Broccoli is a broad-phase collision detection library.
The base data structure is a hybrid between a KD Tree and Sweep and Prune.
Checkout it out on github and on crates.io. Documentation at docs.rs.
Screen capture from the inner demo project.
```rust use broccoli::tree::rect; fn main() { let mut inner1 = 0; let mut inner2 = 0; let mut inner3 = 0;
// Rect is stored directly in tree,
// but inner is not.
let mut aabbs = [
(rect(00, 10, 00, 10), &mut inner1),
(rect(15, 20, 15, 20), &mut inner2),
(rect(05, 15, 05, 15), &mut inner3),
];
// Construct tree by doing many swapping of elements
let mut tree = broccoli::Tree::new(&mut aabbs);
// Find all colliding aabbs.
tree.find_colliding_pairs(|a, b| {
// We aren't given &mut T reference, but instead of AabbPin<&mut T>.
// We call unpack_inner() to extract the portion that we are allowed to mutate.
// (We are not allowed to change the bounding box while in the tree)
**a.unpack_inner() += 1;
**b.unpack_inner() += 1;
});
assert_eq!(inner1, 1);
assert_eq!(inner2, 1);
assert_eq!(inner3, 2);
} ```
I've focused mainly on making finding colliding pairs as fast as possible primarily in distributions where there are a lot of overlapping aabbs.
Quick rundown of what i've spent effort on and a rough estimate of performance cost of each algorithm in general.
| Algorithm | Cost | Effort spent | | ---------------- | ---- | ------------- | | Construction | 7 | 10 | | Colliding Pairs | 8 | 10 | | Collide With | 3 | 2 | | knearest | 1 | 2 | | raycast | 1 | 2 | | rect | 1 | 2 | | nbody | 10 | 1 |
Numbers are out of 10 and are just rough made up numbers. For more in-depth analysis, see the broccoli book.
If you shorten "broad-phase collision" to "broad colli" and say it fast, it sounds like broccoli. Broccoli are also basically small trees and broccoli uses a tree data structure.