate) fn convergence(&mut self, agents: &mut HashMap<Index, Agent>) -> usize {
let epsilon = 1e-6;
let iterations = 20;
@@ -319,7 +319,7 @@ impl Batch {
i
}
pub(crate) fn forward_prior_out(&self, agent: &str) -> Gaussian {
pub(crate) fn forward_prior_out(&self, agent: &Index) -> Gaussian {
let skill = &self.skills[agent];
skill.forward * skill.likelihood
@@ -327,8 +327,8 @@ impl Batch {
pub(crate) fn backward_prior_out(
&self,
agent: &str,
agents: &mut HashMap<String, Agent>,
agent: &Index,
agents: &mut HashMap<Index, Agent>,
) -> Gaussian {
let skill = &self.skills[agent];
let n = skill.likelihood * skill.backward;
@@ -336,7 +336,7 @@ impl Batch {
n.forget(agents[agent].player.gamma, skill.elapsed)
}
pub(crate) fn new_backward_info(&mut self, agents: &mut HashMap<String, Agent>) {
pub(crate) fn new_backward_info(&mut self, agents: &mut HashMap<Index, Agent>) {
for (agent, skill) in self.skills.iter_mut() {
skill.backward = agents[agent].message;
}
@@ -344,7 +344,7 @@ impl Batch {
self.iteration(0, agents);
}
pub(crate) fn new_forward_info(&mut self, agents: &mut HashMap<String, Agent>) {
pub(crate) fn new_forward_info(&mut self, agents: &mut HashMap<Index, Agent>) {
for (agent, skill) in self.skills.iter_mut() {
skill.forward = agents[agent].receive(skill.elapsed);
}
@@ -352,14 +352,14 @@ impl Batch {
self.iteration(0, agents);
}
pub(crate) fn log_evidence2(
pub(crate) fn log_evidence(
&self,
online: bool,
agents2: &Vec<&str>,
targets: &[Index],
forward: bool,
agents: &mut HashMap<String, Agent>,
agents: &mut HashMap<Index, Agent>,
) -> f64 {
if agents2.is_empty() {
if targets.is_empty() {
if online || forward {
self.events
.iter()
@@ -388,7 +388,7 @@ impl Batch {
.teams
.iter()
.flat_map(|team| &team.items)
.any(|item| agents2.contains(&item.agent.as_str()))
.any(|item| targets.contains(&item.agent))
})
.map(|(e, event)| {
Game::new(
@@ -409,7 +409,7 @@ impl Batch {
.teams
.iter()
.flat_map(|team| &team.items)
.any(|item| agents2.contains(&item.agent.as_str()))
.any(|item| targets.contains(&item.agent))
})
.map(|event| event.evidence.ln())
.sum()
@@ -417,19 +417,14 @@ impl Batch {
}
}
pub(crate) fn get_composition(&self) -> Vec<Vec<Vec<&str>>> {
pub(crate) fn get_composition(&self) -> Vec<Vec<Vec<Index>>> {
self.events
.iter()
.map(|event| {
event
.teams
.iter()
.map(|team| {
team.items
.iter()
.map(|item| item.agent.as_str())
.collect::<Vec<_>>()
})
.map(|team| team.items.iter().map(|item| item.agent).collect::<Vec<_>>())
.collect::<Vec<_>>()
})
.collect::<Vec<_>>()
@@ -463,17 +458,26 @@ pub(crate) fn compute_elapsed(last_time: u64, actual_time: u64) -> u64 {
mod tests {
use approx::assert_ulps_eq;
use crate::{agent::Agent, player::Player};
use crate::{agent::Agent, player::Player, IndexMap};
use super::*;
#[test]
fn test_one_event_each() {
let mut index_map = IndexMap::new();
let a = index_map.get_or_create("a");
let b = index_map.get_or_create("b");
let c = index_map.get_or_create("c");
let d = index_map.get_or_create("d");
let e = index_map.get_or_create("e");
let f = index_map.get_or_create("f");
let mut agents = HashMap::new();
for agent in ["a", "b", "c", "d", "e", "f"] {
for agent in [a, b, c, d, e, f] {
agents.insert(
agent.to_string(),
agent,
Agent {
player: Player::new(Gaussian::new(25.0, 25.0 / 3.0), 25.0 / 6.0, 25.0 / 300.0),
..Default::default()
@@ -483,9 +487,9 @@ mod tests {
let mut batch = Batch::new(
vec![
vec![vec!["a"], vec!["b"]],
vec![vec!["c"], vec!["d"]],
vec![vec!["e"], vec!["f"]],
vec![vec![a], vec![b]],
vec![vec![c], vec![d]],
vec![vec![e], vec![f]],
],
vec![vec![1.0, 0.0], vec![0.0, 1.0], vec![1.0, 0.0]],
vec![],
@@ -496,34 +500,32 @@ mod tests {
let post = batch.posteriors();
