2.9 KiB
2.9 KiB
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Commands
cargo build # Build the library
cargo test --lib # Run all library tests
cargo test --lib <test_name> # Run a single test by name
cargo test --lib -- --nocapture # Run tests with stdout output
cargo clippy # Lint
cargo bench # Run benchmarks (criterion)
The approx feature enables approx::AbsDiffEq for Gaussian:
cargo test --features approx
Architecture
This is a Rust port of TrueSkillThroughTime.py — a Bayesian skill rating system that tracks skill evolution over time using Gaussian message passing.
Data flow
History → Batch[] → Game[] → teams/players
History(history.rs) — top-level container. Organizes games by time intoBatches, runs forward/backward message passing across batches, and exposeslearning_curves()andlog_evidence().Batch(batch.rs) — all games at a single time step. Runsiteration()to update skill estimates viaGame::posteriors(), collectingSkilldistributions per player.Game(game.rs) — a single match. Given teams (slices ofGaussian), computes posterior skill distributions using Gaussian factor graphs andmessage.rshelpers.Agent(agent.rs) — wraps aPlayerwith temporal state (last_time,message).receive()applies time-decay (gamma) when the player reappears after a gap.Player(player.rs) — static configuration: priorGaussian,beta(performance noise),gamma(skill drift per time unit).Gaussian(gaussian.rs) — core probability type. Stored as natural parameters (pi = 1/sigma²,tau = mu/sigma²). Arithmetic ops implement message multiplication/division in the factor graph.message.rs—TeamMessageandDiffMessage: intermediate factor graph messages used insideGame.lib.rs— exports the public API (Game,Gaussian,History,Player) and standalone functions (quality(),pdf(),cdf(),erfc()). Also defines global defaults:MU=0.0,SIGMA=6.0,BETA=1.0,GAMMA=0.03,P_DRAW=0.0,EPSILON=1e-6,ITERATIONS=30.
Key design points
HistoryusesIndexMap<K>(defined inlib.rs) to map arbitrary player keys toAgentstate.- Convergence is measured by the maximum
delta()across all skill distributions; iteration stops when belowEPSILONor afterITERATIONSrounds. - The
approxfeature gatesAbsDiffEqonGaussianfor use in tests — the feature is optional and only needed for approximate equality assertions. timeinHistory/Batchis currently anf64; the README notes it needs to become an enum to support richer temporal states.