logaritmiskandClaude Opus 5
d4f91fd221
`Game::ranked` and `Game::scored` validated `p_draw` and `score_sigma`
but never `convergence`. `ConvergenceOptions` has public fields and
`GameOptions` carries one, so a caller could hand the engine a set that
`HistoryBuilder`'s eager asserts never saw. Past that, the only guard
was a `debug_assert!`, which is gone in the profile users ship.
An `alpha` of zero is the bad case, and it fails silently rather than
loudly. Measured in release before the fix:
likelihoods: [[Gaussian { pi: 0.0, tau: 0.0 }],
[Gaussian { pi: 0.0, tau: 0.0 }]]
Every EP update unapplied, every likelihood uninformative, inference
returning the priors it was given — and an `OwnedGame` that looks
entirely ordinary to the caller. `HistoryBuilder::convergence` already
documents exactly this hazard; the `Game` constructors just did not
share the check.
Adds `ConvergenceOptions::validate`, called by both constructors.
Rejects `alpha` outside `(0.0, 1.0]` and negative `epsilon`; NaN fails
both comparisons and is rejected too.
`tests/validation.rs` states the release-mode guarantee for the whole
public surface, not just this hole, and CI already runs the suite in
release. Probing the other conditions #18 lists found five of eight
already enforced — ties without a draw probability, per-event score
sigma, weight/team dimensions, draw-probability range, score-sigma
range — so this closes the remaining gap rather than the whole issue.
The engine keeps its `debug_assert!`s as invariant documentation.
Refs #18
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ
1463 lines
45 KiB
Rust
1463 lines
45 KiB
Rust
use std::cmp::Ordering;
|
||
|
||
use crate::{
|
||
N_INF, N00,
|
||
arena::ScratchArena,
|
||
compute_margin,
|
||
drift::Drift,
|
||
factor::{VarId, margin::MarginFactor, trunc::TruncFactor},
|
||
gaussian::Gaussian,
|
||
rating::Rating,
|
||
time::Time,
|
||
tuple_gt, tuple_max,
|
||
};
|
||
|
||
/// Per-adjacent-pair link factor in the game's diff chain.
|
||
///
|
||
/// `Trunc` is used for `Outcome::Ranked` (rank-based truncation).
|
||
/// `Margin` is used for `Outcome::Scored` (Gaussian observation on the diff).
|
||
#[derive(Debug)]
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||
pub(crate) enum DiffFactor {
|
||
Trunc(TruncFactor),
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||
Margin(MarginFactor),
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||
}
|
||
|
||
impl DiffFactor {
|
||
pub(crate) fn diff(&self) -> VarId {
|
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match self {
|
||
Self::Trunc(f) => f.diff,
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||
Self::Margin(f) => f.diff,
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||
}
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||
}
|
||
|
||
pub(crate) fn msg(&self) -> Gaussian {
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||
match self {
|
||
Self::Trunc(f) => f.msg,
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Self::Margin(f) => f.msg,
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||
}
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||
}
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||
|
||
/// Log of this link's cached evidence.
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///
|
||
/// Accumulating in log space keeps a long diff chain from underflowing:
|
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/// each link contributes a probability in `(0, 1]`, so the linear product
|
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/// over an n-team game decays geometrically and flushes to zero — and
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/// `ln(0.0)` is `-inf` — well within the team counts a large free-for-all
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/// reaches.
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pub(crate) fn log_evidence(&self) -> f64 {
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match self {
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Self::Trunc(f) => f.evidence_cached.unwrap_or(1.0).ln(),
|
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Self::Margin(f) => f.evidence_cached.unwrap_or(1.0).ln(),
|
||
}
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||
}
|
||
|
||
pub(crate) fn propagate(
|
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&mut self,
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vars: &mut crate::factor::VarStore,
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alpha: f64,
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) -> (f64, f64) {
|
||
match self {
|
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Self::Trunc(f) => f.propagate_with_alpha(vars, alpha),
|
||
Self::Margin(f) => f.propagate_with_alpha(vars, alpha),
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||
}
|
||
}
|
||
}
|
||
|
||
/// Per-game inference options.
|
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///
|
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/// `p_draw` and `convergence` apply to ranked outcomes (`Game::ranked`).
|
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/// `score_sigma` applies only to scored outcomes (`Game::scored`); it controls
|
||
/// how much the engine trusts the observed score margin (smaller σ = more trust).
|
||
#[derive(Clone, Copy, Debug)]
|
||
pub struct GameOptions {
|
||
pub p_draw: f64,
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pub score_sigma: f64,
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||
pub convergence: crate::ConvergenceOptions,
|
||
}
|
||
|
||
impl Default for GameOptions {
|
||
fn default() -> Self {
|
||
Self {
|
||
p_draw: crate::P_DRAW,
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||
score_sigma: 1.0,
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||
convergence: crate::ConvergenceOptions::default(),
|
||
}
|
||
}
|
||
}
|
||
|
||
/// Owned variant of `Game` returned by public constructors.
|
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///
|
||
/// Unlike `Game<'a, T, D>` (which borrows its result/weights slices from
|
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/// History's internal state), `OwnedGame<T, D>` owns the team ratings, so it
|
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/// can be returned freely from public constructors. The inference inputs
|
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/// themselves are not retained — nothing reads them back.
|
||
#[derive(Debug)]
|
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pub struct OwnedGame<T: Time, D: Drift<T>> {
|
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teams: Vec<Vec<Rating<T, D>>>,
|
||
pub(crate) likelihoods: Vec<Vec<Gaussian>>,
|
||
pub(crate) log_evidence: f64,
|
||
}
|
||
|
||
impl<T: Time, D: Drift<T>> OwnedGame<T, D> {
|
||
pub(crate) fn new(
|
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teams: Vec<Vec<Rating<T, D>>>,
|
||
result: Vec<f64>,
|
||
weights: Vec<Vec<f64>>,
|
||
p_draw: f64,
|
||
convergence: crate::ConvergenceOptions,
|
||
) -> Self {
|
||
let mut arena = ScratchArena::new();
|
||
|
||
// `Game` takes the teams by value and is dropped here, so take the vec
|
||
// back out of it rather than handing it a clone.
