#include <knncpp.h>

Public Types
typedef Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic >	Matrix

typedef Eigen::Matrix< Scalar, Eigen::Dynamic, 1 >	Vector

typedef knncpp::Matrixi	Matrixi

Public Member Functions
	BruteForce ()=default

	BruteForce (const Matrix &data, const bool copy=false)

void	setSorted (const bool sorted)

void	setTakeRoot (const bool takeRoot)

void	setThreads (const unsigned int threads)

void	setMaxDistance (const Scalar maxDist)

void	setData (const Matrix &data, const bool copy=false)

void	setDistance (const Distance &distance)

void	build ()

template<typename Derived >
void	query (const Eigen::MatrixBase< Derived > &queryPoints, const size_t knn, Matrixi &indices, Matrix &distances) const

Index	size () const

Index	dimension () const

Detailed Description

template<typename Scalar, typename Distance = EuclideanDistance<Scalar>>
class knncpp::BruteForce< Scalar, Distance >

Class for performing brute force knn search.

Definition at line 359 of file knncpp.h.

Member Typedef Documentation

◆ Matrix

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> knncpp::BruteForce< Scalar, Distance >::Matrix

Definition at line 361 of file knncpp.h.

◆ Matrixi

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

typedef knncpp::Matrixi knncpp::BruteForce< Scalar, Distance >::Matrixi

Definition at line 363 of file knncpp.h.

◆ Vector

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> knncpp::BruteForce< Scalar, Distance >::Vector

Definition at line 362 of file knncpp.h.

Constructor & Destructor Documentation

◆ BruteForce() [1/2]

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

knncpp::BruteForce< Scalar, Distance >::BruteForce ( )

default

◆ BruteForce() [2/2]

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

knncpp::BruteForce< Scalar, Distance >::BruteForce	(	const Matrix &	data,
		const bool	copy = `false`
	)

inline

Constructs a brute force instance with the given data.

Parameters

data	NxM matrix, M points of dimension N
copy	if true copies the data, otherwise assumes static data

Definition at line 381 of file knncpp.h.

References copy, and knncpp::BruteForce< Scalar, Distance >::setData().

Member Function Documentation

◆ build()

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

void knncpp::BruteForce< Scalar, Distance >::build ( )

inline

Definition at line 423 of file knncpp.h.

◆ dimension()

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

Index knncpp::BruteForce< Scalar, Distance >::dimension ( ) const

inline

Returns the dimension of the data points in the search index.

Returns: dimension of data points

Definition at line 481 of file knncpp.h.

Referenced by knncpp::BruteForce< Scalar, Distance >::query().

◆ query()

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

template<typename Derived >

void knncpp::BruteForce< Scalar, Distance >::query	(	const Eigen::MatrixBase< Derived > &	queryPoints,
		const size_t	knn,
		Matrixi &	indices,
		Matrix &	distances
	)		const

inline

Definition at line 426 of file knncpp.h.

References knncpp::BruteForce< Scalar, Distance >::dimension(), dist(), knncpp::QueryHeap< Scalar >::front(), knncpp::QueryHeap< Scalar >::full(), knncpp::QueryHeap< Scalar >::pop(), knncpp::QueryHeap< Scalar >::push(), and knncpp::QueryHeap< Scalar >::sort().

◆ setData()

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

void knncpp::BruteForce< Scalar, Distance >::setData	(	const Matrix &	data,
		const bool	copy = `false`
	)

inline

Set the data points used for this tree. This does not build the tree.

Parameters

data	NxM matrix, M points of dimension N
copy	if true data is copied, assumes static data otherwise

Definition at line 412 of file knncpp.h.

References copy.

Referenced by knncpp::BruteForce< Scalar, Distance >::BruteForce().

◆ setDistance()

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

void knncpp::BruteForce< Scalar, Distance >::setDistance ( const Distance & distance )

inline

Definition at line 421 of file knncpp.h.

◆ setMaxDistance()

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

void knncpp::BruteForce< Scalar, Distance >::setMaxDistance ( const Scalar maxDist )

inline

Set the maximum distance for querying the tree. The search will be pruned if the maximum distance is set to any positive number.

Parameters

maxDist maximum distance, <= 0 for no limit

Definition at line 406 of file knncpp.h.

◆ setSorted()

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

void knncpp::BruteForce< Scalar, Distance >::setSorted ( const bool sorted )

inline

Set if the points returned by the queries should be sorted according to their distance to the query points.

Parameters

sorted sort query results

Definition at line 388 of file knncpp.h.

◆ setTakeRoot()

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

void knncpp::BruteForce< Scalar, Distance >::setTakeRoot ( const bool takeRoot )

inline

Set if the distances after the query should be rooted or not. Taking the root of the distances increases query time, but the function will return true distances instead of their powered versions.

Parameters

takeRoot set true if root should be taken else false

Definition at line 395 of file knncpp.h.

◆ setThreads()

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

void knncpp::BruteForce< Scalar, Distance >::setThreads ( const unsigned int threads )

inline

Set the amount of threads that should be used for querying. OpenMP has to be enabled for this to work.

Parameters

threads amount of threads, 0 for optimal choice

Definition at line 400 of file knncpp.h.

◆ size()

template<typename Scalar , typename Distance = EuclideanDistance<Scalar>>

Index knncpp::BruteForce< Scalar, Distance >::size ( void ) const

inline

Returns the amount of data points stored in the search index.

Returns: number of data points

Definition at line 477 of file knncpp.h.

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

/root/ACloudViewer/plugins/core/Standard/qTreeIso/include/knncpp.h

Public Types

Public Member Functions

Detailed Description

template<typename Scalar, typename Distance = EuclideanDistance<Scalar>> class knncpp::BruteForce< Scalar, Distance >

Member Typedef Documentation

◆ Matrix

◆ Matrixi

◆ Vector

Constructor & Destructor Documentation

◆ BruteForce() [1/2]

◆ BruteForce() [2/2]

Member Function Documentation

◆ build()

◆ dimension()

◆ query()

◆ setData()

◆ setDistance()

◆ setMaxDistance()

◆ setSorted()

◆ setTakeRoot()

◆ setThreads()

◆ size()

template<typename Scalar, typename Distance = EuclideanDistance<Scalar>>
class knncpp::BruteForce< Scalar, Distance >