| // Copyright (c) 2006, Stephan Diederich |
| // |
| // This code may be used under either of the following two licences: |
| // |
| // Permission is hereby granted, free of charge, to any person |
| // obtaining a copy of this software and associated documentation |
| // files (the "Software"), to deal in the Software without |
| // restriction, including without limitation the rights to use, |
| // copy, modify, merge, publish, distribute, sublicense, and/or |
| // sell copies of the Software, and to permit persons to whom the |
| // Software is furnished to do so, subject to the following |
| // conditions: |
| // |
| // The above copyright notice and this permission notice shall be |
| // included in all copies or substantial portions of the Software. |
| // |
| // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, |
| // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES |
| // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND |
| // NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT |
| // HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, |
| // WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING |
| // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR |
| // OTHER DEALINGS IN THE SOFTWARE. OF SUCH DAMAGE. |
| // |
| // Or: |
| // |
| // 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) |
| |
| #include <vector> |
| #include <iterator> |
| #include <iostream> |
| #include <algorithm> |
| #include <fstream> |
| |
| #include <boost/test/minimal.hpp> |
| #include <boost/graph/boykov_kolmogorov_max_flow.hpp> |
| |
| #include <boost/graph/adjacency_list.hpp> |
| #include <boost/graph/adjacency_matrix.hpp> |
| #include <boost/graph/random.hpp> |
| #include <boost/property_map/property_map.hpp> |
| #include <boost/random/linear_congruential.hpp> |
| #include <boost/lexical_cast.hpp> |
| |
| using namespace boost; |
| |
| template <typename Graph, typename CapacityMap, typename ReverseEdgeMap> |
| std::pair< typename graph_traits<Graph>::vertex_descriptor,typename graph_traits<Graph>::vertex_descriptor> |
| fill_random_max_flow_graph(Graph& g, CapacityMap cap, ReverseEdgeMap rev, typename graph_traits<Graph>::vertices_size_type n_verts, |
| typename graph_traits<Graph>::edges_size_type n_edges, std::size_t seed) |
| { |
| typedef typename graph_traits<Graph>::edge_descriptor edge_descriptor; |
| typedef typename graph_traits<Graph>::vertex_descriptor vertex_descriptor; |
| const int cap_low = 1; |
| const int cap_high = 1000; |
| |
| //init random numer generator |
| minstd_rand gen(seed); |
| //generate graph |
| generate_random_graph(g, n_verts, n_edges, gen); |
| |
| //init an uniform distribution int generator |
| typedef variate_generator<minstd_rand, uniform_int<int> > tIntGen; |
| tIntGen int_gen(gen, uniform_int<int>(cap_low, cap_high)); |
| //randomize edge-capacities |
| //randomize_property<edge_capacity, Graph, tIntGen> (g,int_gen); //we cannot use this, as we have no idea how properties are stored, right? |
| typename graph_traits<Graph>::edge_iterator ei, e_end; |
| for(boost::tie(ei,e_end) = edges(g); ei != e_end; ++ei) |
| cap[*ei] = int_gen(); |
| |
| //get source and sink node |
| vertex_descriptor s = random_vertex(g, gen); |
| vertex_descriptor t = graph_traits<Graph>::null_vertex(); |
| while(t == graph_traits<Graph>::null_vertex() || t == s) |
| t = random_vertex(g, gen); |
| |
| //add reverse edges (ugly... how to do better?!) |
| std::list<edge_descriptor> edges_copy; |
| boost::tie(ei, e_end) = edges(g); |
| std::copy(ei, e_end, std::back_insert_iterator< std::list<edge_descriptor> >(edges_copy)); |
| while(!edges_copy.empty()){ |
| edge_descriptor old_edge = edges_copy.front(); |
| edges_copy.pop_front(); |
| vertex_descriptor source_vertex = target(old_edge, g); |
| vertex_descriptor target_vertex = source(old_edge, g); |
| bool inserted; |
| edge_descriptor new_edge; |
| boost::tie(new_edge,inserted) = add_edge(source_vertex, target_vertex, g); |
| assert(inserted); |
| rev[old_edge] = new_edge; |