|
||
let g = Game::ranked_with_arena(teams, &result, &weights, p_draw, convergence, &mut arena);
|
||
|
||
Self {
|
||
teams: g.teams,
|
||
likelihoods: g.likelihoods,
|
||
log_evidence: g.log_evidence,
|
||
}
|
||
}
|
||
|
||
pub(crate) fn new_scored(
|
||
teams: Vec<Vec<Rating<T, D>>>,
|
||
scores: Vec<f64>,
|
||
weights: Vec<Vec<f64>>,
|
||
score_sigma: f64,
|
||
convergence: crate::ConvergenceOptions,
|
||
) -> Self {
|
||
let mut arena = ScratchArena::new();
|
||
|
||
let g = Game::scored_with_arena(
|
||
teams,
|
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&scores,
|
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&weights,
|
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score_sigma,
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convergence,
|
||
&mut arena,
|
||
);
|
||
|
||
Self {
|
||
teams: g.teams,
|
||
likelihoods: g.likelihoods,
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||
log_evidence: g.log_evidence,
|
||
}
|
||
}
|
||
|
||
#[must_use]
|
||
pub fn posteriors(&self) -> Vec<Vec<Gaussian>> {
|
||
self.likelihoods
|
||
.iter()
|
||
.zip(self.teams.iter())
|
||
.map(|(l, t)| l.iter().zip(t.iter()).map(|(&l, r)| l * r.prior).collect())
|
||
.collect()
|
||
}
|
||
|
||
#[must_use]
|
||
pub fn log_evidence(&self) -> f64 {
|
||
self.log_evidence
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||
}
|
||
}
|
||
|
||
#[derive(Debug)]
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pub struct Game<'a, T: Time = i64, D: Drift<T> = crate::drift::ConstantDrift> {
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teams: Vec<Vec<Rating<T, D>>>,
|
||
result: &'a [f64],
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||
weights: &'a [Vec<f64>],
|
||
p_draw: f64,
|
||
pub(crate) convergence: crate::ConvergenceOptions,
|
||
pub(crate) likelihoods: Vec<Vec<Gaussian>>,
|
||
pub(crate) log_evidence: f64,
|
||
}
|
||
|
||
impl<'a, T: Time, D: Drift<T>> Game<'a, T, D> {
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||
pub(crate) fn ranked_with_arena(
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teams: Vec<Vec<Rating<T, D>>>,
|
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result: &'a [f64],
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||
weights: &'a [Vec<f64>],
|
||
p_draw: f64,
|
||
convergence: crate::ConvergenceOptions,
|
||
arena: &mut ScratchArena,
|
||
) -> Self {
|
||
debug_assert!(
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result.len() == teams.len(),
|
||
"result must have the same length as teams"
|
||
);
|
||
debug_assert!(
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weights
|
||
.iter()
|
||
.zip(teams.iter())
|
||
.all(|(w, t)| w.len() == t.len()),
|
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"weights must have the same dimensions as teams"
|
||
);
|
||
debug_assert!(
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(0.0..1.0).contains(&p_draw),
|
||
"draw probability must be >= 0.0 and < 1.0"
|
||
);
|
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debug_assert!(
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p_draw > 0.0 || {
|
||
let mut r = result.to_vec();
|
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r.sort_unstable_by(|a, b| a.partial_cmp(b).unwrap());
|
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r.windows(2).all(|w| w[0] != w[1])
|
||
},
|
||
"draw must be > 0.0 if there are teams with draw"
|
||
);
|
||
debug_assert!(
|
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convergence.alpha > 0.0 && convergence.alpha <= 1.0,
|
||
"convergence alpha must be in (0.0, 1.0]"
|
||
);
|
||
|
||
let mut this = Self {
|
||
teams,
|
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result,
|
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weights,
|
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p_draw,
|
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convergence,
|
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likelihoods: Vec::new(),
|
||
log_evidence: 0.0,
|
||
};
|
||
|
||
this.likelihoods(arena);
|
||
this
|
||
}
|
||
|
||
pub(crate) fn scored_with_arena(
|
||
teams: Vec<Vec<Rating<T, D>>>,
|
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scores: &'a [f64],
|
||
weights: &'a [Vec<f64>],
|
||
score_sigma: f64,
|
||
convergence: crate::ConvergenceOptions,
|
||
arena: &mut ScratchArena,
|
||
) -> Self {
|
||
debug_assert!(
|
||
scores.len() == teams.len(),
|
||
"scores must have the same length as teams"
|
||
);
|
||
debug_assert!(
|
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weights
|
||
.iter()
|
||
.zip(teams.iter())
|
||
.all(|(w, t)| w.len() == t.len()),
|
||
"weights must have the same dimensions as teams"
|
||
);
|
||
debug_assert!(score_sigma > 0.0, "score_sigma must be positive");
|
||
debug_assert!(
|
||
convergence.alpha > 0.0 && convergence.alpha <= 1.0,
|
||
"convergence alpha must be in (0.0, 1.0]"
|
||
);
|
||
|
||
let mut this = Self {
|
||
teams,
|
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result: scores,
|
||
weights,
|
||
p_draw: 0.0,
|
||
convergence,
|
||
likelihoods: Vec::new(),
|
||
log_evidence: 0.0,
|
||
};
|
||
|
||
this.likelihoods_scored(arena, score_sigma);
|
||
this
|
||
}
|
||
|
||
fn run_chain<F>(&self, arena: &mut ScratchArena, mut make_link: F) -> (f64, Vec<Vec<Gaussian>>)
|
||
where
|
||
F: FnMut(usize, &[usize], &mut crate::factor::VarStore) -> DiffFactor,
|
||
{
|
||
arena.reset();
|
||
|
||
let alpha = self.convergence.alpha;
|
||
let epsilon = self.convergence.epsilon;
|
||
let max_iter = self.convergence.max_iter;
|
||
|
||
let n_teams = self.teams.len();
|
||
|
||
arena.sort_buf.extend(0..n_teams);
|
||
arena.sort_buf.sort_by(|&i, &j| {
|
||
self.result[j]
|
||
.partial_cmp(&self.result[i])
|
||
.unwrap_or(Ordering::Equal)
|
||
});
|
||
|
||
arena.team_prior.extend(arena.sort_buf.iter().map(|&t| {
|
||
self.teams[t]
|
||
.iter()
|
||
.zip(self.weights[t].iter())
|
||
.fold(N00, |p, (player, &w)| p + (player.performance() * w))
|
||
}));
|
||
|
||
let n_diffs = n_teams.saturating_sub(1);
|
||
|
||
let mut links: Vec<DiffFactor> = (0..n_diffs)
|
||
.map(|i| make_link(i, &arena.sort_buf, &mut arena.vars))
|
||
.collect();
|
||
|
||
arena.lhood_lose.resize(n_teams, N_INF);
|
||
arena.lhood_win.resize(n_teams, N_INF);
|
||
|
||
let mut step = (f64::INFINITY, f64::INFINITY);
|
||
let mut iter = 0;
|
||
|
||
while tuple_gt(step, epsilon) && iter < max_iter {
|
||
step = (0.0_f64, 0.0_f64);
|
||
|
||
for (e, lf) in links[..n_diffs.saturating_sub(1)].iter_mut().enumerate() {
|
||
let pw = arena.team_prior[e] * arena.lhood_lose[e];
|
||
let pl = arena.team_prior[e + 1] * arena.lhood_win[e + 1];
|
||
let raw = pw - pl;
|
||
arena.vars.set(lf.diff(), raw * lf.msg());
|
||
let d = lf.propagate(&mut arena.vars, alpha);
|
||
step = tuple_max(step, d);
|
||
|
||
let new_ll = pw - lf.msg();
|
||
step = tuple_max(step, arena.lhood_lose[e + 1].delta(new_ll));
|
||
arena.lhood_lose[e + 1] = new_ll;
|
||
}
|
||
|
||
for (rev_i, lf) in links[1..].iter_mut().rev().enumerate() {
|
||
let e = n_diffs - 1 - rev_i;
|
||
let pw = arena.team_prior[e] * arena.lhood_lose[e];
|
||
let pl = arena.team_prior[e + 1] * arena.lhood_win[e + 1];
|
||
let raw = pw - pl;
|
||
arena.vars.set(lf.diff(), raw * lf.msg());
|
||
let d = lf.propagate(&mut arena.vars, alpha);
|
||
step = tuple_max(step, d);
|
||
|
||
let new_lw = pl + lf.msg();
|
||
step = tuple_max(step, arena.lhood_win[e].delta(new_lw));
|
||
arena.lhood_win[e] = new_lw;
|
||
}
|
||
|
||
iter += 1;
|
||
}
|
||
|
||
// Special case: exactly 1 diff (2-team game); loop body was empty.
