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https://gitlab.com/veloren/veloren.git
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1af4a04231
This reverts merge request !2172
109 lines
4.3 KiB
Rust
109 lines
4.3 KiB
Rust
use vek::*;
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#[derive(Debug)]
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pub struct SpatialGrid {
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// Uses two scales of grids so that we can have a hard limit on how far to search in the
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// smaller grid
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grid: hashbrown::HashMap<Vec2<i32>, Vec<specs::Entity>>,
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large_grid: hashbrown::HashMap<Vec2<i32>, Vec<specs::Entity>>,
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// Log base 2 of the cell size of the spatial grid
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lg2_cell_size: usize,
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// Log base 2 of the cell size of the large spatial grid
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lg2_large_cell_size: usize,
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// Entities with a radius over this value are store in the coarser large_grid
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// This is the amount of buffer space we need to add when finding the intersections with cells
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// in the regular grid
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radius_cutoff: u32,
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// Stores the largest radius of the entities in the large_grid
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// This is the amount of buffer space we need to add when finding the intersections with cells
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// in the larger grid
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// note: could explore some distance field type thing for querying whether there are large
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// entities nearby that necessitate expanding the cells searched for collision (and querying
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// how much it needs to be expanded)
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// TODO: log this to metrics?
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largest_large_radius: u32,
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}
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impl SpatialGrid {
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pub fn new(lg2_cell_size: usize, lg2_large_cell_size: usize, radius_cutoff: u32) -> Self {
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Self {
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grid: Default::default(),
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large_grid: Default::default(),
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lg2_cell_size,
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lg2_large_cell_size,
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radius_cutoff,
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largest_large_radius: radius_cutoff,
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}
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}
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/// Add an entity at the provided 2d pos into the spatial grid
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pub fn insert(&mut self, pos: Vec2<i32>, radius: u32, entity: specs::Entity) {
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if radius <= self.radius_cutoff {
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let cell = pos.map(|e| e >> self.lg2_cell_size);
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self.grid.entry(cell).or_default().push(entity);
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} else {
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let cell = pos.map(|e| e >> self.lg2_large_cell_size);
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self.large_grid.entry(cell).or_default().push(entity);
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self.largest_large_radius = self.largest_large_radius.max(radius);
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}
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}
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/// Get an iterator over the entities overlapping the
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/// provided axis aligned bounding region
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/// NOTE: for best optimization of the iterator use `for_each` rather than a
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/// for loop
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pub fn in_aabr<'a>(&'a self, aabr: Aabr<i32>) -> impl Iterator<Item = specs::Entity> + 'a {
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let iter = |max_entity_radius, grid: &'a hashbrown::HashMap<_, _>, lg2_cell_size| {
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// Add buffer for other entity radius
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let min = aabr.min - max_entity_radius as i32;
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let max = aabr.max + max_entity_radius as i32;
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// Convert to cells
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let min = min.map(|e| e >> lg2_cell_size);
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let max = max.map(|e| (e + (1 << lg2_cell_size) - 1) >> lg2_cell_size);
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(min.x..=max.x)
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.flat_map(move |x| (min.y..=max.y).map(move |y| Vec2::new(x, y)))
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.flat_map(move |cell| grid.get(&cell).into_iter().flatten())
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.copied()
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};
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iter(self.radius_cutoff, &self.grid, self.lg2_cell_size).chain(iter(
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self.largest_large_radius,
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&self.large_grid,
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self.lg2_large_cell_size,
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))
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}
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/// Get an iterator over the entities overlapping the
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/// axis aligned bounding region that contains the provided circle
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/// NOTE: for best optimization of the iterator use `for_each` rather than a
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/// for loop
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// TODO: using the circle directly would be tighter (how efficient would it be
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// to query the cells intersecting a circle?) (note: if doing this rename
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// the function)
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pub fn in_circle_aabr(
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&self,
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center: Vec2<f32>,
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radius: f32,
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) -> impl Iterator<Item = specs::Entity> + '_ {
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let center = center.map(|e| e as i32);
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let radius = radius.ceil() as i32;
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// From conversion of center above
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const CENTER_TRUNCATION_ERROR: i32 = 1;
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let max_dist = radius + CENTER_TRUNCATION_ERROR;
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let aabr = Aabr {
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min: center - max_dist,
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max: center + max_dist,
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};
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self.in_aabr(aabr)
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}
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pub fn clear(&mut self) {
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self.grid.clear();
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self.large_grid.clear();
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self.largest_large_radius = self.radius_cutoff;
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}
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}
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