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feat: take sparsity into account in Voxels::combine_voxel_states #392

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Merged
sebcrozet merged 1 commit into from
Nov 5, 2025
Merged

feat: take sparsity into account in Voxels::combine_voxel_states #392

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107 changes: 58 additions & 49 deletions src/shape/voxels/voxels_neighborhood.rs
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
use super::VoxelsChunk;
use crate::math::{Point, Vector, DIM};
use crate::math::{Point, Real, Vector, DIM};
use crate::shape::{VoxelState, Voxels};

impl Voxels {
Expand Down Expand Up @@ -139,55 +139,64 @@ impl Voxels {
/// will have coordinates `key + origin_shift` on `self`.
pub fn combine_voxel_states(&mut self, other: &mut Self, origin_shift: Vector<i32>) {
let one = Vector::repeat(1);

// Intersect the domains + 1 cell.
let [my_domain_mins, my_domain_maxs] = self.domain();
let [other_domain_mins, other_domain_maxs] = other.domain();
let d0 = [my_domain_mins - one, my_domain_maxs + one * 2];
let d1 = [
other_domain_mins - one + origin_shift,
other_domain_maxs + one * 2 + origin_shift,
];

let d01 = [d0[0].sup(&d1[0]), d0[1].inf(&d1[1])];
// Iterate on the domain intersection. If the voxel exists (and is non-empty) on both shapes, we
// simply need to combine their bitmasks. If it doesn’t exist on both shapes, we need to
// actually check the neighbors.
//
// The `domain` is expressed in the grid coordinate space of `self`.
for i in d01[0].x..d01[1].x {
for j in d01[0].y..d01[1].y {
#[cfg(feature = "dim2")]
let k_range = 0..1;
#[cfg(feature = "dim3")]
let k_range = d01[0].z..d01[1].z;
for _k in k_range {
#[cfg(feature = "dim2")]
let key0 = Point::new(i, j);
#[cfg(feature = "dim3")]
let key0 = Point::new(i, j, _k);
let key1 = key0 - origin_shift;
let vox0 = self
.linear_index(key0)
.map(|id| &mut self.chunks[id.chunk_id].states[id.id_in_chunk])
.filter(|state| !state.is_empty());
let vox1 = other
.linear_index(key1)
.map(|id| &mut other.chunks[id.chunk_id].states[id.id_in_chunk])
.filter(|state| !state.is_empty());

match (vox0, vox1) {
(Some(vox0), Some(vox1)) => {
vox0.0 |= vox1.0;
vox1.0 |= vox0.0;
}
(Some(vox0), None) => {
vox0.0 |= other.compute_voxel_neighborhood_bits(key1).0;
}
(None, Some(vox1)) => {
vox1.0 |= self.compute_voxel_neighborhood_bits(key0).0;
let origin_shift_worldspace = origin_shift.cast::<Real>().component_mul(&self.voxel_size);

for chunk_key in &self.chunk_keys {
let mut aabb = VoxelsChunk::aabb(chunk_key, &self.voxel_size);
// Enlarge by one-half voxel so we detect cases where we also detect neighbor chunks from `other`.
aabb.mins -= self.voxel_size / 2.0;
aabb.maxs += self.voxel_size / 2.0;
// Shift to the local coordinate system of `other`.
let shifted_aabb = aabb.translated(&-origin_shift_worldspace);

if other.chunk_bvh.intersect_aabb(&shifted_aabb).any(|_| true) {
// Check the voxels from this chunk against the other voxels shape.

// Iterate on the domain intersection. If the voxel exists (and is non-empty) on both shapes, we
// simply need to combine their bitmasks. If it doesn’t exist on both shapes, we need to
// actually check the neighbors.
//
// The `domain` is expressed in the grid coordinate space of `self`.
let mut domain = VoxelsChunk::keys_bounds(chunk_key);
// Enlarge the domain by one voxel so that voxels from `other` but not existing in `self` are updated too.
domain[0] -= one;
domain[1] += one;

for i in domain[0].x..domain[1].x {
for j in domain[0].y..domain[1].y {
#[cfg(feature = "dim2")]
let k_range = 0..1;
#[cfg(feature = "dim3")]
let k_range = domain[0].z..domain[1].z;
for _k in k_range {
#[cfg(feature = "dim2")]
let key0 = Point::new(i, j);
#[cfg(feature = "dim3")]
let key0 = Point::new(i, j, _k);
let key1 = key0 - origin_shift;
let vox0 = self
.linear_index(key0)
.map(|id| &mut self.chunks[id.chunk_id].states[id.id_in_chunk])
.filter(|state| !state.is_empty());
let vox1 = other
.linear_index(key1)
.map(|id| &mut other.chunks[id.chunk_id].states[id.id_in_chunk])
.filter(|state| !state.is_empty());

match (vox0, vox1) {
(Some(vox0), Some(vox1)) => {
vox0.0 |= vox1.0;
vox1.0 |= vox0.0;
}
(Some(vox0), None) => {
vox0.0 |= other.compute_voxel_neighborhood_bits(key1).0;
}
(None, Some(vox1)) => {
vox1.0 |= self.compute_voxel_neighborhood_bits(key0).0;
}
(None, None) => { /* Nothing to adjust. */ }
}
}
(None, None) => { /* Nothing to adjust. */ }
}
}
}
Expand Down