oxihuman-mesh 0.2.1

Mesh processing, topology, and geometry algorithms for OxiHuman
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
193
194

#![allow(dead_code)]
//! Compute per-face and per-mesh centroids.

/// Per-face centroid result.
#[allow(dead_code)]
#[derive(Debug, Clone, PartialEq)]
pub struct FaceCentroidResult {
    pub x: f32,
    pub y: f32,
    pub z: f32,
}

/// Compute the centroid of a single triangle face.
#[allow(dead_code)]
pub fn mc_face_centroid(a: [f32; 3], b: [f32; 3], c: [f32; 3]) -> [f32; 3] {
    [
        (a[0] + b[0] + c[0]) / 3.0,
        (a[1] + b[1] + c[1]) / 3.0,
        (a[2] + b[2] + c[2]) / 3.0,
    ]
}

/// Compute the centroid of an entire mesh (average of all vertex positions).
#[allow(dead_code)]
pub fn mc_mesh_centroid(positions: &[[f32; 3]]) -> [f32; 3] {
    if positions.is_empty() {
        return [0.0; 3];
    }
    let n = positions.len() as f32;
    let mut sum = [0.0f32; 3];
    for p in positions {
        sum[0] += p[0];
        sum[1] += p[1];
        sum[2] += p[2];
    }
    [sum[0] / n, sum[1] / n, sum[2] / n]
}

/// Compute a weighted centroid given positions and weights.
#[allow(dead_code)]
pub fn weighted_centroid(positions: &[[f32; 3]], weights: &[f32]) -> [f32; 3] {
    if positions.is_empty() || weights.is_empty() {
        return [0.0; 3];
    }
    let len = positions.len().min(weights.len());
    let mut sum = [0.0f32; 3];
    let mut w_sum = 0.0f32;
    for i in 0..len {
        sum[0] += positions[i][0] * weights[i];
        sum[1] += positions[i][1] * weights[i];
        sum[2] += positions[i][2] * weights[i];
        w_sum += weights[i];
    }
    if w_sum.abs() < 1e-12 {
        return [0.0; 3];
    }
    [sum[0] / w_sum, sum[1] / w_sum, sum[2] / w_sum]
}

/// Compute centroid of selected vertices by index.
#[allow(dead_code)]
pub fn centroid_of_selection(positions: &[[f32; 3]], indices: &[usize]) -> [f32; 3] {
    if indices.is_empty() {
        return [0.0; 3];
    }
    let mut sum = [0.0f32; 3];
    let mut count = 0u32;
    for &i in indices {
        if i < positions.len() {
            sum[0] += positions[i][0];
            sum[1] += positions[i][1];
            sum[2] += positions[i][2];
            count += 1;
        }
    }
    if count == 0 {
        return [0.0; 3];
    }
    let n = count as f32;
    [sum[0] / n, sum[1] / n, sum[2] / n]
}

/// Euclidean distance between two centroids.
#[allow(dead_code)]
pub fn centroid_distance(a: [f32; 3], b: [f32; 3]) -> f32 {
    let dx = a[0] - b[0];
    let dy = a[1] - b[1];
    let dz = a[2] - b[2];
    (dx * dx + dy * dy + dz * dz).sqrt()
}

/// Convert a centroid to a flat array (identity, for API consistency).
#[allow(dead_code)]
pub fn centroid_to_array(c: [f32; 3]) -> [f32; 3] {
    c
}

/// Compute a cloud of face centroids for all faces.
#[allow(dead_code)]
pub fn centroid_cloud(
    positions: &[[f32; 3]],
    indices: &[[u32; 3]],
) -> Vec<[f32; 3]> {
    indices
        .iter()
        .map(|tri| {
            let a = positions[tri[0] as usize];
            let b = positions[tri[1] as usize];
            let c = positions[tri[2] as usize];
            mc_face_centroid(a, b, c)
        })
        .collect()
}

/// Count the number of centroids that would be produced.
#[allow(dead_code)]
pub fn centroid_count(indices: &[[u32; 3]]) -> usize {
    indices.len()
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_face_centroid_basic() {
        let c = mc_face_centroid([0.0, 0.0, 0.0], [3.0, 0.0, 0.0], [0.0, 3.0, 0.0]);
        assert!((c[0] - 1.0).abs() < 1e-6);
        assert!((c[1] - 1.0).abs() < 1e-6);
        assert!((c[2]).abs() < 1e-6);
    }

    #[test]
    fn test_mesh_centroid_basic() {
        let positions = vec![[1.0, 2.0, 3.0], [3.0, 4.0, 5.0]];
        let c = mc_mesh_centroid(&positions);
        assert!((c[0] - 2.0).abs() < 1e-6);
        assert!((c[1] - 3.0).abs() < 1e-6);
        assert!((c[2] - 4.0).abs() < 1e-6);
    }

    #[test]
    fn test_mesh_centroid_empty() {
        let c = mc_mesh_centroid(&[]);
        assert_eq!(c, [0.0, 0.0, 0.0]);
    }

    #[test]
    fn test_weighted_centroid() {
        let positions = vec![[0.0, 0.0, 0.0], [2.0, 0.0, 0.0]];
        let weights = vec![1.0, 3.0];
        let c = weighted_centroid(&positions, &weights);
        assert!((c[0] - 1.5).abs() < 1e-6);
    }

    #[test]
    fn test_weighted_centroid_zero_weight() {
        let c = weighted_centroid(&[[1.0, 2.0, 3.0]], &[0.0]);
        assert_eq!(c, [0.0, 0.0, 0.0]);
    }

    #[test]
    fn test_centroid_of_selection() {
        let positions = vec![[0.0, 0.0, 0.0], [2.0, 4.0, 6.0], [4.0, 8.0, 12.0]];
        let c = centroid_of_selection(&positions, &[0, 2]);
        assert!((c[0] - 2.0).abs() < 1e-6);
    }

    #[test]
    fn test_centroid_distance() {
        let d = centroid_distance([0.0, 0.0, 0.0], [3.0, 4.0, 0.0]);
        assert!((d - 5.0).abs() < 1e-6);
    }

    #[test]
    fn test_centroid_to_array() {
        assert_eq!(centroid_to_array([1.0, 2.0, 3.0]), [1.0, 2.0, 3.0]);
    }

    #[test]
    fn test_centroid_cloud() {
        let positions = vec![[0.0, 0.0, 0.0], [3.0, 0.0, 0.0], [0.0, 3.0, 0.0]];
        let indices = vec![[0u32, 1, 2]];
        let cloud = centroid_cloud(&positions, &indices);
        assert_eq!(cloud.len(), 1);
        assert!((cloud[0][0] - 1.0).abs() < 1e-6);
    }

    #[test]
    fn test_centroid_count() {
        let indices = vec![[0u32, 1, 2], [1, 2, 3]];
        assert_eq!(centroid_count(&indices), 2);
    }
}