Struct Rtree 

pub struct Rtree<T: Indexable, Params: SplitParameters = Quadratic> { /* private fields */ }

A spatial index over Indexable values, parameterised by a split strategy.

Mirrors boost::geometry::index::rtree<Value, Parameters> (index/rtree.hpp). The default split is Quadratic; pass Linear as Params for cheaper inserts.

Examples

use geometry_cs::Cartesian;
use geometry_model::Point2D;
use geometry_rtree::Rtree;

type P = Point2D<f64, Cartesian>;
let mut tree: Rtree<P> = Rtree::new();
tree.insert(P::new(1.0, 1.0));
tree.insert(P::new(5.0, 5.0));
assert_eq!(tree.len(), 2);

Implementations

impl<T: Indexable, Params: SplitParameters> Rtree<T, Params>

pub fn new() -> Self

An empty tree.

pub fn len(&self) -> usize

Number of values in the tree.

pub fn is_empty(&self) -> bool

Whether the tree holds no values.

pub fn height(&self) -> usize

The height of the tree (a single-leaf tree is height 1).

pub fn insert(&mut self, value: T)

Insert one value.

Descends by least-enlargement to a leaf, inserts, and splits and propagates upward if a node overflows. Mirrors visitors/insert.hpp.

pub fn query(&self, predicate: Predicate) -> Vec<&T>

Iterate every value whose bounds satisfy predicate.

Prunes subtrees whose bounds cannot match. Mirrors visitors/spatial_query.hpp.

pub fn nearest(&self, query: [f64; 2], k: usize) -> Vec<&T>

The k values nearest to the query point, closest first.

Best-first search over node bounding boxes by minimum distance. Mirrors visitors/distance_query.hpp.

Trait Implementations

impl<T: Debug + Indexable, Params: Debug + SplitParameters> Debug for Rtree<T, Params>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<T: Indexable, Params: SplitParameters> Default for Rtree<T, Params>

fn default() -> Self

Returns the “default value” for a type.

impl<T: Indexable, Params: SplitParameters> FromIterator<T> for Rtree<T, Params>

fn from_iter<I: IntoIterator<Item = T>>(iter: I) -> Self

Bulk-load with Sort-Tile-Recursive packing: sort by x-centroid, slice into vertical strips, sort each strip by y-centroid, and pack leaves. Produces a balanced tree in one pass, the analogue of Boost’s pack_create (index/detail/rtree/pack_create.hpp).