T3: rayon-backed concurrency (opt-in) #2

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logaritmisk merged 13 commits from t3-concurrency into main 2026-04-24 13:01:01 +00:00
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@@ -262,17 +262,45 @@ impl<T: Time, D: Drift<T>, O: Observer<T>, K: Eq + Hash + Clone> History<T, D, O
/// Note: `key(idx)` is O(n) per lookup; this method is therefore O(n²) /// Note: `key(idx)` is O(n) per lookup; this method is therefore O(n²)
/// in the number of competitors. Acceptable for T2; T3 may optimize. /// in the number of competitors. Acceptable for T2; T3 may optimize.
pub fn learning_curves(&self) -> HashMap<K, Vec<(T, Gaussian)>> { pub fn learning_curves(&self) -> HashMap<K, Vec<(T, Gaussian)>> {
let mut data: HashMap<K, Vec<(T, Gaussian)>> = HashMap::new(); #[cfg(feature = "rayon")]
for slice in &self.time_slices { {
for (idx, skill) in slice.skills.iter() { use rayon::prelude::*;
if let Some(key) = self.keys.key(idx).cloned() {
data.entry(key) let per_slice: Vec<Vec<(Index, T, Gaussian)>> = self
.or_default() .time_slices
.push((slice.time, skill.posterior())); .par_iter()
.map(|ts| {
ts.skills
.iter()
.map(|(idx, sk)| (idx, ts.time, sk.posterior()))
.collect()
})
.collect();
let mut data: HashMap<K, Vec<(T, Gaussian)>> = HashMap::new();
for slice_contrib in per_slice {
for (idx, t, g) in slice_contrib {
if let Some(key) = self.keys.key(idx).cloned() {
data.entry(key).or_default().push((t, g));
}
} }
} }
data
}
#[cfg(not(feature = "rayon"))]
{
let mut data: HashMap<K, Vec<(T, Gaussian)>> = HashMap::new();
for slice in &self.time_slices {
for (idx, skill) in slice.skills.iter() {
if let Some(key) = self.keys.key(idx).cloned() {
data.entry(key)
.or_default()
.push((slice.time, skill.posterior()));
}
}
}
data
} }
data
} }
/// Skill estimate at the latest time slice the competitor appears in. /// Skill estimate at the latest time slice the competitor appears in.