ra_query_stat.hpp
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1 
13 #ifndef MLPACK_METHODS_RANN_RA_QUERY_STAT_HPP
14 #define MLPACK_METHODS_RANN_RA_QUERY_STAT_HPP
15 
16 #include <mlpack/prereqs.hpp>
17 
19 
22 
23 namespace mlpack {
24 namespace neighbor {
25 
34 template<typename SortPolicy>
36 {
37  public:
42  RAQueryStat() : bound(SortPolicy::WorstDistance()), numSamplesMade(0) { }
43 
47  template<typename TreeType>
48  RAQueryStat(const TreeType& /* node */) :
49  bound(SortPolicy::WorstDistance()),
50  numSamplesMade(0)
51  { }
52 
54  double Bound() const { return bound; }
56  double& Bound() { return bound; }
57 
59  size_t NumSamplesMade() const { return numSamplesMade; }
61  size_t& NumSamplesMade() { return numSamplesMade; }
62 
64  template<typename Archive>
65  void serialize(Archive& ar, const uint32_t /* version */)
66  {
67  ar(CEREAL_NVP(bound));
68  ar(CEREAL_NVP(numSamplesMade));
69  }
70 
71  private:
73  double bound;
75  size_t numSamplesMade;
76 };
77 
78 } // namespace neighbor
79 } // namespace mlpack
80 
81 #endif
double & Bound()
Modify the bound.
Linear algebra utility functions, generally performed on matrices or vectors.
Extra data for each node in the tree.
The core includes that mlpack expects; standard C++ includes and Armadillo.
RAQueryStat()
Initialize the statistic with the worst possible distance according to our sorting policy...
void serialize(Archive &ar, const uint32_t)
Serialize the statistic.
size_t & NumSamplesMade()
Modify the number of samples made.
size_t NumSamplesMade() const
Get the number of samples made.
double Bound() const
Get the bound.
RAQueryStat(const TreeType &)
Initialization for a node.