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refactor(api): generify Drift, Rating, Competitor, TimeSlice, CompetitorStore, History over T: Time

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Drift now takes &T -> &T and is generic over the time axis. Untimed
impls return elapsed=0. ConstantDrift impl covers all T via the Time
trait. An additional variance_for_elapsed(i64) method on the trait
serves callers that work with the pre-cached i64 elapsed count.

Competitor.last_time moves from i64 with MIN sentinel to Option<T>
with None sentinel. receive(&T) computes variance from last_time
dynamically; receive_for_elapsed(i64) uses a pre-cached elapsed count
(needed in convergence sweeps where last_time has already advanced).

TimeSlice.time changes from i64 to T. compute_elapsed is now generic
over T and takes Option<&T> for the last-seen time. new_forward_info
uses receive_for_elapsed to preserve the cached elapsed during sweeps.

History<D> becomes History<T, D>; HistoryBuilder<D> becomes
HistoryBuilder<T, D>; Game<D> becomes Game<T, D>. Defaults keep
existing call sites compiling with zero changes: T = i64,
D = ConstantDrift.

add_events / add_events_with_prior stay on impl History<i64, D> since
times: Vec<i64> is i64-specific (Task 8 will generalise this).

In !self.time mode the old i64::MAX sentinel guaranteed elapsed=1 for
every slice transition regardless of time gaps. Replaced by advancing
all previously-seen agents' last_time to Some(current_slice_time) at
the end of each slice; this preserves elapsed=1 between adjacent
slices in sequential-integer untimed mode.

The time: bool field on History and .time(bool) on HistoryBuilder are
NOT removed by this task — deferred to Task 8 so this commit is
purely a type-level generification.

