Files
trueskill-tt/CLAUDE.md
T
logaritmiskandClaude Opus 5 87fca8dcca docs: correct drifted documentation and compile the README in CI
Four README code blocks no longer compiled: `Player` was renamed `Rating`
in T2, the `Drift` trait gained a `T: Time` parameter and a second method,
and two blocks were missing imports outright. The `Rating` example needed
more than a rename — with the binding unused, `T` is ambiguous because
`ConstantDrift` implements `Drift<T>` for every `T`, so it now carries an
explicit annotation.

Nothing compiled those blocks. `src/lib.rs` gains a `cfg(doctest)` struct
carrying `#[doc = include_str!("../README.md")]`, which turns every `rust`
block into a doctest without displacing the curated crate docs as the
front page. Verified it bites: reintroducing `Player` fails the build with
E0432 rather than shipping. Illustrative blocks are fenced `text` — note
that a bare fence defaults to `rust` under rustdoc, which is how the
`variance_delta = elapsed * γ²` formula became a compile error.

Prose fixes: README claimed `Gaussian::forget` takes a square root (it
works in variance space) and pointed at a `.gamma()` builder method that
does not exist. CLAUDE.md's data-flow diagram spliced the public ingestion
shape into the internal one — `Team` is not in that chain — listed
`cdf()`/`erfc()` as public when they are `pub(crate)` and private, and
called `SkillStore` public when only `CompetitorStore` escapes the crate.

Rustdoc fixes: `EventBuilder::scores_with_sigma` claimed a debug-assert
that `Outcome::scores_with_sigma` never had and whose own docs contradict;
rejection happens at ingestion as `InvalidParameter`. `event.rs` described
`add_events_with_prior` as replaced when it is still the ingestion
chokepoint. `factors.rs` advertised `Game::custom` without noting it is
`#[doc(hidden)]`. Internal T2/T4 milestone labels are dropped from public
items; the ones in the private `time_slice` module are left alone.

Closes #35

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_014b6wy2q8rnFK8U8GPJVQNU
2026-09-01 19:30:32 +02:00

