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/* Author: Mark Moll */
#ifndef FCL_KNN_GREEDY_KCENTERS_H
#define FCL_KNN_GREEDY_KCENTERS_H
#include "fcl/math/sampling.h"
namespace fcl
{
/// @brief An instance of this class can be used to greedily select a given
/// number of representatives from a set of data points that are all far
/// apart from each other.
template<typename _T>
class GreedyKCenters
{
public:
/// @brief The definition of a distance function
typedef boost::function<double(const _T&, const _T&)> DistanceFunction;
GreedyKCenters(void)
{
}
virtual ~GreedyKCenters(void)
{
}
/// @brief Set the distance function to use
void setDistanceFunction(const DistanceFunction &distFun)
{
distFun_ = distFun;
}
/// @brief Get the distance function used
const DistanceFunction& getDistanceFunction(void) const
{
return distFun_;
}
/// @brief Greedy algorithm for selecting k centers
/// @param data a vector of data points
/// @param k the desired number of centers
/// @param centers a vector of length k containing the indices into data of the k centers
/// @param dists a 2-dimensional array such that dists[i][j] is the distance between data[i] and data[center[j]]
void kcenters(const std::vector<_T>& data, unsigned int k,
std::vector<unsigned int>& centers, std::vector<std::vector<double> >& dists)
{
// array containing the minimum distance between each data point
// and the centers computed so far
std::vector<double> minDist(data.size(), std::numeric_limits<double>::infinity());
centers.clear();
centers.reserve(k);
dists.resize(data.size(), std::vector<double>(k));
// first center is picked randomly
centers.push_back(rng_.uniformInt(0, data.size() - 1));
for (unsigned i=1; i<k; ++i)
{
unsigned ind;
const _T& center = data[centers[i - 1]];
double maxDist = -std::numeric_limits<double>::infinity();
for (unsigned j=0; j<data.size(); ++j)
{
if ((dists[j][i-1] = distFun_(data[j], center)) < minDist[j])
minDist[j] = dists[j][i - 1];
// the j-th center is the one furthest away from center 0,..,j-1
if (minDist[j] > maxDist)
{
ind = j;
maxDist = minDist[j];
}
}
// no more centers available
if (maxDist < std::numeric_limits<double>::epsilon()) break;
centers.push_back(ind);
}
const _T& center = data[centers.back()];
unsigned i = centers.size() - 1;
for (unsigned j = 0; j < data.size(); ++j)
dists[j][i] = distFun_(data[j], center);
}
protected:
/// @brief The used distance function
DistanceFunction distFun_;
/// Random number generator used to select first center
RNG rng_;
};
}
#endif
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