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a0c2f78aed |
feat: add the missing trait impls and make #[must_use] consistent
Trait coverage (#76), all additive: History Debug is still absent - see below HistoryBuilder + Debug (it derived Clone but not Debug) Rating + PartialEq (Gaussian had it; Rating is a Gaussian plus three scalars and had none) Event/Team/Member + PartialEq (input value types with no way to compare them, which made round-trip tests awkward) ConvergenceReport + PartialEq `#[must_use]` (#67). The coverage had no rule: `filtered_log_evidence` had it and `log_evidence` did not; `rating` had it and `current_skill` did not; `Rating::with_drift_scale` had it and `Member::with_drift_scale` did not. Now on the types — `EventBuilder`, `HistoryBuilder`, `Prediction`, `Gaussian`, `OwnedGame` — which covers most method returns at once, plus the `History` accessors individually. `EventBuilder` gets a message, because a dropped builder is the worst case in the set: measured, `h.event(1).team(["x"]).team(["y"]).winner(0)` without `.commit()` leaves `time_slices_len() == 0` and every skill `None`, with no warning at all. And `ConvergenceReport`'s `#[must_use]` moves off the TYPE onto `converge_partial`, where its stated reason is true. It read "from `converge_partial` this may describe a fit that stopped at max_iter" but fired on `converge` too — where that is false, since `converge` returns `Err(NotConverged)` in exactly that case. So the crate's own front-page example warned, and every quickstart had to write `let _ =`. Verified from a consumer crate: `h.converge()?;` now compiles clean. Marking the types made eight method-level attributes redundant, which clippy's `double_must_use` caught — that is the type-level marker doing its job, and the eight are removed. Refs #76, #67 Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ |
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4472d98b56 |
refactor!: un-export six types that no caller could reach
`TimeSlice`, `EventKind`, `KeyTable`, `CompetitorStore`, `Competitor` and the `storage` module were all public and none was obtainable from a `History` — `time_slices`, `agents` and `keys` are all private or `pub(crate)`. `TimeSlice` was the worst: `new`, `add_events`, `iteration`, `get_composition` and `get_results` were `pub` on a type you could only build standalone and never feed back into anything. Their sole consumer outside `src/` was `benches/batch.rs`, so a benchmark was dictating six public types. It is rewritten against the public API: a single-slice history's `converge` calls exactly the same per-slice sweep, so capping at one iteration measures the same code path. `N01` had zero references in the entire repository, including inside the crate; removed. `N00` and `N_INF` are EP identities (`Add` and `Mul`) and are now `pub(crate)` — a user reaching for `N_INF` as "an unknown competitor's prior" would get an improper distribution whose `mu()` silently reports 0.0. Adds the accessors their absence forced people around, from #70: `competitors()`, `competitor_count()` and `event_count()` (`size` had no accessor at all). Answering "who is best" previously meant materialising every competitor's full smoothed curve to read the last point of each. `KeyTable::keys` now iterates the dense reverse table rather than the forward `HashMap`, so `competitors()` yields insertion order rather than per-process hash order — the same hazard as #62, caught before it could reach a caller building a standings table. Two `CompetitorStore` methods (`is_empty`, `iter_mut`) had no callers anywhere and are gone; four more are now `#[cfg(test)]`, which is what they always were in practice. Worth recording a mistake: I first deleted `get_composition`/`get_results` on the strength of a "never used" warning, and the build broke — the warning came from the plain-lib target, where `#[cfg(test)]` callers in history.rs are not compiled. A dead-code warning from one target is not evidence about the others. BREAKING CHANGE: `TimeSlice`, `EventKind`, `KeyTable`, `CompetitorStore`, `Competitor`, the `storage` module, `N01`, `N00` and `N_INF` are no longer public. Refs #73, #70 Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ |
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dc1f4d5847 |
fix!: make the Time generic reachable
`History<T: Time, ..>` has always been generic over the time axis,
`Untimed` has always been exported, and `Drift<T>` is generic specifically
so that "seasonal or calendar-aware drift is expressible without going
through i64". None of it was reachable from a downstream crate.
