logaritmiskandClaude Opus 5
8dff7513f7
`gamma` enters only as `gamma * gamma`, so the sign was squared away: measured against the old public-field form, `ConstantDrift(-0.0833)` produced results bit identical to `ConstantDrift(0.0833)`. The sign was neither rejected nor honoured — it vanished. It could not be checked while the field was a public tuple position, because there was nothing to intercept. Validating inside `variance_for_elapsed` would have been worse: it runs in the sweep, so a construction-time mistake would panic mid-inference, and `Gaussian::from_ms` is a worked example of why that is the wrong place — rejecting NaN there turned the NonFiniteResult reporting path into a crash. So `ConstantDrift::new` is the only way in and it checks, with `gamma()` to read the value back. 129 call sites rewritten across src, tests, benches, examples and the README. The dated plan and spec documents under docs/superpowers are left alone: they record what was built at the time, and rewriting them would falsify that. tests/constructor_validation.rs is the more valuable half. This defect class was closed three times in one session and reopened twice, because each fix validated the layer it had just touched and inferred the rest — `HistoryBuilder`, then `Game`'s own entry points, then the constructors beneath both. A per-site fix cannot notice the site nobody thought of, so that file enumerates every public entry point taking a magnitude and asserts each refuses negative and non-finite values. It found an eleventh defect on its first run: `HistoryBuilder::score_sigma` accepted infinity, because `inf > 0.0` is true and the assert only tested positivity. Fixed, and its own `should_panic` message updated to match. `Gaussian::from_ms` is deliberately exempt from the non-finite half, for the reason above: a broken fit produces a NaN sigma legitimately and `converge` must be allowed to report it. The convergence-level drift-variance check stays and is now tested through a custom `Drift` implementation, since `ConstantDrift` can no longer reach it. That check is the only thing standing between a third-party `Drift` and a NaN fit. BREAKING CHANGE: `ConstantDrift`'s field is private. Replace `ConstantDrift(x)` with `ConstantDrift::new(x)`, and `drift().0` with `drift().gamma()`. `HistoryBuilder::score_sigma` now rejects infinity. Closes #65 Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ
72 lines
2.4 KiB
Rust
72 lines
2.4 KiB
Rust
//! Regression: a single time slice with many distinct competitors must converge to finite
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//! skills. Before the `pi <= 0` guard in `Gaussian::mu()/sigma()`, EP message cancellation
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//! produced a tiny-negative precision whose `sigma() = 1/sqrt(pi)` was NaN, which the
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//! moment-space `Sub` in the game chain propagated into every skill once the slice grew past
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//! ~75 competitors (e.g. a real ranking dataset with hundreds of players).
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use trueskill_tt::{ConstantDrift, ConvergenceOptions, EPSILON, History, ITERATIONS, NullObserver};
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/// Tiny deterministic LCG — avoids a dev-dependency on `rand`.
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struct Lcg(u64);
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impl Lcg {
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fn next(&mut self) -> u64 {
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self.0 = self
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.0
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.wrapping_mul(6364136223846793005)
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.wrapping_add(1442695040888963407);
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self.0
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}
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fn below(&mut self, n: usize) -> usize {
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(self.next() >> 33) as usize % n
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}
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fn coin(&mut self) -> bool {
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self.next() & 1 == 0
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}
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}
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fn nan_after_fit(players: usize) -> usize {
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let mut h: History<i64, ConstantDrift, NullObserver, String> = History::builder_with_key()
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.beta(1.0)
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.sigma(6.0)
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.drift(ConstantDrift::new(0.1))
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.convergence(ConvergenceOptions {
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max_iter: ITERATIONS,
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epsilon: EPSILON,
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..Default::default()
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})
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.build();
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let ids: Vec<String> = (0..players).map(|i| format!("p{i:04}")).collect();
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let mut rng = Lcg(1);
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for _ in 0..(players * 4) {
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let a = rng.below(players);
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let mut b = rng.below(players - 1);
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if b >= a {
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b += 1;
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}
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let (w, l) = if rng.coin() { (a, b) } else { (b, a) };
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h.record_winner(&ids[w], &ids[l], 0).unwrap();
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}
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let _ = h.converge().unwrap();
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ids.iter()
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.filter(|id| {
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h.current_skill(id.as_str())
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.map(|g| !g.mu().is_finite() || !g.sigma().is_finite())
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.unwrap_or(true)
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})
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.count()
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}
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#[test]
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fn many_competitors_converge_to_finite_skills() {
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// The NaN regression onset was between 70 and 80 competitors; 250 is comfortably past it
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// and in the range of a real ranking dataset.
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for players in [12usize, 75, 150, 250] {
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assert_eq!(
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nan_after_fit(players),
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0,
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"{players}-competitor history produced NaN skills"
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);
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}
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}
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