|
||
if n_diffs == 1 {
|
||
let raw = (arena.team_prior[0] * arena.lhood_lose[0])
|
||
- (arena.team_prior[1] * arena.lhood_win[1]);
|
||
arena.vars.set(links[0].diff(), raw * links[0].msg());
|
||
links[0].propagate(&mut arena.vars, alpha);
|
||
}
|
||
|
||
// Boundary updates: close the chain at both ends.
|
||
if n_diffs > 0 {
|
||
let pl1 = arena.team_prior[1] * arena.lhood_win[1];
|
||
arena.lhood_win[0] = pl1 + links[0].msg();
|
||
let pw_last = arena.team_prior[n_teams - 2] * arena.lhood_lose[n_teams - 2];
|
||
arena.lhood_lose[n_teams - 1] = pw_last - links[n_diffs - 1].msg();
|
||
}
|
||
|
||
let log_evidence: f64 = links.iter().map(DiffFactor::log_evidence).sum();
|
||
|
||
// Inverse permutation: inv_buf[orig_i] = sorted_i.
|
||
arena.inv_buf.resize(n_teams, 0);
|
||
for (si, &orig_i) in arena.sort_buf.iter().enumerate() {
|
||
arena.inv_buf[orig_i] = si;
|
||
}
|
||
|
||
let likelihoods = self
|
||
.teams
|
||
.iter()
|
||
.zip(self.weights.iter())
|
||
.enumerate()
|
||
.map(|(orig_i, (players, weights))| {
|
||
let si = arena.inv_buf[orig_i];
|
||
let m = arena.lhood_win[si] * arena.lhood_lose[si];
|
||
// Already folded into `team_prior` at the top of the chain,
|
||
// indexed by sorted position.
|
||
let performance = arena.team_prior[si];
|
||
players
|
||
.iter()
|
||
.zip(weights.iter())
|
||
.map(|(player, &w)| {
|
||
((m - performance.exclude(player.performance() * w)) * (1.0 / w))
|
||
.forget(player.beta.powi(2))
|
||
})
|
||
.collect::<Vec<_>>()
|
||
})
|
||
.collect::<Vec<_>>();
|
||
|
||
(log_evidence, likelihoods)
|
||
}
|
||
|
||
fn likelihoods(&mut self, arena: &mut ScratchArena) {
|
||
let (log_evidence, likelihoods) = self.run_chain(arena, |i, sort_buf, vars| {
|
||
let tie = self.result[sort_buf[i]] == self.result[sort_buf[i + 1]];
|
||
let margin = if self.p_draw == 0.0 {
|
||
0.0
|
||
} else {
|
||
let a: f64 = self.teams[sort_buf[i]].iter().map(|p| p.beta.powi(2)).sum();
|
||
let b: f64 = self.teams[sort_buf[i + 1]]
|
||
.iter()
|
||
.map(|p| p.beta.powi(2))
|
||
.sum();
|
||
compute_margin(self.p_draw, (a + b).sqrt())
|
||
};
|
||
let vid = vars.alloc(N_INF);
|
||
DiffFactor::Trunc(TruncFactor::new(vid, margin, tie))
|
||
});
|
||
self.log_evidence = log_evidence;
|
||
self.likelihoods = likelihoods;
|
||
}
|
||
|
||
fn likelihoods_scored(&mut self, arena: &mut ScratchArena, score_sigma: f64) {
|
||
let (log_evidence, likelihoods) = self.run_chain(arena, |i, sort_buf, vars| {
|
||
let m_obs = self.result[sort_buf[i]] - self.result[sort_buf[i + 1]];
|
||
let vid = vars.alloc(N_INF);
|
||
DiffFactor::Margin(MarginFactor::new(vid, m_obs, score_sigma))
|
||
});
|
||
self.log_evidence = log_evidence;
|
||
self.likelihoods = likelihoods;
|
||
}
|
||
|
||
#[must_use]
|
||
pub fn posteriors(&self) -> Vec<Vec<Gaussian>> {
|
||
self.likelihoods
|
||
.iter()
|
||
.zip(self.teams.iter())
|
||
.map(|(l, t)| {
|
||
l.iter()
|
||
.zip(t.iter())
|
||
.map(|(&l, p)| l * p.prior)
|
||
.collect::<Vec<_>>()
|
||
})
|
||
.collect::<Vec<_>>()
|
||
}
|
||
|
||
#[must_use]
|
||
pub fn log_evidence(&self) -> f64 {
|
||
self.log_evidence
|
||
}
|
||
}
|
||
|
||
impl<T: Time, D: Drift<T>> Game<'_, T, D> {
|
||
/// # Errors
|
||
///
|
||
/// - `InvalidParameter` if `options.convergence` is out of range — an
|
||
/// `alpha` of zero would leave every EP update unapplied and silently
|
||
/// return the priors.