Every construction route pinned `T = i64`: `History::builder()`,
`History::builder_with_key()`, and the only `Default` impl on
`HistoryBuilder`. Its fields are private and it had no `new`. So all three
escape routes failed to compile, and a consumer with domain timestamps
had to convert to i64 — which is the exact thing the parameter exists to
avoid. One of `History`'s four type parameters was paid for at every
signature and could never be varied.
`Default` is now generic over `T` and `K`, `HistoryBuilder::new()` exists,
and `time_type::<T2>()` / `key_type::<K2>()` join `drift` and `observer`
as type-changing setters:
History::builder().time_type::<Untimed>().build()
History::builder().key_type::<String>().build()
HistoryBuilder::<Season, _, _, String>::new().build()
`key_type` replaces `builder_with_key`, which could not be turbofished —
`K` sat on the impl rather than the function, so callers had to spell
`History::<i64, _, _, String>::builder_with_key()`. 18 call sites across
15 files migrated.
tests/time_axis.rs is the part that matters. NOTHING in the repository
constructed a non-i64 history, which is precisely why this survived, so
the fix is only half done without a test that exercises the generic. It
defines a `Season(u16)` time type and a `SeasonalDrift` that accumulates
between seasons but not within one — the calendar-aware case the trait's
docs cite — and checks the whole path: fit, converge, and read a learning
curve whose times come back as `Season`, not as integers.
Two of the six tests are controls rather than assertions about output.
`Untimed` must ignore drift entirely, since elapsed is always zero, so
gamma 0.0 and gamma 5.0 must agree bit for bit. And a custom `Drift` must
actually widen a gap across seasons, or the test above would pass whether
or not the drift was consulted at all.
The README's ticked "Generalise a time axis" box is now true.
BREAKING CHANGE: `History::builder_with_key()` is removed. Use
`History::builder().key_type::<K>()`.
Closes #68
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ
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8dff7513f7 |
fix!: seal ConstantDrift's field so gamma can be validated
`gamma` enters only as `gamma * gamma`, so the sign was squared away: measured against the old public-field form, `ConstantDrift(-0.0833)` produced results bit identical to `ConstantDrift(0.0833)`. The sign was neither rejected nor honoured — it vanished. It could not be checked while the field was a public tuple position, because there was nothing to intercept. Validating inside `variance_for_elapsed` would have been worse: it runs in the sweep, so a construction-time mistake would panic mid-inference, and `Gaussian::from_ms` is a worked example of why that is the wrong place — rejecting NaN there turned the NonFiniteResult reporting path into a crash. So `ConstantDrift::new` is the only way in and it checks, with `gamma()` to read the value back. 129 call sites rewritten across src, tests, benches, examples and the README. The dated plan and spec documents under docs/superpowers are left alone: they record what was built at the time, and rewriting them would falsify that. tests/constructor_validation.rs is the more valuable half. This defect class was closed three times in one session and reopened twice, because each fix validated the layer it had just touched and inferred the rest — `HistoryBuilder`, then `Game`'s own entry points, then the constructors beneath both. A per-site fix cannot notice the site nobody thought of, so that file enumerates every public entry point taking a magnitude and asserts each refuses negative and non-finite values. It found an eleventh defect on its first run: `HistoryBuilder::score_sigma` accepted infinity, because `inf > 0.0` is true and the assert only tested positivity. Fixed, and its own `should_panic` message updated to match. `Gaussian::from_ms` is deliberately exempt from the non-finite half, for the reason above: a broken fit produces a NaN sigma legitimately and `converge` must be allowed to report it. The convergence-level drift-variance check stays and is now tested through a custom `Drift` implementation, since `ConstantDrift` can no longer reach it. That check is the only thing standing between a third-party `Drift` and a NaN fit. BREAKING CHANGE: `ConstantDrift`'s field is private. Replace `ConstantDrift(x)` with `ConstantDrift::new(x)`, and `drift().0` with `drift().gamma()`. `HistoryBuilder::score_sigma` now rejects infinity. Closes #65 Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ |
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1bb6bb31d8 |
feat: factorise the joint once with History::joint
`posterior_of`, `posterior_of_at` and `expected_variance_reduction` each
built the joint precision matrix, factorised it, asked one question and
threw it away. The factorisation is O(n^3) in the history's appearances
and depends only on the fit, so a caller asking about every pair in a
standings table, every cell in a grid, or every candidate in an
active-learning sweep paid for the same factorisation once per question.