| rev[new_edge] = old_edge ; |
| cap[new_edge] = 0; |
| } |
| return std::make_pair(s,t); |
| } |
| |
| long test_adjacency_list_vecS(int n_verts, int n_edges, std::size_t seed){ |
| typedef adjacency_list_traits<vecS, vecS, directedS> tVectorTraits; |
| typedef adjacency_list<vecS, vecS, directedS, |
| property<vertex_index_t, long, |
| property<vertex_predecessor_t, tVectorTraits::edge_descriptor, |
| property<vertex_color_t, boost::default_color_type, |
| property<vertex_distance_t, long> > > >, |
| property<edge_capacity_t, long, |
| property<edge_residual_capacity_t, long, |
| property<edge_reverse_t, tVectorTraits::edge_descriptor > > > > tVectorGraph; |
| |
| tVectorGraph g; |
| |
| graph_traits<tVectorGraph>::vertex_descriptor src,sink; |
| boost::tie(src,sink) = fill_random_max_flow_graph(g, get(edge_capacity,g), get(edge_reverse, g), n_verts, n_edges, seed); |
| |
| return boykov_kolmogorov_max_flow(g, get(edge_capacity, g), |
| get(edge_residual_capacity, g), |
| get(edge_reverse, g), |
| get(vertex_predecessor, g), |
| get(vertex_color, g), |
| get(vertex_distance, g), |
| get(vertex_index, g), |
| src, sink); |
| } |
| |
| long test_adjacency_list_listS(int n_verts, int n_edges, std::size_t seed){ |
| typedef adjacency_list_traits<listS, listS, directedS> tListTraits; |
| typedef adjacency_list<listS, listS, directedS, |
| property<vertex_index_t, long, |
| property<vertex_predecessor_t, tListTraits::edge_descriptor, |
| property<vertex_color_t, boost::default_color_type, |
| property<vertex_distance_t, long> > > >, |
| property<edge_capacity_t, long, |
| property<edge_residual_capacity_t, long, |
| property<edge_reverse_t, tListTraits::edge_descriptor > > > > tListGraph; |
| |
| tListGraph g; |
| |
| graph_traits<tListGraph>::vertex_descriptor src,sink; |
| boost::tie(src,sink) = fill_random_max_flow_graph(g, get(edge_capacity,g), get(edge_reverse, g), n_verts, n_edges, seed); |
| |
| //initialize vertex indices |
| graph_traits<tListGraph>::vertex_iterator vi,v_end; |
| graph_traits<tListGraph>::vertices_size_type index = 0; |
| for(boost::tie(vi, v_end) = vertices(g); vi != v_end; ++vi){ |
| put(vertex_index, g, *vi, index++); |
| } |
| return boykov_kolmogorov_max_flow(g, get(edge_capacity, g), |
| get(edge_residual_capacity, g), |
| get(edge_reverse, g), |
| get(vertex_predecessor, g), |
| get(vertex_color, g), |
| get(vertex_distance, g), |
| get(vertex_index, g), |
| src, sink); |
| } |
| |
| template<typename EdgeDescriptor> |
| struct Node{ |
| boost::default_color_type vertex_color; |
| long vertex_distance; |
| EdgeDescriptor vertex_predecessor; |
| }; |
| |
| template<typename EdgeDescriptor> |
| struct Link{ |
| long edge_capacity; |
| long edge_residual_capacity; |
| EdgeDescriptor edge_reverse; |
| }; |
| |
| long test_bundled_properties(int n_verts, int n_edges, std::size_t seed){ |
| typedef adjacency_list_traits<vecS, vecS, directedS> tTraits; |
| typedef Node<tTraits::edge_descriptor> tVertex; |
| typedef Link<tTraits::edge_descriptor> tEdge; |
| typedef adjacency_list<vecS, vecS, directedS, tVertex, tEdge> tBundleGraph; |
| |
| tBundleGraph g; |
| |
| graph_traits<tBundleGraph>::vertex_descriptor src,sink; |
| boost::tie(src,sink) = fill_random_max_flow_graph(g, get(&tEdge::edge_capacity,g), get(&tEdge::edge_reverse, g), n_verts, n_edges, seed); |
| return boykov_kolmogorov_max_flow(g, get(&tEdge::edge_capacity, g), |
| get(&tEdge::edge_residual_capacity, g), |
| get(&tEdge::edge_reverse, g), |
| get(&tVertex::vertex_predecessor, g), |
| get(&tVertex::vertex_color, g), |
| get(&tVertex::vertex_distance, g), |
| get(vertex_index, g), |
| src, sink); |
| } |
| |
| long test_overloads(int n_verts, int n_edges, std::size_t seed){ |
| typedef adjacency_list_traits<vecS, vecS, directedS> tTraits; |
| typedef property <edge_capacity_t, long, |
| property<edge_residual_capacity_t, long, |
| property<edge_reverse_t, tTraits::edge_descriptor> > >tEdgeProperty; |
| typedef adjacency_list<vecS, vecS, directedS, no_property, tEdgeProperty> tGraph; |
