MLPACK
1.0.10

The RangeSearch class is a template class for performing range searches. More...
Public Member Functions  
RangeSearch (const typename TreeType::Mat &referenceSet, const typename TreeType::Mat &querySet, const bool naive=false, const bool singleMode=false, const MetricType metric=MetricType())  
Initialize the RangeSearch object with a different reference set and a query set. More...  
RangeSearch (const typename TreeType::Mat &referenceSet, const bool naive=false, const bool singleMode=false, const MetricType metric=MetricType())  
Initialize the RangeSearch object with only a reference set, which will also be used as a query set. More...  
RangeSearch (TreeType *referenceTree, TreeType *queryTree, const typename TreeType::Mat &referenceSet, const typename TreeType::Mat &querySet, const bool singleMode=false, const MetricType metric=MetricType())  
Initialize the RangeSearch object with the given datasets and preconstructed trees. More...  
RangeSearch (TreeType *referenceTree, const typename TreeType::Mat &referenceSet, const bool singleMode=false, const MetricType metric=MetricType())  
Initialize the RangeSearch object with the given reference dataset and preconstructed tree. More...  
~RangeSearch ()  
Destroy the RangeSearch object. More...  
void  Search (const math::Range &range, std::vector< std::vector< size_t > > &neighbors, std::vector< std::vector< double > > &distances) 
Search for all points in the given range, returning the results in the neighbors and distances objects. More...  
std::string  ToString () const 
Private Attributes  
bool  hasQuerySet 
If true, a query set was passed; if false, the query set is the reference set. More...  
MetricType  metric 
Instantiated distance metric. More...  
bool  naive 
If true, O(n^2) naive computation is used. More...  
size_t  numPrunes 
The number of pruned nodes during computation. More...  
std::vector< size_t >  oldFromNewQueries 
Mappings to old query indices (used when this object builds trees). More...  
std::vector< size_t >  oldFromNewReferences 
Mappings to old reference indices (used when this object builds trees). More...  
TreeType::Mat  queryCopy 
Copy of query matrix; used when a tree is built internally. More...  
const TreeType::Mat &  querySet 
Query set (data should be accessed using this). More...  
TreeType *  queryTree 
Query tree (may be NULL). More...  
TreeType::Mat  referenceCopy 
Copy of reference matrix; used when a tree is built internally. More...  
const TreeType::Mat &  referenceSet 
Reference set (data should be accessed using this). More...  
TreeType *  referenceTree 
Reference tree. More...  
bool  singleMode 
If true, singletree computation is used. More...  
bool  treeOwner 
If true, this object is responsible for deleting the trees. More...  
Detailed Description
template<typename MetricType = mlpack::metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, RangeSearchStat>>
class mlpack::range::RangeSearch< MetricType, TreeType >
The RangeSearch class is a template class for performing range searches.
It is implemented in the style of a generalized treeindependent dualtree algorithm; for more details on the actual algorithm, see the RangeSearchRules class.
Definition at line 43 of file range_search.hpp.
Constructor & Destructor Documentation
◆ RangeSearch() [1/4]
mlpack::range::RangeSearch< MetricType, TreeType >::RangeSearch  (  const typename TreeType::Mat &  referenceSet, 
const typename TreeType::Mat &  querySet,  
const bool  naive = false , 

const bool  singleMode = false , 

const MetricType  metric = MetricType() 

) 
Initialize the RangeSearch object with a different reference set and a query set.
Optionally, perform the computation in naive mode or singletree mode, and set the leaf size used for treebuilding. Additionally, an instantiated metric can be given, for cases where the distance metric holds data.
This method will copy the matrices to internal copies, which are rearranged during treebuilding. You can avoid this extra copy by preconstructing the trees and passing them using a different constructor.
 Parameters

referenceSet Reference dataset. querySet Query dataset. naive Whether the computation should be done in O(n^2) naive mode. singleMode Whether singletree computation should be used (as opposed to dualtree computation). leafSize The leaf size to be used during tree construction. metric Instantiated distance metric.
◆ RangeSearch() [2/4]
mlpack::range::RangeSearch< MetricType, TreeType >::RangeSearch  (  const typename TreeType::Mat &  referenceSet, 
const bool  naive = false , 

const bool  singleMode = false , 

const MetricType  metric = MetricType() 

) 
Initialize the RangeSearch object with only a reference set, which will also be used as a query set.
Optionally, perform the computation in naive mode or singletree mode, and set the leaf size used for treebuilding. Additionally an instantiated metric can be given, for cases where the distance metric holds data.
This method will copy the reference matrix to an internal copy, which is rearranged during treebuilding. You can avoid this extra copy by preconstructing the reference tree and passing it using a different constructor.
 Parameters

referenceSet Reference dataset. naive Whether the computation should be done in O(n^2) naive mode. singleMode Whether singletree computation should be used (as opposed to dualtree computation). leafSize The leaf size to be used during tree construction. metric Instantiated distance metric.
◆ RangeSearch() [3/4]
mlpack::range::RangeSearch< MetricType, TreeType >::RangeSearch  (  TreeType *  referenceTree, 
TreeType *  queryTree,  
const typename TreeType::Mat &  referenceSet,  
const typename TreeType::Mat &  querySet,  
const bool  singleMode = false , 

const MetricType  metric = MetricType() 