`History::joint()` returns a `Joint` handle that pays it once. Measured
on 1976 appearances, 90 queries: 68.4s one-shot against 745ms factorise
plus 93ms of queries — 81.6x, with bit-identical answers. Per query,
Criterion at 480 appearances: 9.0ms one-shot against 48us cached, 187x.
The handle borrows the history, which is what makes it correct with no
invalidation logic: the borrow checker forbids adding events or refitting
while it is alive, so there is no window in which the factorisation could
describe a fit that no longer exists. It also makes the lifetime of the
n^2 factor explicit rather than parking it in the history forever — at
4000 appearances that is 128MB, which is not something to cache silently.
Every question the joint answers turns out to be a bilinear form,
c^T A^-1 a = (L^-1 c) . (L^-1 a)
so no caller ever needs L^-1 c itself. Replacing the general solve with a
forward substitution drops the back substitution as wasted work, halving
a query, and removes a failure mode: a variance as `c . (A^-1 c)` is a
difference of products that can round negative, where `|L^-1 c|^2` is a
sum of squares and cannot.
The one-shot calls are unchanged in cost and now delegate to the handle,
so the two paths cannot drift apart. tests/joint_handle.rs asserts they
agree bit for bit, including at pinned times, under UnknownKeys::Prior,
and across candidate matchups.
Refs #51
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ
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c12bc830a5 |
feat!: name the unknown key, expose tail probabilities, flag short fits
Three issues from two downstream consumers, all small, all sharing a theme: the crate had the information and would not hand it over. #44 — `UnknownKey { team: 0, member: 0 }` did not say which key. A consumer upgrading 0.1.2 -> 0.4.1 had every one of 5591 predictions return this error, fell back to a neutral 0.5, and lost its entire metadata model for a day. Nothing crashed and nothing logged; it was found by sweeping an unrelated parameter and noticing the output did not move. The 0.4.0 change that made unknown keys an error was right — the error was just too anonymous to act on. It now carries the key's `Debug` rendering, and its `Display` says what to do about it. The precondition is documented on every prediction entry point, which the reporter said would alone have saved the day. #43 — `cdf` was `pub(crate)`, so a consumer asking "is this competitor below the cutoff" approximated it with a `mu + z * sigma` band and had no way to say what confidence any `z` bought. Adds `Gaussian::probability_below` / `probability_above`. The second is separate on purpose: `1 - cdf` collapses to exactly zero past ~8.3 sigma, and a stopping rule is evaluated precisely there. Both route through the survival function added in 0.4.1, so this is visibility rather than new numerics. #50 — `ConvergenceReport` was not `#[must_use]`, so the one signal that a fit stopped short was trivially discarded. It now is, and that immediately found 78 sites doing exactly that — including this crate's own ATP example, which was capped at 10 sweeps when the history needs 30. The example now reads the report and says so. `ITERATIONS = 30` is documented as the floor it is, with the three measurements to hand: 400 events over 100 competitors already stops there at ~7e-3 against a 1e-6 tolerance, the ATP example needs 30 at a much looser one, and a consumer's 2000-node model needs 76 to 161. BREAKING CHANGE: `InferenceError::UnknownKey` gains a `key` field, and the prediction methods now require `K: Debug` in order to fill it. Closes #43, #50. Refs #44 — its third ask, an opt-in `UnknownKeys::Skip` mode, is a live API question and deliberately not answered here. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ |
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aff3fb948d |
refactor!: replace emptiness-as-sentinel with Option for results and weights
