Struct RTree 

pub struct RTree<T>
where
    T: Clone,
{ /* private fields */ }

R-tree for spatial indexing and queries

Examples

use scirs2_spatial::rtree::RTree;
use scirs2_core::ndarray::array;

// Create points
let points = array![
    [0.0, 0.0],
    [1.0, 1.0],
    [2.0, 2.0],
    [3.0, 3.0],
    [4.0, 4.0],
];

// Build R-tree with points
let mut rtree = RTree::new(2, 4, 8).unwrap();
for (i, point) in points.rows().into_iter().enumerate() {
    rtree.insert(point.to_owned(), i).unwrap();
}

// Search for points within a range
let query_min = array![0.5, 0.5];
let query_max = array![2.5, 2.5];

// The views need to be passed explicitly in the actual code
let query_min_view = query_min.view();
let query_max_view = query_max.view();
let results = rtree.search_range(&query_min_view, &query_max_view).unwrap();

println!("Found {} points in range", results.len());

// Find the nearest neighbors to a point
let query_point = array![2.5, 2.5];
let query_point_view = query_point.view();
let nearest = rtree.nearest(&query_point_view, 2).unwrap();

println!("Nearest points: {:?}", nearest);

Implementations

impl<T: Clone> RTree<T>

pub fn delete<F>( &mut self, point: &ArrayView1<'_, f64>, data_predicate: Option<F>, ) -> SpatialResult<bool>

where F: Fn(&T) -> bool + Copy,

Delete a data point from the R-tree

Arguments

• point - The point coordinates to delete
• data_predicate - An optional function that takes a reference to the data and returns true if it should be deleted. This is useful when multiple data points share the same coordinates.

Returns

A SpatialResult containing true if a point was deleted, false otherwise

impl<T: Clone> RTree<T>

pub fn insert(&mut self, point: Array1<f64>, data: T) -> SpatialResult<()>

Insert a data point into the R-tree

Arguments

• point - The point coordinates
• data - The data associated with the point

Returns

A SpatialResult containing nothing if successful, or an error if the point has invalid dimensions

pub fn insert_rectangle( &mut self, min: Array1<f64>, max: Array1<f64>, data: T, ) -> SpatialResult<()>

Insert a rectangle into the R-tree

Arguments

• min - The minimum coordinates of the rectangle
• max - The maximum coordinates of the rectangle
• data - The data associated with the rectangle

Returns

A SpatialResult containing nothing if successful, or an error if the rectangle has invalid dimensions

impl<T: Clone> RTree<T>

pub fn new( ndim: usize, min_entries: usize, maxentries: usize, ) -> SpatialResult<Self>

Create a new R-tree

Arguments

• ndim - Number of dimensions
• min_entries - Minimum number of entries in each node (except the root)
• maxentries - Maximum number of entries in each node

Returns

A SpatialResult containing the new R-tree, or an error if the parameters are invalid

pub fn ndim(&self) -> usize

Get the number of dimensions in the R-tree

pub fn size(&self) -> usize

Get the number of data points in the R-tree

pub fn height(&self) -> usize

Get the height of the R-tree

pub fn is_empty(&self) -> bool

Check if the R-tree is empty

pub fn clear(&mut self)

Clear the R-tree, removing all data points

impl<T: Clone> RTree<T>

pub fn optimize(&mut self) -> SpatialResult<()>

Optimize the R-tree by rebuilding it with the current data

This can significantly improve query performance by reducing overlap and creating a more balanced tree.

Returns

A SpatialResult containing nothing if successful

pub fn bulk_load( ndim: usize, min_entries: usize, max_entries: usize, points: Vec<(Array1<f64>, T)>, ) -> SpatialResult<Self>

Perform bulk loading of the R-tree with sorted data points

This is more efficient than inserting points one by one.

Arguments

• points - A vector of (point, data) pairs to insert

Returns

A SpatialResult containing a new R-tree built from the data points

pub fn calculate_total_overlap(&self) -> SpatialResult<f64>

Calculate the total overlap in the R-tree

This is a quality metric for the tree. Lower overlap generally means better query performance.

Returns

The total overlap area between all pairs of nodes at each level

impl<T: Clone> RTree<T>

pub fn search_range( &self, min: &ArrayView1<'_, f64>, max: &ArrayView1<'_, f64>, ) -> SpatialResult<Vec<(usize, T)>>

Search for data points within a range

Arguments

• min - Minimum coordinates of the search range
• max - Maximum coordinates of the search range

Returns

A SpatialResult containing a vector of (index, data) pairs for data points within the range, or an error if the range has invalid dimensions

pub fn nearest( &self, point: &ArrayView1<'_, f64>, k: usize, ) -> SpatialResult<Vec<(usize, T, f64)>>

Find the k nearest neighbors to a query point

Arguments

• point - The query point
• k - The number of nearest neighbors to find

Returns

A SpatialResult containing a vector of (index, data, distance) tuples for the k nearest data points, sorted by distance (closest first), or an error if the point has invalid dimensions

pub fn spatial_join<U, P>( &self, other: &RTree<U>, predicate: P, ) -> SpatialResult<Vec<(T, U)>>

where U: Clone, P: Fn(&Rectangle, &Rectangle) -> SpatialResult<bool>,

Perform a spatial join between this R-tree and another

Arguments

• other - The other R-tree to join with
• predicate - A function that takes MBRs from both trees and returns true if they should be joined, e.g., for an intersection join: |mbr1, mbr2| mbr1.intersects(mbr2)

Returns

A SpatialResult containing a vector of pairs of data from both trees that satisfy the predicate, or an error if the R-trees have different dimensions

Trait Implementations

impl<T> Clone for RTree<T>

where T: Clone + Clone,

fn clone(&self) -> RTree<T>

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<T> Debug for RTree<T>

where T: Clone + Debug,

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

Formats the value using the given formatter.