Files
trueskill-tt/src/error.rs
T
logaritmiskandClaude Opus 5 fdd1539cab refactor: one word per concept
Three vocabulary collisions, from #75.

**"rating" meant three things**, one the opposite of the exported type.
`Rating` is documented as static *configuration* — "this returns what it
was told", against every other accessor's "what inference inferred". But
`quality`'s parameter was `rating_groups: &[&[Gaussian]]` and its prose
said "rating groups" four times, where "rating" means a *posterior* — the
one thing `Rating` is documented not to be. Two error messages used it
that way too.

So a reader who learned `Rating = config` passed `Rating` values to
`quality`, which takes `Gaussian`; and one who learned "rating = what
comes out" was baffled that `h.rating(&k)` is not their skill.

"rating" is now reserved for the type. `quality(teams: &[&[Gaussian]])`,
and "every rating is finite" became "every posterior is finite".

**"agent" was a private fourth name for a competitor** — ~200 identifiers
against 236 uses of "competitor", and it leaked into two `pub` signatures
on `TimeSlice`. Now that #73 has made those internal this is a pure
rename, so the crate has one word for the entity throughout.

**"player" survived in one public signature** — `free_for_all(players:)`
plus two doc lines. Renamed, along with three internal closure bindings.
Doc examples that use "player" as a *key* are left alone: that is a
user's data, not the crate's vocabulary.

The panic-message expectations in tests/quality.rs moved with the prose,
which is the point of asserting on message text — the tests caught the
rename rather than papering over it.

Not touched: "performance" (always skill widened by beta), "skill",
"member" and "team" are each used for exactly one thing already.

