fixes

Cargo.toml

@@ -18,7 +18,7 @@ num-traits = "0.2"
 thiserror = "1.0"
 
 [[bench]]
-name = "bench_critrion"
+name = "bench"
 harness = false
 
 [dependencies.serde]
@@ -30,4 +30,5 @@ version = "1.0"
 optional = true
 
 [features]
-serialize = ["serde", "serde_derive"]
+serialize = ["serde", "serde_derive"]
+

benches/bench.rs

@@ -1,18 +1,17 @@
-#![feature(test)]
 extern crate kdtree;
 extern crate rand;
-extern crate test;
 
+extern crate criterion;
+
+use criterion::{criterion_group, criterion_main, Criterion};
 use kdtree::distance::squared_euclidean;
 use kdtree::KdTree;
-use test::Bencher;
 
 fn rand_data() -> ([f64; 3], f64) {
     rand::random()
 }
 
-#[bench]
-fn bench_add_to_kdtree_with_1k_3d_points(b: &mut Bencher) {
+fn bench_add_to_kdtree_with_1k_3d_points(c: &mut Criterion) {
     let len = 1000usize;
     let point = rand_data();
     let mut points = vec![];
@@ -23,11 +22,12 @@ fn bench_add_to_kdtree_with_1k_3d_points(b: &mut Bencher) {
     for i in 0..points.len() {
         kdtree.add(&points[i].0, points[i].1).unwrap();
     }
-    b.iter(|| kdtree.add(&point.0, point.1).unwrap());
+    c.bench_function("bench_add_to_kdtree_with_1k_3d_points", |b| {
+        b.iter(|| kdtree.add(&point.0, point.1).unwrap());
+    });
 }
 
-#[bench]
-fn bench_nearest_from_kdtree_with_1k_3d_points(b: &mut Bencher) {
+fn bench_nearest_from_kdtree_with_1k_3d_points(c: &mut Criterion) {
     let len = 1000usize;
     let point = rand_data();
     let mut points = vec![];
@@ -38,11 +38,12 @@ fn bench_nearest_from_kdtree_with_1k_3d_points(b: &mut Bencher) {
     for i in 0..points.len() {
         kdtree.add(&points[i].0, points[i].1).unwrap();
     }
-    b.iter(|| kdtree.nearest(&point.0, 8, &squared_euclidean).unwrap());
+    c.bench_function("bench_nearest_from_kdtree_with_1k_3d_points", |b| {
+        b.iter(|| kdtree.nearest(&point.0, 8, &squared_euclidean).unwrap());
+    });
 }
 
-#[bench]
-fn bench_within_2k_data_01_radius(b: &mut Bencher) {
+fn bench_within_2k_data_01_radius(c: &mut Criterion) {
     let len = 2000usize;
     let point = rand_data();
     let mut points = vec![];
@@ -54,11 +55,12 @@ fn bench_within_2k_data_01_radius(b: &mut Bencher) {
         kdtree.add(&points[i].0, points[i].1).unwrap();
     }
 
-    b.iter(|| kdtree.within(&point.0, 0.1, &squared_euclidean).unwrap());
+    c.bench_function("bench_within_2k_data_01_radius", |b| {
+        b.iter(|| kdtree.within(&point.0, 0.1, &squared_euclidean).unwrap());
+    });
 }
 
-#[bench]
-fn bench_within_2k_data_02_radius(b: &mut Bencher) {
+fn bench_within_2k_data_02_radius(c: &mut Criterion) {
     let len = 2000usize;
     let point = rand_data();
     let mut points = vec![];
@@ -69,12 +71,12 @@ fn bench_within_2k_data_02_radius(b: &mut Bencher) {
     for i in 0..points.len() {
         kdtree.add(&points[i].0, points[i].1).unwrap();
     }
-
-    b.iter(|| kdtree.within(&point.0, 0.2, &squared_euclidean).unwrap());
+    c.bench_function("bench_within_2k_data_02_radius", |b| {
+        b.iter(|| kdtree.within(&point.0, 0.2, &squared_euclidean).unwrap());
+    });
 }
 
