[−][src]Struct kd_tree::KdIndexTreeN
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>
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pub fn source(&self) -> &'a [T]
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pub fn indices(&self) -> &KdSliceN<usize, N>
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pub fn item(&self, i: usize) -> &'a T
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pub fn build_by<F>(source: &'a [T], compare: F) -> Self where
F: Fn(&T, &T, usize) -> Ordering + Copy,
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F: Fn(&T, &T, usize) -> Ordering + Copy,
pub fn build_by_key<Key, F>(source: &'a [T], kd_key: F) -> Self where
Key: Ord,
F: Fn(&T, usize) -> Key + Copy,
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Key: Ord,
F: Fn(&T, usize) -> Key + Copy,
pub fn build_by_ordered_float(points: &'a [T]) -> Self where
T: KdPoint<Dim = N>,
T::Scalar: Float,
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T: KdPoint<Dim = N>,
T::Scalar: Float,
pub fn build(points: &'a [T]) -> Self where
T: KdPoint<Dim = N>,
T::Scalar: Ord,
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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>>
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&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>,
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&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>>
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&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>,
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&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>
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&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>
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&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>,
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&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>
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&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>,
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&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>
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pub fn clone(&self) -> KdIndexTreeN<'a, T, N>
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pub fn clone_from(&mut self, source: &Self)
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impl<'a, T: Debug, N: Debug + Unsigned> Debug for KdIndexTreeN<'a, T, N>
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impl<'a, T: Eq, N: Eq + Unsigned> Eq for KdIndexTreeN<'a, T, N>
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impl<'a, T: PartialEq, N: PartialEq + Unsigned> PartialEq<KdIndexTreeN<'a, T, N>> for KdIndexTreeN<'a, T, N>
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pub fn eq(&self, other: &KdIndexTreeN<'a, T, N>) -> bool
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pub fn ne(&self, other: &KdIndexTreeN<'a, T, N>) -> bool
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impl<'a, T, N: Unsigned> StructuralEq for KdIndexTreeN<'a, T, N>
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impl<'a, T, N: Unsigned> StructuralPartialEq for KdIndexTreeN<'a, T, N>
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Auto Trait Implementations
impl<'a, T, N> RefUnwindSafe for KdIndexTreeN<'a, T, N> where
N: RefUnwindSafe,
T: RefUnwindSafe,
N: RefUnwindSafe,
T: RefUnwindSafe,
impl<'a, T, N> Send for KdIndexTreeN<'a, T, N> where
N: Send,
T: Sync,
N: Send,
T: Sync,
impl<'a, T, N> Sync for KdIndexTreeN<'a, T, N> where
N: Sync,
T: Sync,
N: Sync,
T: Sync,
impl<'a, T, N> Unpin for KdIndexTreeN<'a, T, N> where
N: Unpin,
N: Unpin,
impl<'a, T, N> UnwindSafe for KdIndexTreeN<'a, T, N> where
N: UnwindSafe,
T: RefUnwindSafe,
N: UnwindSafe,
T: RefUnwindSafe,
Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
pub fn borrow_mut(&mut self) -> &mut T
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impl<T> From<T> for T
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impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<T> Same<T> for T
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type Output = T
Should always be Self
impl<T> ToOwned for T where
T: Clone,
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T: Clone,
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T
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pub fn clone_into(&self, target: &mut T)
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impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,