GreedyKCenters.h
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34 
35 /* Author: Mark Moll */
36 
37 #ifndef OMPL_DATASTRUCTURES_GREEDY_K_CENTERS_
38 #define OMPL_DATASTRUCTURES_GREEDY_K_CENTERS_
39 
40 #include "ompl/util/RandomNumbers.h"
41 
42 namespace ompl
43 {
47  template<typename _T>
49  {
50  public:
52  typedef boost::function<double(const _T&, const _T&)> DistanceFunction;
53 
55  {
56  }
57 
58  virtual ~GreedyKCenters()
59  {
60  }
61 
63  void setDistanceFunction(const DistanceFunction &distFun)
64  {
65  distFun_ = distFun;
66  }
67 
69  const DistanceFunction& getDistanceFunction() const
70  {
71  return distFun_;
72  }
73 
82  void kcenters(const std::vector<_T>& data, unsigned int k,
83  std::vector<unsigned int>& centers, std::vector<std::vector<double> >& dists)
84  {
85  // array containing the minimum distance between each data point
86  // and the centers computed so far
87  std::vector<double> minDist(data.size(), std::numeric_limits<double>::infinity());
88 
89  centers.clear();
90  centers.reserve(k);
91  dists.resize(data.size(), std::vector<double>(k));
92  // first center is picked randomly
93  centers.push_back(rng_.uniformInt(0, data.size() - 1));
94  for (unsigned i=1; i<k; ++i)
95  {
96  unsigned ind;
97  const _T& center = data[centers[i - 1]];
98  double maxDist = -std::numeric_limits<double>::infinity();
99  for (unsigned j=0; j<data.size(); ++j)
100  {
101  if ((dists[j][i-1] = distFun_(data[j], center)) < minDist[j])
102  minDist[j] = dists[j][i - 1];
103  // the j-th center is the one furthest away from center 0,..,j-1
104  if (minDist[j] > maxDist)
105  {
106  ind = j;
107  maxDist = minDist[j];
108  }
109  }
110  // no more centers available
111  if (maxDist < std::numeric_limits<double>::epsilon()) break;
112  centers.push_back(ind);
113  }
114 
115  const _T& center = data[centers.back()];
116  unsigned i = centers.size() - 1;
117  for (unsigned j = 0; j < data.size(); ++j)
118  dists[j][i] = distFun_(data[j], center);
119  }
120 
121  protected:
123  DistanceFunction distFun_;
124 
127  };
128 }
129 
130 #endif
DistanceFunction distFun_
The used distance function.
An instance of this class can be used to greedily select a given number of representatives from a set...
boost::function< double(const _T &, const _T &)> DistanceFunction
The definition of a distance function.
Main namespace. Contains everything in this library.
Definition: Cost.h:42
Random number generation. An instance of this class cannot be used by multiple threads at once (membe...
Definition: RandomNumbers.h:54
const DistanceFunction & getDistanceFunction() const
Get the distance function used.
void setDistanceFunction(const DistanceFunction &distFun)
Set the distance function to use.
void kcenters(const std::vector< _T > &data, unsigned int k, std::vector< unsigned int > &centers, std::vector< std::vector< double > > &dists)
Greedy algorithm for selecting k centers.
int uniformInt(int lower_bound, int upper_bound)
Generate a random integer within given bounds: [lower_bound, upper_bound].
Definition: RandomNumbers.h:75