-#[bench]
-fn bench_within_unsorted_2k_data_01_radius(b: &mut Bencher) {
+fn bench_within_unsorted_2k_data_01_radius(c: &mut Criterion) {
     let len = 2000usize;
     let point = rand_data();
     let mut points = vec![];
@@ -85,12 +87,12 @@ fn bench_within_unsorted_2k_data_01_radius(b: &mut Bencher) {
     for i in 0..points.len() {
         kdtree.add(&points[i].0, points[i].1).unwrap();
     }
-
-    b.iter(|| kdtree.within_unsorted(&point.0, 0.1, &squared_euclidean).unwrap());
+    c.bench_function("bench_within_unsorted_2k_data_01_radius", |b| {
+        b.iter(|| kdtree.within_unsorted(&point.0, 0.1, &squared_euclidean).unwrap());
+    });
 }
 
-#[bench]
-fn bench_within_unsorted_2k_data_02_radius(b: &mut Bencher) {
+fn bench_within_unsorted_2k_data_02_radius(c: &mut Criterion) {
     let len = 2000usize;
     let point = rand_data();
     let mut points = vec![];
@@ -101,12 +103,12 @@ fn bench_within_unsorted_2k_data_02_radius(b: &mut Bencher) {
     for i in 0..points.len() {
         kdtree.add(&points[i].0, points[i].1).unwrap();
     }
-
-    b.iter(|| kdtree.within_unsorted(&point.0, 0.2, &squared_euclidean).unwrap());
+    c.bench_function("bench_within_unsorted_2k_data_02_radius", |b| {
+        b.iter(|| kdtree.within_unsorted(&point.0, 0.2, &squared_euclidean).unwrap());
+    });
 }
 
-#[bench]
-fn bench_within_count_2k_data_01_radius(b: &mut Bencher) {
+fn bench_within_count_2k_data_01_radius(c: &mut Criterion) {
     let len = 2000usize;
     let point = rand_data();
     let mut points = vec![];
@@ -117,12 +119,12 @@ fn bench_within_count_2k_data_01_radius(b: &mut Bencher) {
     for i in 0..points.len() {
         kdtree.add(&points[i].0, points[i].1).unwrap();
     }
-
-    b.iter(|| kdtree.within_count(&point.0, 0.1, &squared_euclidean).unwrap());
+    c.bench_function("bench_within_count_2k_data_01_radius", |b| {
+        b.iter(|| kdtree.within_count(&point.0, 0.1, &squared_euclidean).unwrap());
+    });
 }
 
-#[bench]
-fn bench_within_count_2k_data_02_radius(b: &mut Bencher) {
+fn bench_within_count_2k_data_02_radius(c: &mut Criterion) {
     let len = 2000usize;
     let point = rand_data();
     let mut points = vec![];
@@ -133,6 +135,21 @@ fn bench_within_count_2k_data_02_radius(b: &mut Bencher) {
     for i in 0..points.len() {
         kdtree.add(&points[i].0, points[i].1).unwrap();
     }
-
-    b.iter(|| kdtree.within_count(&point.0, 0.2, &squared_euclidean).unwrap());
+    c.bench_function("bench_within_count_2k_data_02_radius", |b| {
+        b.iter(|| kdtree.within_count(&point.0, 0.2, &squared_euclidean).unwrap());
+    });
 }
+
+criterion_group!(
+    benches,
+    bench_add_to_kdtree_with_1k_3d_points,
+    bench_nearest_from_kdtree_with_1k_3d_points,
+    bench_within_2k_data_01_radius,
+    bench_within_2k_data_02_radius,
+    bench_within_unsorted_2k_data_01_radius,
+    bench_within_unsorted_2k_data_02_radius,
+    bench_within_count_2k_data_01_radius,
+    bench_within_count_2k_data_02_radius,
+);
+
+criterion_main!(benches);