trueskill-tt/tests/degenerate_inputs.rs

//! Degenerate, boundary, and error-path coverage.
//!
//! These run in both debug and release: the defects they pin were all
//! guarded only by `debug_assert!`, so a debug-only suite never saw them.

mod common;

use common::assert_finite;
use trueskill_tt::{
    ConstantDrift, ConvergenceOptions, Game, GameOptions, Gaussian, History, InferenceError,
    NullObserver, Outcome, Rating,
};

type R = Rating<i64, ConstantDrift>;

fn rating() -> R {
    R::new(
        Gaussian::from_ms(25.0, 25.0 / 3.0),
        25.0 / 6.0,
        ConstantDrift(25.0 / 300.0),
    )
}

#[test]
fn record_draw_without_draw_probability_is_rejected() {
    let mut h = History::default();
    let err = h.record_draw(&"a", &"b", 1).unwrap_err();
    assert!(matches!(
        err,
        InferenceError::TieWithoutDrawProbability { .. }
    ));
}

#[test]
fn builder_draw_without_draw_probability_is_rejected() {
    let mut h = History::default();
    let err = h
        .event(1)
        .team(["a"])
        .team(["b"])
        .draw()
        .commit()
        .unwrap_err();
    assert!(matches!(
        err,
        InferenceError::TieWithoutDrawProbability { .. }
    ));
}

#[test]
fn draw_with_positive_draw_probability_is_finite() {
    let mut h = History::builder().p_draw(0.25).build();
    h.record_draw(&"a", &"b", 1).unwrap();
    let report = h.converge().unwrap();

    assert_finite(h.current_skill("a").unwrap(), "drawn competitor skill");
    assert_finite(h.current_skill("b").unwrap(), "drawn competitor skill");
    assert!(report.log_evidence.is_finite());
    assert!(report.converged);
}

#[test]
fn game_ranked_rejects_tie_without_draw_probability() {
    let a = [rating()];
    let b = [rating()];
    let teams: Vec<&[R]> = vec![&a, &b];
    let err = Game::ranked(&teams, Outcome::draw(2), &GameOptions::default()).unwrap_err();
    assert!(matches!(
        err,
        InferenceError::TieWithoutDrawProbability { .. }
    ));
}

/// `Outcome::winner(w, n)` ties every loser, so any n >= 3 free-for-all hits
/// the tie path even though the caller never asked for a draw.
#[test]
fn winner_of_three_or_more_requires_draw_probability() {
    let a = [rating()];
    let b = [rating()];
    let c = [rating()];
    let teams: Vec<&[R]> = vec![&a, &b, &c];

    let err = Game::ranked(&teams, Outcome::winner(0, 3), &GameOptions::default()).unwrap_err();
    assert!(matches!(
        err,
        InferenceError::TieWithoutDrawProbability { .. }
    ));

    let opts = GameOptions {
        p_draw: 0.1,
        ..GameOptions::default()
    };
    let game = Game::ranked(&teams, Outcome::winner(0, 3), &opts).unwrap();
    for team in game.posteriors() {
        for skill in team {
            assert_finite(skill, "3-team winner posterior");
        }
    }
}

#[test]
fn full_ranking_without_ties_needs_no_draw_probability() {
    let a = [rating()];
    let b = [rating()];
    let c = [rating()];
    let teams: Vec<&[R]> = vec![&a, &b, &c];
    let game = Game::ranked(&teams, Outcome::ranking([0, 1, 2]), &GameOptions::default()).unwrap();

    for team in game.posteriors() {
        for skill in team {
            assert_finite(skill, "strict ranking posterior");
        }
    }
}

#[test]
fn empty_history_converges_trivially() {
    let mut h = History::default();
    let report = h.converge().unwrap();
    assert_eq!(report.iterations, 0);
    assert!(report.converged);
}

