Files
trueskill-tt/tests/prediction_guards.rs
logaritmiskandClaude Opus 5 061c481aad refactor!: typed discriminators for InferenceError
Six of fifteen variants carried a `&'static str` discriminator, about
thirty magic strings between them, and the only thing a caller could do
with one was print it. Four new enums replace them:

    Parameter        13 variants, replacing 9 strings in InvalidParameter
    Shape             4 variants, replacing 10 in MismatchedShape
    OutcomeKind       2 variants, replacing WrongOutcomeKind's three fields
    CompetitorField   2 variants, replacing ConflictingCompetitorConfig's

`InvalidProbability` folds into `InvalidParameter` as
`Parameter::PDraw`. It was a bespoke variant for one scalar while every
other scalar shared `InvalidParameter`, and it omitted the parameter
name — so the same parameter had two mechanisms.

`JointUnavailable { reason: &'static str }` splits into `EmptyHistory`,
`JointRequiresScoredEvents` and `NotPositiveDefinite`. The three are
conditions a caller branches on differently — add events, use
`predict_win_probabilities`, or reconsider the priors — and telling them
apart used to mean string-matching English. One test already proved the
distinction was load-bearing: the blanket conversion mapped the
empty-history case onto the ranked one and `an_empty_history_has_no_joint`
caught it immediately.

`NonFiniteResult` splits into `NonFiniteStep { context, step }` and
`NonFiniteSkill { mu, sigma }`. One `step: (f64, f64)` field was
carrying a sweep step from `converge` and a skill's own moments from a
prediction — two situations in one variant, and a field name that could
only be right for one of them.

`InvalidParameter { name: "beta with point-mass skills" }` becomes
`NoPerformanceVariance`. It was never a parameter out of range: both
values are individually valid and it is their combination that leaves
nothing varying.

Three `Display` impls did not meet the standard the others set, and the
typed data is what makes fixing them possible:

    before  drift variance is invalid: NaN
    after   drift variance must be finite and non-negative (got NaN)

    before  kinds: expected length 3, got 2
    after   the outcome describes a different number of teams than the
            event has: expected 3, got 2

    before  Game::ranked: expected Outcome::Ranked, got Outcome::Scored
    after   expected Outcome::Ranked, got Outcome::Scored; call
            Game::scored for a scored outcome

`Parameter::range()` states each parameter's actual bounds, which no
`&'static str` name could have. `error::message_tests` renders every one
and asserts each is a sentence rather than a label, and that the three
above now carry a range or a next step.

The four internal `MismatchedShape` kinds — `results`, `times`, `kinds`,
and the weights array — collapse to `Shape::Internal`, whose `Display`
says plainly that reaching it is a bug in this crate. They are checks on
`add_events_with_prior`'s own parallel arrays and are unreachable
through the public API; they stay checked rather than becoming
`debug_assert!`s, because release is where this crate's defects hide.

Closes #74.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ
2026-09-10 07:31:31 +02:00

153 lines
4.6 KiB
Rust

//! No prediction path may answer from a fit it cannot answer from.
//!
//! `converge` grew a `NonFiniteResult` guard; nothing stopped a caller from
//! ignoring that error and predicting anyway. The three failures that produced
//! were each differently wrong: `Ok(NaN)`, a panic out of a `Result`-returning
//! method, and `Ok([0.0, 0.0])` — finite, plausible, summing to zero against a
//! doc that promises one.
//!
//! Every test here has a healthy control, so none can pass by everything
//! returning `Err`.
use trueskill_tt::{
ConstantDrift, Event, Gaussian, History, InferenceError, Member, Outcome, Team,
};
type H = History;
fn build(beta: f64, prior: Option<Gaussian>, outcome: Outcome) -> H {
let mut h: H = History::builder()
.beta(beta)
.drift(ConstantDrift::new(0.0))
.build();
let member = |k: &'static str| match prior {
Some(p) => Member::new(k).with_prior(p),
None => Member::new(k),
};
let _ = h.add_events(vec![Event {
time: 1,
teams: [
Team::with_members([member("a")]),
Team::with_members([member("b")]),
]
.into_iter()
.collect(),
outcome,
}]);
h
}
/// Point-mass priors with `beta(0.0)` on a *ranked* event: `converge` reports
/// `NonFiniteResult` and the stored posteriors are `pi: NaN, tau: NaN`.
fn nan_poisoned() -> H {
let mut h = build(
0.0,
Some(Gaussian::from_ms(0.0, 0.0)),
Outcome::winner(0, 2),
);
let err = h.converge().expect_err("this fixture must not converge");
assert!(
matches!(err, InferenceError::NonFiniteStep { .. }),
"{err:?}"
);
h
}
/// The same degenerate parameters on a *scored* event, where inference
/// converges cleanly and leaves legitimate point-mass posteriors behind. The
/// fit is fine; it is prediction that has nothing to work with.
fn degenerate_but_converged() -> H {
let mut h = build(
0.0,
Some(Gaussian::from_ms(0.0, 0.0)),
Outcome::scores([1.0, 0.0]),
);
h.converge().expect("this fixture converges");
h
}
fn healthy() -> H {
let mut h = build(1.0, None, Outcome::winner(0, 2));
h.converge().expect("control converges");
h
}
macro_rules! all_predictions {
($h:ident, $f:expr) => {{
let teams: &[&[&&'static str]] = &[&[&"a"], &[&"b"]];
let f = $f;
f("quality", $h.quality(teams).map(|_| ()));
f(
"predict_win_probabilities",
$h.predict_win_probabilities(teams).map(|_| ()),
);
f("predict_outcome", $h.predict_outcome(teams).map(|_| ()));
f(
"predict_ranking",
$h.predict_ranking(teams, &[0, 1]).map(|_| ()),
);
f(
"expected_information_gain",
$h.expected_information_gain(teams).map(|_| ()),
);
}};
}
#[test]
fn a_nan_poisoned_fit_is_refused_by_every_prediction_path() {
let h = nan_poisoned();
all_predictions!(h, |name: &str, r: Result<(), InferenceError>| {
match r {
Err(InferenceError::NonFiniteSkill { .. }) => {}
other => panic!("{name} answered from a NaN fit: {other:?}"),
}
});
}
#[test]
fn degenerate_performances_are_refused_rather_than_answered_wrongly() {
let h = degenerate_but_converged();
// The fit itself is sound — the posteriors are point masses, not NaN.
let skill = h.current_skill("a").expect("a played");
assert_eq!(skill.sigma(), 0.0);
assert!(skill.mu().is_finite());
// `quality` previously PANICKED here, out of a method that returns
// `Result`: the contrast covariance is exactly singular when beta is zero
// and every skill is a point mass.
all_predictions!(h, |name: &str, r: Result<(), InferenceError>| {
match r {
Err(InferenceError::NoPerformanceVariance) => {}
other => panic!("{name} predicted from a degenerate fit: {other:?}"),
}
});
}
#[test]
fn the_control_history_answers_every_prediction() {
let h = healthy();
all_predictions!(h, |name: &str, r: Result<(), InferenceError>| {
assert!(r.is_ok(), "{name} failed on a healthy history: {r:?}");
});
}
#[test]
fn win_probabilities_sum_to_one_on_the_control() {
// The promise the `Ok([0.0, 0.0])` case broke. Asserted on the control so
// the guard above cannot be "fixed" by making every path error.
let h = healthy();
let p = h
.predict_win_probabilities(&[&[&"a"], &[&"b"]])
.expect("control predicts");
let total: f64 = p.iter().sum();
assert!(
(total - 1.0).abs() < 1e-6,
"win probabilities sum to {total}"
);
}