Third of the five remaining items on #23. `add_events_with_prior` and `TimeSlice::add_events` took `Vec<Vec<f64>>` and `Vec<Vec<Vec<f64>>>` where an empty vec meant "not supplied" — so an empty outer vec and a genuinely empty event list were the same value, and every reader had to know which. Both are now `Option`, and the "not supplied" branches read as `None` arms rather than `is_empty()` checks. Two things fell out of the change that a sentinel would have hidden: The tie pre-check iterated `results` directly. Under `Option` it needs `.iter().flatten()`, which makes explicit that a `None` results list has no ties to reject — previously an empty vec silently skipped the same loop and looked identical to "checked, found nothing". `MismatchedShape.got` could no longer be `results.len()`, because at the point of the error there may be no vec to take a length from. It is now computed as `map_or(0, Vec::len)` before the error is built. MSRV note: my first draft used let-chains for the two validations. Those need Rust 1.88 and this crate pins 1.85 — it compiled locally on 1.98 and would have failed only in the MSRV CI job. Rewritten with `is_some_and`, and verified by installing 1.85.0 and building against it rather than by assuming the removal was complete. Breaking: `TimeSlice::add_events` is public. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01T5SYDExxL4vZgvunrcNSMc |
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9e8515b7cd |
docs: refresh README and CLAUDE.md; add ingest benchmark
The CLAUDE.md architecture section still described the pre-redesign engine: its data flow named `Batch`, `Agent`, `Player` and `message.rs`, none of which have existed since T2, and the public API it listed did not match `lib.rs`. It is the first thing a fresh session reads, so it was actively misleading. Rewritten against the current module layout, with the invariants that are easy to violate — ties needing a positive `p_draw`, NaN never being convergence, log-space evidence, color contiguity, `forbid(unsafe_code)`, and ingestion-order equivalence — written down. The README Todo list had five entries that were already done, including "Time needs to be an enum": `Time` has been a trait since T2, and the `batch::compute_elapsed()` it pointed at no longer exists. The genuinely open item — cross-checking `quality()` against sublee/trueskill — stays. `benches/ingest.rs` measures one-event-per-call against a single batched call. The rest of the suite only measured batched construction, which is why the quadratic fixed earlier on this branch went unnoticed for so long. `TimeSlice::log_evidence` also hashes its target set once instead of scanning the slice per player per event, so `log_evidence_for` with many keys is no longer quadratic. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01DnsaJg74eNSva3PJjK2eej |
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872f91797d |
refactor(time_slice): add convergence field, rename iterate_to_convergence
TimeSlice<T> gains a pub(crate) convergence: ConvergenceOptions field set at construction. TimeSlice::new now takes it as a third parameter (breaking change to the pub constructor, acceptable in 0.1.x). History::add_events_with_prior passes self.convergence so the propagated value reaches every TimeSlice. The pre-existing convergence-the-method is renamed to iterate_to_convergence to disambiguate from the new convergence-the-field. The field is wired but not yet read by inference -- the three Game::*_with_arena callsites in time_slice.rs still hardcode ConvergenceOptions::default(). Task 2 changes that. Bit-equal because the propagated value equals the hardcoded value end-to-end. Also updated benches/batch.rs which has a fourth TimeSlice::new callsite (not enumerated in the plan -- only src/ files were). |
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0705986929 |
feat(game): plumb ConvergenceOptions through to run_chain
Game and OwnedGame gain a convergence: ConvergenceOptions field set at
construction. Game::{ranked,scored} forward options.convergence into
OwnedGame::{new,new_scored} (previously dropped on the floor).
{ranked,scored}_with_arena take it as a parameter. run_chain reads
self.convergence.{epsilon, max_iter, alpha} instead of hardcoded
1e-6 / 10 / undamped. DiffFactor::propagate gains an alpha parameter
and dispatches into Trunc/MarginFactor::propagate_with_alpha.
In-tree callsites in src/time_slice.rs and src/history.rs pass
ConvergenceOptions::default(). Pre-existing T2 fallout in tests,
benches, and the atp example (struct literals missing the new alpha
field) is fixed by adding alpha: 1.0 so the workspace builds clean.
Default alpha is 1.0, so all 96 lib + 27 integration test goldens
remain bit-equal.
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8b53cacd64 |
T4 (MarginFactor): scored outcomes via Gaussian-margin EP evidence
Adds soft Gaussian-observation evidence on the per-pair diff variable,
enabling continuous score margins as a richer alternative to ranks.
Public API:
- `Outcome::Scored([scores])` (non-breaking enum extension under
`#[non_exhaustive]`).
- `Game::scored(teams, outcome, options)` constructor parallel to
`Game::ranked`.
- `EventBuilder::scores([...])` fluent helper.
- `HistoryBuilder::score_sigma(σ)` knob (default 1.0, validated > 0).