Part of T2 of docs/superpowers/specs/2026-04-23-trueskill-engine-redesign-design.md.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Anders Olsson
2026-04-24 11:50:35 +02:00
parent a285c1a0f2
commit 59e4cb35cc
8 changed files with 228 additions and 165 deletions
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97
src/game.rs
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@@ -8,12 +8,13 @@ use crate::{
factor::{Factor, trunc::TruncFactor},
gaussian::Gaussian,
rating::Rating,
time::Time,
tuple_gt, tuple_max,
};
#[derive(Debug)]
pub struct Game<'a, D: Drift> {
teams: Vec<Vec<Rating<D>>>,
pub struct Game<'a, T: Time = i64, D: Drift<T> = crate::drift::ConstantDrift> {
teams: Vec<Vec<Rating<T, D>>>,
result: &'a [f64],
weights: &'a [Vec<f64>],
p_draw: f64,
@@ -21,9 +22,9 @@ pub struct Game<'a, D: Drift> {
pub(crate) evidence: f64,
}
impl<'a, D: Drift> Game<'a, D> {
impl<'a, T: Time, D: Drift<T>> Game<'a, T, D> {
pub fn new(
teams: Vec<Vec<Rating<D>>>,
teams: Vec<Vec<Rating<T, D>>>,
result: &'a [f64],
weights: &'a [Vec<f64>],
p_draw: f64,
@@ -227,14 +228,16 @@ mod tests {
use super::*;
use crate::{ConstantDrift, GAMMA, Gaussian, N_INF, Rating, arena::ScratchArena};
type R = Rating<i64, ConstantDrift>;
#[test]
fn test_1vs1() {
let t_a = Rating::new(
let t_a = R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
);
let t_b = Rating::new(
let t_b = R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
@@ -256,12 +259,12 @@ mod tests {
assert_ulps_eq!(a, Gaussian::from_ms(20.794779, 7.194481), epsilon = 1e-6);
assert_ulps_eq!(b, Gaussian::from_ms(29.205220, 7.194481), epsilon = 1e-6);
let t_a = Rating::new(
let t_a = R::new(
Gaussian::from_ms(29.0, 1.0),
25.0 / 6.0,
ConstantDrift(GAMMA),
);
let t_b = Rating::new(
let t_b = R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(GAMMA),
@@ -283,8 +286,8 @@ mod tests {
assert_ulps_eq!(a, Gaussian::from_ms(28.896475, 0.996604), epsilon = 1e-6);
assert_ulps_eq!(b, Gaussian::from_ms(32.189211, 6.062063), epsilon = 1e-6);
let t_a = Rating::new(Gaussian::from_ms(1.139, 0.531), 1.0, ConstantDrift(0.2125));
let t_b = Rating::new(Gaussian::from_ms(15.568, 0.51), 1.0, ConstantDrift(0.2125));
let t_a = R::new(Gaussian::from_ms(1.139, 0.531), 1.0, ConstantDrift(0.2125));
let t_b = R::new(Gaussian::from_ms(15.568, 0.51), 1.0, ConstantDrift(0.2125));
let w = [vec![1.0], vec![1.0]];
let g = Game::new(
@@ -302,17 +305,17 @@ mod tests {
#[test]
fn test_1vs1vs1() {
let teams = vec![
vec![Rating::new(
vec![R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
)],
vec![Rating::new(
vec![R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
)],
vec![Rating::new(
vec![R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
@@ -367,12 +370,12 @@ mod tests {
#[test]
fn test_1vs1_draw() {
let t_a = Rating::new(
let t_a = R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
);
let t_b = Rating::new(
let t_b = R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
@@ -394,12 +397,12 @@ mod tests {
assert_ulps_eq!(a, Gaussian::from_ms(24.999999, 6.469480), epsilon = 1e-6);
assert_ulps_eq!(b, Gaussian::from_ms(24.999999, 6.469480), epsilon = 1e-6);
let t_a = Rating::new(
let t_a = R::new(
Gaussian::from_ms(25.0, 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
);
let t_b = Rating::new(
let t_b = R::new(
Gaussian::from_ms(29.0, 2.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
@@ -424,17 +427,17 @@ mod tests {
#[test]
fn test_1vs1vs1_draw() {
let t_a = Rating::new(
let t_a = R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
);
let t_b = Rating::new(
let t_b = R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
);
let t_c = Rating::new(
let t_c = R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
@@ -460,17 +463,17 @@ mod tests {
assert_ulps_eq!(b, Gaussian::from_ms(25.0, 5.707424), epsilon = 1e-6);
assert_ulps_eq!(c, Gaussian::from_ms(25.0, 5.729069), epsilon = 1e-6);
let t_a = Rating::new(
let t_a = R::new(
Gaussian::from_ms(25.0, 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
);
let t_b = Rating::new(
let t_b = R::new(
Gaussian::from_ms(25.0, 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
);
let t_c = Rating::new(
let t_c = R::new(
Gaussian::from_ms(29.0, 2.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
@@ -498,29 +501,29 @@ mod tests {
#[test]
fn test_2vs1vs2_mixed() {
let t_a = vec![
Rating::new(
R::new(
Gaussian::from_ms(12.0, 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
),
Rating::new(
R::new(
Gaussian::from_ms(18.0, 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
),
];
let t_b = vec![Rating::new(
let t_b = vec![R::new(
Gaussian::from_ms(30.0, 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
)];
let t_c = vec![
Rating::new(
R::new(
Gaussian::from_ms(14.0, 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
),
Rating::new(
R::new(
Gaussian::from_ms(16., 3.0),
25.0 / 6.0,
ConstantDrift(25.0 / 300.0),
@@ -549,12 +552,12 @@ mod tests {
let w_a = vec![1.0];
let w_b = vec![2.0];
let t_a = vec![Rating::new(
let t_a = vec![R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(0.0),
)];
let t_b = vec![Rating::new(
let t_b = vec![R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(0.0),
@@ -632,16 +635,8 @@ mod tests {
let w_a = vec![1.0];
let w_b = vec![0.0];
let t_a = vec![Rating::new(
Gaussian::from_ms(2.0, 6.0),
1.0,
ConstantDrift(0.0),
)];
let t_b = vec![Rating::new(
Gaussian::from_ms(2.0, 6.0),
1.0,
ConstantDrift(0.0),
)];
let t_a = vec![R::new(Gaussian::from_ms(2.0, 6.0), 1.0, ConstantDrift(0.0))];
let t_b = vec![R::new(Gaussian::from_ms(2.0, 6.0), 1.0, ConstantDrift(0.0))];
let w = [w_a, w_b];
let g = Game::new(
@@ -667,16 +662,8 @@ mod tests {
let w_a = vec![1.0];
let w_b = vec![-1.0];
let t_a = vec![Rating::new(
Gaussian::from_ms(2.0, 6.0),
1.0,
ConstantDrift(0.0),
)];
let t_b = vec![Rating::new(
Gaussian::from_ms(2.0, 6.0),
1.0,
ConstantDrift(0.0),
)];
let t_a = vec![R::new(Gaussian::from_ms(2.0, 6.0), 1.0, ConstantDrift(0.0))];
let t_b = vec![R::new(Gaussian::from_ms(2.0, 6.0), 1.0, ConstantDrift(0.0))];
let w = [w_a, w_b];
let g = Game::new(
@@ -694,12 +681,12 @@ mod tests {
#[test]
fn test_2vs2_weighted() {
let t_a = vec![
Rating::new(
R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(0.0),
),
Rating::new(
R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(0.0),
@@ -708,12 +695,12 @@ mod tests {
let w_a = vec![0.4, 0.8];
let t_b = vec![
Rating::new(
R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(0.0),
),
Rating::new(
R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(0.0),
@@ -824,7 +811,7 @@ mod tests {
let g = Game::new(
vec![
t_a.clone(),
vec![Rating::new(
vec![R::new(
Gaussian::from_ms(25.0, 25.0 / 3.0),
25.0 / 6.0,
ConstantDrift(0.0),