assert_ulps_eq!(post["a"].mu, 29.205220743876975, epsilon = 0.000001);
assert_ulps_eq!(post["a"].sigma, 7.194481422570443, epsilon = 0.000001);
assert_ulps_eq!(post["b"].mu, 20.79477925612302, epsilon = 0.000001);
assert_ulps_eq!(post["b"].sigma, 7.194481422570443, epsilon = 0.000001);
assert_ulps_eq!(post["c"].mu, 20.79477925612302, epsilon = 0.000001);
assert_ulps_eq!(post["c"].sigma, 7.194481422570443, epsilon = 0.000001);
assert_ulps_eq!(post["d"].mu, 29.205220743876975, epsilon = 0.000001);
assert_ulps_eq!(post["d"].sigma, 7.194481422570443, epsilon = 0.000001);
assert_ulps_eq!(post["e"].mu, 29.205220743876975, epsilon = 0.000001);
assert_ulps_eq!(post["e"].sigma, 7.194481422570443, epsilon = 0.000001);
assert_ulps_eq!(post["f"].mu, 20.79477925612302, epsilon = 0.000001);
assert_ulps_eq!(post["f"].sigma, 7.194481422570443, epsilon = 0.000001);
assert_ulps_eq!(post[&a], Gaussian::new(29.205220, 7.194481), epsilon = 1e-6);
assert_ulps_eq!(post[&b], Gaussian::new(20.794779, 7.194481), epsilon = 1e-6);
assert_ulps_eq!(post[&c], Gaussian::new(20.794779, 7.194481), epsilon = 1e-6);
assert_ulps_eq!(post[&d], Gaussian::new(29.205220, 7.194481), epsilon = 1e-6);
assert_ulps_eq!(post[&e], Gaussian::new(29.205220, 7.194481), epsilon = 1e-6);
assert_ulps_eq!(post[&f], Gaussian::new(20.794779, 7.194481), epsilon = 1e-6);
assert_eq!(batch.convergence(&mut agents), 1);
}
#[test]
fn test_same_strength() {
let mut index_map = IndexMap::new();
let a = index_map.get_or_create("a");
let b = index_map.get_or_create("b");
let c = index_map.get_or_create("c");
let d = index_map.get_or_create("d");
let e = index_map.get_or_create("e");
let f = index_map.get_or_create("f");
let mut agents = HashMap::new();
for agent in ["a", "b", "c", "d", "e", "f"] {
for agent in [a, b, c, d, e, f] {
agents.insert(
agent.to_string(),
agent,
Agent {
player: Player::new(Gaussian::new(25.0, 25.0 / 3.0), 25.0 / 6.0, 25.0 / 300.0),
..Default::default()
@@ -533,9 +535,9 @@ mod tests {
let mut batch = Batch::new(
vec![
vec![vec!["a"], vec!["b"]],
vec![vec!["a"], vec!["c"]],
vec![vec!["b"], vec!["c"]],
vec![vec![a], vec![b]],
vec![vec![a], vec![c]],
vec![vec![b], vec![c]],
],
vec![vec![1.0, 0.0], vec![0.0, 1.0], vec![1.0, 0.0]],
vec![],
@@ -546,36 +548,35 @@ mod tests {
let post = batch.posteriors();
assert_ulps_eq!(post["a"].mu, 24.96097857478182, epsilon = 0.000001);
assert_ulps_eq!(post["a"].sigma, 6.298544763358269, epsilon = 0.000001);
assert_ulps_eq!(post["b"].mu, 27.095590669107086, epsilon = 0.000001);
assert_ulps_eq!(post["b"].sigma, 6.010330439043099, epsilon = 0.000001);
assert_ulps_eq!(post["c"].mu, 24.88968178743119, epsilon = 0.000001);
assert_ulps_eq!(post["c"].sigma, 5.866311348102562, epsilon = 0.000001);
assert_ulps_eq!(post[&a], Gaussian::new(24.960978, 6.298544), epsilon = 1e-6);
assert_ulps_eq!(post[&b], Gaussian::new(27.095590, 6.010330), epsilon = 1e-6);
assert_ulps_eq!(post[&c], Gaussian::new(24.889681, 5.866311), epsilon = 1e-6);
assert!(batch.convergence(&mut agents) > 1);
let post = batch.posteriors();
assert_ulps_eq!(post["a"].mu, 25.000000, epsilon = 0.000001);
assert_ulps_eq!(post["a"].sigma, 5.4192120, epsilon = 0.000001);
assert_ulps_eq!(post["b"].mu, 25.000000, epsilon = 0.000001);
assert_ulps_eq!(post["b"].sigma, 5.4192120, epsilon = 0.000001);
assert_ulps_eq!(post["c"].mu, 25.000000, epsilon = 0.000001);
assert_ulps_eq!(post["c"].sigma, 5.4192120, epsilon = 0.000001);
assert_ulps_eq!(post[&a], Gaussian::new(25.000000, 5.419212), epsilon = 1e-6);
assert_ulps_eq!(post[&b], Gaussian::new(25.000000, 5.419212), epsilon = 1e-6);
assert_ulps_eq!(post[&c], Gaussian::new(25.000000, 5.419212), epsilon = 1e-6);
