A binary space partitioning tree, such as a KD-tree or a ball tree. More...

#include <binary_space_tree.hpp>

Classes
class	BreadthFirstDualTreeTraverser

class	DualTreeTraverser
	A dual-tree traverser for binary space trees; see dual_tree_traverser.hpp. More...

class	SingleTreeTraverser
	A single-tree traverser for binary space trees; see single_tree_traverser.hpp for implementation. More...

Public Types
typedef MatType	Mat
	So other classes can use TreeType::Mat.

typedef MatType::elem_type	ElemType
	The type of element held in MatType.

typedef SplitType< BoundType< MetricType >, MatType >	Split

Public Member Functions
	BinarySpaceTree (const MatType &data, const size_t maxLeafSize=20)
	Construct this as the root node of a binary space tree using the given dataset. More...

	BinarySpaceTree (const MatType &data, std::vector< size_t > &oldFromNew, const size_t maxLeafSize=20)
	Construct this as the root node of a binary space tree using the given dataset. More...

	BinarySpaceTree (const MatType &data, std::vector< size_t > &oldFromNew, std::vector< size_t > &newFromOld, const size_t maxLeafSize=20)
	Construct this as the root node of a binary space tree using the given dataset. More...

	BinarySpaceTree (MatType &&data, const size_t maxLeafSize=20)
	Construct this as the root node of a binary space tree using the given dataset. More...

	BinarySpaceTree (MatType &&data, std::vector< size_t > &oldFromNew, const size_t maxLeafSize=20)
	Construct this as the root node of a binary space tree using the given dataset. More...

	BinarySpaceTree (MatType &&data, std::vector< size_t > &oldFromNew, std::vector< size_t > &newFromOld, const size_t maxLeafSize=20)
	Construct this as the root node of a binary space tree using the given dataset. More...

	BinarySpaceTree (BinarySpaceTree *parent, const size_t begin, const size_t count, SplitType< BoundType< MetricType >, MatType > &splitter, const size_t maxLeafSize=20)
	Construct this node as a child of the given parent, starting at column begin and using count points. More...

	BinarySpaceTree (BinarySpaceTree *parent, const size_t begin, const size_t count, std::vector< size_t > &oldFromNew, SplitType< BoundType< MetricType >, MatType > &splitter, const size_t maxLeafSize=20)
	Construct this node as a child of the given parent, starting at column begin and using count points. More...

	BinarySpaceTree (BinarySpaceTree *parent, const size_t begin, const size_t count, std::vector< size_t > &oldFromNew, std::vector< size_t > &newFromOld, SplitType< BoundType< MetricType >, MatType > &splitter, const size_t maxLeafSize=20)
	Construct this node as a child of the given parent, starting at column begin and using count points. More...

	BinarySpaceTree (const BinarySpaceTree &other)
	Create a binary space tree by copying the other tree. More...

	BinarySpaceTree (BinarySpaceTree &&other)
	Move constructor for a BinarySpaceTree; possess all the members of the given tree. More...

BinarySpaceTree &	operator= (const BinarySpaceTree &other)
	Copy the given BinarySaceTree. More...

BinarySpaceTree &	operator= (BinarySpaceTree &&other)
	Take ownership of the given BinarySpaceTree. More...

template<typename Archive >
	BinarySpaceTree (Archive &ar, const typename std::enable_if_t< cereal::is_loading< Archive >()> *=0)
	Initialize the tree from a cereal archive. More...

	~BinarySpaceTree ()
	Deletes this node, deallocating the memory for the children and calling their destructors in turn. More...

const BoundType< MetricType > &	Bound () const
	Return the bound object for this node.

BoundType< MetricType > &	Bound ()
	Return the bound object for this node.

const StatisticType &	Stat () const
	Return the statistic object for this node.

StatisticType &	Stat ()
	Return the statistic object for this node.

bool	IsLeaf () const
	Return whether or not this node is a leaf (true if it has no children).

BinarySpaceTree *	Left () const
	Gets the left child of this node.

