#kdtree #spatial-index #spatial #spatial-geometry #search-algorithms #geometry

kdbush

A very fast static spatial index for 2D points based on a flat KD-tree

2 unstable releases

0.2.0 Apr 21, 2020
0.1.0 Jun 17, 2017

#2349 in Algorithms

Download history 266/week @ 2024-11-29 201/week @ 2024-12-06 129/week @ 2024-12-13 62/week @ 2024-12-20 12/week @ 2024-12-27 82/week @ 2025-01-03 113/week @ 2025-01-10 128/week @ 2025-01-17 151/week @ 2025-01-24 211/week @ 2025-01-31 139/week @ 2025-02-07 115/week @ 2025-02-14 90/week @ 2025-02-21 105/week @ 2025-02-28 83/week @ 2025-03-07 144/week @ 2025-03-14

435 downloads per month
Used in 5 crates

ISC license

15KB
317 lines

kdbush

Documentation

A Rust port of kdbush, a very fast static spatial index for 2D points based on a flat KD-tree.

Introduction: A dive into spatial search algorithms

Comparison of point and box spatial index libraries.

Usage

let points = vec![(54.0, 1.0), (97.0, 21.0), (65.0, 35.0)];
let index = KDBush::create(points, kdbush::DEFAULT_NODE_SIZE); // make an index
index.range(20.0, 30.0, 50.0, 70.0, |id| print!("{} ", id));   // bbox search - minX, minY, maxX, maxY
index.within(50.0, 50.0, 20.0, |id| print!("{} ", id));        // radius search - x, y, radius

No runtime deps