Refs #75

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ
2026-09-09 20:54:47 +02:00

286 lines
12 KiB
Rust

use std::fmt;
/// How a prediction should treat a key the history has never seen.
///
/// Configured once per history via
/// [`HistoryBuilder::unknown_keys`](crate::HistoryBuilder::unknown_keys).
/// Neither known consumer wants this to vary between queries — one predicts
/// thousands of candidate matchups in a loop, the other's headline feature is
/// predicting a competitor nobody has faced — so it is a property of how you
/// intend to use the model rather than an argument on five call sites.
///
/// # There is deliberately no `Skip`
///
/// Dropping an unknown member is the obvious third option and it is wrong. A
/// team's performance is the *sum* of its members, so removing one removes its
/// variance too: measured on a two-member team with one unknown, skipping gives
/// a performance sigma of 2.37 where treating the member as unknown gives 6.53.
/// An unknown competitor would make the model *more* certain, which is
/// backwards. `Prior` is also the answer the model already gives for a
/// competitor it knows about but has no evidence for, so it corresponds to a
/// state the model can actually be in; skipping does not.
#[derive(Clone, Copy, Debug, Default, PartialEq, Eq)]
#[non_exhaustive]
pub enum UnknownKeys {
/// Reject the prediction with [`InferenceError::UnknownKey`].
///
/// The default, and the right one when every key is expected to be known:
/// a team of strangers should not silently produce a confident-looking
/// answer.
#[default]
Reject,
/// Treat an unknown competitor as one sitting at the history's configured
/// prior.
///
/// This is the honest Bayesian reading — a competitor you have never
/// observed is exactly the prior — and it makes "predict a matchup
/// involving someone new" a first-class question rather than something a
/// caller fakes with a neutral constant.
Prior,
}
#[derive(Debug, Clone, PartialEq)]
#[non_exhaustive]
pub enum InferenceError {
/// Expected and actual lengths of some array-shaped input differ.
#[non_exhaustive]
MismatchedShape {
kind: &'static str,
expected: usize,
got: usize,
},
/// An `Outcome` of the wrong variant was supplied for the requested inference.
#[non_exhaustive]
WrongOutcomeKind {
context: &'static str,
expected: &'static str,
got: &'static str,
},
/// A probability value is outside `[0, 1]`.
#[non_exhaustive]
InvalidProbability { value: f64 },
/// A scalar parameter is outside its valid range.
#[non_exhaustive]
InvalidParameter { name: &'static str, value: f64 },
/// An event contains tied teams, but the draw probability is zero.
///
/// A zero draw probability asserts that draws cannot occur, so a tied
/// result has no representable likelihood. Configure a positive `p_draw`
/// (via `HistoryBuilder::p_draw` or `GameOptions::p_draw`) to admit ties.
#[non_exhaustive]
TieWithoutDrawProbability { teams: (usize, usize) },
/// The convergence sweep hit `max_iter` with the step still above
/// `epsilon`.
///
/// A fit that stops short is wrong by a little, which is the worst
/// available failure: every posterior is finite, the ordering looks sensible,
/// and nothing in the numbers says they were still moving. Reported rather
/// than returned as a flag on an `Ok`, because a flag has to be checked
/// and `let _ = h.converge()` is the natural way not to.
///
/// Either the history needs more iterations — raise `max_iter` — or it is
/// oscillating rather than converging, in which case `alpha < 1.0` damps
/// the within-game EP loop. [`History::converge_partial`](crate::History::converge_partial)
/// returns the short fit instead when that is genuinely what is wanted.
#[non_exhaustive]
NotConverged {
iterations: usize,
final_step: (f64, f64),
epsilon: f64,
},
/// Inference produced a non-finite value (NaN or infinity).
///
/// Indicates numerical breakdown; the resulting skills are meaningless
/// and must not be treated as a converged estimate.
#[non_exhaustive]
NonFiniteResult {
context: &'static str,
step: (f64, f64),
},
/// One batch declared two different values for the same competitor's
/// configuration.
///
/// `prior` and `drift_scale` configure a competitor, not an event, so a
/// batch that sets one of them twice with different values has no
/// well-defined meaning: events within a batch are not ordered, so
/// "last one wins" would make the result depend on iteration order.
/// Declaring the same value repeatedly is fine and is the expected shape
/// when a competitor's configuration is a property of the domain.
#[non_exhaustive]
ConflictingCompetitorConfig {
competitor: usize,
field: &'static str,
},
/// A prediction referenced a key the history has no skill for.
///
/// Reported rather than skipped: dropping unknown keys turns a team of
/// strangers into a confident-looking probability about nobody.
///
/// `key` is the offending key's `Debug` rendering. It is carried because
/// the indices alone are not actionable: a caller that logs
/// `UnknownKey { team: 0, member: 0 }` learns nothing about *which* of its
/// keys the history has not seen, and the natural handling — fall back to a
