Files
trueskill-tt/tests/event_builder_members.rs
T
logaritmiskandClaude Opus 5 076a7ded8c feat!: Gaussian's EP operations stop wearing arithmetic's clothes
`Gaussian` publicly implemented `Mul`, `Div`, `Add` and `Sub`. They were
the EP product, cavity and variance-space convolutions, and every one of
them lies to a reader who takes the operator at face value:

    a = N(10, 2)   b = N(4, 3)   c = N(1, 1)

    a * b        N(8.15, 1.66)   not 40
    a - b        sigma GREW, 2 -> sqrt(4 + 9)
    a * N(1, 0)  mu = NaN        "multiply by one"
    a / c        pi = -0.75      mu() prints a confident 0

The last is this crate's signature defect on a public operator. `Div` is
the cavity and can legitimately leave a negative precision, which is not
a distribution — and `mu()`/`sigma()` guard `pi <= 0` and report `0.0`
and `inf`, so it comes back as a plausible number with no panic, no
`Debug` marker and nothing to test against.

The four impls are now `pub(crate)` inherent methods that say what they
do: `ep_product`, `cavity`, `convolve`, `convolve_diff`, plus `scale`
for the one operation that genuinely is arithmetic. Nothing in a user's
workflow needed operator syntax; inference did, and it still has it.

`pi()` and `tau()` follow. Storing natural parameters is a performance
decision — it makes message passing two adds — not a contract. The
public surface is now exactly: `from_ms`, `from_mv`, `mu`, `sigma`,
`variance`, `probability_below`, `probability_above`. `from_mv` and
`variance` are promoted from `pub(crate)`; they are the honest pair for
callers who already hold a variance and should not pay a round trip
through the square root.

Four integration tests asserted bit-identity on `(pi, tau)`. They assert
it on `(mu, variance)` instead — still `assert_eq!`, still exact, and
`1/pi` and `tau/pi` are deterministic, so bit-equal natural parameters
give bit-equal moments. `a_nan_sigma_passes_through_from_ms` drops its
`|| g.pi().is_nan()` half: `sigma()` substitutes for `pi <= 0` and
`pi == inf`, so NaN survives to it only from a NaN precision.

`benches/gaussian.rs` is deleted. It timed two f64 additions through the
public operators, and keeping those public solely to feed it is the same
thing #73 objected to when a benchmark was dictating five public types.
The paths it covered are exercised by `batch` and `history_converge`
through the real call chain.

Closes #71.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ
2026-09-09 23:13:10 +02:00