BinarySpaceTree *&	Left ()
	Modify the left child of this node.

BinarySpaceTree *	Right () const
	Gets the right child of this node.

BinarySpaceTree *&	Right ()
	Modify the right child of this node.

BinarySpaceTree *	Parent () const
	Gets the parent of this node.

BinarySpaceTree *&	Parent ()
	Modify the parent of this node.

const MatType &	Dataset () const
	Get the dataset which the tree is built on.

MatType &	Dataset ()
	Modify the dataset which the tree is built on. Be careful!

MetricType	Metric () const
	Get the metric that the tree uses.

size_t	NumChildren () const
	Return the number of children in this node. More...

template<typename VecType >
size_t	GetNearestChild (const VecType &point, typename std::enable_if_t< IsVector< VecType >::value > *=0)
	Return the index of the nearest child node to the given query point. More...

template<typename VecType >
size_t	GetFurthestChild (const VecType &point, typename std::enable_if_t< IsVector< VecType >::value > *=0)
	Return the index of the furthest child node to the given query point. More...

size_t	GetNearestChild (const BinarySpaceTree &queryNode)
	Return the index of the nearest child node to the given query node. More...

size_t	GetFurthestChild (const BinarySpaceTree &queryNode)
	Return the index of the furthest child node to the given query node. More...

ElemType	FurthestPointDistance () const
	Return the furthest distance to a point held in this node. More...

ElemType	FurthestDescendantDistance () const
	Return the furthest possible descendant distance. More...

ElemType	MinimumBoundDistance () const
	Return the minimum distance from the center of the node to any bound edge. More...

ElemType	ParentDistance () const
	Return the distance from the center of this node to the center of the parent node. More...

ElemType &	ParentDistance ()
	Modify the distance from the center of this node to the center of the parent node. More...

BinarySpaceTree &	Child (const size_t child) const
	Return the specified child (0 will be left, 1 will be right). More...

BinarySpaceTree *&	ChildPtr (const size_t child)

size_t	NumPoints () const
	Return the number of points in this node (0 if not a leaf). More...

size_t	NumDescendants () const
	Return the number of descendants of this node. More...

size_t	Descendant (const size_t index) const
	Return the index (with reference to the dataset) of a particular descendant of this node. More...

size_t	Point (const size_t index) const
	Return the index (with reference to the dataset) of a particular point in this node. More...

ElemType	MinDistance (const BinarySpaceTree &other) const
	Return the minimum distance to another node.

ElemType	MaxDistance (const BinarySpaceTree &other) const
	Return the maximum distance to another node.

math::RangeType< ElemType >	RangeDistance (const BinarySpaceTree &other) const
	Return the minimum and maximum distance to another node.

template<typename VecType >
ElemType	MinDistance (const VecType &point, typename std::enable_if_t< IsVector< VecType >::value > *=0) const
	Return the minimum distance to another point.

template<typename VecType >
ElemType	MaxDistance (const VecType &point, typename std::enable_if_t< IsVector< VecType >::value > *=0) const
	Return the maximum distance to another point.

template<typename VecType >
math::RangeType< ElemType >	RangeDistance (const VecType &point, typename std::enable_if_t< IsVector< VecType >::value > *=0) const
	Return the minimum and maximum distance to another point.

size_t	Begin () const
	Return the index of the beginning point of this subset.

size_t &	Begin ()
	Modify the index of the beginning point of this subset.

size_t	Count () const
	Return the number of points in this subset.

size_t &	Count ()
	Modify the number of points in this subset.

void	Center (arma::vec &center) const
	Store the center of the bounding region in the given vector.

template<typename Archive >
void	serialize (Archive &ar, const uint32_t version)
	Serialize the tree.

Protected Member Functions
	BinarySpaceTree ()
	A default constructor. More...

Friends
class	cereal::access
	Friend access is given for the default constructor.

Detailed Description

template<typename MetricType, typename StatisticType = EmptyStatistic, typename MatType = arma::mat, template< typename BoundMetricType, typename... > class BoundType = bound::HRectBound, template< typename SplitBoundType, typename SplitMatType > class SplitType = MidpointSplit>
class mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >

A binary space partitioning tree, such as a KD-tree or a ball tree.