| |
| tGraph g; |
| |
| graph_traits<tGraph>::vertex_descriptor src,sink; |
| boost::tie(src,sink) = fill_random_max_flow_graph(g, get(edge_capacity,g), get(edge_reverse, g), n_verts, n_edges, seed); |
| |
| std::vector<graph_traits<tGraph>::edge_descriptor> predecessor_vec(n_verts); |
| std::vector<default_color_type> color_vec(n_verts); |
| std::vector<graph_traits<tGraph>::vertices_size_type> distance_vec(n_verts); |
| |
| long flow_overload_1 = |
| boykov_kolmogorov_max_flow(g, |
| get(edge_capacity,g), |
| get(edge_residual_capacity,g), |
| get(edge_reverse,g), |
| get(vertex_index,g), |
| src, sink); |
| |
| long flow_overload_2 = |
| boykov_kolmogorov_max_flow(g, |
| get(edge_capacity,g), |
| get(edge_residual_capacity,g), |
| get(edge_reverse,g), |
| &(color_vec[0]), |
| get(vertex_index,g), |
| src, sink); |
| |
| BOOST_CHECK(flow_overload_1 == flow_overload_2); |
| return flow_overload_1; |
| } |
| |
| template<class Graph, |
| class EdgeCapacityMap, |
| class ResidualCapacityEdgeMap, |
| class ReverseEdgeMap, |
| class PredecessorMap, |
| class ColorMap, |
| class DistanceMap, |
| class IndexMap> |
| class boykov_kolmogorov_test |
| : public detail::bk_max_flow< |
| Graph, EdgeCapacityMap, ResidualCapacityEdgeMap, ReverseEdgeMap, |
| PredecessorMap, ColorMap, DistanceMap, IndexMap |
| > |
| { |
| |
| typedef typename graph_traits<Graph>::edge_descriptor tEdge; |
| typedef typename graph_traits<Graph>::vertex_descriptor tVertex; |
| typedef typename property_traits< typename property_map<Graph, edge_capacity_t>::const_type>::value_type tEdgeVal; |
| typedef typename graph_traits<Graph>::vertex_iterator tVertexIterator; |
| typedef typename graph_traits<Graph>::out_edge_iterator tOutEdgeIterator; |
| typedef typename property_traits<ColorMap>::value_type tColorValue; |
| typedef color_traits<tColorValue> tColorTraits; |
| typedef typename property_traits<DistanceMap>::value_type tDistanceVal; |
| typedef typename detail::bk_max_flow< |
| Graph, EdgeCapacityMap, ResidualCapacityEdgeMap, ReverseEdgeMap, |
| PredecessorMap, ColorMap, DistanceMap, IndexMap |
| > tSuper; |
| public: |
| boykov_kolmogorov_test(Graph& g, |
| typename graph_traits<Graph>::vertex_descriptor src, |
| typename graph_traits<Graph>::vertex_descriptor sink) |
| : tSuper(g, get(edge_capacity,g), get(edge_residual_capacity,g), |
| get(edge_reverse, g), get(vertex_predecessor, g), |
| get(vertex_color, g), get(vertex_distance, g), |
| get(vertex_index, g), src, sink) |
| { } |
| |
| void invariant_four(tVertex v) const{ |
| //passive nodes in S or T |
| if(v == tSuper::m_source || v == tSuper::m_sink) |
| return; |
| typename std::list<tVertex>::const_iterator it = find(tSuper::m_orphans.begin(), tSuper::m_orphans.end(), v); |
| // a node is active, if its in the active_list AND (is has_a_parent, or its already in the orphans_list or its the sink, or its the source) |
| bool is_active = (tSuper::m_in_active_list_map[v] && (tSuper::has_parent(v) || it != tSuper::m_orphans.end() )); |
| if(this->get_tree(v) != tColorTraits::gray() && !is_active){ |
| typename graph_traits<Graph>::out_edge_iterator ei,e_end; |
| for(boost::tie(ei, e_end) = out_edges(v, tSuper::m_g); ei != e_end; ++ei){ |
| const tVertex& other_node = target(*ei, tSuper::m_g); |
| if(this->get_tree(other_node) != this->get_tree(v)){ |
| if(this->get_tree(v) == tColorTraits::black()) |
| BOOST_CHECK(tSuper::m_res_cap_map[*ei] == 0); |
| else |
| BOOST_CHECK(tSuper::m_res_cap_map[tSuper::m_rev_edge_map[*ei]] == 0); |
| } |
| } |
| } |
| } |
| |
| void invariant_five(const tVertex& v) const{ |
| BOOST_CHECK(this->get_tree(v) != tColorTraits::gray() || tSuper::m_time_map[v] <= tSuper::m_time); |
| } |
| |
| void invariant_six(const tVertex& v) const{ |
| if(this->get_tree(v) == tColorTraits::gray() || tSuper::m_time_map[v] != tSuper::m_time) |
| return; |
| else{ |
| tVertex current_node = v; |
| tDistanceVal distance = 0; |
| tColorValue color = this->get_tree(v); |
