.TH "mlpack::range::RangeSearch< MetricType, TreeType >" 3 "Tue Sep 9 2014" "Version 1.0.10" "MLPACK" \" -*- nroff -*-
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.SH NAME
mlpack::range::RangeSearch< MetricType, TreeType > \- 
.PP
The \fBRangeSearch\fP class is a template class for performing range searches\&.  

.SH SYNOPSIS
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.PP
.SS "Public Member Functions"

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.RI "\fBRangeSearch\fP (const typename TreeType::Mat &\fBreferenceSet\fP, const typename TreeType::Mat &\fBquerySet\fP, const bool \fBnaive\fP=false, const bool \fBsingleMode\fP=false, const MetricType \fBmetric\fP=MetricType())"
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.RI "\fIInitialize the \fBRangeSearch\fP object with a different reference set and a query set\&. \fP"
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.RI "\fBRangeSearch\fP (const typename TreeType::Mat &\fBreferenceSet\fP, const bool \fBnaive\fP=false, const bool \fBsingleMode\fP=false, const MetricType \fBmetric\fP=MetricType())"
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.RI "\fIInitialize the \fBRangeSearch\fP object with only a reference set, which will also be used as a query set\&. \fP"
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.RI "\fBRangeSearch\fP (TreeType *\fBreferenceTree\fP, TreeType *\fBqueryTree\fP, const typename TreeType::Mat &\fBreferenceSet\fP, const typename TreeType::Mat &\fBquerySet\fP, const bool \fBsingleMode\fP=false, const MetricType \fBmetric\fP=MetricType())"
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.RI "\fIInitialize the \fBRangeSearch\fP object with the given datasets and pre-constructed trees\&. \fP"
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.RI "\fBRangeSearch\fP (TreeType *\fBreferenceTree\fP, const typename TreeType::Mat &\fBreferenceSet\fP, const bool \fBsingleMode\fP=false, const MetricType \fBmetric\fP=MetricType())"
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.RI "\fIInitialize the \fBRangeSearch\fP object with the given reference dataset and pre-constructed tree\&. \fP"
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.RI "\fB~RangeSearch\fP ()"
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.RI "\fIDestroy the \fBRangeSearch\fP object\&. \fP"
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.RI "void \fBSearch\fP (const \fBmath::Range\fP &range, std::vector< std::vector< size_t > > &neighbors, std::vector< std::vector< double > > &distances)"
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.RI "\fISearch for all points in the given range, returning the results in the neighbors and distances objects\&. \fP"
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.RI "std::string \fBToString\fP () const "
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.SS "Private Attributes"

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.RI "bool \fBhasQuerySet\fP"
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.RI "\fIIf true, a query set was passed; if false, the query set is the reference set\&. \fP"
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.RI "MetricType \fBmetric\fP"
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.RI "\fIInstantiated distance metric\&. \fP"
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.RI "bool \fBnaive\fP"
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.RI "\fIIf true, O(n^2) naive computation is used\&. \fP"
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.RI "size_t \fBnumPrunes\fP"
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.RI "\fIThe number of pruned nodes during computation\&. \fP"
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.RI "std::vector< size_t > \fBoldFromNewQueries\fP"
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.RI "\fIMappings to old query indices (used when this object builds trees)\&. \fP"
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.RI "std::vector< size_t > \fBoldFromNewReferences\fP"
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.RI "\fIMappings to old reference indices (used when this object builds trees)\&. \fP"
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.RI "TreeType::Mat \fBqueryCopy\fP"
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.RI "\fICopy of query matrix; used when a tree is built internally\&. \fP"
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.RI "const TreeType::Mat & \fBquerySet\fP"
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.RI "\fIQuery set (data should be accessed using this)\&. \fP"
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.RI "TreeType * \fBqueryTree\fP"
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.RI "\fIQuery tree (may be NULL)\&. \fP"
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.RI "TreeType::Mat \fBreferenceCopy\fP"
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.RI "\fICopy of reference matrix; used when a tree is built internally\&. \fP"
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.RI "const TreeType::Mat & \fBreferenceSet\fP"
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.RI "\fIReference set (data should be accessed using this)\&. \fP"
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.RI "TreeType * \fBreferenceTree\fP"
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.RI "\fIReference tree\&. \fP"
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.RI "bool \fBsingleMode\fP"
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.RI "\fIIf true, single-tree computation is used\&. \fP"
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.RI "bool \fBtreeOwner\fP"
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.RI "\fIIf true, this object is responsible for deleting the trees\&. \fP"
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.SH "Detailed Description"
.PP 

.SS "template<typename MetricType = mlpack::metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>>class mlpack::range::RangeSearch< MetricType, TreeType >"
The \fBRangeSearch\fP class is a template class for performing range searches\&. 