}
#[test]
fn test_add_events() {
let mut index_map = IndexMap::new();
let a = index_map.get_or_create("a");
let b = index_map.get_or_create("b");
let c = index_map.get_or_create("c");
let d = index_map.get_or_create("d");
let e = index_map.get_or_create("e");
let f = index_map.get_or_create("f");
let mut agents = HashMap::new();
for agent in ["a", "b", "c", "d", "e", "f"] {
for agent in [a, b, c, d, e, f] {
agents.insert(
agent.to_string(),
agent,
Agent {
player: Player::new(Gaussian::new(25.0, 25.0 / 3.0), 25.0 / 6.0, 25.0 / 300.0),
..Default::default()
@@ -585,9 +586,9 @@ mod tests {
let mut batch = Batch::new(
vec![
vec![vec!["a"], vec!["b"]],
vec![vec!["a"], vec!["c"]],
vec![vec!["b"], vec!["c"]],
vec![vec![a], vec![b]],
vec![vec![a], vec![c]],
vec![vec![b], vec![c]],
],
vec![vec![1.0, 0.0], vec![0.0, 1.0], vec![1.0, 0.0]],
vec![],
@@ -600,29 +601,15 @@ mod tests {
let post = batch.posteriors();
assert_ulps_eq!(
post["a"],
Gaussian::new(25.000000, 5.4192120),
epsilon = 0.000001
);
assert_ulps_eq!(
post["b"],
Gaussian::new(25.000000, 5.4192120),
epsilon = 0.000001
);
assert_ulps_eq!(
post["c"],
Gaussian::new(25.000000, 5.4192120),
epsilon = 0.000001
);
assert_ulps_eq!(post[&a], Gaussian::new(25.000000, 5.419212), epsilon = 1e-6);
assert_ulps_eq!(post[&b], Gaussian::new(25.000000, 5.419212), epsilon = 1e-6);
assert_ulps_eq!(post[&c], Gaussian::new(25.000000, 5.419212), epsilon = 1e-6);
batch.add_events(
vec![
vec![vec!["a"], vec!["b"]],
vec![vec!["a"], vec!["c"]],
vec![vec!["b"], vec!["c"]],
vec![vec![a], vec![b]],
vec![vec![a], vec![c]],
vec![vec![b], vec![c]],
],
vec![vec![1.0, 0.0], vec![0.0, 1.0], vec![1.0, 0.0]],
vec![],
@@ -635,20 +622,8 @@ mod tests {
let post = batch.posteriors();
assert_ulps_eq!(
post["a"],
Gaussian::new(25.00000315330858, 3.880150268080797),
epsilon = 0.000001
);
assert_ulps_eq!(
post["b"],
Gaussian::new(25.00000315330858, 3.880150268080797),
epsilon = 0.000001
);
assert_ulps_eq!(
post["c"],
Gaussian::new(25.00000315330858, 3.880150268080797),
epsilon = 0.000001
);
assert_ulps_eq!(post[&a], Gaussian::new(25.000003, 3.880150), epsilon = 1e-6);
assert_ulps_eq!(post[&b], Gaussian::new(25.000003, 3.880150), epsilon = 1e-6);
assert_ulps_eq!(post[&c], Gaussian::new(25.000003, 3.880150), epsilon = 1e-6);
}
}

685
src/history.rs
View File

File diff suppressed because it is too large Load Diff

45
src/lib.rs
View File

@@ -1,5 +1,8 @@
use std::borrow::{Borrow, ToOwned};
use std::cmp::Reverse;
use std::collections::HashMap;
use std::f64::consts::{FRAC_1_SQRT_2, FRAC_2_SQRT_PI, SQRT_2};
use std::hash::Hash;
mod agent;
#[cfg(feature = "approx")]
@@ -27,19 +30,55 @@ pub const ITERATIONS: usize = 30;
const SQRT_TAU: f64 = 2.5066282746310002;
const N01: Gaussian = Gaussian {
pub const N01: Gaussian = Gaussian {
mu: 0.0,
sigma: 1.0,
};
pub(crate) const N00: Gaussian = Gaussian {
pub const N00: Gaussian = Gaussian {
mu: 0.0,
sigma: 0.0,
};
pub(crate) const N_INF: Gaussian = Gaussian {
pub const N_INF: Gaussian = Gaussian {
mu: 0.0,
sigma: f64::INFINITY,
};
#[derive(Copy, Clone, Default, PartialEq, PartialOrd, Eq, Ord, Hash, Debug)]
pub struct Index(usize);
impl From<usize> for Index {
fn from(ix: usize) -> Self {
Self(ix)
}
}
pub struct IndexMap<K>(HashMap<K, Index>);
impl<K> IndexMap<K>
where
K: Eq + Hash,
{
pub fn new() -> Self {
Self(HashMap::new())
}
pub fn get_or_create<Q: ?Sized>(&mut self, k: &Q) -> Index
where
K: Borrow<Q>,
Q: Hash + Eq + ToOwned<Owned = K>,
{
if let Some(idx) = self.0.get(k) {
*idx
} else {
let idx = Index::from(self.0.len());
self.0.insert(k.to_owned(), idx);
idx
}
}
}
fn erfc(x: f64) -> f64 {
let z = x.abs();
let t = 1.0 / (1.0 + z / 2.0);