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