Keep track of candidate order using BinaryHeap

src/lib.rs

@@ -1,4 +1,5 @@
 use std::cmp::{max, min, Ordering, Reverse};
+use std::collections::BinaryHeap;
 use std::hash::Hash;
 use std::ops::Index;
 
@@ -316,7 +317,7 @@ pub struct Search {
     /// Nodes visited so far (`v` in the paper)
     visited: HashSet<PointId>,
     /// Candidates for further inspection (`C` in the paper)
-    candidates: Vec<Candidate>,
+    candidates: BinaryHeap<Reverse<Candidate>>,
     /// Nearest neighbors found so far (`W` in the paper)
     nearest: Vec<Candidate>,
     /// Maximum number of nearest neighbors to retain (`ef` in the paper)
@@ -364,7 +365,7 @@ impl Search {
         }
 
         let new = Candidate { distance, pid };
-        self.candidates.push(new);
+        self.candidates.push(Reverse(new));
         self.nearest.push(new);
         self.furthest = max(self.furthest, distance);
     }
@@ -379,8 +380,12 @@ impl Search {
     fn cull(&mut self) {
         self.nearest.truncate(self.ef); // Limit size of the set of nearest neighbors
         self.furthest = self.nearest.last().unwrap().distance;
+
         self.candidates.clear();
-        self.candidates.extend(&self.nearest);
+        for &candidate in self.nearest.iter() {
+            self.candidates.push(Reverse(candidate));
+        }
+
         self.visited.clear();
         self.visited.extend(self.nearest.iter().map(|c| c.pid));
     }
@@ -390,7 +395,7 @@ impl Default for Search {
     fn default() -> Self {
         Self {
             visited: HashSet::new(),
-            candidates: Vec::new(),
+            candidates: BinaryHeap::new(),
             nearest: Vec::new(),
             ef: 1,
             furthest: OrderedFloat::from(f32::INFINITY),
@@ -486,9 +491,9 @@ trait Layer {
     /// representation matching the zero layer even when we're referring to a higher layer. In that
     /// case, we use `links` to constrain the number of per-candidate links we consider for search.
     fn search<P: Point>(&self, point: &P, search: &mut Search, points: &[P], links: usize) {
-        while let Some(candidate) = search.candidates.pop() {
+        while let Some(Reverse(candidate)) = search.candidates.pop() {
             if candidate.distance > search.furthest {
-                continue;
+                break;
             }
 
             for pid in self.nearest_iter(candidate.pid).take(links) {