|
||
/// - `InvalidProbability` if `options.p_draw` is outside `[0.0, 1.0)`.
|
||
/// - `MismatchedShape` if the outcome's rank count differs from `teams.len()`.
|
||
/// - `WrongOutcomeKind` if `outcome` is not `Outcome::Ranked`.
|
||
/// - `TieWithoutDrawProbability` if the outcome ties two teams while
|
||
/// `p_draw` is zero: the truncation margin is then zero and the two-sided
|
||
/// tie update evaluates `0/0`.
|
||
pub fn ranked(
|
||
teams: &[&[Rating<T, D>]],
|
||
outcome: crate::Outcome,
|
||
options: &GameOptions,
|
||
) -> Result<OwnedGame<T, D>, crate::InferenceError> {
|
||
options.convergence.validate()?;
|
||
if !(0.0..1.0).contains(&options.p_draw) {
|
||
return Err(crate::InferenceError::InvalidProbability {
|
||
value: options.p_draw,
|
||
});
|
||
}
|
||
if outcome.team_count() != teams.len() {
|
||
return Err(crate::InferenceError::MismatchedShape {
|
||
kind: "outcome ranks vs teams",
|
||
expected: teams.len(),
|
||
got: outcome.team_count(),
|
||
});
|
||
}
|
||
|
||
let ranks = outcome
|
||
.as_ranks()
|
||
.ok_or(crate::InferenceError::WrongOutcomeKind {
|
||
context: "Game::ranked",
|
||
expected: "Outcome::Ranked",
|
||
got: "Outcome::Scored",
|
||
})?;
|
||
|
||
let tied = if options.p_draw == 0.0 {
|
||
crate::first_tied_pair(ranks)
|
||
} else {
|
||
None
|
||
};
|
||
|
||
if let Some(teams) = tied {
|
||
return Err(crate::InferenceError::TieWithoutDrawProbability { teams });
|
||
}
|
||
|
||
let max_rank = ranks.iter().copied().max().unwrap_or(0) as f64;
|
||
let result: Vec<f64> = ranks.iter().map(|&r| max_rank - r as f64).collect();
|
||
let teams_owned: Vec<Vec<Rating<T, D>>> = teams.iter().map(|t| t.to_vec()).collect();
|
||
let weights: Vec<Vec<f64>> = teams.iter().map(|t| vec![1.0; t.len()]).collect();
|
||
|
||
Ok(OwnedGame::new(
|
||
teams_owned,
|
||
result,
|
||
weights,
|
||
options.p_draw,
|
||
options.convergence,
|
||
))
|
||
}
|
||
|
||
/// # Errors
|
||
///
|
||
/// - `InvalidParameter` if `options.score_sigma` is not strictly positive
|
||
/// or is NaN, or if `options.convergence` is out of range.
|
||
/// - `MismatchedShape` if the outcome's score count differs from `teams.len()`.
|
||
/// - `WrongOutcomeKind` if `outcome` is not `Outcome::Scored`.
|
||
pub fn scored(
|
||
teams: &[&[Rating<T, D>]],
|
||
outcome: crate::Outcome,
|
||
options: &GameOptions,
|
||
) -> Result<OwnedGame<T, D>, crate::InferenceError> {
|
||
options.convergence.validate()?;
|
||
if options.score_sigma <= 0.0 || options.score_sigma.is_nan() {
|
||
return Err(crate::InferenceError::InvalidParameter {
|
||
name: "score_sigma",
|
||
value: options.score_sigma,
|
||
});
|
||
}
|
||
if outcome.team_count() != teams.len() {
|
||
return Err(crate::InferenceError::MismatchedShape {
|
||
kind: "outcome scores vs teams",
|
||
expected: teams.len(),
|
||
got: outcome.team_count(),
|
||
});
|
||
}
|
||
let scores = outcome
|
||
.as_scores()
|
||
.ok_or(crate::InferenceError::WrongOutcomeKind {
|
||
context: "Game::scored",
|
||
expected: "Outcome::Scored",
|
||
got: "Outcome::Ranked",
|
||
})?
|
||
.to_vec();
|
||
let teams_owned: Vec<Vec<Rating<T, D>>> = teams.iter().map(|t| t.to_vec()).collect();
|
||
let weights: Vec<Vec<f64>> = teams.iter().map(|t| vec![1.0; t.len()]).collect();
|
||
Ok(OwnedGame::new_scored(
|
||
teams_owned,
|
||
scores,
|
||
weights,
|
||
options.score_sigma,
|
||
options.convergence,
|
||
))
|
||
}
|
||
|
||
/// Convenience wrapper over [`Game::ranked`] for two single-player teams.
|
||
///
|
||
/// # Errors
|
||
///
|
||
/// Delegates to [`Game::ranked`], so it returns the same errors — in
|
||
/// practice `WrongOutcomeKind` for a non-ranked outcome, or
|
||
/// `TieWithoutDrawProbability` for a draw when `options.p_draw` is zero.
|
||
pub fn one_v_one(
|
||
a: &Rating<T, D>,
|
||
b: &Rating<T, D>,
|
||
outcome: crate::Outcome,
|
||
options: &GameOptions,
|
||
) -> Result<(Gaussian, Gaussian), crate::InferenceError> {
|
||
let game = Self::ranked(&[&[*a], &[*b]], outcome, options)?;
|
||
let post = game.posteriors();
|
||
Ok((post[0][0], post[1][0]))
|
||
}
|
||
|
||
/// # Errors
|
||
///
|
||
/// Wraps each player in a one-member team and delegates to
|
||
/// [`Game::ranked`], so it returns the same errors.