- `GameOptions::score_sigma`.
- `EventKind` re-exported from `lib.rs` (annotated `#[non_exhaustive]`).
- New `InferenceError::InvalidParameter { name, value }` variant.
Internals:
- `MarginFactor` (`factor/margin.rs`): Gaussian observation factor that
closes in one EP step; cavity-cached log-evidence mirrors `TruncFactor`.
- `BuiltinFactor::Margin` dispatch arm.
- `DiffFactor` enum in `game.rs` lets `Game::likelihoods` and the new
`likelihoods_scored` share the per-pair link abstraction.
- Per-event `EventKind { Ranked, Scored { score_sigma } }` routed through
`TimeSlice::add_events`, `iteration_direct`, and `log_evidence`.
Tests: 88 lib + 27 integration (4 new in `tests/scored.rs`); existing
goldens byte-identical. Bench: `benches/scored.rs` baseline ~960µs for
60 events × 20-player pool with default convergence.
Plan: docs/superpowers/plans/2026-04-27-t4-margin-factor.md
Spec item marked Done.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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6bf3e7e294 |
T3: rayon-backed concurrency (opt-in) (#2)
Implements T3 of `docs/superpowers/specs/2026-04-23-trueskill-engine-redesign-design.md` Section 6. Plan: `docs/superpowers/plans/2026-04-24-t3-concurrency.md` (11 tasks).
## Summary
### Breaking
- `Send + Sync` bounds added to public traits: `Time`, `Drift<T>`, `Observer<T>`, `Factor`, `Schedule`. All built-in impls satisfy these via auto-derive; downstream custom impls will need the bounds.
### New
- Opt-in `rayon` cargo feature. When enabled:
- Within-slice event iteration runs color-group events in parallel via `par_iter_mut` (`TimeSlice::sweep_color_groups`).
- `History::learning_curves` computes per-slice posteriors in parallel; merges sequentially in slice order.
- `History::log_evidence` / `log_evidence_for` use per-slice parallel computation with deterministic sequential reduction (sum in slice order) — bit-identical to the sequential baseline.
- `ColorGroups` infrastructure (`src/color_group.rs`) with greedy graph coloring. Events sharing no `Index` go into the same color group; events in the same group can run concurrently without touching each other's skills.
- `tests/determinism.rs` asserts bit-identical posteriors across `RAYON_NUM_THREADS={1, 2, 4, 8}`.
- `benches/history_converge.rs` measures end-to-end convergence on three workload shapes.
## Performance
### Sequential (no rayon, default build)
| Metric | Before T3 | After T3 | Delta |
|---|---|---|---|
| `Batch::iteration` | 22.88 µs | 23.23 µs | **+1.5%** (noise) |
| `Gaussian::*` | ≈218–264 ps | ≈236 ps | within noise |
**No sequential regression.** Default build is as fast as T2.
### Parallel (`--features rayon`, Apple M5 Pro, auto thread count)
| Workload | Sequential | Parallel | Speedup |
|---|---:|---:|---:|
| 500 events / 100 competitors / 10 per slice | 4.03 ms | 4.24 ms | **1.0×** |
| 2000 events / 200 competitors / 20 per slice | 20.18 ms | 19.82 ms | **1.0×** |
| 5000 events / 50000 competitors / 1 slice | 11.88 ms | 9.10 ms | **1.3×** |
### ⚠️ The spec's >=2× target was not met on realistic workloads.
T3's within-slice color-group parallelism only shows material benefit when a slice holds many events AND the competitor pool is large enough to give the greedy coloring room to partition. Typical TrueSkill workloads (tens of events per slice) don't fit that profile — rayon's task-spawn overhead dominates.
**Cross-slice parallelism (dirty-bit slice skipping per spec Section 5) is the natural next step** for real-workload speedup and would deliver the spec's ~50–500× online-add speedup. Deferred to a future tier.
## Determinism
`tests/determinism.rs` runs a 200-event history at thread counts {1, 2, 4, 8} via `rayon::ThreadPoolBuilder::install` and asserts every `(time, posterior)` pair has bit-identical `mu` and `sigma` (compared via `f64::to_bits()`). Passes.