Once the bound and type of dataset is defined, the tree will construct itself. Call the constructor with the dataset to build the tree on, and the entire tree will be built.

This particular tree does not allow growth, so you cannot add or delete nodes from it. If you need to add or delete a node, the better procedure is to rebuild the tree entirely.

This tree does take one runtime parameter in the constructor, which is the max leaf size to be used.

Template Parameters

MetricType	The metric used for tree-building. The BoundType may place restrictions on the metrics that can be used.
StatisticType	Extra data contained in the node. See statistic.hpp for the necessary skeleton interface.
MatType	The dataset class.
BoundType	The bound used for each node. HRectBound, the default, requires that an LMetric<> is used for MetricType (so, EuclideanDistance, ManhattanDistance, etc.).
SplitType	The class that partitions the dataset/points at a particular node into two parts. Its definition decides the way this split is done.

Constructor & Destructor Documentation

◆ BinarySpaceTree() [1/13]

template<typename MetricType , typename StatisticType , typename MatType, template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree	(	const MatType &	data,
		const size_t	maxLeafSize = `20`
	)

Construct this as the root node of a binary space tree using the given dataset.

This will copy the input matrix; if you don't want this, consider using the constructor that takes an rvalue reference and use std::move().

Parameters

data	Dataset to create tree from. This will be copied!
maxLeafSize	Size of each leaf in the tree.

◆ BinarySpaceTree() [2/13]

template<typename MetricType , typename StatisticType , typename MatType, template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree	(	const MatType &	data,
		std::vector< size_t > &	oldFromNew,
		const size_t	maxLeafSize = `20`
	)

Construct this as the root node of a binary space tree using the given dataset.

This will copy the input matrix and modify its ordering; a mapping of the old point indices to the new point indices is filled. If you don't want the matrix to be copied, consider using the constructor that takes an rvalue reference and use std::move().

Parameters

data	Dataset to create tree from. This will be copied!
oldFromNew	Vector which will be filled with the old positions for each new point.
maxLeafSize	Size of each leaf in the tree.

◆ BinarySpaceTree() [3/13]

template<typename MetricType , typename StatisticType , typename MatType, template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree	(	const MatType &	data,
		std::vector< size_t > &	oldFromNew,
		std::vector< size_t > &	newFromOld,
		const size_t	maxLeafSize = `20`
	)

Construct this as the root node of a binary space tree using the given dataset.

This will copy the input matrix and modify its ordering; a mapping of the old point indices to the new point indices is filled, as well as a mapping of the new point indices to the old point indices. If you don't want the matrix to be copied, consider using the constructor that takes an rvalue reference and use std::move().

Parameters

data	Dataset to create tree from. This will be copied!
oldFromNew	Vector which will be filled with the old positions for each new point.
newFromOld	Vector which will be filled with the new positions for each old point.
maxLeafSize	Size of each leaf in the tree.

◆ BinarySpaceTree() [4/13]

template<typename MetricType , typename StatisticType , typename MatType, template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree	(	MatType &&	data,
		const size_t	maxLeafSize = `20`
	)

Construct this as the root node of a binary space tree using the given dataset.

This will take ownership of the data matrix; if you don't want this, consider using the constructor that takes a const reference to a dataset.

Parameters

data	Dataset to create tree from.
maxLeafSize	Size of each leaf in the tree.

◆ BinarySpaceTree() [5/13]

template<typename MetricType , typename StatisticType , typename MatType, template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree	(	MatType &&	data,
		std::vector< size_t > &	oldFromNew,
		const size_t	maxLeafSize = `20`
	)

Construct this as the root node of a binary space tree using the given dataset.

This will take ownership of the data matrix; a mapping of the old point indices to the new point indices is filled. If you don't want the matrix to have its ownership taken, consider using the constructor that takes a const reference to a dataset.

