Avoid recomputing the squared-distance in the implementation of neare…

…st_neighbors.

rstar/src/algorithm/nearest_neighbor.rs

@@ -286,26 +286,25 @@ pub fn nearest_neighbors<T>(
 where
     T: PointDistance,
 {
-    let mut nearest_neighbors = NearestNeighborIterator::new(node, query_point.clone());
+    let mut nearest_neighbors = NearestNeighborDistance2Iterator::new(node, query_point.clone());
 
-    let first_nearest_neighbor = match nearest_neighbors.next() {
-        None => return vec![], // If we have an empty tree, just return an empty vector.
-        Some(nn) => nn,
+    let (first, first_distance_2) = match nearest_neighbors.next() {
+        Some(item) => item,
+        // If we have an empty tree, just return an empty vector.
+        None => return Vec::new(),
     };
 
     // The result will at least contain the first nearest neighbor.
-    let mut result = vec![first_nearest_neighbor];
-
-    // We compute the distance to the first nearest neighbor, and use
-    // that distance to filter out the rest of the nearest neighbors that are farther
-    // than this first neighbor.
-    let distance = first_nearest_neighbor.envelope().distance_2(&query_point);
-    nearest_neighbors
-        .take_while(|nearest_neighbor| {
-            let next_distance = nearest_neighbor.envelope().distance_2(&query_point);
-            next_distance == distance
-        })
-        .for_each(|nearest_neighbor| result.push(nearest_neighbor));
+    let mut result = vec![first];
+
+    // Use the distance to the first nearest neighbor
+    // to filter out the rest of the nearest neighbors
+    // that are farther than this first neighbor.
+    result.extend(
+        nearest_neighbors
+            .take_while(|(_, next_distance_2)| next_distance_2 == &first_distance_2)
+            .map(|(next, _)| next),
+    );
 
     result
 }