## Internals
- Parallel path uses an `unsafe` block to concurrently write to `SkillStore` from color-group-disjoint events. Soundness rests on the color-group invariant (events in the same color touch no shared `Index`), guaranteed by construction in `TimeSlice::recompute_color_groups`. Sequential path unchanged from T2.
- `RAYON_THRESHOLD = 64` — color groups smaller than this fall back to sequential inside `sweep_color_groups` to avoid task-spawn overhead.
- Thread-local `ScratchArena` per rayon worker thread.
## Test plan
- [x] `cargo test --features approx` — 96 tests pass (74 lib + 22 integration)
- [x] `cargo test --features approx,rayon` — 97 tests pass (+1 determinism)
- [x] `cargo clippy --all-targets --features approx -- -D warnings` — clean
- [x] `cargo clippy --all-targets --features approx,rayon -- -D warnings` — clean
- [x] `cargo +nightly fmt --check` — clean
- [x] `cargo bench --bench batch --features approx` — 23.23 µs (no regression vs T2)
- [x] `cargo bench --bench history_converge --features approx,rayon` — runs on all three workloads
- [x] Bit-identical posteriors across `RAYON_NUM_THREADS={1, 2, 4, 8}` — verified
## Commit history
13 commits on `t3-concurrency`. Each task is self-contained and bisectable. See `git log main..t3-concurrency` for the full list.
## Deferred
- **Cross-slice parallelism** (dirty-bit slice skipping) — the path that would actually speed up typical TrueSkill workloads.
- **Default-on `rayon` feature** — spec called for default-on; we keep it opt-in until the feature proves stable in production use.
- **Synchronous-EP schedule with barrier merge** — alternative parallel strategy per spec Section 6.
- **`MarginFactor` / `Outcome::Scored`** — T4.
- **`Damped` / `Residual` schedules** — T4.
- **N-team `predict_outcome`** — T4.
- **`Game::custom` full ergonomics** — T4.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Reviewed-on: #2
Co-authored-by: Anders Olsson <anders.e.olsson@gmail.com>
Co-committed-by: Anders Olsson <anders.e.olsson@gmail.com>
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d2aab82c1e |
T0 + T1 + T2: engine redesign through new API surface (#1)
Implements tiers T0, T1, T2 of `docs/superpowers/specs/2026-04-23-trueskill-engine-redesign-design.md`. All three tiers have landed together on this branch because they build on one another; this PR rolls them up for a single review pass. Per-tier plans: - T0: `docs/superpowers/plans/2026-04-23-t0-numerical-parity.md` - T1: `docs/superpowers/plans/2026-04-24-t1-factor-graph.md` - T2: `docs/superpowers/plans/2026-04-24-t2-new-api-surface.md` ## Summary ### T0 — Numerical parity (internal) - `Gaussian` switched to natural-parameter storage `(pi, tau)`; mul/div now ~7× faster (218 ps vs 1.57 ns). - `HashMap<Index, _>` → dense `Vec<_>` keyed by `Index.0` (via `AgentStore<D>`, `SkillStore`). - `ScratchArena` eliminates per-event allocations in `Game::likelihoods`. - `InferenceError` seed type added (1 variant). - 38 → 53 tests passing through T1. - Benchmark: `Batch::iteration` 29.84 → 21.25 µs. ### T1 — Factor graph machinery (internal) - `Factor` trait + `BuiltinFactor` enum (TeamSum / RankDiff / Trunc) driving within-game inference. - `VarStore` flat storage for variable marginals. - `Schedule` trait + `EpsilonOrMax` impl replacing the hand-rolled EP loop. - `Game::likelihoods` rebuilt on the factor-graph machinery; iteration counts and goldens preserved to within 1e-6. - 53 tests passing. - Benchmark: `Batch::iteration` 23.01 µs (slight regression absorbed in T2). ### T2 — New API surface (breaking) **Renames:** - `IndexMap → KeyTable`, `Player → Rating`, `Agent → Competitor`, `Batch → TimeSlice` **New types:** - `Time` trait with `Untimed` ZST and `i64` impls; `Drift<T>`, `Rating<T, D>`, `Competitor<T, D>`, `TimeSlice<T>`, `History<T, D, O, K>` all