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

#include <nanoflann.hpp>

Collaboration diagram for nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >:

Public Types
using	ElementType = typename Distance::ElementType
using	DistanceType = typename Distance::DistanceType
using	Offset = typename KDTreeSingleIndexDynamicAdaptor_< Distance, DatasetAdaptor, DIM >::Offset
using	Size = typename KDTreeSingleIndexDynamicAdaptor_< Distance, DatasetAdaptor, DIM >::Size
using	Dimension = typename KDTreeSingleIndexDynamicAdaptor_< Distance, DatasetAdaptor, DIM >::Dimension

Public Member Functions
const std::vector< index_container_t > &	getAllIndices () const
	KDTreeSingleIndexDynamicAdaptor (const int dimensionality, const DatasetAdaptor &inputData, const KDTreeSingleIndexAdaptorParams &params=KDTreeSingleIndexAdaptorParams(), const size_t maximumPointCount=1000000000U)
	KDTreeSingleIndexDynamicAdaptor (const KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType > &)=delete
void	addPoints (IndexType start, IndexType end)
void	removePoint (size_t idx)
template<typename RESULTSET >
bool	findNeighbors (RESULTSET &result, const ElementType *vec, const SearchParameters &searchParams={}) const

Public Attributes
Distance	distance_

Protected Types
using	index_container_t = KDTreeSingleIndexDynamicAdaptor_< Distance, DatasetAdaptor, DIM, IndexType >

Protected Attributes
Size	leaf_max_size_
Size	treeCount_
Size	pointCount_
const DatasetAdaptor &	dataset_
	The source of our data.
std::vector< int >	treeIndex_
std::unordered_set< int >	removedPoints_
KDTreeSingleIndexAdaptorParams	index_params_
Dimension	dim_
	Dimensionality of each data point.
std::vector< index_container_t >	index_

Detailed Description

template<typename Distance, class DatasetAdaptor, int32_t DIM = -1, typename IndexType = uint32_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

Member Typedef Documentation

Dimension

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

using nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Dimension = typename KDTreeSingleIndexDynamicAdaptor_<Distance, DatasetAdaptor, DIM>::Dimension

DistanceType

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

using nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::DistanceType = typename Distance::DistanceType

ElementType

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

using nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::ElementType = typename Distance::ElementType

index_container_t

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

using nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::index_container_t = KDTreeSingleIndexDynamicAdaptor_<Distance, DatasetAdaptor, DIM, IndexType>

protected

Offset

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

using nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Offset = typename KDTreeSingleIndexDynamicAdaptor_<Distance, DatasetAdaptor, DIM>::Offset

Size

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

using nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Size = typename KDTreeSingleIndexDynamicAdaptor_<Distance, DatasetAdaptor, DIM>::Size

Constructor & Destructor Documentation

KDTreeSingleIndexDynamicAdaptor() [1/2]

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::KDTreeSingleIndexDynamicAdaptor ( const int  dimensionality, const DatasetAdaptor &  inputData, const KDTreeSingleIndexAdaptorParams &  params = KDTreeSingleIndexAdaptorParams(), const size_t  maximumPointCount = 1000000000U  )

inlineexplicit

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. Its lifetime must be equal or longer than that of the instance of this class.
params	Basically, the maximum leaf node size

KDTreeSingleIndexDynamicAdaptor() [2/2]

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

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

explicitdelete

Deleted copy constructor

Member Function Documentation

addPoints()

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

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

inline

Add points to the set, Inserts all points from [start, end]

findNeighbors()

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

template<typename RESULTSET >

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

Note

If L2 norms are used, all returned distances are actually squared distances.

getAllIndices()

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

const std::vector< index_container_t > & nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::getAllIndices ( ) const

inline

Get a const ref to the internal list of indices; the number of indices is adapted dynamically as the dataset grows in size.

removePoint()

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

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

inline

Remove a point from the set (Lazy Deletion)

Member Data Documentation

dataset_

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

const DatasetAdaptor& nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::dataset_

protected

The source of our data.

The dataset used by this index

dim_

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

Dimension nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::dim_

protected

Dimensionality of each data point.

distance_

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

Distance nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::distance_

index_

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

std::vector<index_container_t> nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::index_

protected

index_params_

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

KDTreeSingleIndexAdaptorParams nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::index_params_

protected

leaf_max_size_

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

Size nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::leaf_max_size_

protected

pointCount_

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

Size nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::pointCount_

protected

removedPoints_

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

std::unordered_set<int> nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::removedPoints_

protected

treeCount_

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

Size nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::treeCount_

protected

treeIndex_

template<typename Distance , class DatasetAdaptor , int32_t DIM = -1, typename IndexType = uint32_t>

std::vector<int> nanoflann::KDTreeSingleIndexDynamicAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::treeIndex_

protected

treeIndex[idx] is the index of tree in which point at idx is stored. treeIndex[idx]=-1 means that point has been removed.

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

• src/lib/patchGeneration/nanoflann.hpp