From 2027591d361f45223b521552aedb1ff31a7f1b4a Mon Sep 17 00:00:00 2001
From: Andrey Tkachenko <andreytkachenko64@gmail.com>
Date: Wed, 12 Dec 2018 17:05:43 +0400
Subject: [PATCH] make search point sent by value

---
 src/kdtree/mod.rs          | 12 ++++++------
 tests/integration_tests.rs |  2 +-
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/src/kdtree/mod.rs b/src/kdtree/mod.rs
index 3d0dcb0..5c08fd1 100644
--- a/src/kdtree/mod.rs
+++ b/src/kdtree/mod.rs
@@ -22,20 +22,20 @@ pub trait KdTreePoint: Copy + PartialEq {
     }
 }
 
-pub struct NearestNeighboursIter<'a, 'b, T> {
+pub struct NearestNeighboursIter<'a, T> {
     range: f64,
     kdtree: &'a KdTree<T>,
-    ref_node: &'b T,
+    ref_node: T,
     node_stack: Vec<usize>,
 }
 
-impl<'a, 'b, T> Iterator for NearestNeighboursIter<'a, 'b, T>
+impl<'a, T> Iterator for NearestNeighboursIter<'a, T>
     where T: KdTreePoint
 {
     type Item = (f64, &'a T);
 
     fn next(&mut self) -> Option<Self::Item> {
-        let p = self.ref_node;
+        let p = &self.ref_node;
 
         loop {
             let node_idx = self.node_stack.pop()?;
@@ -130,13 +130,13 @@ impl<KP: KdTreePoint> KdTree<KP> {
         (best_distance, &self.nodes[nearest_neighbor].point)
     }
 
-    pub fn nearest_search_dist<'a, 'b>(&'a self, node: &'b KP, dist: f64) -> NearestNeighboursIter<'a, 'b, KP> {
+    pub fn nearest_search_dist(&self, node: KP, dist: f64) -> NearestNeighboursIter<'_, KP> {
         let mut node_stack = Vec::with_capacity(16);
         node_stack.push(0);
 
         NearestNeighboursIter {
             range: dist,
-            kdtree: &self,
+            kdtree: self,
             ref_node: node,
             node_stack,
         }
diff --git a/tests/integration_tests.rs b/tests/integration_tests.rs
index 4154015..844be6f 100644
--- a/tests/integration_tests.rs
+++ b/tests/integration_tests.rs
@@ -120,7 +120,7 @@ fn test_neighbour_search_with_distance() {
         let p = Point3WithId::new(0i32, gen_random(), gen_random(), gen_random());
 
         let mut found_by_linear_search = find_neigbours_with_linear_search(&points, p, dist * dist);
-        let mut point_found_by_kdtree: Vec<_> = tree.nearest_search_dist(&p, dist * dist).collect();
+        let mut point_found_by_kdtree: Vec<_> = tree.nearest_search_dist(p, dist * dist).collect();
 
         assert_eq!(found_by_linear_search.len(), point_found_by_kdtree.len());