|
||
pub fn free_for_all(
|
||
players: &[&Rating<T, D>],
|
||
outcome: crate::Outcome,
|
||
options: &GameOptions,
|
||
) -> Result<OwnedGame<T, D>, crate::InferenceError> {
|
||
let teams: Vec<Vec<Rating<T, D>>> = players.iter().map(|p| vec![**p]).collect();
|
||
let team_refs: Vec<&[Rating<T, D>]> = teams.iter().map(|t| t.as_slice()).collect();
|
||
Self::ranked(&team_refs, outcome, options)
|
||
}
|
||
|
||
#[doc(hidden)]
|
||
pub fn custom<S: crate::graph::Schedule>(
|
||
factors: &mut [crate::graph::BuiltinFactor],
|
||
vars: &mut crate::graph::VarStore,
|
||
schedule: &S,
|
||
) -> crate::graph::ScheduleReport {
|
||
schedule.run(factors, vars)
|
||
}
|
||
}
|
||
|
||
#[cfg(test)]
|
||
mod tests {
|
||
use ::approx::assert_ulps_eq;
|
||
|
||
use super::*;
|
||
use crate::{ConstantDrift, GAMMA, Gaussian, N_INF, Rating, arena::ScratchArena};
|
||
|
||
type R = Rating<i64, ConstantDrift>;
|
||
|
||
#[test]
|
||
fn test_1vs1() {
|
||
let t_a = R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
let t_b = R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
|
||
let w = [vec![1.0], vec![1.0]];
|
||
let g = Game::ranked_with_arena(
|
||
vec![vec![t_a], vec![t_b]],
|
||
&[0.0, 1.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
let a = p[0][0];
|
||
let b = p[1][0];
|
||
|
||
assert_ulps_eq!(a, Gaussian::from_ms(20.794779, 7.194481), epsilon = 1e-6);
|
||
assert_ulps_eq!(b, Gaussian::from_ms(29.205220, 7.194481), epsilon = 1e-6);
|
||
|
||
let t_a = R::new(
|
||
Gaussian::from_ms(29.0, 1.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(GAMMA),
|
||
);
|
||
let t_b = R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(GAMMA),
|
||
);
|
||
|
||
let w = [vec![1.0], vec![1.0]];
|
||
let g = Game::ranked_with_arena(
|
||
vec![vec![t_a], vec![t_b]],
|
||
&[0.0, 1.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
let a = p[0][0];
|
||
let b = p[1][0];
|
||
|
||
assert_ulps_eq!(a, Gaussian::from_ms(28.896475, 0.996604), epsilon = 1e-6);
|
||
assert_ulps_eq!(b, Gaussian::from_ms(32.189211, 6.062063), epsilon = 1e-6);
|
||
|
||
let t_a = R::new(Gaussian::from_ms(1.139, 0.531), 1.0, ConstantDrift(0.2125));
|
||
let t_b = R::new(Gaussian::from_ms(15.568, 0.51), 1.0, ConstantDrift(0.2125));
|
||
|
||
let w = [vec![1.0], vec![1.0]];
|
||
let g = Game::ranked_with_arena(
|
||
vec![vec![t_a], vec![t_b]],
|
||
&[0.0, 1.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
|
||
assert_eq!(g.likelihoods[0][0], N_INF);
|
||
assert_eq!(g.likelihoods[1][0], N_INF);
|
||
}
|
||
|
||
#[test]
|
||
fn test_1vs1vs1() {
|
||
let teams = vec![
|
||
vec![R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
)],
|
||
vec![R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
)],
|
||
vec![R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
)],
|
||
];
|
||
|
||
let w = [vec![1.0], vec![1.0], vec![1.0]];
|
||
let g = Game::ranked_with_arena(
|
||
teams.clone(),
|
||
&[1.0, 2.0, 0.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
let a = p[0][0];
|
||
let b = p[1][0];
|
||
|
||
assert_ulps_eq!(a, Gaussian::from_ms(25.000000, 6.238469), epsilon = 1e-6);
|
||
assert_ulps_eq!(b, Gaussian::from_ms(31.311358, 6.698818), epsilon = 1e-6);
|
||
|
||
let w = [vec![1.0], vec![1.0], vec![1.0]];
|
||
let g = Game::ranked_with_arena(
|
||
teams.clone(),
|
||
&[2.0, 1.0, 0.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
let a = p[0][0];
|
||
let b = p[1][0];
|
||
|
||
assert_ulps_eq!(a, Gaussian::from_ms(31.311358, 6.698818), epsilon = 1e-6);
|
||
assert_ulps_eq!(b, Gaussian::from_ms(25.000000, 6.238469), epsilon = 1e-6);
|
||
|
||
let w = [vec![1.0], vec![1.0], vec![1.0]];
|
||
let g = Game::ranked_with_arena(
|
||
teams,
|
||
&[1.0, 2.0, 0.0],
|
||
&w,
|
||
0.5,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
let a = p[0][0];
|
||
let b = p[1][0];
|
||
let c = p[2][0];
|
||
|
||
// T1 ULP shift: mu rounds to 25.0 (was 24.999999) under natural-parameter storage.
|
||
assert_ulps_eq!(a, Gaussian::from_ms(25.0, 6.092561), epsilon = 1e-6);
|
||
assert_ulps_eq!(b, Gaussian::from_ms(33.379314, 6.483575), epsilon = 1e-6);
|
||
assert_ulps_eq!(c, Gaussian::from_ms(16.620685, 6.483575), epsilon = 1e-6);
|
||
}
|
||
|
||
#[test]
|
||
fn test_1vs1_draw() {
|
||
let t_a = R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
let t_b = R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
|
||
let w = [vec![1.0], vec![1.0]];
|
||
let g = Game::ranked_with_arena(
|
||
vec![vec![t_a], vec![t_b]],
|
||
&[0.0, 0.0],
|
||
&w,
|
||
0.25,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
let a = p[0][0];
|
||
let b = p[1][0];
|
||
|
||
// Two identical competitors drawing must land on their shared prior
|
||
// mean exactly, by symmetry. The reference transcription of 24.999999
|
||
// is that value rounded to six decimals; asserting it at epsilon 1e-6
|
||
// left no headroom. The root-free variance path now hits 25.0 exactly.
|
||
assert_ulps_eq!(a, Gaussian::from_ms(25.0, 6.469480), epsilon = 1e-6);
|
||
assert_ulps_eq!(b, Gaussian::from_ms(25.0, 6.469480), epsilon = 1e-6);
|
||
|
||
let t_a = R::new(
|
||
Gaussian::from_ms(25.0, 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
let t_b = R::new(
|
||
Gaussian::from_ms(29.0, 2.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
|
||
let w = [vec![1.0], vec![1.0]];
|
||
let g = Game::ranked_with_arena(
|
||
vec![vec![t_a], vec![t_b]],
|
||
&[0.0, 0.0],
|
||
&w,
|
||
0.25,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
let a = p[0][0];
|
||
let b = p[1][0];
|
||
|
||
assert_ulps_eq!(a, Gaussian::from_ms(25.736001, 2.709956), epsilon = 1e-6);
|
||
assert_ulps_eq!(b, Gaussian::from_ms(28.672888, 1.916471), epsilon = 1e-6);
|
||
}
|
||
|
||
#[test]
|
||
fn test_1vs1vs1_draw() {
|
||
let t_a = R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
let t_b = R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
let t_c = R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
|
||
let w = [vec![1.0], vec![1.0], vec![1.0]];
|
||
let g = Game::ranked_with_arena(
|
||
vec![vec![t_a], vec![t_b], vec![t_c]],
|
||
&[0.0, 0.0, 0.0],
|
||
&w,
|
||
0.25,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
let a = p[0][0];
|
||
let b = p[1][0];
|
||
let c = p[2][0];
|
||
|
||
// Goldens updated for natural-parameter storage: mu rounds to 25.0 (was 24.999999),
|
||
// sigma shifts by ~3e-7 ULPs (within 1e-6 of original). Both bounded differences.
