DBSCANT.hh

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#ifndef DBSCAN_HH_
#define DBSCAN_HH_
 
#include <vector>
#include <iterator>
#include <algorithm>
 
/*
 * Private functions.
 */
#include "DBSCANT_impl.hh"
 
namespace ACG {
namespace Algorithm {
 
template<typename INPUT_ITERATOR, typename DISTANCE_FUNC, typename OUTPUT_ITERATOR, typename WEIGHT_FUNC>
int DBSCAN(const INPUT_ITERATOR first, const INPUT_ITERATOR last, DISTANCE_FUNC distance_func,
           OUTPUT_ITERATOR result, const double epsilon, const double n_min, WEIGHT_FUNC weight_func) {
 
    const size_t input_size = std::distance(first, last);
 
    std::vector<int> id_cache(input_size, -1);
 
    int idx = 0;
    int current_cluster_id = 0;
 
    for (INPUT_ITERATOR it = first; it != last; ++it, ++idx) {
 
        // Visit every element only once.
        if (id_cache[idx] >= 0) continue;
 
        // Gather neighborhood.
        std::vector<INPUT_ITERATOR> neighborhood; neighborhood.reserve(input_size);
        _DBSCAN_PRIVATE::region_query(first, last, it, distance_func, std::back_inserter(neighborhood), epsilon);
 
        if (_DBSCAN_PRIVATE::neighborhoodWeight(neighborhood.begin(), neighborhood.end(), weight_func) < n_min) {
            // It's noise.
            id_cache[idx] = 0;
        } else {
            // It's the seed of a cluster.
            _DBSCAN_PRIVATE::expand_cluster(first, last, it, distance_func, epsilon, n_min, id_cache, ++current_cluster_id, weight_func);
        }
    }
 
    std::copy(id_cache.begin(), id_cache.end(), result);
 
    return current_cluster_id;
}
 
template<typename INPUT_ITERATOR, typename DISTANCE_FUNC, typename OUTPUT_ITERATOR>
int DBSCAN(const INPUT_ITERATOR first, const INPUT_ITERATOR last, DISTANCE_FUNC distance_func,
           OUTPUT_ITERATOR result, const double epsilon, const double n_min) {
    return DBSCAN(first, last, distance_func, result, epsilon, n_min, typename _DBSCAN_PRIVATE::constant_1<typename INPUT_ITERATOR::value_type>());
}
 
} /* namespace Algorithm */
} /* namespace ACG */
#endif /* DBSCAN_HH_ */