logaritmiskandClaude Opus 5
355cdb7e05
`Add`, `Sub`, `exclude` and `forget` combined variances by way of standard
deviations: `sigma()` takes a square root, `.powi(2)` squares it away,
`var.sqrt()` takes another, and `from_ms` squares that one back. Three roots
to compute a value that is `1/pi` all along.
They now go through `variance()` and a new `from_mv(mu, var)`, which skip
both conversions. `Sub` is the hot one — `RankDiffFactor::propagate` is
`a - b`, run for every adjacent team pair on every forward and backward
sweep of every EP iteration.
`run_chain` also stopped recomputing each team's weighted performance in the
likelihood loop; the fold is already in `arena.team_prior`, indexed by the
sorted position the loop has in hand. Each `performance()` is itself a
`forget`, so the duplicate cost scaled with players per team.
Measured on this machine, before and after, same fixtures:
Batch::iteration 23.57us -> 19.31us (-18%)
scored_history_60_events 1.071ms -> 983us (-8%)
The `Gaussian::add`/`sub` microbenchmarks cannot resolve the change: they
sit at ~234ps against a ~218ps floor that `mul`/`div` also hit, so the
harness overhead dominates a single operation.
One golden moved. Two identical competitors drawing must land on their
shared prior mean exactly, by symmetry; the root-free path now returns
25.0 where the reference transcription recorded 24.999999 — that value
rounded to six decimals. Asserting a six-decimal transcription at
epsilon 1e-6 left no headroom, so the expectation is now the exact value.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01DnsaJg74eNSva3PJjK2eej
57 lines
2.1 KiB
Rust
57 lines
2.1 KiB
Rust
//! Equivalence tests: every historical golden from the pre-T2 tests is
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//! reproduced here at the integration level via the new public API.
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//!
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//! The in-crate tests in `src/history.rs::tests` and
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//! `src/time_slice.rs::tests` are the primary regression net for numerical
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//! behavior. This file provides Game-level goldens that stand alone and are
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//! more naturally expressed as integration tests.
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use approx::assert_ulps_eq;
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use trueskill_tt::{ConstantDrift, Game, GameOptions, Gaussian, Outcome, Rating};
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type R = Rating<i64, ConstantDrift>;
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fn ts_rating(mu: f64, sigma: f64, beta: f64, gamma: f64) -> R {
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R::new(Gaussian::from_ms(mu, sigma), beta, ConstantDrift(gamma))
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}
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#[test]
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fn game_1v1_golden_matches_historical() {
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let a = ts_rating(25.0, 25.0 / 3.0, 25.0 / 6.0, 25.0 / 300.0);
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let b = ts_rating(25.0, 25.0 / 3.0, 25.0 / 6.0, 25.0 / 300.0);
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let (a_post, b_post) = Game::<i64, _>::one_v_one(&a, &b, Outcome::winner(0, 2)).unwrap();
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// Historical golden from pre-T2 test_1vs1 (team 0 wins):
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assert_ulps_eq!(
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a_post,
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Gaussian::from_ms(29.205220, 7.194481),
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epsilon = 1e-6
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);
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assert_ulps_eq!(
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b_post,
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Gaussian::from_ms(20.794779, 7.194481),
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epsilon = 1e-6
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);
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}
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#[test]
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fn game_1v1_draw_golden() {
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let a = ts_rating(25.0, 25.0 / 3.0, 25.0 / 6.0, 25.0 / 300.0);
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let b = ts_rating(25.0, 25.0 / 3.0, 25.0 / 6.0, 25.0 / 300.0);
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let g = Game::<i64, _>::ranked(
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&[&[a], &[b]],
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Outcome::draw(2),
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&GameOptions {
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p_draw: 0.25,
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score_sigma: 1.0,
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convergence: Default::default(),
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},
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)
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.unwrap();
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let p = g.posteriors();
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// Historical golden from pre-T2 test_1vs1_draw. The mean is 25.0 exactly
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// by symmetry — two identical competitors drawing cannot move apart — and
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// the reference's 24.999999 is that value transcribed to six decimals.
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assert_ulps_eq!(p[0][0], Gaussian::from_ms(25.0, 6.469480), epsilon = 1e-6);
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assert_ulps_eq!(p[1][0], Gaussian::from_ms(25.0, 6.469480), epsilon = 1e-6);
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}
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