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accounting.hpp
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adjacency_iterator.hpp
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adjacency_list.hpp
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adjacency_matrix.hpp
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degree_centrality.hpp
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dijkstra_shortest_paths.hpp
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dimacs.hpp
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directed_graph.hpp
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dll_import_export.hpp
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dominator_tree.hpp
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eccentricity.hpp
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edge_coloring.hpp
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edge_connectivity.hpp
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edge_list.hpp
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edmonds_karp_max_flow.hpp
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graphml.hpp
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graphviz.hpp
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graph_archetypes.hpp
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graph_as_tree.hpp
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graph_concepts.hpp
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graph_mutability_traits.hpp
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graph_selectors.hpp
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graph_stats.hpp
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graph_traits.hpp
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isomorphism.hpp
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king_ordering.hpp
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kruskal_min_spanning_tree.hpp
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labeled_graph.hpp
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leda_graph.hpp
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lookup_edge.hpp
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loop_erased_random_walk.hpp
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matrix_as_graph.hpp
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maximum_adjacency_search.hpp
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maximum_weighted_matching.hpp
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max_cardinality_matching.hpp
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mcgregor_common_subgraphs.hpp
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mesh_graph_generator.hpp
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neighbor_bfs.hpp
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numeric_values.hpp
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one_bit_color_map.hpp
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overloading.hpp
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page_rank.hpp
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planar_canonical_ordering.hpp
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plod_generator.hpp
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point_traits.hpp
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prim_minimum_spanning_tree.hpp
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profile.hpp
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properties.hpp
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property_iter_range.hpp
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push_relabel_max_flow.hpp
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random.hpp
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random_spanning_tree.hpp
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read_dimacs.hpp
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relax.hpp
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reverse_graph.hpp
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rmat_graph_generator.hpp
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r_c_shortest_paths.hpp
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sequential_vertex_coloring.hpp
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simple_point.hpp
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sloan_ordering.hpp
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smallest_last_ordering.hpp
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small_world_generator.hpp
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ssca_graph_generator.hpp
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stanford_graph.hpp
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strong_components.hpp
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subgraph.hpp
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successive_shortest_path_nonnegative_weights.hpp
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/usr/include/boost/graph/edge_connectivity.hpp
(6796B)
