DBSCANT_impl.hh

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#include <queue>

namespace ACG {
namespace Algorithm {

namespace _DBSCAN_PRIVATE {

template<typename VALUE_TYPE>
class constant_1 {
    public:
        inline double operator()(VALUE_TYPE it) const {
            return 1.0;
        }
};

template<typename INPUT_ITERATOR, typename WEIGHT_FUNC>
inline double neighborhoodWeight(INPUT_ITERATOR first, const INPUT_ITERATOR last, WEIGHT_FUNC &weight_func) {
    double result = 0;
    for (; first != last; ++first)
        result += weight_func(**first);
    return result;
}

/*
 * Private functions.
 */
template<typename INPUT_ITERATOR, typename DISTANCE_FUNC, typename OUTPUT_ITERATOR>
inline
void region_query(INPUT_ITERATOR first, const INPUT_ITERATOR last, const INPUT_ITERATOR center,
                  DISTANCE_FUNC &distance_func, OUTPUT_ITERATOR result, const double epsilon) {

    for (; first != last; ++first) {
        if (center == first) continue;
        if (distance_func(*center, *first) <= epsilon) {
            *result++ = first;
        }
    }
}


template<typename INPUT_ITERATOR, typename DISTANCE_FUNC, typename WEIGHT_FUNC>
inline
void expand_cluster(INPUT_ITERATOR first, const INPUT_ITERATOR last, const INPUT_ITERATOR center,
                    DISTANCE_FUNC &distance_func, const double epsilon, const double n_min,
                    std::vector<int> &id_cache, const int current_cluster_id, WEIGHT_FUNC &weight_func) {


    std::queue<INPUT_ITERATOR> bfq;
    bfq.push(center);

    id_cache[std::distance(first, center)] = current_cluster_id;

    std::vector<INPUT_ITERATOR> neighborhood; neighborhood.reserve(std::distance(first, last));

    while (!bfq.empty()) {

        INPUT_ITERATOR current_element = bfq.front();
        bfq.pop();

        /*
         * Precondition: id_cache[current_idx] > 0
         */

        neighborhood.clear();
        region_query(first, last, current_element, distance_func, std::back_inserter(neighborhood), epsilon);

        /*
         * If the current element is not inside a dense area,
         * we don't use it as a seed to expand the cluster.
         */
        if (neighborhoodWeight(neighborhood.begin(), neighborhood.end(), weight_func) < n_min)
            continue;

        /*
         * Push yet unvisited elements onto the queue.
         */
        for (typename std::vector<INPUT_ITERATOR>::iterator it = neighborhood.begin(), it_end = neighborhood.end();
                it != it_end; ++it) {
            const size_t neighbor_idx = std::distance(first, *it);
            /*
             * Is the element classified as non-noise, yet?
             */
            if (id_cache[neighbor_idx] <= 0) {
                /*
                 * Classify it and use it as a seed.
                 */
                id_cache[neighbor_idx] = current_cluster_id;
                bfq.push(*it);
            }
        }
    }
}

} /* namespace _DBSCAN_PRIVATE */

} /* namespace Algorithm */
} /* namespace ACG */