Struct linfa_nn::BallTree

pub struct BallTree;

Implementation of ball tree, a space partitioning data structure that partitions its points into nested hyperspheres called “balls”. It performs spatial queries in O(k * logN) time, where k is the number of points returned by the query. Calling from_batch returns a BallTreeIndex.

More details can be found here. This implementation is based off of the ball_tree crate.

Implementations

impl BallTree

pub fn new() -> Self

Creates an instance of BallTree

Trait Implementations

impl Clone for BallTree

fn clone(&self) -> BallTree

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for BallTree

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

Formats the value using the given formatter.

impl Default for BallTree

fn default() -> BallTree

Returns the “default value” for a type.

impl NearestNeighbour for BallTree

fn from_batch_with_leaf_size<'a, F: Float, DT: Data<Elem = F>, D: 'a + Distance<F>>(
    &self,
    batch: &'a ArrayBase<DT, Ix2>,
    leaf_size: usize,
    dist_fn: D
) -> Result<Box<dyn NearestNeighbourIndex<F> + 'a>, BuildError>

Builds a spatial index using a MxN two-dimensional array representing M points with N dimensions. Also takes leaf_size, which specifies the number of elements in the leaf nodes of tree-like index structures.

fn from_batch<'a, F: Float, DT: Data<Elem = F>, D: 'a + Distance<F>>(
    &self,
    batch: &'a ArrayBase<DT, Ix2>,
    dist_fn: D
) -> Result<Box<dyn NearestNeighbourIndex<F> + 'a>, BuildError>

Builds a spatial index using a default leaf size. See from_batch_with_leaf_size for more information.