示例#1
0
// for documentation see technical reports of christian schulz  
void contraction::contract(const PartitionConfig & partition_config, 
                           graph_access & G, 
                           graph_access & coarser, 
                           const Matching & edge_matching,
                           const CoarseMapping & coarse_mapping,
                           const NodeID & no_of_coarse_vertices,
                           const NodePermutationMap & permutation) const {

        if(partition_config.combine) {
                coarser.resizeSecondPartitionIndex(no_of_coarse_vertices);
        }

        std::vector<NodeID> new_edge_targets(G.number_of_edges());
        forall_edges(G, e) {
                new_edge_targets[e] = coarse_mapping[G.getEdgeTarget(e)];
        } endfor

        std::vector<EdgeID> edge_positions(no_of_coarse_vertices, UNDEFINED_EDGE);

        //we dont know the number of edges jet, so we use the old number for 
        //construction of the coarser graph and then resize the field according
        //to the number of edges we really got
        coarser.start_construction(no_of_coarse_vertices, G.number_of_edges());

        NodeID cur_no_vertices = 0;

        forall_nodes(G, n) {
                NodeID node = permutation[n];
                //we look only at the coarser nodes
                if(coarse_mapping[node] != cur_no_vertices) 
                        continue;
                
                NodeID coarseNode = coarser.new_node();
                coarser.setNodeWeight(coarseNode, G.getNodeWeight(node));

                if(partition_config.combine) {
                        coarser.setSecondPartitionIndex(coarseNode, G.getSecondPartitionIndex(node));
                }

                // do something with all outgoing edges (in auxillary graph)
                forall_out_edges(G, e, node) {
                        visit_edge(G, coarser, edge_positions, coarseNode, e, new_edge_targets);                        
                } endfor
示例#2
0
// implements our version of gal combine
// compute a matching between blocks (greedily) 
// extend to partition
// apply our refinements and tabu search
void gal_combine::perform_gal_combine( PartitionConfig & config, graph_access & G) {
        //first greedily compute a matching of the partitions
        std::vector< std::unordered_map<PartitionID, unsigned> > counters(config.k);
        forall_nodes(G, node) {
                //boundary_pair bp;
                if(counters[G.getPartitionIndex(node)].find(G.getSecondPartitionIndex(node)) != counters[G.getPartitionIndex(node)].end()) {
                        counters[G.getPartitionIndex(node)][G.getSecondPartitionIndex(node)] += 1;
                } else {
                        counters[G.getPartitionIndex(node)][G.getSecondPartitionIndex(node)] = 1;
                }
        } endfor

        std::vector< PartitionID > permutation(config.k);
        for( unsigned i = 0; i < permutation.size(); i++) {
                permutation[i] = i;
        }

        random_functions::permutate_vector_good_small(permutation); 
        std::vector<bool> rhs_matched(config.k, false);
        std::vector<PartitionID> bipartite_matching(config.k);
        for( unsigned i = 0; i < permutation.size(); i++) {
                PartitionID cur_partition   = permutation[i];
                PartitionID best_unassigned = config.k;
                NodeWeight  best_value      = 0;

                for( std::unordered_map<PartitionID, unsigned>::iterator it = counters[cur_partition].begin(); 
                     it != counters[cur_partition].end(); ++it) {
                        if( rhs_matched[it->first] == false && it->second > best_value ) {
                                best_unassigned = it->first; 
                                best_value = it->second;
                        }
                }

                bipartite_matching[cur_partition] = best_unassigned;
                if( best_unassigned != config.k ) {
                        rhs_matched[best_unassigned] = true;
                }
        }

        std::vector<bool> blocked_vertices(G.number_of_nodes(), false);
        forall_nodes(G, node) {
                if( bipartite_matching[G.getPartitionIndex(node)] == G.getSecondPartitionIndex(node) ){
                        blocked_vertices[node] = true;
                } else {
                        // we will reassign this vertex since the partitions do not agree on it
                        G.setPartitionIndex(node, config.k); 
                }
        } endfor

        construct_partition cp;
        cp.construct_starting_from_partition( config, G );

        refinement* refine = new mixed_refinement();

        double real_epsilon = config.imbalance/100.0;
        double epsilon = random_functions::nextDouble(real_epsilon+0.005,real_epsilon+config.kabaE_internal_bal); 
        PartitionConfig copy = config;
        copy.upper_bound_partition = (1+epsilon)*ceil(config.largest_graph_weight/(double)config.k);

        complete_boundary boundary(&G);
        boundary.build();

        tabu_search ts;
        ts.perform_refinement( copy, G, boundary);
        
        //now obtain the quotient graph
        complete_boundary boundary2(&G);
        boundary2.build();

        copy = config;
        copy.upper_bound_partition = (1+epsilon)*ceil(config.largest_graph_weight/(double)config.k);

        refine->perform_refinement( copy, G, boundary2);

        copy = config;
        cycle_refinement cr;
        cr.perform_refinement(config, G, boundary2);
        delete refine;

        
}