use spart::geometry::{DistanceMetric, EuclideanDistance, Point2D, Rectangle};
use spart::quadtree::Quadtree;
struct ManhattanDistance;
impl<T> DistanceMetric<Point2D<T>> for ManhattanDistance {
fn distance_sq(p1: &Point2D<T>, p2: &Point2D<T>) -> f64 {
((p1.x - p2.x).abs() + (p1.y - p2.y).abs()).powi(2)
}
}
fn main() {
let boundary = Rectangle {
x: 0.0,
y: 0.0,
width: 100.0,
height: 100.0,
};
let mut quadtree = Quadtree::<u32>::new(&boundary, 4).unwrap();
quadtree.insert(Point2D::new(10.0, 20.0, Some(1)));
quadtree.insert(Point2D::new(80.0, 30.0, Some(2)));
quadtree.insert(Point2D::new(45.0, 70.0, Some(3)));
let query_point = Point2D::new(12.0, 22.0, None);
let results_euclidean = quadtree.knn_search::<EuclideanDistance>(&query_point, 2);
println!(
"2 nearest neighbors to {:?} (Euclidean): {:?}",
query_point, results_euclidean
);
let results_manhattan = quadtree.knn_search::<ManhattanDistance>(&query_point, 2);
println!(
"2 nearest neighbors to {:?} (Manhattan): {:?}",
query_point, results_manhattan
);
let encoded: Vec<u8> = bincode::serialize(&quadtree).unwrap();
let decoded: Quadtree<u32> = bincode::deserialize(&encoded[..]).unwrap();
let results_decoded = decoded.knn_search::<EuclideanDistance>(&query_point, 2);
println!(
"2 nearest neighbors to {:?} (Euclidean, decoded): {:?}",
query_point, results_decoded
);
}