) 
Initialize the RangeSearch object with the given datasets and preconstructed trees.
It is assumed that the points in referenceSet and querySet correspond to the points in referenceTree and queryTree, respectively. Optionally, choose to use singletree mode. Naive mode is not available as an option for this constructor; instead, to run naive computation, construct a tree with all the points in one leaf (i.e. leafSize = number of points). Additionally, an instantiated distance metric can be given, for cases where the distance metric holds data.
There is no copying of the data matrices in this constructor (because treebuilding is not necessary), so this is the constructor to use when copies absolutely must be avoided.
 Note
 Because treebuilding (at least with BinarySpaceTree) modifies the ordering of a matrix, be sure you pass the modified matrix to this object! In addition, mapping the points of the matrix back to their original indices is not done when this constructor is used.
 Parameters

referenceTree Prebuilt tree for reference points. queryTree Prebuilt tree for query points. referenceSet Set of reference points corresponding to referenceTree. querySet Set of query points corresponding to queryTree. singleMode Whether singletree computation should be used (as opposed to dualtree computation). metric Instantiated distance metric.
◆ RangeSearch() [4/4]
mlpack::range::RangeSearch< MetricType, TreeType >::RangeSearch  (  TreeType *  referenceTree, 
const typename TreeType::Mat &  referenceSet,  
const bool  singleMode = false , 

const MetricType  metric = MetricType() 

) 
Initialize the RangeSearch object with the given reference dataset and preconstructed tree.
It is assumed that the points in referenceSet correspond to the points in referenceTree. Optionally, choose to use singletree mode. Naive mode is not available as an option for this constructor; instead, to run naive computation, construct a tree with all the points in one leaf (i.e. leafSize = number of points). Additionally, an instantiated distance metric can be given, for the case where the distance metric holds data.
There is no copying of the data matrices in this constructor (because treebuilding is not necessary), so this is the constructor to use when copies absolutely must be avoided.
 Note
 Because treebuilding (at least with BinarySpaceTree) modifies the ordering of a matrix, be sure you pass the modified matrix to this object! In addition, mapping the points of the matrix back to their original indices is not done when this constructor is used.
 Parameters

referenceTree Prebuilt tree for reference points. referenceSet Set of reference points corresponding to referenceTree. singleMode Whether singletree computation should be used (as opposed to dualtree computation). metric Instantiated distance metric.
◆ ~RangeSearch()
mlpack::range::RangeSearch< MetricType, TreeType >::~RangeSearch  (  ) 
Destroy the RangeSearch object.
If trees were created, they will be deleted.
Member Function Documentation
◆ Search()
void mlpack::range::RangeSearch< MetricType, TreeType >::Search  (  const math::Range &  range, 
std::vector< std::vector< size_t > > &  neighbors,  
std::vector< std::vector< double > > &  distances  
) 
Search for all points in the given range, returning the results in the neighbors and distances objects.
Each entry in the external vector corresponds to a query point. Each of these entries holds a vector which contains the indices and distances of the reference points falling into the given range.
That is:
 neighbors.size() and distances.size() both equal the number of query points.
 neighbors[i] contains the indices of all the points in the reference set which have distances inside the given range to query point i.
 distances[i] contains all of the distances corresponding to the indices contained in neighbors[i].
 neighbors[i] and distances[i] are not sorted in any particular order.
 Parameters

range Range of distances in which to search. neighbors Object which will hold the list of neighbors for each point which fell into the given range, for each query point. distances Object which will hold the list of distances for each point which fell into the given range, for each query point.
◆ ToString()
std::string mlpack::range::RangeSearch< MetricType, TreeType >::ToString  (  )  const 
Member Data Documentation
◆ hasQuerySet

private 
If true, a query set was passed; if false, the query set is the reference set.
Definition at line 227 of file range_search.hpp.
◆ metric

private 
Instantiated distance metric.
Definition at line 235 of file range_search.hpp.
◆ naive

private 
If true, O(n^2) naive computation is used.
Definition at line 230 of file range_search.hpp.
◆ numPrunes

private 
The number of pruned nodes during computation.
Definition at line 238 of file range_search.hpp.
◆ oldFromNewQueries

private 
Mappings to old query indices (used when this object builds trees).
Definition at line 221 of file range_search.hpp.
◆ oldFromNewReferences

private 
Mappings to old reference indices (used when this object builds trees).
Definition at line 219 of file range_search.hpp.
◆ queryCopy

private 
Copy of query matrix; used when a tree is built internally.
Definition at line 206 of file range_search.hpp.
◆ querySet

private 
Query set (data should be accessed using this).
Definition at line 211 of file range_search.hpp.
◆ queryTree

private 
Query tree (may be NULL).
Definition at line 216 of file range_search.hpp.
◆ referenceCopy

private 
Copy of reference matrix; used when a tree is built internally.
Definition at line 204 of file range_search.hpp.
◆ referenceSet

private 
Reference set (data should be accessed using this).
Definition at line 209 of file range_search.hpp.
◆ referenceTree

private 
Reference tree.
Definition at line 214 of file range_search.hpp.
◆ singleMode

private 
If true, singletree computation is used.
Definition at line 232 of file range_search.hpp.
◆ treeOwner

private 
If true, this object is responsible for deleting the trees.
Definition at line 224 of file range_search.hpp.
The documentation for this class was generated from the following file:
 src/mlpack/methods/range_search/range_search.hpp
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