Parameters

data	Dataset to create tree from.
oldFromNew	Vector which will be filled with the old positions for each new point.
maxLeafSize	Size of each leaf in the tree.

◆ BinarySpaceTree() [6/13]

template<typename MetricType , typename StatisticType , typename MatType, template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree	(	MatType &&	data,
		std::vector< size_t > &	oldFromNew,
		std::vector< size_t > &	newFromOld,
		const size_t	maxLeafSize = `20`
	)

Construct this as the root node of a binary space tree using the given dataset.

This will take ownership of the data matrix; a mapping of the old point indices to the new point indices is filled, as well as a mapping of the new point indices to the old point indices. If you don't want the matrix to have its ownership taken, consider using the constructor that takes a const reference to a dataset.

Parameters

data	Dataset to create tree from.
oldFromNew	Vector which will be filled with the old positions for each new point.
newFromOld	Vector which will be filled with the new positions for each old point.
maxLeafSize	Size of each leaf in the tree.

◆ BinarySpaceTree() [7/13]

template<typename MetricType, typename StatisticType , typename MatType, template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree	(	BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > *	parent,
		const size_t	begin,
		const size_t	count,
		SplitType< BoundType< MetricType >, MatType > &	splitter,
		const size_t	maxLeafSize = `20`
	)

Construct this node as a child of the given parent, starting at column begin and using count points.

The ordering of that subset of points in the parent's data matrix will be modified! This is used for recursive tree-building by the other constructors which don't specify point indices.

Parameters

parent	Parent of this node. Its dataset will be modified!
begin	Index of point to start tree construction with.
count	Number of points to use to construct tree.
splitter	Instantiated node splitter object.
maxLeafSize	Size of each leaf in the tree.

◆ BinarySpaceTree() [8/13]

template<typename MetricType, typename StatisticType , typename MatType, template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree	(	BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > *	parent,
		const size_t	begin,
		const size_t	count,
		std::vector< size_t > &	oldFromNew,
		SplitType< BoundType< MetricType >, MatType > &	splitter,
		const size_t	maxLeafSize = `20`
	)

Construct this node as a child of the given parent, starting at column begin and using count points.

The ordering of that subset of points in the parent's data matrix will be modified! This is used for recursive tree-building by the other constructors which don't specify point indices.

A mapping of the old point indices to the new point indices is filled, but it is expected that the vector is already allocated with size greater than or equal to (begin + count), and if that is not true, invalid memory reads (and writes) will occur.

Parameters

parent	Parent of this node. Its dataset will be modified!
begin	Index of point to start tree construction with.
count	Number of points to use to construct tree.
oldFromNew	Vector which will be filled with the old positions for each new point.
splitter	Instantiated node splitter object.
maxLeafSize	Size of each leaf in the tree.

◆ BinarySpaceTree() [9/13]

template<typename MetricType, typename StatisticType , typename MatType, template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree	(	BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > *	parent,
		const size_t	begin,
		const size_t	count,
		std::vector< size_t > &	oldFromNew,
		std::vector< size_t > &	newFromOld,
		SplitType< BoundType< MetricType >, MatType > &	splitter,
		const size_t	maxLeafSize = `20`
	)

Construct this node as a child of the given parent, starting at column begin and using count points.

The ordering of that subset of points in the parent's data matrix will be modified! This is used for recursive tree-building by the other constructors which don't specify point indices.

A mapping of the old point indices to the new point indices is filled, as well as a mapping of the new point indices to the old point indices. It is expected that the vector is already allocated with size greater than or equal to (begin_in + count_in), and if that is not true, invalid memory reads (and writes) will occur.

Parameters

parent	Parent of this node. Its dataset will be modified!
begin	Index of point to start tree construction with.
count	Number of points to use to construct tree.
oldFromNew	Vector which will be filled with the old positions for each new point.
newFromOld	Vector which will be filled with the new positions for each old point.
splitter	Splitter matrix to use.
maxLeafSize	Size of each leaf in the tree.

