spart 0.5.1

A collection of space partitioning tree data structures for Rust
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
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175

//! Property-based tests for RTree

use proptest::prelude::*;
use spart::geometry::{Cube, DistanceMetric, EuclideanDistance, Point2D, Point3D, Rectangle};
use spart::rtree::RTree;

prop_compose! {
    fn arb_point_2d()(x in -100.0..100.0, y in -100.0..100.0) -> (f64, f64) {
        (x, y)
    }
}

prop_compose! {
    fn arb_point_3d()(x in -100.0..100.0, y in -100.0..100.0, z in -100.0..100.0) -> (f64, f64, f64) {
        (x, y, z)
    }
}

prop_compose! {
    fn arb_rectangle()(x in -100.0..100.0, y in -100.0..100.0, width in 1.0..200.0, height in 1.0..200.0) -> Rectangle {
        Rectangle { x, y, width, height }
    }
}

prop_compose! {
    fn arb_cube()(x in -100.0..100.0, y in -100.0..100.0, z in -100.0..100.0, width in 1.0..200.0, height in 1.0..200.0, depth in 1.0..200.0) -> Cube {
        Cube { x, y, z, width, height, depth }
    }
}

fn points_2d_from_coords(coords: &[(f64, f64)]) -> Vec<Point2D<i32>> {
    coords
        .iter()
        .enumerate()
        .map(|(idx, (x, y))| Point2D::new(*x, *y, Some(idx as i32)))
        .collect()
}

fn points_3d_from_coords(coords: &[(f64, f64, f64)]) -> Vec<Point3D<i32>> {
    coords
        .iter()
        .enumerate()
        .map(|(idx, (x, y, z))| Point3D::new(*x, *y, *z, Some(idx as i32)))
        .collect()
}

proptest! {
    #[test]
    fn test_rtree_knn_finds_inserted_point_2d(
        coords in prop::collection::vec(arb_point_2d(), 1..30)
    ) {
        let points = points_2d_from_coords(&coords);
        let mut tree: RTree<Point2D<i32>> = RTree::new(4).unwrap();
        for point in &points {
            tree.insert(point.clone());
        }

        for point in &points {
            let results = tree.knn_search::<EuclideanDistance>(point, 1);
            prop_assert_eq!(results.len(), 1);
            let nearest = results[0];
            let dist = EuclideanDistance::distance_sq(point, nearest);
            prop_assert!(dist <= 1e-9);
        }
    }

    #[test]
    fn test_rtree_range_search_bbox_2d(
        coords in prop::collection::vec(arb_point_2d(), 1..40),
        query in arb_rectangle()
    ) {
        let points = points_2d_from_coords(&coords);
        let mut tree: RTree<Point2D<i32>> = RTree::new(4).unwrap();
        for point in &points {
            tree.insert(point.clone());
        }

        let results = tree.range_search_bbox(&query);
        for point in results {
            prop_assert!(query.contains(point));
        }
    }

    #[test]
    fn test_rtree_range_search_radius_2d(
        coords in prop::collection::vec(arb_point_2d(), 1..40),
        target_coords in arb_point_2d(),
        radius in 0.0..150.0
    ) {
        let points = points_2d_from_coords(&coords);
        let target = Point2D::new(target_coords.0, target_coords.1, Some(-1));
        let mut tree: RTree<Point2D<i32>> = RTree::new(4).unwrap();
        for point in &points {
            tree.insert(point.clone());
        }

        let results = tree.range_search::<EuclideanDistance>(&target, radius);
        for point in results {
            let dist = EuclideanDistance::distance_sq(&target, point);
            prop_assert!(dist <= radius * radius + 1e-9);
        }
    }

    #[test]
    fn test_rtree_delete_removes_point_2d(
        coords in prop::collection::vec(arb_point_2d(), 1..30)
    ) {
        let points = points_2d_from_coords(&coords);
        let mut tree: RTree<Point2D<i32>> = RTree::new(4).unwrap();
        for point in &points {
            tree.insert(point.clone());
        }

        let to_delete = points[0].clone();
        prop_assert!(tree.delete(&to_delete));
        let results = tree.range_search::<EuclideanDistance>(&to_delete, 0.0);
        prop_assert!(results.is_empty());
    }

    #[test]
    fn test_rtree_knn_finds_inserted_point_3d(
        coords in prop::collection::vec(arb_point_3d(), 1..25)
    ) {
        let points = points_3d_from_coords(&coords);
        let mut tree: RTree<Point3D<i32>> = RTree::new(4).unwrap();
        for point in &points {
            tree.insert(point.clone());
        }

        for point in &points {
            let results = tree.knn_search::<EuclideanDistance>(point, 1);
            prop_assert_eq!(results.len(), 1);
            let nearest = results[0];
            let dist = EuclideanDistance::distance_sq(point, nearest);
            prop_assert!(dist <= 1e-9);
        }
    }

    #[test]
    fn test_rtree_range_search_bbox_3d(
        coords in prop::collection::vec(arb_point_3d(), 1..30),
        query in arb_cube()
    ) {
        let points = points_3d_from_coords(&coords);
        let mut tree: RTree<Point3D<i32>> = RTree::new(4).unwrap();
        for point in &points {
            tree.insert(point.clone());
        }

        let results = tree.range_search_bbox(&query);
        for point in results {
            prop_assert!(query.contains(point));
        }
    }

    #[test]
    fn test_rtree_range_search_radius_3d(
        coords in prop::collection::vec(arb_point_3d(), 1..30),
        target_coords in arb_point_3d(),
        radius in 0.0..150.0
    ) {
        let points = points_3d_from_coords(&coords);
        let target = Point3D::new(target_coords.0, target_coords.1, target_coords.2, Some(-1));
        let mut tree: RTree<Point3D<i32>> = RTree::new(4).unwrap();
        for point in &points {
            tree.insert(point.clone());
        }

        let results = tree.range_search::<EuclideanDistance>(&target, radius);
        for point in results {
            let dist = EuclideanDistance::distance_sq(&target, point);
            prop_assert!(dist <= radius * radius + 1e-9);
        }
    }
}