115 lines
5.7 KiB
Markdown

# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Commands
```bash
just test # Full suite across every feature combination CI checks
just check # Fast inner loop: cargo test --features approx
just lint # clippy, warnings denied
just fmt # ALWAYS nightly — rustfmt.toml uses nightly-only options
just determinism # Bit-identical posteriors at RAYON_NUM_THREADS 1/2/4/8
just ci # Everything CI runs
cargo test --lib <test_name> # A single test by name
cargo bench # Criterion benchmarks
```
**Run tests in release too.** `debug_assert!` is compiled out there, and that
is where several defects have hidden — a debug-only run is not evidence.
`just test` includes a release job.
### Feature flags
- `approx``approx::AbsDiffEq` etc. for `Gaussian`. Most numerical goldens need it.
- `rayon` — opt-in parallel within-slice sweep and per-slice query passes.
## Architecture
A Rust port of [TrueSkillThroughTime.py](https://github.com/glandfried/TrueSkillThroughTime.py):
Bayesian skill rating that infers skill at every point in time, propagating
evidence both forward and backward across a history.
### Data flow
Ingestion (public types, `event.rs`):
```
Event<T, K> → Team<K>[] → Member<K>[]
```
`History::add_events` flattens that into indices; teams survive only as
grouping, not as a value. Inference then runs on the internal shapes:
```
History → TimeSlice[] → Event[] → Item[]
Game (factor graph) → Schedule → BuiltinFactor[]
```
- **`History`** (`history.rs`) — top level. Interns keys, groups events into
`TimeSlice`s by time, runs the forward/backward sweep in `converge()`, and
answers `learning_curves()`, `current_skill()`, `log_evidence()`,
`predict_quality()`, `predict_outcome()`. Built via `HistoryBuilder`.
- **`TimeSlice`** (`time_slice.rs`) — all events at one time. Owns a
`SkillStore` and a `ScratchArena`; `iteration()` sweeps its events, using
`ColorGroups` to partition independent ones.
- **`Event`** — two distinct types, do not confuse them. The *public* ingestion
`Event<T, K>` is in `event.rs` (with `Team`/`Member`); the *internal*
`pub(crate) Event` in `time_slice.rs` is one match during inference, where
`compute()` runs inference reading skills immutably and `apply()` folds the
result back. That split is what lets a color group run in parallel with no
`unsafe`.
- **`Game`** (`game.rs`) — a single match's factor graph. `run_chain` builds the
diff chain between rank-adjacent teams and drives it to convergence.
- **`Gaussian`** (`gaussian.rs`) — natural parameters (`pi = 1/sigma²`,
`tau = mu/sigma²`). `Mul`/`Div` are the EP product/cavity: pure adds and
subtracts. Variance-space ops (`Add`, `Sub`, `exclude`, `forget`) go through
`from_mv`/`variance()` and take no square root.
- **`factor/`** — `TeamSumFactor`, `RankDiffFactor`, `TruncFactor` (ranked),
`MarginFactor` (scored), over a flat `VarStore`. `BuiltinFactor` dispatches
by enum rather than `dyn`.
- **`Schedule`** (`schedule.rs`) — drives factor propagation. `EpsilonOrMax` is
the only implementation.
- **`Competitor`** (`competitor.rs`) — per-history temporal state (`message`,
`last_time`). **`Rating`** (`rating.rs`) — static config (prior, `beta`, drift).
- **`storage/`** — `SkillStore` (per slice, `pub(crate)`) and `CompetitorStore`
(per history, public), both indexed by `Index`. The module is `pub`, but only
`CompetitorStore` is reachable from outside the crate.
- **`KeyTable`** (`key_table.rs`) — user key ↔ `Index`, both directions O(1).
- **`Drift`** (`drift.rs`) / **`Time`** (`time.rs`) — traits. `Time` is a *trait*
(`i64`, `Untimed`), not an enum.
- **`lib.rs`** — public exports, global defaults (`MU`, `SIGMA`, `BETA`,
`GAMMA`, `P_DRAW`, `EPSILON`, `ITERATIONS`), and the standalone `quality()`.
The `cdf()` / `erfc()` helpers live here too but are `pub(crate)` and private
respectively — not public API.
### Invariants worth knowing
- **A tie needs `p_draw > 0`.** With `p_draw == 0.0` the truncation margin is
zero and the two-sided tie update evaluates `0/0`. Ingestion rejects such
events with `InferenceError::TieWithoutDrawProbability`. This includes
`Outcome::winner(w, n)` for `n >= 3`, which ties every loser.
- **NaN is never convergence.** Comparisons against NaN are all false, so
`tuple_gt` reads NaN as "below epsilon". Use `step_converged` /
`step_is_finite`, never `!tuple_gt(..)` alone.
- **Evidence accumulates in log space.** A linear product over a long diff
chain underflows to zero, and `ln(0)` is `-inf`.
- **Colors are contiguous.** `recompute_color_groups` reorders events so each
color occupies one range; `ColorGroups::groups_are_contiguous` asserts it.
- **The crate is `#![forbid(unsafe_code)]`.** Keep it that way.
- **Ingestion order must not change the answer.** Events added one at a time
must converge to the same fixed point as the same events batched — see
`tests/ingestion_equivalence.rs`.
### Testing notes
- Numerical goldens are cross-validated against the Python/Julia reference.
Some are *convergence residuals*, not exact values; treat a small movement
as suspicious but check whether the new value is closer to the analytic
truth (symmetric fixtures converge to their prior mean exactly) before
assuming a regression.
- `tests/degenerate_inputs.rs` covers empty/boundary/error paths,
`tests/ingestion_equivalence.rs` covers batching order, `tests/quality.rs`
covers N-group quality, `tests/determinism.rs` covers thread counts.