◆ BinarySpaceTree() [10/13]

template<typename MetricType, typename StatisticType , typename MatType, template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree ( const BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > & other )

Create a binary space tree by copying the other tree.

Be careful! This can take a long time and use a lot of memory.

Parameters

other Tree to be copied.

Be careful! This can take a long time and use a lot of memory.

◆ BinarySpaceTree() [11/13]

template<typename MetricType, typename StatisticType , typename MatType, template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree ( BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > && other )

Move constructor for a BinarySpaceTree; possess all the members of the given tree.

Move constructor.

◆ BinarySpaceTree() [12/13]

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

template<typename Archive >

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree	(	Archive &	ar,
		const typename std::enable_if_t< cereal::is_loading< Archive >()> *	= `0`
	)

Initialize the tree from a cereal archive.

Initialize the tree from an archive.

Parameters

ar	Archive to load tree from. Must be an iarchive, not an oarchive.

◆ ~BinarySpaceTree()

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::~BinarySpaceTree ( )

Deletes this node, deallocating the memory for the children and calling their destructors in turn.

This will invalidate any pointers or references to any nodes which are children of this one.

◆ BinarySpaceTree() [13/13]

template<typename MetricType, typename StatisticType , typename MatType, template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::BinarySpaceTree ( )

protected

A default constructor.

This is meant to only be used with cereal, which is allowed with the friend declaration below. This does not return a valid tree! The method must be protected, so that the serialization shim can work with the default constructor.

Member Function Documentation

◆ Child()

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > & mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::Child ( const size_t child ) const

inline

Return the specified child (0 will be left, 1 will be right).

Return the specified child.

If the index is greater than 1, this will return the right child.

Parameters

child Index of child to return.

◆ Descendant()

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

size_t mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::Descendant ( const size_t index ) const

inline

Return the index (with reference to the dataset) of a particular descendant of this node.

Return the index of a particular descendant contained in this node.

The index should be greater than zero but less than the number of descendants.

Parameters

index Index of the descendant.

◆ FurthestDescendantDistance()

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::ElemType mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::FurthestDescendantDistance ( ) const

inline

Return the furthest possible descendant distance.

This returns the maximum distance from the centroid to the edge of the bound and not the empirical quantity which is the actual furthest descendant distance. So the actual furthest descendant distance may be less than what this method returns (but it will never be greater than this).

This returns the maximum distance from the center to the edge of the bound and not the empirical quantity which is the actual furthest descendant distance. So the actual furthest descendant distance may be less than what this method returns (but it will never be greater than this).

◆ FurthestPointDistance()

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::ElemType mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::FurthestPointDistance ( ) const

inline

Return the furthest distance to a point held in this node.

Return a bound on the furthest point in the node from the center.

If this is not a leaf node, then the distance is 0 because the node holds no points.

This returns 0 unless the node is a leaf.

◆ GetFurthestChild() [1/2]

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

template<typename VecType >

size_t mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::GetFurthestChild	(	const VecType &	point,
		typename std::enable_if_t< IsVector< VecType >::value > *	= `0`
	)

Return the index of the furthest child node to the given query point.

If this is a leaf node, it will return NumChildren() (invalid index).

◆ GetFurthestChild() [2/2]

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

size_t mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::GetFurthestChild ( const BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > & queryNode )

Return the index of the furthest child node to the given query node.

If it can't decide, it will return NumChildren() (invalid index).

◆ GetNearestChild() [1/2]

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

template<typename VecType >

size_t mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::GetNearestChild	(	const VecType &	point,
		typename std::enable_if_t< IsVector< VecType >::value > *	= `0`
	)

Return the index of the nearest child node to the given query point.

If this is a leaf node, it will return NumChildren() (invalid index).

◆ GetNearestChild() [2/2]

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

size_t mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::GetNearestChild ( const BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > & queryNode )

Return the index of the nearest child node to the given query node.

If it can't decide, it will return NumChildren() (invalid index).

◆ MinimumBoundDistance()

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::ElemType mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::MinimumBoundDistance ( ) const

inline

Return the minimum distance from the center of the node to any bound edge.

