trueskill-tt/src/factor/mod.rs

//! Factor graph machinery for within-game inference.

use crate::gaussian::Gaussian;

/// Identifier for a variable in a `VarStore`.
///
/// Variables hold the current Gaussian marginal and are owned by exactly one
/// `VarStore`. `VarId` is meaningful only within its owning store.
#[derive(Copy, Clone, Debug, PartialEq, Eq, Hash)]
pub struct VarId(pub u32);

/// Flat storage of variable marginals.
///
/// Variables are allocated by `alloc()` and accessed by `VarId`. The store is
/// reused across `Game::ranked_with_arena` calls (it lives in the `ScratchArena`); call
/// `clear()` before reuse.
#[derive(Debug, Default)]
pub struct VarStore {
    pub(crate) marginals: Vec<Gaussian>,
}

impl VarStore {
    pub fn new() -> Self {
        Self::default()
    }

    pub fn clear(&mut self) {
        self.marginals.clear();
    }

    pub fn len(&self) -> usize {
        self.marginals.len()
    }

    pub fn is_empty(&self) -> bool {
        self.marginals.is_empty()
    }

    pub fn alloc(&mut self, init: Gaussian) -> VarId {
        let id = VarId(self.marginals.len() as u32);
        self.marginals.push(init);
        id
    }

    pub fn get(&self, id: VarId) -> Gaussian {
        self.marginals[id.0 as usize]
    }

    pub fn set(&mut self, id: VarId, g: Gaussian) {
        self.marginals[id.0 as usize] = g;
    }
}

/// A factor in the EP graph.
///
/// Factors hold their own outgoing messages and propagate them by reading
/// connected variable marginals from a `VarStore` and writing back updated
/// marginals.
pub trait Factor: Send + Sync {
    /// Update outgoing messages and write back to the var store.
    ///
    /// Returns the max delta `(|Δmu|, |Δsigma|)` across writes this
    /// propagation. Used by the `Schedule` to detect convergence.
    fn propagate(&mut self, vars: &mut VarStore) -> (f64, f64);

    /// Optional log-evidence contribution. Default 0.0 (no contribution).
    fn log_evidence(&self, _vars: &VarStore) -> f64 {
        0.0
    }
}

/// Enum dispatcher for the built-in factor types.
///
/// Using an enum instead of `Box<dyn Factor>` keeps factor data inline and
/// avoids virtual-call overhead in the hot inference loop.
#[derive(Debug)]
pub enum BuiltinFactor {
    TeamSum(team_sum::TeamSumFactor),
    RankDiff(rank_diff::RankDiffFactor),
    Trunc(trunc::TruncFactor),
    Margin(margin::MarginFactor),
}

impl Factor for BuiltinFactor {
    fn propagate(&mut self, vars: &mut VarStore) -> (f64, f64) {
        match self {
            Self::TeamSum(f) => f.propagate(vars),
            Self::RankDiff(f) => f.propagate(vars),
            Self::Trunc(f) => f.propagate(vars),
            Self::Margin(f) => f.propagate(vars),
        }
    }

    fn log_evidence(&self, vars: &VarStore) -> f64 {
        match self {
            Self::Trunc(f) => f.log_evidence(vars),
            Self::Margin(f) => f.log_evidence(vars),
            _ => 0.0,
        }
    }
}

pub mod margin;
pub mod rank_diff;
pub mod team_sum;
pub mod trunc;

#[cfg(test)]
mod tests {
    use super::*;
    use crate::N_INF;

    #[test]
    fn alloc_assigns_sequential_ids() {
        let mut store = VarStore::new();
        let a = store.alloc(N_INF);
        let b = store.alloc(N_INF);
        let c = store.alloc(N_INF);
        assert_eq!(a, VarId(0));
        assert_eq!(b, VarId(1));
        assert_eq!(c, VarId(2));
        assert_eq!(store.len(), 3);
    }

    #[test]
    fn get_returns_initial_value() {
        let mut store = VarStore::new();
        let g = Gaussian::from_ms(2.5, 1.0);
        let id = store.alloc(g);
        assert_eq!(store.get(id), g);
    }

    #[test]
    fn set_updates_value() {
        let mut store = VarStore::new();
        let id = store.alloc(N_INF);
        let new = Gaussian::from_ms(3.0, 0.5);
        store.set(id, new);
        assert_eq!(store.get(id), new);
    }

    #[test]
    fn clear_resets_length_keeping_capacity() {
        let mut store = VarStore::new();
        store.alloc(N_INF);
        store.alloc(N_INF);
        let cap = store.marginals.capacity();
        store.clear();
        assert_eq!(store.len(), 0);
        assert_eq!(store.marginals.capacity(), cap);
    }

    #[test]
    fn builtin_factor_dispatches_to_margin() {
        use super::margin::MarginFactor;
        let mut vars = VarStore::new();
        let diff = vars.alloc(Gaussian::from_ms(0.0, 6.0));
        let mut f = BuiltinFactor::Margin(MarginFactor::new(diff, 5.0, 1.0));

        f.propagate(&mut vars);

        let result = vars.get(diff);
        assert!((result.mu() - 4.864864864864865).abs() < 1e-12);

        let logz = f.log_evidence(&vars);
        assert!((logz - (-3.062235327364623)).abs() < 1e-10);
    }
}