|
||
assert_ulps_eq!(a, Gaussian::from_ms(25.0, 5.729069), epsilon = 1e-6);
|
||
assert_ulps_eq!(b, Gaussian::from_ms(25.0, 5.707424), epsilon = 1e-6);
|
||
assert_ulps_eq!(c, Gaussian::from_ms(25.0, 5.729069), epsilon = 1e-6);
|
||
|
||
let t_a = R::new(
|
||
Gaussian::from_ms(25.0, 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
let t_b = R::new(
|
||
Gaussian::from_ms(25.0, 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
let t_c = R::new(
|
||
Gaussian::from_ms(29.0, 2.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
|
||
let w = [vec![1.0], vec![1.0], vec![1.0]];
|
||
let g = Game::ranked_with_arena(
|
||
vec![vec![t_a], vec![t_b], vec![t_c]],
|
||
&[0.0, 0.0, 0.0],
|
||
&w,
|
||
0.25,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
let a = p[0][0];
|
||
let b = p[1][0];
|
||
let c = p[2][0];
|
||
|
||
assert_ulps_eq!(a, Gaussian::from_ms(25.488507, 2.638208), epsilon = 1e-6);
|
||
assert_ulps_eq!(b, Gaussian::from_ms(25.510671, 2.628751), epsilon = 1e-6);
|
||
assert_ulps_eq!(c, Gaussian::from_ms(28.555920, 1.885689), epsilon = 1e-6);
|
||
}
|
||
|
||
#[test]
|
||
fn test_2vs1vs2_mixed() {
|
||
let t_a = vec![
|
||
R::new(
|
||
Gaussian::from_ms(12.0, 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
),
|
||
R::new(
|
||
Gaussian::from_ms(18.0, 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
),
|
||
];
|
||
let t_b = vec![R::new(
|
||
Gaussian::from_ms(30.0, 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
)];
|
||
let t_c = vec![
|
||
R::new(
|
||
Gaussian::from_ms(14.0, 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
),
|
||
R::new(
|
||
Gaussian::from_ms(16., 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
),
|
||
];
|
||
|
||
let w = [vec![1.0, 1.0], vec![1.0], vec![1.0, 1.0]];
|
||
let g = Game::ranked_with_arena(
|
||
vec![t_a, t_b, t_c],
|
||
&[1.0, 0.0, 0.0],
|
||
&w,
|
||
0.25,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
assert_ulps_eq!(p[0][0], Gaussian::from_ms(13.051, 2.864), epsilon = 1e-3);
|
||
assert_ulps_eq!(p[0][1], Gaussian::from_ms(19.051, 2.864), epsilon = 1e-3);
|
||
assert_ulps_eq!(p[1][0], Gaussian::from_ms(29.292, 2.764), epsilon = 1e-3);
|
||
assert_ulps_eq!(p[2][0], Gaussian::from_ms(13.658, 2.813), epsilon = 1e-3);
|
||
assert_ulps_eq!(p[2][1], Gaussian::from_ms(15.658, 2.813), epsilon = 1e-3);
|
||
}
|
||
|
||
#[test]
|
||
fn test_1vs1_weighted() {
|
||
let w_a = vec![1.0];
|
||
let w_b = vec![2.0];
|
||
|
||
let t_a = vec![R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(0.0),
|
||
)];
|
||
let t_b = vec![R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(0.0),
|
||
)];
|
||
|
||
let w = [w_a, w_b];
|
||
let g = Game::ranked_with_arena(
|
||
vec![t_a.clone(), t_b.clone()],
|
||
&[1.0, 0.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
assert_ulps_eq!(
|
||
p[0][0],
|
||
Gaussian::from_ms(30.625173, 7.765472),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[1][0],
|
||
Gaussian::from_ms(13.749653, 5.733840),
|
||
epsilon = 1e-6
|
||
);
|
||
|
||
let w_a = vec![1.0];
|
||
let w_b = vec![0.7];
|
||
|
||
let w = [w_a, w_b];
|
||
let g = Game::ranked_with_arena(
|
||
vec![t_a.clone(), t_b.clone()],
|
||
&[1.0, 0.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
assert_ulps_eq!(
|
||
p[0][0],
|
||
Gaussian::from_ms(27.630080, 7.206676),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[1][0],
|
||
Gaussian::from_ms(23.158943, 7.801628),
|
||
epsilon = 1e-6
|
||
);
|
||
|
||
let w_a = vec![1.6];
|
||
let w_b = vec![0.7];
|
||
|
||
let w = [w_a, w_b];
|
||
let g = Game::ranked_with_arena(
|
||
vec![t_a, t_b],
|
||
&[1.0, 0.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
assert_ulps_eq!(
|
||
p[0][0],
|
||
Gaussian::from_ms(26.142438, 7.573088),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[1][0],
|
||
Gaussian::from_ms(24.500183, 8.193278),
|
||
epsilon = 1e-6
|
||
);
|
||
|
||
let w_a = vec![1.0];
|
||
let w_b = vec![0.0];
|
||
|
||
let t_a = vec![R::new(Gaussian::from_ms(2.0, 6.0), 1.0, ConstantDrift(0.0))];
|
||
let t_b = vec![R::new(Gaussian::from_ms(2.0, 6.0), 1.0, ConstantDrift(0.0))];
|
||
|
||
let w = [w_a, w_b];
|
||
let g = Game::ranked_with_arena(
|
||
vec![t_a, t_b],
|
||
&[1.0, 0.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
assert_ulps_eq!(
|
||
p[0][0],
|
||
Gaussian::from_ms(5.557067, 4.052826),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[1][0],
|
||
Gaussian::from_ms(2.000000, 6.000000),
|
||
epsilon = 1e-6
|
||
);
|
||
|
||
let w_a = vec![1.0];
|
||
let w_b = vec![-1.0];
|
||
|
||
let t_a = vec![R::new(Gaussian::from_ms(2.0, 6.0), 1.0, ConstantDrift(0.0))];
|
||
let t_b = vec![R::new(Gaussian::from_ms(2.0, 6.0), 1.0, ConstantDrift(0.0))];
|
||
|
||
let w = [w_a, w_b];
|
||
let g = Game::ranked_with_arena(
|
||
vec![t_a, t_b],
|
||
&[1.0, 0.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
assert_ulps_eq!(p[0][0], p[1][0], epsilon = 1e-6);
|
||
}
|
||
|
||
#[test]
|
||
fn diff_factor_dispatch_trunc_and_margin() {
|
||
use super::DiffFactor;
|
||
use crate::factor::{VarStore, margin::MarginFactor, trunc::TruncFactor};
|
||
|
||
let mut vars = VarStore::new();
|
||
let dt = vars.alloc(Gaussian::from_ms(0.0, 6.0));
|
||
let dm = vars.alloc(Gaussian::from_ms(0.0, 6.0));
|
||
|
||
let mut t = DiffFactor::Trunc(TruncFactor::new(dt, 0.0, false));
|
||
let mut m = DiffFactor::Margin(MarginFactor::new(dm, 5.0, 1.0));
|
||
|
||
let _ = t.propagate(&mut vars, 1.0);
|
||
let _ = m.propagate(&mut vars, 1.0);
|
||
|
||
// Smoke: both diffs got written; their msgs are non-N_INF.
