Struct SRTree

pub struct SRTree<T, M> {
    pub root_index: usize,
    pub points: Vec<Point<T>>,
    pub nodes: Vec<Node<T>>,
    pub params: Params,
    pub metric: M,
}

Fields

root_index: usize

points: Vec<Point<T>>

nodes: Vec<Node<T>>

params: Params

metric: M

Implementations

impl<T, M> SRTree<T, M>

where T: Float + Send + Sync, M: Metric<T>,

pub fn bulk_load(&mut self, point_indices: Vec<usize>) -> usize

impl<T, M> SRTree<T, M>

where T: Float + Send + Sync, M: Metric<T>,

pub fn query(&self, point_coords: &[T], k: usize) -> (Vec<usize>, Vec<T>)

impl<T, M> SRTree<T, M>

where T: Float + Send + Sync, M: Metric<T>,

pub fn query_radius(&self, point_coords: &[T], radius: T) -> Vec<usize>

impl<T, M> SRTree<T, M>

where T: Float + Send + Sync, M: Metric<T>,

pub fn distance(&self, a: &Point<T>, b: &Point<T>) -> T

pub fn distance_squared(&self, a: &Point<T>, b: &Point<T>) -> T

pub fn point_to_rect_min_distance(&self, point: &Point<T>, rect: &Rect<T>) -> T

pub fn point_to_rect_max_distance(&self, point: &Point<T>, rect: &Rect<T>) -> T

pub fn point_to_sphere_min_distance( &self, point: &Point<T>, sphere: &Sphere<T>, ) -> T

pub fn point_to_sphere_max_distance( &self, point: &Point<T>, sphere: &Sphere<T>, ) -> T

pub fn point_to_node_min_distance(&self, point: &Point<T>, node: &Node<T>) -> T

pub fn point_to_node_max_distance(&self, point: &Point<T>, node: &Node<T>) -> T

impl<T, M> SRTree<T, M>

where T: Float + Send + Sync, M: Metric<T>,

pub fn calculate_mean(&self, node_index: usize) -> Vec<T>

impl<T, M> SRTree<T, M>

where T: Float + Send + Sync, M: Metric<T>,

pub fn calculate_points_variance(&self, point_indices: &[usize]) -> Vec<T>

impl<T, M> SRTree<T, M>

where T: Float + Send + Sync, M: Metric<T>,

pub fn reshape(&mut self, node_index: usize)

impl<T, M> SRTree<T, M>

where T: Float + Send + Sync, M: Metric<T>,

pub fn new( pts: &[Vec<T>], params: Params, metric: M, ) -> Result<Self, ArrayError>

Builds SRTree with the given points, params and metric.

Errors

• ArrayError::Empty if the input array is empty.
• ArrayError::DimensionMismatch if the input array contains points of different dimensions.

pub fn default(pts: &[Vec<T>], metric: M) -> Result<Self, ArrayError>

Builds SRTree with the given points (using default params) and metric.

Errors

• ArrayError::Empty if the input array is empty.
• ArrayError::DimensionMismatch if the input array contains points of different dimensions.

pub fn add_node(&mut self, node: Node<T>) -> usize

pub fn num_nodes(&self) -> usize

pub fn num_points(&self) -> usize

pub fn num_leaves(&self) -> usize

pub fn height(&self) -> usize

pub fn children_of(&self, node_index: usize) -> Option<&[usize]>

pub fn points_of(&self, node_index: usize) -> &[usize]

pub fn node_distance_lower_bound( &self, node_index: usize, other_node_index: usize, ) -> T

pub fn radius_of(&self, node_index: usize) -> T

pub fn compare_nodes( &self, node_index: usize, other_node_index: usize, ) -> Option<Ordering>

impl<T> SRTree<T, Euclidean>

where T: Float + Send + Sync,

pub fn euclidean_with_params( pts: &[Vec<T>], params: Params, ) -> Result<Self, ArrayError>

Builds SRTree with the given points, params and Euclidean metric.

Errors

• ArrayError::Empty if the input array is empty.
• ArrayError::DimensionMismatch if the input array contains points of different dimensions.

pub fn euclidean(pts: &[Vec<T>]) -> Result<Self, ArrayError>

Builds SRTree with the given points (using default params) and Euclidean metric.

Errors

• ArrayError::Empty if the input array is empty.
• ArrayError::DimensionMismatch if the input array contains points of different dimensions.