198 lines
6.1 KiB
Rust

//! `EventBuilder::members` must reach exactly what the typed path reaches.
//!
//! Before this existed, `EventBuilder` could set weights and nothing else, so
//! `prior` and `drift_scale` were expressible only through `Event`/`Team`/
//! `Member` + `add_events`. Which ingestion route a competitor arrived through
//! decided whether it could be configured at all.
use smallvec::smallvec;
use trueskill_tt::{
ConstantDrift, ConvergenceOptions, Event, Gaussian, History, InferenceError, Member, Outcome,
Team,
};
type H = History<i64, ConstantDrift, trueskill_tt::NullObserver, &'static str>;
fn history() -> H {
History::builder()
.mu(0.0)
.sigma(6.0)
.beta(1.0)
.score_sigma(2.0)
.drift(ConstantDrift::new(0.5))
.convergence(ConvergenceOptions {
max_iter: 20_000,
epsilon: 1e-13,
alpha: 1.0,
})
.build()
}
const PRIOR: Gaussian = Gaussian::from_ms(3.0, 1.5);
/// The contract that makes the escape hatch worth having: same configuration,
/// same fit, bit for bit.
#[test]
fn members_matches_the_typed_path_exactly() {
let mut typed = history();
typed
.add_events(vec![Event {
time: 1,
teams: smallvec![
Team::with_members([Member::new("player")]),
Team::with_members([Member::new("layout_7")
.with_drift_scale(0.0)
.with_prior(PRIOR)]),
],
outcome: Outcome::scores([5.0, 2.0]),
}])
.unwrap();
assert!(typed.converge().unwrap().converged);
let mut fluent = history();
fluent
.event(1)
.team(["player"])
.members([Member::new("layout_7")
.with_drift_scale(0.0)
.with_prior(PRIOR)])
.scores([5.0, 2.0])
.commit()
.unwrap();
assert!(fluent.converge().unwrap().converged);
for key in ["player", "layout_7"] {
let a = typed.current_skill(&key).unwrap();
let b = fluent.current_skill(&key).unwrap();
// Exact equality, on the public moments rather than the natural
// parameters: `mu` and `variance` are `tau/pi` and `1/pi`, so
// bit-equal natural parameters give bit-equal moments.
assert_eq!(a.mu(), b.mu(), "{key} mu");
assert_eq!(a.variance(), b.variance(), "{key} variance");
}
}
/// The configuration has to actually take effect, not merely round-trip: a
/// competitor pinned with `drift_scale = 0.0` must not move across slices,
/// where an unpinned one does.
///
/// The comparison is against a control rather than against a fixed epsilon.
/// Pinned marginals are not bit-identical across slices — each slice combines
/// its own forward and backward messages, so the arithmetic order differs and
/// the last bit moves. What "pinned" promises is that no drift variance
/// accumulates, and the control is what makes that measurable.
#[test]
fn a_drift_scale_set_through_members_is_applied() {
fn spread(h: &H, key: &'static str) -> f64 {
let curve = h.learning_curve(&key).unwrap();
assert!(curve.len() >= 2, "{key}: expected several appearances");
let (lo, hi) = curve.iter().fold((f64::MAX, f64::MIN), |(lo, hi), (_, g)| {
(lo.min(g.sigma()), hi.max(g.sigma()))
});
(hi - lo) / hi
}
let mut h = history();
for t in 1..=4 {
h.event(t)
.team(["player"])
.members([Member::new("pinned").with_drift_scale(0.0)])
.scores([5.0, 2.0])
.commit()
.unwrap();
// Same shape, no pinning: the control.
h.event(t)
.team(["rival"])
.team(["drifting"])
.scores([5.0, 2.0])
.commit()
.unwrap();
}
assert!(h.converge().unwrap().converged);
let pinned = spread(&h, "pinned");
let drifting = spread(&h, "drifting");
assert!(pinned < 1e-9, "pinned competitor moved: {pinned:e}");
assert!(
drifting > 1e-3,
"control did not move, so the test proves nothing: {drifting:e}"
);
}
/// `weights` still applies to a team added through `members`, and still
/// records a mismatch rather than partially applying it.
#[test]
fn weights_still_guards_a_members_team() {
let mut h = history();
let err = h
.event(1)
.team(["a"])
.members([Member::new("b"), Member::new("c")])
.weights([1.0])
.winner(0)
.commit()
.unwrap_err();
assert!(
matches!(
err,
InferenceError::MismatchedShape {
kind: "weights",
expected: 2,
got: 1,
..
}
),
"{err:?}"
);
assert!(h.current_skill(&"b").is_none(), "nothing may reach history");
}
/// An invalid `drift_scale` surfaces from `commit`, not from a panic and not
/// silently.
#[test]
fn an_invalid_drift_scale_surfaces_from_commit() {
for bad in [-1.0, f64::NAN, f64::INFINITY] {
let mut h = history();
let err = h
.event(1)
.team(["a"])
.members([Member::new("b").with_drift_scale(bad)])
.winner(0)
.commit()
.unwrap_err();
assert!(
matches!(
err,
InferenceError::InvalidParameter {
name: "drift_scale",
..
}
),
"{bad}: {err:?}"
);
assert!(h.current_skill(&"b").is_none(), "{bad} reached the history");
}
}
/// `members` and `team` compose in either order.
#[test]
fn members_and_team_interleave() {
let mut h = history();
h.event(1)
.members([Member::new("a").with_prior(PRIOR)])
.team(["b"])
.scores([3.0, 1.0])
.commit()
.unwrap();
h.event(2)
.team(["b"])
.members([Member::new("c").with_prior(PRIOR)])
.scores([2.0, 4.0])
.commit()
.unwrap();
assert!(h.converge().unwrap().converged);
for key in ["a", "b", "c"] {
assert!(h.current_skill(&key).is_some(), "{key} missing");
}
}