A Rust library providing a simple and efficient Hilbert R-tree implementation for spatial queries on axis-aligned bounding boxes (AABBs).

• Hilbert Curve Ordering: Uses Hilbert space-filling curve for improved spatial locality
• AABB Intersection Queries: Fast rectangular bounding box intersection testing
• Simple API: Easy to use with minimal setup
• Static Optimization: Efficient for static or infrequently-modified spatial data

Add this to your Cargo.toml:

[dependencies]
aabb = "0.2"

use aabb::prelude::*;

fn main() {
    let mut tree = HilbertRTree::new();
    
    // Add bounding boxes (min_x, min_y, max_x, max_y)
    tree.add(0.0, 0.0, 1.0, 1.0);
    tree.add(0.5, 0.5, 1.5, 1.5);
    tree.add(2.0, 2.0, 3.0, 3.0);
    
    // Build the spatial index
    tree.build();
    
    // Query for intersecting boxes
    let mut results = Vec::new();
    tree.query_intersecting(0.7, 0.7, 1.3, 1.3, &mut results);
    
    println!("Found {} intersecting boxes", results.len());
    // Results contains indices of boxes that intersect the query
}

The Hilbert R-tree stores bounding boxes in a flat array and sorts them by their Hilbert curve index (computed from box centers). This provides good spatial locality for most spatial queries while maintaining a simple, cache-friendly data structure.

• HilbertRTree::new() - Create a new empty tree
• add(min_x, min_y, max_x, max_y) - Add a bounding box
• build() - Build the spatial index (required before querying)

• query_intersecting(min_x, min_y, max_x, max_y, results) - Find boxes that intersect a rectangle
• query_intersecting_k(min_x, min_y, max_x, max_y, k, results) - Find first K intersecting boxes
• query_point(x, y, results) - Find boxes that contain a point
• query_containing(min_x, min_y, max_x, max_y, results) - Find boxes that contain a rectangle
• query_contained_by(min_x, min_y, max_x, max_y, results) - Find boxes contained within a rectangle

• query_nearest_k(x, y, k, results) - Find K nearest boxes to a point
• query_nearest(x, y) -> Option<usize> - Find the single nearest box to a point
• query_within_distance(x, y, max_distance, results) - Find boxes within distance of a point
• query_circle(center_x, center_y, radius, results) - Find boxes intersecting a circular region

• query_in_direction(rect_min_x, rect_min_y, rect_max_x, rect_max_y, direction_x, direction_y, distance, results) - Find boxes intersecting a rectangle's movement path
• query_in_direction_k(rect_min_x, rect_min_y, rect_max_x, rect_max_y, direction_x, direction_y, k, distance, results) - Find K nearest boxes intersecting a rectangle's movement path

• Cache-Friendly: Flat array storage with Hilbert curve ordering for good spatial locality
• Static Optimization: Optimized for static or infrequently-modified spatial data

This project is licensed under the MIT License.