|
||
assert!(t.msg().pi() > 0.0);
|
||
assert!(m.msg().pi() > 0.0);
|
||
assert_eq!(t.diff(), dt);
|
||
assert_eq!(m.diff(), dm);
|
||
}
|
||
|
||
#[test]
|
||
fn scored_path_sharper_when_margin_is_large() {
|
||
let prior = R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
let teams = vec![vec![prior], vec![prior]];
|
||
let result = vec![10.0, 0.0]; // a beat b by 10
|
||
let weights = [vec![1.0], vec![1.0]];
|
||
let mut arena = ScratchArena::new();
|
||
let g = Game::scored_with_arena(
|
||
teams,
|
||
&result,
|
||
&weights,
|
||
1.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut arena,
|
||
);
|
||
let p = g.posteriors();
|
||
let a = p[0][0];
|
||
let b = p[1][0];
|
||
assert!(
|
||
a.mu() > b.mu(),
|
||
"expected team a posterior mu > team b; got {} vs {}",
|
||
a.mu(),
|
||
b.mu()
|
||
);
|
||
|
||
// Tighter score_sigma should produce a stronger update.
|
||
let mut arena2 = ScratchArena::new();
|
||
let g_tight = Game::scored_with_arena(
|
||
vec![vec![prior], vec![prior]],
|
||
&result,
|
||
&weights,
|
||
0.1,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut arena2,
|
||
);
|
||
let p_tight = g_tight.posteriors();
|
||
let a_tight = p_tight[0][0];
|
||
assert!(
|
||
a_tight.mu() > a.mu(),
|
||
"expected tighter sigma to push posterior further; {} vs {}",
|
||
a_tight.mu(),
|
||
a.mu()
|
||
);
|
||
}
|
||
|
||
#[test]
|
||
fn game_scored_public_ctor() {
|
||
use crate::Outcome;
|
||
let prior = R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
let opts = GameOptions {
|
||
score_sigma: 1.0,
|
||
..GameOptions::default()
|
||
};
|
||
let g = Game::scored(&[&[prior], &[prior]], Outcome::scores([8.0, 2.0]), &opts).unwrap();
|
||
let p = g.posteriors();
|
||
assert!(p[0][0].mu() > p[1][0].mu());
|
||
}
|
||
|
||
#[test]
|
||
fn game_scored_rejects_ranked_outcome() {
|
||
let prior = R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
let err = Game::scored(
|
||
&[&[prior], &[prior]],
|
||
crate::Outcome::winner(0, 2),
|
||
&GameOptions::default(),
|
||
)
|
||
.unwrap_err();
|
||
assert!(matches!(
|
||
err,
|
||
crate::InferenceError::WrongOutcomeKind { .. }
|
||
));
|
||
}
|
||
|
||
#[test]
|
||
fn game_scored_rejects_zero_score_sigma() {
|
||
let prior = R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(25.0 / 300.0),
|
||
);
|
||
let opts = GameOptions {
|
||
score_sigma: 0.0,
|
||
..GameOptions::default()
|
||
};
|
||
let err = Game::scored(
|
||
&[&[prior], &[prior]],
|
||
crate::Outcome::scores([1.0, 0.0]),
|
||
&opts,
|
||
)
|
||
.unwrap_err();
|
||
assert!(matches!(
|
||
err,
|
||
crate::InferenceError::InvalidParameter {
|
||
name: "score_sigma",
|
||
..