Return the minimum distance from the center to any bound edge.

◆ NumChildren()

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

size_t mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::NumChildren ( ) const

inline

Return the number of children in this node.

Returns the number of children in this node.

◆ NumDescendants()

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

size_t mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::NumDescendants ( ) const

inline

Return the number of descendants of this node.

Return the number of descendants contained in the node.

For a non-leaf in a binary space tree, this is the number of points at the descendant leaves. For a leaf, this is the number of points in the leaf.

◆ NumPoints()

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

size_t mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::NumPoints ( ) const

inline

Return the number of points in this node (0 if not a leaf).

Return the number of points contained in this node.

◆ operator=() [1/2]

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > & mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::operator= ( const BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > & other )

Copy the given BinarySaceTree.

Copy assignment operator: copy the given other tree.

Parameters

other The tree to be copied.

◆ operator=() [2/2]

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > & mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::operator= ( BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > && other )

Take ownership of the given BinarySpaceTree.

Move assignment operator: take ownership of the given tree.

Parameters

other The tree to take ownership of.

◆ ParentDistance() [1/2]

template<typename MetricType, typename StatisticType = EmptyStatistic, typename MatType = arma::mat, template< typename BoundMetricType, typename... > class BoundType = bound::HRectBound, template< typename SplitBoundType, typename SplitMatType > class SplitType = MidpointSplit>

ElemType mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::ParentDistance ( ) const

inline

Return the distance from the center of this node to the center of the parent node.

◆ ParentDistance() [2/2]

template<typename MetricType, typename StatisticType = EmptyStatistic, typename MatType = arma::mat, template< typename BoundMetricType, typename... > class BoundType = bound::HRectBound, template< typename SplitBoundType, typename SplitMatType > class SplitType = MidpointSplit>

ElemType& mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::ParentDistance ( )

inline

Modify the distance from the center of this node to the center of the parent node.

◆ Point()

template<typename MetricType , typename StatisticType , typename MatType , template< typename BoundMetricType, typename... > class BoundType, template< typename SplitBoundType, typename SplitMatType > class SplitType>

size_t mlpack::tree::BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::Point ( const size_t index ) const

inline

Return the index (with reference to the dataset) of a particular point in this node.

Return the index of a particular point contained in this node.

This will happily return invalid indices if the given index is greater than the number of points in this node (obtained with NumPoints()) – be careful.

Parameters

index Index of point for which a dataset index is wanted.

The documentation for this class was generated from the following files:

src/mlpack/core/tree/binary_space_tree/binary_space_tree.hpp
src/mlpack/core/tree/binary_space_tree/binary_space_tree_impl.hpp

Classes

Public Types

Public Member Functions

Protected Member Functions

Friends

Detailed Description

Constructor & Destructor Documentation

◆ BinarySpaceTree() [1/13]

◆ BinarySpaceTree() [2/13]

◆ BinarySpaceTree() [3/13]

◆ BinarySpaceTree() [4/13]

◆ BinarySpaceTree() [5/13]

◆ BinarySpaceTree() [6/13]

◆ BinarySpaceTree() [7/13]

◆ BinarySpaceTree() [8/13]

◆ BinarySpaceTree() [9/13]

◆ BinarySpaceTree() [10/13]

◆ BinarySpaceTree() [11/13]

◆ BinarySpaceTree() [12/13]

◆ ~BinarySpaceTree()

◆ BinarySpaceTree() [13/13]

Member Function Documentation

◆ Child()

◆ Descendant()

◆ FurthestDescendantDistance()

◆ FurthestPointDistance()

◆ GetFurthestChild() [1/2]

◆ GetFurthestChild() [2/2]

◆ GetNearestChild() [1/2]

◆ GetNearestChild() [2/2]

◆ MinimumBoundDistance()

◆ NumChildren()

◆ NumDescendants()

◆ NumPoints()

◆ operator=() [1/2]

◆ operator=() [2/2]

◆ ParentDistance() [1/2]

◆ ParentDistance() [2/2]

◆ Point()