nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType > Class Template Reference

#include <nanoflann.hpp>

Public Types
typedef Distance::ElementType	ElementType
typedef Distance::DistanceType	DistanceType

Public Member Functions
	KDTreeSingleIndexDynamicAdaptor (const int dimensionality, DatasetAdaptor &inputData, const KDTreeSingleIndexAdaptorParams &params=KDTreeSingleIndexAdaptorParams(), const int maximumPointCount=1e9)
	~KDTreeSingleIndexDynamicAdaptor ()
void	addPoints (IndexType start, IndexType end)
void	removePoint (int idx)
template<typename RESULTSET >
bool	findNeighbors (RESULTSET &result, const ElementType *vec, const SearchParams &searchParams) const

Public Attributes
Distance	distance

Protected Attributes
size_t	m_leaf_max_size
int	treeCount
int	pointCount
DatasetAdaptor &	dataset
	The source of our data. More...
std::vector< int >	treeIndex
	treeIndex[idx] is the index of tree in which point at idx is stored. treeIndex[idx]=-1 means that point has been removed.
KDTreeSingleIndexAdaptorParams	index_params
int	dim
	Dimensionality of each data point.
std::vector < KDTreeSingleIndexDynamicAdaptor_ < Distance, DatasetAdaptor, DIM > >	index

Detailed Description

template<typename Distance, class DatasetAdaptor, int DIM = -1, typename IndexType = size_t>
class nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >

kd-tree dynaimic index

class to create multiple static index and merge their results to behave as single dynamic index as proposed in Logarithmic Approach.

Example of usage: examples/dynamic_pointcloud_example.cpp

Template Parameters

DatasetAdaptor	The user-provided adaptor (see comments above).
Distance	The distance metric to use: nanoflann::metric_L1, nanoflann::metric_L2, nanoflann::metric_L2_Simple, etc.
DIM	Dimensionality of data points (e.g. 3 for 3D points)
IndexType	Will be typically size_t or int

Constructor & Destructor Documentation

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::KDTreeSingleIndexDynamicAdaptor ( const int  dimensionality, DatasetAdaptor &  inputData, const KDTreeSingleIndexAdaptorParams &  params = KDTreeSingleIndexAdaptorParams(), const int  maximumPointCount = 1e9  )

inline

KDTree constructor

Refer to docs in README.md or online in https://github.com/jlblancoc/nanoflann

The KD-Tree point dimension (the length of each point in the datase, e.g. 3 for 3D points) is determined by means of:

• The DIM template parameter if >0 (highest priority)
• Otherwise, the dimensionality parameter of this constructor.

Parameters

inputData	Dataset with the input features
params	Basically, the maximum leaf node size

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::~KDTreeSingleIndexDynamicAdaptor ( )

inline

Standard destructor

Member Function Documentation

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::addPoints ( IndexType  start, IndexType  end  )

inline

Add points to the set

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

template<typename RESULTSET >

bool nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::findNeighbors ( RESULTSET &  result, const ElementType *  vec, const SearchParams &  searchParams  ) const

inline

Find set of nearest neighbors to vec[0:dim-1]. Their indices are stored inside the result object.

Params: result = the result object in which the indices of the nearest-neighbors are stored vec = the vector for which to search the nearest neighbors

Template Parameters

RESULTSET

Should be any ResultSet<DistanceType>

Returns

True if the requested neighbors could be found.

See Also

knnSearch, radiusSearch

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::removePoint ( int  idx )

inline

Remove a point from the set (Lazy Deletion)

Member Data Documentation

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

DatasetAdaptor& nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::dataset

protected

The source of our data.

The dataset used by this index

---

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

• include/nanoflann.hpp