Struct kd_tree::KdIndexTreeN

pub struct KdIndexTreeN<'a, T, N: Unsigned> { /* private fields */ }

This type refers a slice of items, [T], and contains kd-tree of indices to the items, KdTree<usize, N>. Unlike KdSliceN::sort, KdIndexTreeN::build doesn’t sort input items.

let items = vec![[1, 2, 3], [3, 1, 2], [2, 3, 1]];
let kdtree = kd_tree::KdIndexTree::build(&items);
assert_eq!(kdtree.nearest(&[3, 1, 2]).unwrap().item, &1); // nearest() returns an index of items.

Implementations

impl<'a, T, N: Unsigned> KdIndexTreeN<'a, T, N>

pub fn source(&self) -> &'a [T]

pub fn indices(&self) -> &KdSliceN<usize, N>

pub fn item(&self, i: usize) -> &'a T

pub fn build_by<F>(source: &'a [T], compare: F) -> Selfwhere
    F: Fn(&T, &T, usize) -> Ordering + Copy,

pub fn build_by_key<Key, F>(source: &'a [T], kd_key: F) -> Selfwhere
    Key: Ord,
    F: Fn(&T, usize) -> Key + Copy,

pub fn build_by_ordered_float(points: &'a [T]) -> Selfwhere
    T: KdPoint<Dim = N>,
    T::Scalar: Float,

pub fn build(points: &'a [T]) -> Selfwhere
    T: KdPoint<Dim = N>,
    T::Scalar: Ord,

pub fn nearest_by<Q: KdPoint<Dim = N>>(
    &self,
    query: &Q,
    coord: impl Fn(&T, usize) -> Q::Scalar + Copy
) -> Option<ItemAndDistance<'_, usize, Q::Scalar>>

pub fn nearest(
    &self,
    query: &impl KdPoint<Scalar = T::Scalar, Dim = N>
) -> Option<ItemAndDistance<'_, usize, T::Scalar>>where
    T: KdPoint<Dim = N>,

Example

let mut items: Vec<[i32; 3]> = vec![[1, 2, 3], [3, 1, 2], [2, 3, 1]];
let kdtree = kd_tree::KdIndexTree3::build(&items);
assert_eq!(kdtree.nearest(&[3, 1, 2]).unwrap().item, &1);

pub fn nearests_by<Q: KdPoint<Dim = N>>(
    &self,
    query: &Q,
    num: usize,
    coord: impl Fn(&T, usize) -> Q::Scalar + Copy
) -> Vec<ItemAndDistance<'_, usize, Q::Scalar>>

pub fn nearests(
    &self,
    query: &impl KdPoint<Scalar = T::Scalar, Dim = N>,
    num: usize
) -> Vec<ItemAndDistance<'_, usize, T::Scalar>>where
    T: KdPoint<Dim = N>,

Returns kNN(k nearest neighbors) from the input point.

Example

let mut items: Vec<[i32; 3]> = vec![[1, 2, 3], [3, 1, 2], [2, 3, 1], [3, 2, 2]];
let kdtree = kd_tree::KdIndexTree::build(&mut items);
let nearests = kdtree.nearests(&[3, 1, 2], 2);
assert_eq!(nearests.len(), 2);
assert_eq!(nearests[0].item, &1);
assert_eq!(nearests[1].item, &3);

pub fn within_by_cmp(
    &self,
    compare: impl Fn(&T, usize) -> Ordering + Copy
) -> Vec<&usize>

pub fn within_by<Q: KdPoint<Dim = N>>(
    &self,
    query: &[Q; 2],
    coord: impl Fn(&T, usize) -> Q::Scalar + Copy
) -> Vec<&usize>

pub fn within(
    &self,
    query: &[impl KdPoint<Scalar = T::Scalar, Dim = N>; 2]
) -> Vec<&usize>where
    T: KdPoint<Dim = N>,

pub fn within_radius_by<Q: KdPoint<Dim = N>>(
    &self,
    query: &Q,
    radius: Q::Scalar,
    coord: impl Fn(&T, usize) -> Q::Scalar + Copy
) -> Vec<&usize>

pub fn within_radius(
    &self,
    query: &impl KdPoint<Scalar = T::Scalar, Dim = N>,
    radius: T::Scalar
) -> Vec<&usize>where
    T: KdPoint<Dim = N>,

Trait Implementations

impl<'a, T: Clone, N: Clone + Unsigned> Clone for KdIndexTreeN<'a, T, N>

fn clone(&self) -> KdIndexTreeN<'a, T, N>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<'a, T: Debug, N: Debug + Unsigned> Debug for KdIndexTreeN<'a, T, N>

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

Formats the value using the given formatter.

impl<'a, T: PartialEq, N: PartialEq + Unsigned> PartialEq<KdIndexTreeN<'a, T, N>> for KdIndexTreeN<'a, T, N>

fn eq(&self, other: &KdIndexTreeN<'a, T, N>) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<'a, T: Eq, N: Eq + Unsigned> Eq for KdIndexTreeN<'a, T, N>

impl<'a, T, N: Unsigned> StructuralEq for KdIndexTreeN<'a, T, N>

impl<'a, T, N: Unsigned> StructuralPartialEq for KdIndexTreeN<'a, T, N>