/// Issue #27's exact reproduction: a non-default key type reaching `converge`
/// with no events at all. The underflow it reported trapped in debug and
/// indexed out of bounds in release, so this must run in both profiles.
#[test]
fn converge_on_an_empty_history_with_owned_keys() {
    let mut history: History<i64, ConstantDrift, NullObserver, String> =
        History::builder_with_key().score_sigma(5.0).build();

    let report = history.converge().unwrap();

    assert_eq!(report.iterations, 0);
    assert!(report.converged);
}

/// A weights/team length mismatch used to be a `debug_assert!`, so release
/// builds ingested the event with the weights silently unapplied. This file's
/// CI job runs in release too, which is the point of pinning it here.
#[test]
fn event_builder_rejects_a_weights_length_mismatch() {
    let mut h = History::default();

    let err = h
        .event(1)
        .team(["a"])
        .weights([1.0, 2.0])
        .team(["b"])
        .winner(0)
        .commit()
        .unwrap_err();

    assert!(
        matches!(
            err,
            InferenceError::MismatchedShape {
                kind: "weights",
                expected: 1,
                got: 2,
            }
        ),
        "expected a weights MismatchedShape, got {err:?}"
    );
}

/// The mismatch must not be applied even partially — a half-weighted team
/// reaching the history would be worse than the error.
#[test]
fn event_builder_weights_mismatch_leaves_the_history_untouched() {
    let mut h = History::default();

    // Two teams, so ingestion would otherwise succeed — a one-team event is
    // rejected for an unrelated reason and would pass this vacuously.
    let _ = h
        .event(1)
        .team(["a"])
        .weights([1.0, 2.0])
        .team(["b"])
        .winner(0)
        .commit();

    assert!(h.learning_curve("a").is_empty());
}

#[test]
fn empty_event_stream_then_converge() {
    let mut h = History::default();
    h.add_events(std::iter::empty()).unwrap();
    let report = h.converge().unwrap();
    assert_eq!(report.iterations, 0);
}

#[test]
fn empty_history_queries_do_not_panic() {
    let h = History::default();
    assert!(h.learning_curves().is_empty());
    assert!(h.learning_curve("nobody").is_empty());
    assert!(h.current_skill("nobody").is_none());
}

#[test]
fn single_event_history_converges() {
    let mut h = History::default();
    h.record_winner(&"a", &"b", 1).unwrap();
    let report = h.converge().unwrap();
    assert!(report.converged);
    assert_finite(h.current_skill("a").unwrap(), "single-event skill");
}

#[test]
fn scored_event_rejects_non_positive_sigma() {
    let mut h = History::builder().score_sigma(2.0).build();
    let err = h
        .event(1)
        .team(["a"])
        .team(["b"])
        .scores_with_sigma([3.0, 1.0], f64::NAN)
        .commit()
        .unwrap_err();
    assert!(matches!(
        err,
        InferenceError::InvalidParameter {
            name: "score_sigma",
            ..
        }
    ));
}

#[test]
fn convergence_reports_are_finite_across_many_teams() {
    let opts = GameOptions {
        p_draw: 0.1,
        convergence: ConvergenceOptions::default(),
        ..GameOptions::default()
    };
    let holders: Vec<[R; 1]> = (0..12).map(|_| [rating()]).collect();
    let teams: Vec<&[R]> = holders.iter().map(|t| t.as_slice()).collect();
    let game = Game::ranked(&teams, Outcome::ranking(0..12), &opts).unwrap();

    assert!(
        game.log_evidence().is_finite(),
        "12-team log-evidence must be finite, got {}",
        game.log_evidence()
    );
    for team in game.posteriors() {
        for skill in team {
            assert_finite(skill, "12-team posterior");
        }
    }
}

/// A long diff chain underflows a linear evidence product: each link
/// contributes a probability in (0, 1], so ~1000 links flush the product to
/// exactly 0.0 and `ln(0.0)` is `-inf`. Accumulating in log space keeps it
/// finite.
#[test]
fn log_evidence_survives_a_long_diff_chain() {
    let holders: Vec<[R; 1]> = (0..1200).map(|_| [rating()]).collect();
    let teams: Vec<&[R]> = holders.iter().map(|t| t.as_slice()).collect();
    let game = Game::ranked(
        &teams,
        Outcome::ranking(0..holders.len() as u32),
        &GameOptions::default(),
    )
    .unwrap();

    let log_evidence = game.log_evidence();
    assert!(
        log_evidence.is_finite(),
        "1200-team log-evidence must be finite, got {log_evidence}"
    );
    assert!(
        log_evidence < 0.0,
        "log-evidence of a probability must be negative, got {log_evidence}"
    );
}