/// neutral value — turns the whole thing into a plausible constant.
#[non_exhaustive]
UnknownKey {
team: usize,
member: usize,
key: String,
},
/// `History::register` was called for a competitor that already exists.
///
/// Registration states a competitor's configuration before anything has
/// been observed about them, so a competitor that already exists has
/// already been configured — by an earlier `register`, or by an event that
/// created them. Silently overwriting would reintroduce exactly the
/// order-dependence registration exists to remove.
///
/// To change an existing competitor's configuration, supply it on an event
/// through `Member`; that refits the whole history.
#[non_exhaustive]
AlreadyRegistered { key: String },
/// A prediction was given a team with no members.
#[non_exhaustive]
EmptyTeam { team: usize },
/// The prediction grid cannot resolve the narrowest feature in the matchup.
///
/// `predict_outcome` and `predict_ranking` integrate every team's density
/// on one shared grid, whose resolution is set by the narrowest sigma (or a
/// narrower draw margin). When the widest and narrowest are far enough
/// apart, resolving the narrow one across the wide one's support needs more
/// nodes than the grid is allowed to hold.
///
/// Reported rather than clamped. Clamping is what this replaced, and it
/// returned probabilities greater than one — measured, a `P` of 2.79 and a
/// `Prediction::total()` of 5.41 — because the trapezoid rule stops
/// resolving a density once the step exceeds roughly 1.7 of its sigma.
///
/// `predict_win_probabilities` answers the same matchup through adaptive
/// quadrature and is accurate here; use it when only the per-team win
/// probabilities are needed.
#[non_exhaustive]
GridTooCoarse {
/// Nodes required to resolve the narrowest feature.
needed: usize,
/// Nodes the grid may hold.
max: usize,
},
/// A joint posterior was requested where one cannot be formed exactly.
#[non_exhaustive]
JointUnavailable { reason: &'static str },
/// Fewer than two teams were supplied to a prediction.
#[non_exhaustive]
NotEnoughTeams { got: usize },
/// The full outcome distribution was requested for too many teams.
///
/// Each realisation sorts into exactly one (order, tie-pattern) event, so
/// the space holds `n! * 2^(n-1)` members — 1_920 at five teams, 23_040 at
/// six, 322_560 at seven. Past `max` this stops being something to
/// enumerate on a caller's behalf; ask for individual rankings with
/// `predict_ranking`, or for `predict_win_probabilities`, both of which
/// stay cheap at any team count.
#[non_exhaustive]
TooManyTeams { got: usize, max: usize },
}
impl fmt::Display for InferenceError {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
match self {
Self::MismatchedShape {
kind,
expected,
got,
} => {
write!(f, "{kind}: expected length {expected}, got {got}")
}
Self::WrongOutcomeKind {
context,
expected,
got,
} => {
write!(f, "{context}: expected {expected}, got {got}")
}
Self::InvalidProbability { value } => {
write!(f, "probability must be in [0, 1]; got {value}")
}
Self::TieWithoutDrawProbability { teams } => {
write!(
f,
"teams {} and {} are tied, but p_draw is 0.0; set a positive draw probability to admit ties",
teams.0, teams.1
)
}
Self::NotConverged {
iterations,
final_step,
epsilon,
} => {
write!(
f,
"did not converge in {iterations} iterations: final step {final_step:?} \
is still above epsilon {epsilon}; raise max_iter, or damp with \
alpha < 1.0 if it is oscillating"
)
}
Self::NonFiniteResult { context, step } => {
write!(
f,
"{context}: inference produced a non-finite result (step = {step:?})"
)
}
Self::InvalidParameter { name, value } => {
write!(f, "{name} is invalid: {value}")
}
Self::ConflictingCompetitorConfig { competitor, field } => {
write!(
f,
"competitor {competitor}: this batch sets {field} to two different values"
)
}
Self::UnknownKey { team, member, key } => {
write!(
f,
"team {team}, member {member}: no skill recorded for key {key} \
(every key must already be known to the history; pre-filter \
with `lookup` or `current_skill` if that is not guaranteed)"
)
}
Self::AlreadyRegistered { key } => {
write!(
f,
"competitor {key} is already registered; registration states \
configuration before anything is observed, so re-registering \
would silently overwrite it"
)
}
Self::EmptyTeam { team } => {
write!(f, "team {team} has no members")
}
Self::GridTooCoarse { needed, max } => {
write!(
f,
"the prediction grid needs {needed} nodes to resolve the narrowest \
team's density across the widest team's support, but may hold only \
{max}; the sigmas in this matchup are too far apart to integrate on \
one grid. Use predict_win_probabilities, which is accurate here"
)
}
Self::JointUnavailable { reason } => {
write!(f, "no exact joint posterior is available: {reason}")
}
Self::NotEnoughTeams { got } => {
write!(f, "prediction needs at least 2 teams, got {got}")
}
Self::TooManyTeams { got, max } => {
write!(
f,
"the outcome distribution over {got} teams is too large to enumerate (limit {max}); \
use predict_ranking or predict_win_probabilities instead"
)
}
}
}
}
impl std::error::Error for InferenceError {}