pub struct KdTree;
Expand description

Implementation of K-D tree, a fast space-partitioning data structure. For each parent node, the indexed points are split with a hyperplane into two child nodes. Due to its tree-like structure, the K-D tree performs spatial queries in O(k * logN) time, where k is the number of points returned by the query. Calling from_batch returns a KdTree.

More details can be found here.

Unlike other NearestNeighbour implementations, KdTree requires that points be laid out contiguously in memory and will panic otherwise.

Implementations

Creates an instance of KdTree

Trait Implementations

Returns a copy of the value. Read more

Performs copy-assignment from source. Read more

Formats the value using the given formatter. Read more

Returns the “default value” for a type. Read more

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. Read more

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

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

This method tests for !=.

Auto Trait Implementations

Blanket Implementations

Gets the TypeId of self. Read more

Immutably borrows from an owned value. Read more

Mutably borrows from an owned value. Read more

Compare self to key and return true if they are equal.

Returns the argument unchanged.

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

The resulting type after obtaining ownership.

Creates owned data from borrowed data, usually by cloning. Read more

Uses borrowed data to replace owned data, usually by cloning. Read more

The type returned in the event of a conversion error.

Performs the conversion.

The type returned in the event of a conversion error.

Performs the conversion.