Expand description
k-dimensional tree.
§Usage
// construct kd-tree
let kdtree = kd_tree::KdTree::build_by_ordered_float(vec![
[1.0, 2.0, 3.0],
[3.0, 1.0, 2.0],
[2.0, 3.0, 1.0],
]);
// search the nearest neighbor
let found = kdtree.nearest(&[3.1, 0.9, 2.1]).unwrap();
assert_eq!(found.item, &[3.0, 1.0, 2.0]);
// search k-nearest neighbors
let found = kdtree.nearests(&[1.5, 2.5, 1.8], 2);
assert_eq!(found[0].item, &[2.0, 3.0, 1.0]);
assert_eq!(found[1].item, &[1.0, 2.0, 3.0]);
// search points within a sphere
let found = kdtree.within_radius(&[2.0, 1.5, 2.5], 1.5);
assert_eq!(found.len(), 2);
assert!(found.iter().any(|&&p| p == [1.0, 2.0, 3.0]));
assert!(found.iter().any(|&&p| p == [3.0, 1.0, 2.0]));Structs§
- This type refers a slice of items,
[T], and contains kd-tree of indices to the items,KdTree<usize, N>. UnlikeKdSliceN::sort,KdIndexTreeN::builddoesn’t sort input items. - A slice of kd-tree. This type implements
std::ops::Derefto[T]. This is an unsized type, meaning that it must always be used as a reference. For an owned version of this type, seeKdTree. - An owned kd-tree. This type implements
std::ops::DereftoKdSlice.
Traits§
- A trait to represent k-dimensional point.
Type Aliases§
- kd-tree of key-value pairs.
- kd-tree slice of key-value pairs.