kdtree 0.8.1

K-dimensional tree in Rust for fast geospatial indexing and nearest neighbors lookup
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156

extern crate criterion;
extern crate kdtree;

use criterion::{BenchmarkId, Criterion, criterion_group, criterion_main};
use kdtree::KdTree;
use kdtree::distance::squared_euclidean;
use std::collections::BTreeSet;

fn deterministic_points(len: usize) -> (Vec<([f64; 3], f64)>, ([f64; 3], f64)) {
    fn next(state: &mut u64) -> f64 {
        *state = state.wrapping_mul(636_413_622_384_679_3005).wrapping_add(1);
        ((*state >> 11) as f64) / ((1u64 << 53) as f64)
    }

    let mut state = 0x1a2b_3c4d_5e6f_7788;
    let mut points = Vec::with_capacity(len);
    for _ in 0..len {
        let coords = [next(&mut state), next(&mut state), next(&mut state)];
        let value = next(&mut state);
        points.push((coords, value));
    }
    let point = ([next(&mut state), next(&mut state), next(&mut state)], next(&mut state));
    (points, point)
}

fn bench_add_to_kdtree_with_1k_3d_points(c: &mut Criterion) {
    let len = 1000usize;
    let (points, point) = deterministic_points(len);
    let mut kdtree = KdTree::with_capacity(3, 16);
    for point in points.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());
    });
}

fn bench_nearest_from_kdtree_with_1k_3d_points(c: &mut Criterion) {
    let len = 1000usize;
    let (points, point) = deterministic_points(len);
    let mut kdtree = KdTree::with_capacity(3, 16);
    for point in points.iter() {
        kdtree.add(&point.0, point.1).unwrap();
    }
    c.bench_function("bench_nearest_from_kdtree_with_1k_3d_points", |b| {
        b.iter(|| kdtree.nearest(&point.0, 8, &squared_euclidean).unwrap());
    });
}

fn bench_nearest_within_radius_from_kdtree_with_1k_3d_points(c: &mut Criterion) {
    let len = 1000usize;
    let (points, point) = deterministic_points(len);
    let mut kdtree = KdTree::with_capacity(3, 16);
    for point in points.iter() {
        kdtree.add(&point.0, point.1).unwrap();
    }
    c.bench_function("bench_nearest_within_radius_from_kdtree_with_1k_3d_points", |b| {
        b.iter(|| {
            kdtree
                .nearest_within_radius(&point.0, 8, Some(0.02), &squared_euclidean)
                .unwrap()
        });
    });
}

fn bench_nearest_within_radius_comparisons(c: &mut Criterion) {
    let len = 1000usize;
    let (points, point) = deterministic_points(len);
    let mut kdtree = KdTree::with_capacity(3, 16);
    for entry in points.iter() {
        kdtree.add(&entry.0, entry.1).unwrap();
    }
    let mut group = c.benchmark_group("nearest_within_radius_comparisons_1k_3d_points");
    let scenarios: &[(usize, f64)] = &[(4, 0.02), (8, 0.02), (8, 0.2)];
    for k in scenarios.iter().map(|(k, _)| *k).collect::<BTreeSet<_>>() {
        group.bench_with_input(BenchmarkId::new("nearest", format!("k{}", k)), &k, |b, &k| {
            b.iter(|| kdtree.nearest(&point.0, k, &squared_euclidean).unwrap());
        });
    }
    for &(k, radius) in scenarios {
        group.bench_with_input(
            BenchmarkId::new("nearest_within_radius", format!("k{}_r_{:.2}", k, radius)),
            &(k, radius),
            |b, &(k, radius)| {
                b.iter(|| {
                    kdtree
                        .nearest_within_radius(&point.0, k, Some(radius), &squared_euclidean)
                        .unwrap()
                });
            },
        );
    }
    group.finish();
}

fn bench_within_2k_data_01_radius(c: &mut Criterion) {
    let len = 2000usize;
    let (points, point) = deterministic_points(len);
    let mut kdtree = KdTree::with_capacity(3, 16);
    for point in points.iter() {
        kdtree.add(&point.0, point.1).unwrap();
    }
    c.bench_function("bench_within_2k_data_01_radius", |b| {
        b.iter(|| kdtree.within(&point.0, 0.1, &squared_euclidean).unwrap());
    });
}

fn bench_within_2k_data_02_radius(c: &mut Criterion) {
    let len = 2000usize;
    let (points, point) = deterministic_points(len);
    let mut kdtree = KdTree::with_capacity(3, 16);
    for point in points.iter() {
        kdtree.add(&point.0, point.1).unwrap();
    }
    c.bench_function("bench_within_2k_data_02_radius", |b| {
        b.iter(|| kdtree.within(&point.0, 0.2, &squared_euclidean).unwrap());
    });
}

fn bench_within_count_2k_data_01_radius(c: &mut Criterion) {
    let len = 2000usize;
    let (points, point) = deterministic_points(len);
    let mut kdtree = KdTree::with_capacity(3, 16);
    for point in points.iter() {
        kdtree.add(&point.0, point.1).unwrap();
    }
    c.bench_function("bench_within_count_2k_data_01_radius", |b| {
        b.iter(|| kdtree.within_count(&point.0, 0.1, &squared_euclidean).unwrap());
    });
}

fn bench_within_count_2k_data_02_radius(c: &mut Criterion) {
    let len = 2000usize;
    let (points, point) = deterministic_points(len);
    let mut kdtree = KdTree::with_capacity(3, 16);
    for point in points.iter() {
        kdtree.add(&point.0, point.1).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_nearest_within_radius_from_kdtree_with_1k_3d_points,
    bench_nearest_within_radius_comparisons,
    bench_within_2k_data_01_radius,
    bench_within_2k_data_02_radius,
    bench_within_count_2k_data_01_radius,
    bench_within_count_2k_data_02_radius,
);

criterion_main!(benches);