|
||
}
|
||
));
|
||
}
|
||
|
||
#[test]
|
||
fn test_2vs2_weighted() {
|
||
let t_a = vec![
|
||
R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(0.0),
|
||
),
|
||
R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(0.0),
|
||
),
|
||
];
|
||
let w_a = vec![0.4, 0.8];
|
||
|
||
let t_b = vec![
|
||
R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(0.0),
|
||
),
|
||
R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(0.0),
|
||
),
|
||
];
|
||
let w_b = vec![0.9, 0.6];
|
||
|
||
let w = [w_a, w_b];
|
||
let g = Game::ranked_with_arena(
|
||
vec![t_a.clone(), t_b.clone()],
|
||
&[1.0, 0.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
assert_ulps_eq!(
|
||
p[0][0],
|
||
Gaussian::from_ms(27.539023, 8.129639),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[0][1],
|
||
Gaussian::from_ms(30.078046, 7.485372),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[1][0],
|
||
Gaussian::from_ms(19.287197, 7.243465),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[1][1],
|
||
Gaussian::from_ms(21.191465, 7.867608),
|
||
epsilon = 1e-6
|
||
);
|
||
|
||
let w_a = vec![1.3, 1.5];
|
||
let w_b = vec![0.7, 0.4];
|
||
|
||
let w = [w_a, w_b];
|
||
let g = Game::ranked_with_arena(
|
||
vec![t_a.clone(), t_b.clone()],
|
||
&[1.0, 0.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
assert_ulps_eq!(
|
||
p[0][0],
|
||
Gaussian::from_ms(25.190190, 8.220511),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[0][1],
|
||
Gaussian::from_ms(25.219450, 8.182783),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[1][0],
|
||
Gaussian::from_ms(24.897589, 8.300779),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[1][1],
|
||
Gaussian::from_ms(24.941479, 8.322717),
|
||
epsilon = 1e-6
|
||
);
|
||
|
||
let w_a = vec![1.6, 0.2];
|
||
let w_b = vec![0.7, 2.4];
|
||
|
||
let w = [w_a, w_b];
|
||
let g = Game::ranked_with_arena(
|
||
vec![t_a.clone(), t_b.clone()],
|
||
&[1.0, 0.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
assert_ulps_eq!(
|
||
p[0][0],
|
||
Gaussian::from_ms(31.674697, 7.501180),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[0][1],
|
||
Gaussian::from_ms(25.834337, 8.320970),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[1][0],
|
||
Gaussian::from_ms(22.079819, 8.180607),
|
||
epsilon = 1e-6
|
||
);
|
||
assert_ulps_eq!(
|
||
p[1][1],
|
||
Gaussian::from_ms(14.987953, 6.308469),
|
||
epsilon = 1e-6
|
||
);
|
||
|
||
let w = [vec![1.0, 1.0], vec![1.0]];
|
||
let g = Game::ranked_with_arena(
|
||
vec![
|
||
t_a.clone(),
|
||
vec![R::new(
|
||
Gaussian::from_ms(25.0, 25.0 / 3.0),
|
||
25.0 / 6.0,
|
||
ConstantDrift(0.0),
|
||
)],
|
||
],
|
||
&[1.0, 0.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let post_2vs1 = g.posteriors();
|
||
|
||
let w_a = vec![1.0, 1.0];
|
||
let w_b = vec![1.0, 0.0];
|
||
|
||
let w = [w_a, w_b];
|
||
let g = Game::ranked_with_arena(
|
||
vec![t_a, t_b.clone()],
|
||
&[1.0, 0.0],
|
||
&w,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut ScratchArena::new(),
|
||
);
|
||
let p = g.posteriors();
|
||
|
||
assert_ulps_eq!(p[0][0], post_2vs1[0][0], epsilon = 1e-6);
|
||
assert_ulps_eq!(p[0][1], post_2vs1[0][1], epsilon = 1e-6);
|
||
assert_ulps_eq!(p[1][0], post_2vs1[1][0], epsilon = 1e-6);
|
||
assert_ulps_eq!(p[1][1], t_b[1].prior, epsilon = 1e-6);
|
||
}
|
||
|
||
#[test]
|
||
fn run_chain_honours_max_iter_in_convergence_options() {
|
||
let players: Vec<R> = (0..4).map(|_| R::default()).collect();
|
||
let teams: Vec<Vec<_>> = players.iter().map(|p| vec![*p]).collect();
|
||
let result = vec![3.0, 2.0, 1.0, 0.0];
|
||
let weights = vec![vec![1.0]; 4];
|
||
|
||
// Capped at 1 iteration: cannot fully propagate down a 4-team chain.
|
||
let mut arena = ScratchArena::new();
|
||
let g_capped = Game::ranked_with_arena(
|
||
teams.clone(),
|
||
&result,
|
||
&weights,
|
||
0.0,
|
||
crate::ConvergenceOptions {
|
||
max_iter: 1,
|
||
..crate::ConvergenceOptions::default()
|
||
},
|
||
&mut arena,
|
||
);
|
||
let posteriors_capped = g_capped.posteriors();
|
||
|
||
// Same inputs, plenty of iterations: fully converged.
|
||
let mut arena = ScratchArena::new();
|
||
let g_full = Game::ranked_with_arena(
|
||
teams,
|
||
&result,
|
||
&weights,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut arena,
|
||
);
|
||
let posteriors_full = g_full.posteriors();
|
||
|
||
// The two posteriors should differ — capped did not converge.
|
||
let mut max_diff: f64 = 0.0;
|
||
for (team_capped, team_full) in posteriors_capped.iter().zip(posteriors_full.iter()) {
|
||
for (g_capped, g_full) in team_capped.iter().zip(team_full.iter()) {
|
||
max_diff = max_diff.max((g_capped.mu() - g_full.mu()).abs());
|
||
max_diff = max_diff.max((g_capped.sigma() - g_full.sigma()).abs());
|
||
}
|
||
}
|
||
assert!(
|
||
max_diff > 1e-6,
|
||
"max_iter=1 should differ from full convergence; max_diff={max_diff}"
|
||
);
|
||
}
|
||
|
||
#[test]
|
||
fn run_chain_with_damping_converges_to_same_posterior() {
|
||
let players: Vec<R> = (0..4).map(|_| R::default()).collect();
|
||
let teams: Vec<Vec<_>> = players.iter().map(|p| vec![*p]).collect();
|
||
let result = vec![3.0, 2.0, 1.0, 0.0];
|
||
let weights = vec![vec![1.0]; 4];
|
||
|
||
let mut arena = ScratchArena::new();
|
||
let g_undamped = Game::ranked_with_arena(
|
||
teams.clone(),
|
||
&result,
|
||
&weights,
|
||
0.0,
|
||
crate::ConvergenceOptions::default(),
|
||
&mut arena,
|
||
);
|
||
let posteriors_undamped = g_undamped.posteriors();
|
||
|
||
// alpha=0.5 with extra iterations: should reach the same fixed point.
|
||
let mut arena = ScratchArena::new();
|
||
let g_damped = Game::ranked_with_arena(
|
||
teams,
|
||
&result,
|
||
&weights,
|
||
0.0,
|
||
crate::ConvergenceOptions {
|
||
alpha: 0.5,
|
||
max_iter: 100,
|
||
..crate::ConvergenceOptions::default()
|
||
},
|
||
&mut arena,
|
||
);
|
||
let posteriors_damped = g_damped.posteriors();
|
||
|
||
let mut max_diff: f64 = 0.0;
|
||
for (team_u, team_d) in posteriors_undamped.iter().zip(posteriors_damped.iter()) {
|
||
for (g_u, g_d) in team_u.iter().zip(team_d.iter()) {
|
||
max_diff = max_diff.max((g_u.mu() - g_d.mu()).abs());
|
||
max_diff = max_diff.max((g_u.sigma() - g_d.sigma()).abs());
|
||
}
|
||
}
|
||
assert!(
|
||
max_diff < 1e-4,
|
||
"α=0.5 should reach the same fixed point as α=1.0; max_diff={max_diff}"
|
||
);
|
||
}
|
||
}
|