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range_search.hpp
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1 
13 #ifndef MLPACK_METHODS_RANGE_SEARCH_RANGE_SEARCH_HPP
14 #define MLPACK_METHODS_RANGE_SEARCH_RANGE_SEARCH_HPP
15 
16 #include <mlpack/prereqs.hpp>
19 #include "range_search_stat.hpp"
20 
21 namespace mlpack {
22 namespace range {
23 
25 class TrainVisitor;
26 
37 template<typename MetricType = metric::EuclideanDistance,
38  typename MatType = arma::mat,
39  template<typename TreeMetricType,
40  typename TreeStatType,
41  typename TreeMatType> class TreeType = tree::KDTree>
43 {
44  public:
46  typedef TreeType<MetricType, RangeSearchStat, MatType> Tree;
47 
64  RangeSearch(MatType referenceSet,
65  const bool naive = false,
66  const bool singleMode = false,
67  const MetricType metric = MetricType());
68 
91  RangeSearch(Tree* referenceTree,
92  const bool singleMode = false,
93  const MetricType metric = MetricType());
94 
105  RangeSearch(const bool naive = false,
106  const bool singleMode = false,
107  const MetricType metric = MetricType());
108 
115  RangeSearch(const RangeSearch& other);
116 
122  RangeSearch(RangeSearch&& other);
123 
131 
136  ~RangeSearch();
137 
149  void Train(MatType referenceSet);
150 
154  void Train(Tree* referenceTree);
155 
183  void Search(const MatType& querySet,
184  const math::Range& range,
185  std::vector<std::vector<size_t>>& neighbors,
186  std::vector<std::vector<double>>& distances);
187 
224  void Search(Tree* queryTree,
225  const math::Range& range,
226  std::vector<std::vector<size_t>>& neighbors,
227  std::vector<std::vector<double>>& distances);
228 
258  void Search(const math::Range& range,
259  std::vector<std::vector<size_t>>& neighbors,
260  std::vector<std::vector<double>>& distances);
261 
263  bool SingleMode() const { return singleMode; }
265  bool& SingleMode() { return singleMode; }
266 
268  bool Naive() const { return naive; }
270  bool& Naive() { return naive; }
271 
273  size_t BaseCases() const { return baseCases; }
275  size_t Scores() const { return scores; }
276 
278  template<typename Archive>
279  void serialize(Archive& ar, const unsigned int version);
280 
282  const MatType& ReferenceSet() const { return *referenceSet; }
283 
285  Tree* ReferenceTree() { return referenceTree; }
286 
287  private:
289  std::vector<size_t> oldFromNewReferences;
291  Tree* referenceTree;
294  const MatType* referenceSet;
295 
297  bool treeOwner;
298 
300  bool naive;
302  bool singleMode;
303 
305  MetricType metric;
306 
308  size_t baseCases;
310  size_t scores;
311 
313  friend class TrainVisitor;
314 };
315 
316 } // namespace range
317 } // namespace mlpack
318 
319 // Include implementation.
320 #include "range_search_impl.hpp"
321 
322 #endif
The RangeSearch class is a template class for performing range searches.
bool & Naive()
Modify whether naive search is being used.
Tree * ReferenceTree()
Return the reference tree (or NULL if in naive mode).
size_t BaseCases() const
Get the number of base cases during the last search.
The core includes that mlpack expects; standard C++ includes and Armadillo.
RangeSearch & operator=(RangeSearch other)
Copy the given RangeSearch model.
A binary space partitioning tree, such as a KD-tree or a ball tree.
void Train(MatType referenceSet)
Set the reference set to a new reference set, and build a tree if necessary.
bool SingleMode() const
Get whether single-tree search is being used.
bool & SingleMode()
Modify whether single-tree search is being used.
void serialize(Archive &ar, const unsigned int version)
Serialize the model.
~RangeSearch()
Destroy the RangeSearch object.
TrainVisitor sets the reference set to a new reference set on the given RSType.
Definition: rs_model.hpp:125
TreeType< MetricType, RangeSearchStat, MatType > Tree
Convenience typedef.
void Search(const MatType &querySet, const math::Range &range, std::vector< std::vector< size_t >> &neighbors, std::vector< std::vector< double >> &distances)
Search for all reference points in the given range for each point in the query set, returning the results in the neighbors and distances objects.
RangeSearch(MatType referenceSet, const bool naive=false, const bool singleMode=false, const MetricType metric=MetricType())
Initialize the RangeSearch object with a given reference dataset (this is the dataset which is search...
const MatType & ReferenceSet() const
Return the reference set.
size_t Scores() const
Get the number of scores during the last search.
LMetric< 2, true > EuclideanDistance
The Euclidean (L2) distance.
Definition: lmetric.hpp:112
bool Naive() const
Get whether naive search is being used.