//======================================================================= // Copyright 2000 University of Notre Dame. // Authors: Jeremy G. Siek, Andrew Lumsdaine, Lie-Quan Lee // // Distributed under the Boost Software License, Version 1.0. (See // accompanying file LICENSE_1_0.txt or copy at // http://www.boost.org/LICENSE_1_0.txt) //======================================================================= #ifndef BOOST_EDGE_CONNECTIVITY #define BOOST_EDGE_CONNECTIVITY // WARNING: not-yet fully tested! #include <boost/config.hpp> #include <vector> #include <set> #include <algorithm> #include <boost/graph/edmonds_karp_max_flow.hpp> namespace boost { namespace detail { template < class Graph > inline std::pair< typename graph_traits< Graph >::vertex_descriptor, typename graph_traits< Graph >::degree_size_type > min_degree_vertex(Graph& g) { typedef graph_traits< Graph > Traits; typename Traits::vertex_descriptor p; typedef typename Traits::degree_size_type size_type; size_type delta = (std::numeric_limits< size_type >::max)(); typename Traits::vertex_iterator i, iend; for (boost::tie(i, iend) = vertices(g); i != iend; ++i) if (degree(*i, g) < delta) { delta = degree(*i, g); p = *i; } return std::make_pair(p, delta); } template < class Graph, class OutputIterator > void neighbors(const Graph& g, typename graph_traits< Graph >::vertex_descriptor u, OutputIterator result) { typename graph_traits< Graph >::adjacency_iterator ai, aend; for (boost::tie(ai, aend) = adjacent_vertices(u, g); ai != aend; ++ai) *result++ = *ai; } template < class Graph, class VertexIterator, class OutputIterator > void neighbors(const Graph& g, VertexIterator first, VertexIterator last, OutputIterator result) { for (; first != last; ++first) neighbors(g, *first, result); } } // namespace detail // O(m n) template < class VertexListGraph, class OutputIterator > typename graph_traits< VertexListGraph >::degree_size_type edge_connectivity( VertexListGraph& g, OutputIterator disconnecting_set) { //------------------------------------------------------------------------- // Type Definitions typedef graph_traits< VertexListGraph > Traits; typedef typename Traits::vertex_iterator vertex_iterator; typedef typename Traits::edge_iterator edge_iterator; typedef typename Traits::out_edge_iterator out_edge_iterator; typedef typename Traits::vertex_descriptor vertex_descriptor; typedef typename Traits::degree_size_type degree_size_type; typedef color_traits< default_color_type > Color; typedef adjacency_list_traits< vecS, vecS, directedS > Tr; typedef typename Tr::edge_descriptor Tr_edge_desc; typedef adjacency_list< vecS, vecS, directedS, no_property, property< edge_capacity_t, degree_size_type, property< edge_residual_capacity_t, degree_size_type, property< edge_reverse_t, Tr_edge_desc > > > > FlowGraph; typedef typename graph_traits< FlowGraph >::edge_descriptor edge_descriptor; //------------------------------------------------------------------------- // Variable Declarations vertex_descriptor u, v, p, k; edge_descriptor e1, e2; bool inserted; vertex_iterator vi, vi_end; edge_iterator ei, ei_end; degree_size_type delta, alpha_star, alpha_S_k; std::set< vertex_descriptor > S, neighbor_S; std::vector< vertex_descriptor > S_star, non_neighbor_S; std::vector< default_color_type > color(num_vertices(g)); std::vector< edge_descriptor > pred(num_vertices(g)); //------------------------------------------------------------------------- // Create a network flow graph out of the undirected graph FlowGraph flow_g(num_vertices(g)); typename property_map< FlowGraph, edge_capacity_t >::type cap = get(edge_capacity, flow_g); typename property_map< FlowGraph, edge_residual_capacity_t >::type res_cap = get(edge_residual_capacity, flow_g); typename property_map< FlowGraph, edge_reverse_t >::type rev_edge = get(edge_reverse, flow_g); for (boost::tie(ei, ei_end) = edges(g); ei != ei_end; ++ei) { u = source(*ei, g), v = target(*ei, g); boost::tie(e1, inserted) = add_edge(u, v, flow_g); cap[e1] = 1; boost::tie(e2, inserted) = add_edge(v, u, flow_g); cap[e2] = 1; // not sure about this rev_edge[e1] = e2; rev_edge[e2] = e1; } //------------------------------------------------------------------------- // The Algorithm boost::tie(p, delta) = detail::min_degree_vertex(g); S_star.push_back(p); alpha_star = delta; S.insert(p); neighbor_S.insert(p); detail::neighbors( g, S.begin(), S.end(), std::inserter(neighbor_S, neighbor_S.begin())); boost::tie(vi, vi_end) = vertices(g); std::set_difference(vi, vi_end, neighbor_S.begin(), neighbor_S.end(), std::back_inserter(non_neighbor_S)); while (!non_neighbor_S.empty()) { // at most n - 1 times k = non_neighbor_S.front(); alpha_S_k = edmonds_karp_max_flow( flow_g, p, k, cap, res_cap, rev_edge, &color[0], &pred[0]); if (alpha_S_k < alpha_star) { alpha_star = alpha_S_k; S_star.clear(); for (boost::tie(vi, vi_end) = vertices(flow_g); vi != vi_end; ++vi) if (color[*vi] != Color::white()) S_star.push_back(*vi); } S.insert(k); neighbor_S.insert(k); detail::neighbors(g, k, std::inserter(neighbor_S, neighbor_S.begin())); non_neighbor_S.clear(); boost::tie(vi, vi_end) = vertices(g); std::set_difference(vi, vi_end, neighbor_S.begin(), neighbor_S.end(), std::back_inserter(non_neighbor_S)); } //------------------------------------------------------------------------- // Compute edges of the cut [S*, ~S*] std::vector< bool > in_S_star(num_vertices(g), false); typename std::vector< vertex_descriptor >::iterator si; for (si = S_star.begin(); si != S_star.end(); ++si) in_S_star[*si] = true; degree_size_type c = 0; for (si = S_star.begin(); si != S_star.end(); ++si) { out_edge_iterator ei, ei_end; for (boost::tie(ei, ei_end) = out_edges(*si, g); ei != ei_end; ++ei) if (!in_S_star[target(*ei, g)]) { *disconnecting_set++ = *ei; ++c; } } return c; } } // namespace boost #endif // BOOST_EDGE_CONNECTIVITY
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