Fix clippy warnings

src/algorithm/neighbour/cover_tree.rs

@@ -117,7 +117,7 @@ impl<T: Debug + PartialEq, F: RealNumber, D: Distance<T, F>> CoverTree<T, F, D>
         }
 
         let e = self.get_data_value(self.root.idx);
-        let mut d = self.distance.distance(&e, p);
+        let mut d = self.distance.distance(e, p);
 
         let mut current_cover_set: Vec<(F, &Node<F>)> = Vec::new();
         let mut zero_set: Vec<(F, &Node<F>)> = Vec::new();
@@ -175,7 +175,7 @@ impl<T: Debug + PartialEq, F: RealNumber, D: Distance<T, F>> CoverTree<T, F, D>
             if ds.0 <= upper_bound {
                 let v = self.get_data_value(ds.1.idx);
                 if !self.identical_excluded || v != p {
-                    neighbors.push((ds.1.idx, ds.0, &v));
+                    neighbors.push((ds.1.idx, ds.0, v));
                 }
             }
         }
@@ -200,7 +200,7 @@ impl<T: Debug + PartialEq, F: RealNumber, D: Distance<T, F>> CoverTree<T, F, D>
         let mut zero_set: Vec<(F, &Node<F>)> = Vec::new();
 
         let e = self.get_data_value(self.root.idx);
-        let mut d = self.distance.distance(&e, p);
+        let mut d = self.distance.distance(e, p);
         current_cover_set.push((d, &self.root));
 
         while !current_cover_set.is_empty() {
@@ -230,7 +230,7 @@ impl<T: Debug + PartialEq, F: RealNumber, D: Distance<T, F>> CoverTree<T, F, D>
         for ds in zero_set {
             let v = self.get_data_value(ds.1.idx);
             if !self.identical_excluded || v != p {
-                neighbors.push((ds.1.idx, ds.0, &v));
+                neighbors.push((ds.1.idx, ds.0, v));
             }
         }
 
@@ -287,7 +287,7 @@ impl<T: Debug + PartialEq, F: RealNumber, D: Distance<T, F>> CoverTree<T, F, D>
         if point_set.is_empty() {
             self.new_leaf(p)
         } else {
-            let max_dist = self.max(&point_set);
+            let max_dist = self.max(point_set);
             let next_scale = (max_scale - 1).min(self.get_scale(max_dist));
             if next_scale == std::i64::MIN {
                 let mut children: Vec<Node<F>> = Vec::new();

src/algorithm/neighbour/linear_search.rs

@@ -74,7 +74,7 @@ impl<T, F: RealNumber, D: Distance<T, F>> LinearKNNSearch<T, F, D> {
         }
 
         for i in 0..self.data.len() {
-            let d = self.distance.distance(&from, &self.data[i]);
+            let d = self.distance.distance(from, &self.data[i]);
             let datum = heap.peek_mut();
             if d < datum.distance {
                 datum.distance = d;
@@ -104,7 +104,7 @@ impl<T, F: RealNumber, D: Distance<T, F>> LinearKNNSearch<T, F, D> {
         let mut neighbors: Vec<(usize, F, &T)> = Vec::new();
 
         for i in 0..self.data.len() {
-            let d = self.distance.distance(&from, &self.data[i]);
+            let d = self.distance.distance(from, &self.data[i]);
 
             if d <= radius {
                 neighbors.push((i, d, &self.data[i]));

src/algorithm/sort/heap_select.rs

@@ -53,8 +53,7 @@ impl<'a, T: PartialOrd + Debug> HeapSelection<T> {
         if self.sorted {
             &self.heap[0]
         } else {
-            &self
-                .heap
+            self.heap
                 .iter()
                 .max_by(|a, b| a.partial_cmp(b).unwrap())
                 .unwrap()