generic. - `Event<T, K>`, `Team<K>`, `Member<K>`, `Outcome` (`Ranked` variant; `#[non_exhaustive]`). - `Observer<T>` trait + `NullObserver`. - `ConvergenceOptions`, `ConvergenceReport`. - `GameOptions`, `OwnedGame<T, D>`. **Three-tier ingestion:** - `history.record_winner(&K, &K, T)` / `record_draw(&K, &K, T)` — 1v1 convenience. - `history.add_events(iter)` — typed bulk. - `history.event(T).team([...]).weights([...]).ranking([...]).commit()` — fluent. **Query API:** `current_skill`, `learning_curve`, `learning_curves` (keyed on `K`), `log_evidence`, `log_evidence_for`, `predict_quality`, `predict_outcome`. **Game constructors:** `ranked`, `one_v_one`, `free_for_all`, `custom` — all returning `Result<_, InferenceError>`. **`factors` module:** `Factor`, `Schedule`, `VarStore`, `VarId`, `BuiltinFactor`, `EpsilonOrMax`, `ScheduleReport`, `TeamSumFactor`, `RankDiffFactor`, `TruncFactor` now public. **Errors:** `InferenceError` gains `MismatchedShape`, `InvalidProbability`, `ConvergenceFailed`; boundary panics converted to `Result`. **Removed (breaking):** `History::convergence(iters, eps, verbose)`, `HistoryBuilder::gamma(f64)`, `HistoryBuilder::time(bool)`, `History.time: bool`, `learning_curves_by_index`, nested-Vec public `add_events`. ## Behavior change (documented in CHANGELOG) `Time = Untimed` has `elapsed_to → 0`, so no drift accumulates between slices. The old `time=false` mode implicitly forced `elapsed=1` on reappearance via an `i64::MAX` sentinel — that quirk is not reproducible under a typed time axis. Tests that depended on it now use `History::<i64, _>` with explicit `1..=n` timestamps. One test (`test_env_ttt`) had 3 Gaussian goldens updated to reflect the corrected semantics; documented in commit `33a7d90`. ## Final numbers | Metric | Before T0 | After T2 | Delta | |---|---|---|---| | `Batch::iteration` | 29.84 µs | 21.36 µs | **-28%** | | `Gaussian::mul` | 1.57 ns | 219 ps | **-86%** | | `Gaussian::div` | 1.57 ns | 219 ps | **-86%** | | Tests passing | 38 | 90 | +52 | All other Gaussian ops unchanged (~219 ps add/sub, ~264 ps pi/tau reads). ## Test plan - [x] `cargo test --features approx` — 90/90 pass (68 lib + 10 api_shape + 6 game + 4 record_winner + 2 equivalence) - [x] `cargo clippy --all-targets --features approx -- -D warnings` — clean - [x] `cargo +nightly fmt --check` — clean - [x] `cargo bench --bench batch` — 21.36 µs - [x] `cargo bench --bench gaussian` — unchanged from T1 - [x] `cargo run --example atp --features approx` — rewritten in new API, runs clean - [x] Historical Game-level goldens preserved in `tests/equivalence.rs` - [x] Public API matches spec Section 4 (verified by integration tests in `tests/api_shape.rs`) ## Commit history ~45 commits total across T0 + T1 + T2. Each task is self-contained and individually tested; the branch is bisectable. See `git log main..t2-new-api-surface` for the full list. ## Deferred to later tiers - `Outcome::Scored` + `MarginFactor` — T4 - `Damped` / `Residual` schedules — T4 - `Send + Sync` bounds + Rayon parallelism — T3 - N-team `predict_outcome` — T4 - `Game::custom` full ergonomics — T4 🤖 Generated with [Claude Code](https://claude.com/claude-code) Reviewed-on: #1 Co-authored-by: Anders Olsson <anders.e.olsson@gmail.com> Co-committed-by: Anders Olsson <anders.e.olsson@gmail.com> |
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04d5478ee4 | style: cargo fmt | ||
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dc47964310 | added benchmark | ||
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a1f282a1c8 | feat: added a Drift trait and a "default" ConstantDrift implementation | ||
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d152e356f1 | Remove unnecessary allocations | ||
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e3906aebaa | Small refactor | ||
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2b83ee5ef9 | Added benchmark for Batch |