parry3d 0.26.0

3 dimensional collision detection library in 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
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192

use super::bvh_tree::{BvhBuildStrategy, BvhNodeIndex, BvhNodeWide};
use super::{Bvh, BvhNode, BvhWorkspace};
use crate::bounding_volume::{Aabb, BoundingVolume};
use crate::math::Real;

impl Bvh {
    /// Fully rebuilds this BVH using the given strategy.
    ///
    /// This rebuilds a BVH with the same leaves, but different intermediate nodes and depth using
    /// the specified building strategy.
    pub fn rebuild(&mut self, workspace: &mut BvhWorkspace, strategy: BvhBuildStrategy) {
        if self.nodes.len() < 2 {
            // Nothing to rebuild if the tree is empty or only contains the root.
            // This takes care of the case where we have a partial root too.
            return;
        }

        workspace.rebuild_leaves.clear();
        for node in self.nodes.iter() {
            if node.left.is_leaf() {
                workspace.rebuild_leaves.push(node.left);
            }
            if node.right.is_leaf() {
                workspace.rebuild_leaves.push(node.right);
            }
        }

        self.nodes.clear();
        self.parents.clear();
        self.nodes.push(BvhNodeWide::zeros());
        self.parents.push(BvhNodeIndex::default());

        match strategy {
            BvhBuildStrategy::Binned => self.rebuild_range_binned(0, &mut workspace.rebuild_leaves),
            BvhBuildStrategy::Ploc => self.rebuild_range_ploc(0, &mut workspace.rebuild_leaves),
        }
    }

    pub(crate) fn rebuild_range_binned(&mut self, target_node_id: u32, leaves: &mut [BvhNode]) {
        // PERF: calculate an optimal bin count dynamically based on the number of leaves to split?
        //       The paper suggests (4 + 2 * sqrt(num_leaves).floor()).min(16)
        const NUM_BINS: usize = 8;
        const BIN_EPSILON: Real = 1.0e-5;

        let mut bins = [BvhBin::default(); NUM_BINS];

        assert!(leaves.len() > 1);

        let centroid_aabb = Aabb::from_points(leaves.iter().map(|node| node.center()));
        let bins_axis = centroid_aabb.extents().max_position();
        let bins_range = [centroid_aabb.mins[bins_axis], centroid_aabb.maxs[bins_axis]];

        // Compute bins characteristics.
        let k1 = NUM_BINS as Real * (1.0 - BIN_EPSILON) / (bins_range[1] - bins_range[0]);
        let k0 = bins_range[0];
        for leaf in &*leaves {
            let bin_id = (k1 * (leaf.center()[bins_axis] - k0)) as usize;
            let bin = &mut bins[bin_id];
            bin.aabb.merge(&leaf.aabb());
            bin.leaf_count += 1;
        }

        // Select the best splitting plane (there are NUM_BINS - 1 splitting planes) based on SAH.
        let mut right_merges = bins;
        let mut right_acc = bins[NUM_BINS - 1];

        for i in 1..NUM_BINS - 1 {
            right_acc.aabb.merge(&right_merges[NUM_BINS - 1 - i].aabb);
            right_acc.leaf_count += &right_merges[NUM_BINS - 1 - i].leaf_count;
            right_merges[NUM_BINS - 1 - i] = right_acc;
        }

        let mut best_cost = Real::MAX;
        let mut best_plane = 0;
        let mut left_merge = bins[0];
        let mut best_leaf_count = bins[0].leaf_count;

        for i in 0..NUM_BINS - 1 {
            let right = &right_merges[i + 1];

            let cost = left_merge.aabb.volume() * left_merge.leaf_count as Real
                + right.aabb.volume() * right.leaf_count as Real;
            if cost < best_cost {
                best_cost = cost;
                best_plane = i;
                best_leaf_count = left_merge.leaf_count;
            }

            left_merge.aabb.merge(&bins[i + 1].aabb);
            left_merge.leaf_count += bins[i + 1].leaf_count;
        }

        // With the splitting plane selected, sort & split the leaves in place.
        let mut mid = best_leaf_count as usize;

        // In degenerate cases where all the node end up on the same bin,
        // just split the range in two.
        if mid == 0 || mid == leaves.len() {
            mid = leaves.len() / 2;
        } else {
            // Sort in-place.
            // TODO PERF: try with using teh leaves_tmp instead of in-place sorting.
            let bin = |leaves: &mut [BvhNode], id: usize| {
                let node = &leaves[id];
                (k1 * (node.center()[bins_axis] - k0)) as usize
            };

            let mut left_id = 0;
            let mut right_id = mid;

            'outer: while left_id != mid && right_id != leaves.len() {
                while bin(leaves, left_id) <= best_plane {
                    left_id += 1;

                    if left_id == mid {
                        break 'outer;
                    }
                }

                while bin(leaves, right_id) > best_plane {
                    right_id += 1;

                    if right_id == leaves.len() {
                        break 'outer;
                    }
                }

                leaves.swap(left_id, right_id);
                left_id += 1;
                right_id += 1;
            }
        }

        // Recurse.
        let (left_leaves, right_leaves) = leaves.split_at_mut(mid);

        assert!(!left_leaves.is_empty() && !right_leaves.is_empty());

        // Recurse.
        if left_leaves.len() == 1 {
            let target = &mut self.nodes[target_node_id as usize];
            target.left = left_leaves[0];

            if target.left.is_leaf() {
                self.leaf_node_indices[target.left.children as usize] =
                    BvhNodeIndex::left(target_node_id);
            } else {
                self.parents[target.left.children as usize] = BvhNodeIndex::left(target_node_id);
            }
        } else {
            let left_id = self.nodes.len() as u32;
            self.nodes.push(BvhNodeWide::zeros());
            self.parents.push(BvhNodeIndex::left(target_node_id));
            self.rebuild_range_binned(left_id, left_leaves);
            self.nodes[target_node_id as usize].left = self.nodes[left_id as usize].merged(left_id);
        }

        if right_leaves.len() == 1 {
            let target = &mut self.nodes[target_node_id as usize];
            target.right = right_leaves[0];

            if target.right.is_leaf() {
                self.leaf_node_indices[target.right.children as usize] =
                    BvhNodeIndex::right(target_node_id);
            } else {
                self.parents[target.right.children as usize] = BvhNodeIndex::right(target_node_id);
            }
        } else {
            let right_id = self.nodes.len() as u32;
            self.nodes.push(BvhNodeWide::zeros());
            self.parents.push(BvhNodeIndex::right(target_node_id));
            self.rebuild_range_binned(right_id, right_leaves);
            self.nodes[target_node_id as usize].right =
                self.nodes[right_id as usize].merged(right_id);
        }
    }
}

#[derive(Copy, Clone, Debug)]
struct BvhBin {
    aabb: Aabb,
    leaf_count: u32,
}

impl Default for BvhBin {
    fn default() -> Self {
        Self {
            aabb: Aabb::new_invalid(),
            leaf_count: 0,
        }
    }
}