It is implemented in the style of a generalized tree-independent dual-tree algorithm; for more details on the actual algorithm, see the \fBRangeSearchRules\fP class\&. 
.PP
Definition at line 43 of file range_search\&.hpp\&.
.SH "Constructor & Destructor Documentation"
.PP 
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::\fBRangeSearch\fP (const typename TreeType::Mat &referenceSet, const typename TreeType::Mat &querySet, const boolnaive = \fCfalse\fP, const boolsingleMode = \fCfalse\fP, const MetricTypemetric = \fCMetricType()\fP)"

.PP
Initialize the \fBRangeSearch\fP object with a different reference set and a query set\&. Optionally, perform the computation in naive mode or single-tree mode, and set the leaf size used for tree-building\&. Additionally, an instantiated metric can be given, for cases where the distance metric holds data\&.
.PP
This method will copy the matrices to internal copies, which are rearranged during tree-building\&. You can avoid this extra copy by pre-constructing the trees and passing them using a different constructor\&.
.PP
\fBParameters:\fP
.RS 4
\fIreferenceSet\fP Reference dataset\&. 
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\fIquerySet\fP Query dataset\&. 
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\fInaive\fP Whether the computation should be done in O(n^2) naive mode\&. 
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\fIsingleMode\fP Whether single-tree computation should be used (as opposed to dual-tree computation)\&. 
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\fIleafSize\fP The leaf size to be used during tree construction\&. 
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\fImetric\fP Instantiated distance metric\&. 
.RE
.PP

.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::\fBRangeSearch\fP (const typename TreeType::Mat &referenceSet, const boolnaive = \fCfalse\fP, const boolsingleMode = \fCfalse\fP, const MetricTypemetric = \fCMetricType()\fP)"

.PP
Initialize the \fBRangeSearch\fP object with only a reference set, which will also be used as a query set\&. Optionally, perform the computation in naive mode or single-tree mode, and set the leaf size used for tree-building\&. Additionally an instantiated metric can be given, for cases where the distance metric holds data\&.
.PP
This method will copy the reference matrix to an internal copy, which is rearranged during tree-building\&. You can avoid this extra copy by pre-constructing the reference tree and passing it using a different constructor\&.
.PP
\fBParameters:\fP
.RS 4
\fIreferenceSet\fP Reference dataset\&. 
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\fInaive\fP Whether the computation should be done in O(n^2) naive mode\&. 
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\fIsingleMode\fP Whether single-tree computation should be used (as opposed to dual-tree computation)\&. 
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\fIleafSize\fP The leaf size to be used during tree construction\&. 
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\fImetric\fP Instantiated distance metric\&. 
.RE
.PP

.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::\fBRangeSearch\fP (TreeType *referenceTree, TreeType *queryTree, const typename TreeType::Mat &referenceSet, const typename TreeType::Mat &querySet, const boolsingleMode = \fCfalse\fP, const MetricTypemetric = \fCMetricType()\fP)"

.PP
Initialize the \fBRangeSearch\fP object with the given datasets and pre-constructed trees\&. It is assumed that the points in referenceSet and querySet correspond to the points in referenceTree and queryTree, respectively\&. Optionally, choose to use single-tree 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\&.
.PP
There is no copying of the data matrices in this constructor (because tree-building is not necessary), so this is the constructor to use when copies absolutely must be avoided\&.
.PP
\fBNote:\fP
.RS 4
Because tree-building (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\&. 
.RE
.PP
\fBParameters:\fP
.RS 4
\fIreferenceTree\fP Pre-built tree for reference points\&. 
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\fIqueryTree\fP Pre-built tree for query points\&. 
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\fIreferenceSet\fP Set of reference points corresponding to referenceTree\&. 
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\fIquerySet\fP Set of query points corresponding to queryTree\&. 
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\fIsingleMode\fP Whether single-tree computation should be used (as opposed to dual-tree computation)\&. 
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\fImetric\fP Instantiated distance metric\&. 
.RE
.PP

.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::\fBRangeSearch\fP (TreeType *referenceTree, const typename TreeType::Mat &referenceSet, const boolsingleMode = \fCfalse\fP, const MetricTypemetric = \fCMetricType()\fP)"