/// A near-certain outcome rounds the losing tail to exactly zero in the
/// `erfc` approximation; the evidence floor keeps `ln` finite.
#[test]
fn log_evidence_finite_for_near_certain_outcome() {
    let overwhelming = R::new(Gaussian::from_ms(5_000.0, 0.5), 1.0, ConstantDrift(0.0));
    let hopeless = R::new(Gaussian::from_ms(-5_000.0, 0.5), 1.0, ConstantDrift(0.0));
    let a = [overwhelming];
    let b = [hopeless];
    let teams: Vec<&[R]> = vec![&a, &b];

    let game = Game::ranked(&teams, Outcome::winner(0, 2), &GameOptions::default()).unwrap();
    assert!(
        game.log_evidence().is_finite(),
        "got {}",
        game.log_evidence()
    );

    // And the reverse — a colossal upset — must also stay finite.
    let upset = Game::ranked(&teams, Outcome::winner(1, 2), &GameOptions::default()).unwrap();
    assert!(
        upset.log_evidence().is_finite(),
        "upset log-evidence must be finite, got {}",
        upset.log_evidence()
    );
}

#[test]
fn empty_history_has_no_filtered_estimates() {
    let history: History = History::builder().build();

    assert_eq!(history.filtered_log_evidence(), 0.0);

    assert!(history.filtered_learning_curves().is_empty());

    assert!(history.filtered_learning_curve("nobody").is_empty());
}

// --- Boundary inputs (#26) ----------------------------------------------

fn tight() -> ConvergenceOptions {
    ConvergenceOptions {
        max_iter: 2_000,
        epsilon: 1e-12,
        ..ConvergenceOptions::default()
    }
}

fn assert_curve_finite(h: &History, keys: &[&str], what: &str) {
    for key in keys {
        for (time, g) in h.learning_curve(*key) {
            assert!(
                g.mu().is_finite() && g.sigma().is_finite(),
                "{what}: non-finite posterior for {key} at t={time} (mu={} sigma={})",
                g.mu(),
                g.sigma()
            );
        }
    }
}

/// A zero weight reaches `(m - performance.exclude(..)) * (1.0 / w)`, i.e. a
/// division by zero. The commit is accepted today, so this pins that the
/// resulting posterior is still finite rather than quietly NaN.
#[test]
fn zero_weight_does_not_produce_a_non_finite_posterior() {
    let mut h = History::builder().build();

    h.event(1)
        .team(["a"])
        .weights([0.0])
        .team(["b"])
        .winner(0)
        .commit()
        .expect("a zero weight is accepted today; update this test if that changes");

    let _ = h.converge().unwrap();

    assert_curve_finite(&h, &["a", "b"], "zero weight");
}

#[test]
fn negative_weight_does_not_produce_a_non_finite_posterior() {
    let mut h = History::builder().build();

    h.event(1)
        .team(["a"])
        .weights([-1.0])
        .team(["b"])
        .winner(0)
        .commit()
        .expect("a negative weight is accepted today; update this test if that changes");

    let _ = h.converge().unwrap();

    assert_curve_finite(&h, &["a", "b"], "negative weight");
}

/// Events supplied newest-first must land in the same slices as oldest-first:
/// ingestion sorts by time rather than trusting arrival order.
#[test]
fn out_of_order_timestamps_converge_to_the_same_answer() {
    fn build(descending: bool) -> History {
        let mut h = History::builder().convergence(tight()).build();

        let mut times: Vec<i64> = (1..=6).collect();
        if descending {
            times.reverse();
        }

        for time in times {
            h.record_winner(&"a", &"b", time).unwrap();
        }

        let _ = h.converge().unwrap();
        h
    }

    let ascending = build(false);
    let descending = build(true);

    let one = ascending.current_skill("a").unwrap();
    let other = descending.current_skill("a").unwrap();

    assert!(
        (one.mu() - other.mu()).abs() < 1e-8 && (one.sigma() - other.sigma()).abs() < 1e-8,
        "arrival order changed the answer: ascending mu={} sigma={}, descending mu={} sigma={}",
        one.mu(),
        one.sigma(),
        other.mu(),
        other.sigma()
    );
}

#[test]
fn extreme_beta_and_sigma_stay_finite() {
    for (beta, sigma) in [(1e-6, 1e-6), (1e6, 1e6), (1e-6, 1e6), (1e6, 1e-6)] {
        let mut h = History::builder().beta(beta).sigma(sigma).build();

        h.record_winner(&"a", &"b", 1).unwrap();
        h.record_winner(&"a", &"b", 2).unwrap();
        let _ = h.converge().unwrap();

        assert_curve_finite(&h, &["a", "b"], &format!("beta={beta} sigma={sigma}"));
    }
}