Anders Olsson
8b53cacd64
Adds soft Gaussian-observation evidence on the per-pair diff variable,
enabling continuous score margins as a richer alternative to ranks.
Public API:
- `Outcome::Scored([scores])` (non-breaking enum extension under
`#[non_exhaustive]`).
- `Game::scored(teams, outcome, options)` constructor parallel to
`Game::ranked`.
- `EventBuilder::scores([...])` fluent helper.
- `HistoryBuilder::score_sigma(σ)` knob (default 1.0, validated > 0).
- `GameOptions::score_sigma`.
- `EventKind` re-exported from `lib.rs` (annotated `#[non_exhaustive]`).
- New `InferenceError::InvalidParameter { name, value }` variant.
Internals:
- `MarginFactor` (`factor/margin.rs`): Gaussian observation factor that
closes in one EP step; cavity-cached log-evidence mirrors `TruncFactor`.
- `BuiltinFactor::Margin` dispatch arm.
- `DiffFactor` enum in `game.rs` lets `Game::likelihoods` and the new
`likelihoods_scored` share the per-pair link abstraction.
- Per-event `EventKind { Ranked, Scored { score_sigma } }` routed through
`TimeSlice::add_events`, `iteration_direct`, and `log_evidence`.
Tests: 88 lib + 27 integration (4 new in `tests/scored.rs`); existing
goldens byte-identical. Bench: `benches/scored.rs` baseline ~960µs for
60 events × 20-player pool with default convergence.
Plan: docs/superpowers/plans/2026-04-27-t4-margin-factor.md
Spec item marked Done.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
63 lines
1.9 KiB
Rust
63 lines
1.9 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:
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assert_ulps_eq!(
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p[0][0],
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Gaussian::from_ms(24.999999, 6.469480),
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epsilon = 1e-6
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);
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assert_ulps_eq!(
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p[1][0],
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Gaussian::from_ms(24.999999, 6.469480),
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epsilon = 1e-6
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);
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}
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