.PP
Initialize the \fBRangeSearch\fP object with the given reference dataset and pre-constructed tree\&. It is assumed that the points in referenceSet correspond to the points in referenceTree\&. Optionally, choose to use single-tree 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\&.
.PP
There is no copying of the data matrices in this constructor (because tree-building is not necessary), so this is the constructor to use when copies absolutely must be avoided\&.
.PP
\fBNote:\fP
.RS 4
Because tree-building (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\&. 
.RE
.PP
\fBParameters:\fP
.RS 4
\fIreferenceTree\fP Pre-built tree for reference points\&. 
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\fIreferenceSet\fP Set of reference points corresponding to referenceTree\&. 
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\fIsingleMode\fP Whether single-tree computation should be used (as opposed to dual-tree computation)\&. 
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\fImetric\fP Instantiated distance metric\&. 
.RE
.PP

.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::~\fBRangeSearch\fP ()"

.PP
Destroy the \fBRangeSearch\fP object\&. If trees were created, they will be deleted\&. 
.SH "Member Function Documentation"
.PP 
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> void \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::Search (const \fBmath::Range\fP &range, std::vector< std::vector< size_t > > &neighbors, std::vector< std::vector< double > > &distances)"

.PP
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\&.
.PP
That is:
.PP
.IP "\(bu" 2
neighbors\&.size() and distances\&.size() both equal the number of query points\&.
.IP "\(bu" 2
neighbors[i] contains the indices of all the points in the reference set which have distances inside the given range to query point i\&.
.IP "\(bu" 2
distances[i] contains all of the distances corresponding to the indices contained in neighbors[i]\&.
.IP "\(bu" 2
neighbors[i] and distances[i] are not sorted in any particular order\&.
.PP
.PP
\fBParameters:\fP
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\fIrange\fP Range of distances in which to search\&. 
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\fIneighbors\fP Object which will hold the list of neighbors for each point which fell into the given range, for each query point\&. 
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\fIdistances\fP Object which will hold the list of distances for each point which fell into the given range, for each query point\&. 
.RE
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.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> std::string \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::ToString () const"

.SH "Member Data Documentation"
.PP 
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> bool \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::hasQuerySet\fC [private]\fP"

.PP
If true, a query set was passed; if false, the query set is the reference set\&. 
.PP
Definition at line 227 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> MetricType \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::metric\fC [private]\fP"

.PP
Instantiated distance metric\&. 
.PP
Definition at line 235 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> bool \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::naive\fC [private]\fP"

.PP
If true, O(n^2) naive computation is used\&. 
.PP
Definition at line 230 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> size_t \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::numPrunes\fC [private]\fP"

.PP
The number of pruned nodes during computation\&. 
.PP
Definition at line 238 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> std::vector<size_t> \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::oldFromNewQueries\fC [private]\fP"

.PP
Mappings to old query indices (used when this object builds trees)\&. 
.PP
Definition at line 221 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> std::vector<size_t> \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::oldFromNewReferences\fC [private]\fP"

.PP
Mappings to old reference indices (used when this object builds trees)\&. 
.PP
Definition at line 219 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> TreeType::Mat \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::queryCopy\fC [private]\fP"

.PP
Copy of query matrix; used when a tree is built internally\&. 
.PP
Definition at line 206 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> const TreeType::Mat& \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::querySet\fC [private]\fP"

.PP
Query set (data should be accessed using this)\&. 
.PP
Definition at line 211 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> TreeType* \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::queryTree\fC [private]\fP"

.PP
Query tree (may be NULL)\&. 
.PP
Definition at line 216 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> TreeType::Mat \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::referenceCopy\fC [private]\fP"

.PP
Copy of reference matrix; used when a tree is built internally\&. 
.PP
Definition at line 204 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> const TreeType::Mat& \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::referenceSet\fC [private]\fP"

.PP
Reference set (data should be accessed using this)\&. 
.PP
Definition at line 209 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> TreeType* \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::referenceTree\fC [private]\fP"

.PP
Reference tree\&. 
.PP
Definition at line 214 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> bool \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::singleMode\fC [private]\fP"

.PP
If true, single-tree computation is used\&. 
.PP
Definition at line 232 of file range_search\&.hpp\&.
.SS "template<typename MetricType  = mlpack::metric::EuclideanDistance, typename TreeType  = tree::BinarySpaceTree<bound::HRectBound<2>,                                                   RangeSearchStat>> bool \fBmlpack::range::RangeSearch\fP< MetricType, TreeType >::treeOwner\fC [private]\fP"

.PP
If true, this object is responsible for deleting the trees\&. 
.PP
Definition at line 224 of file range_search\&.hpp\&.

.SH "Author"
.PP 
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