| tVertex terminal = (color == tColorTraits::black()) ? tSuper::m_source : tSuper::m_sink; |
| while(current_node != terminal){ |
| BOOST_CHECK(tSuper::has_parent(current_node)); |
| tEdge e = this->get_edge_to_parent(current_node); |
| ++distance; |
| current_node = (color == tColorTraits::black())? source(e, tSuper::m_g) : target(e, tSuper::m_g); |
| if(distance > tSuper::m_dist_map[v]) |
| break; |
| } |
| BOOST_CHECK(distance == tSuper::m_dist_map[v]); |
| } |
| } |
| |
| void invariant_seven(const tVertex& v) const{ |
| if(this->get_tree(v) == tColorTraits::gray()) |
| return; |
| else{ |
| tColorValue color = this->get_tree(v); |
| long time = tSuper::m_time_map[v]; |
| tVertex current_node = v; |
| while(tSuper::has_parent(current_node)){ |
| tEdge e = this->get_edge_to_parent(current_node); |
| current_node = (color == tColorTraits::black()) ? source(e, tSuper::m_g) : target(e, tSuper::m_g); |
| BOOST_CHECK(tSuper::m_time_map[current_node] >= time); |
| } |
| } |
| }//invariant_seven |
| |
| void invariant_eight(const tVertex& v) const{ |
| if(this->get_tree(v) == tColorTraits::gray()) |
| return; |
| else{ |
| tColorValue color = this->get_tree(v); |
| long time = tSuper::m_time_map[v]; |
| tDistanceVal distance = tSuper::m_dist_map[v]; |
| tVertex current_node = v; |
| while(tSuper::has_parent(current_node)){ |
| tEdge e = this->get_edge_to_parent(current_node); |
| current_node = (color == tColorTraits::black()) ? source(e, tSuper::m_g) : target(e, tSuper::m_g); |
| if(tSuper::m_time_map[current_node] == time) |
| BOOST_CHECK(tSuper::m_dist_map[current_node] < distance); |
| } |
| } |
| }//invariant_eight |
| |
| void check_invariants(){ |
| tVertexIterator vi, v_end; |
| for(boost::tie(vi, v_end) = vertices(tSuper::m_g); vi != v_end; ++vi){ |
| invariant_four(*vi); |
| invariant_five(*vi); |
| invariant_six(*vi); |
| invariant_seven(*vi); |
| invariant_eight(*vi); |
| } |
| } |
| |
| tEdgeVal test(){ |
| this->add_active_node(this->m_sink); |
| this->augment_direct_paths(); |
| check_invariants(); |
| //start the main-loop |
| while(true){ |
| bool path_found; |
| tEdge connecting_edge; |
| boost::tie(connecting_edge, path_found) = this->grow(); //find a path from source to sink |
| if(!path_found){ |
| //we're finished, no more paths were found |
| break; |
| } |
| check_invariants(); |
| this->m_time++; |
| this->augment(connecting_edge); //augment that path |
| check_invariants(); |
| this->adopt(); //rebuild search tree structure |
| check_invariants(); |
| } |
| |
| //check if flow is the sum of outgoing edges of src |
| tOutEdgeIterator ei, e_end; |
| tEdgeVal src_sum = 0; |
| for(boost::tie(ei, e_end) = out_edges(this->m_source, this->m_g); ei != e_end; ++ei){ |
| src_sum += this->m_cap_map[*ei] - this->m_res_cap_map[*ei]; |
| } |
| BOOST_CHECK(this->m_flow == src_sum); |
| //check if flow is the sum of ingoing edges of sink |
| tEdgeVal sink_sum = 0; |
| for(boost::tie(ei, e_end) = out_edges(this->m_sink, this->m_g); ei != e_end; ++ei){ |
| tEdge in_edge = this->m_rev_edge_map[*ei]; |
| sink_sum += this->m_cap_map[in_edge] - this->m_res_cap_map[in_edge]; |
| } |
| BOOST_CHECK(this->m_flow == sink_sum); |
| return this->m_flow; |
| } |
| }; |
| |
| long test_algorithms_invariant(int n_verts, int n_edges, std::size_t seed) |
| { |
| typedef adjacency_list_traits<vecS, vecS, directedS> tVectorTraits; |
| typedef adjacency_list<vecS, vecS, directedS, |
| property<vertex_index_t, long, |
| property<vertex_predecessor_t, tVectorTraits::edge_descriptor, |
| property<vertex_color_t, default_color_type, |
| property<vertex_distance_t, long> > > >, |
| property<edge_capacity_t, long, |
| property<edge_residual_capacity_t, long, |
| property<edge_reverse_t, tVectorTraits::edge_descriptor > > > > tVectorGraph; |
| |
| tVectorGraph g; |
| |
| graph_traits<tVectorGraph>::vertex_descriptor src, sink; |
| boost::tie(src,sink) = fill_random_max_flow_graph(g, get(edge_capacity,g), get(edge_reverse, g), n_verts, n_edges, seed); |
| |
| typedef property_map<tVectorGraph, edge_capacity_t>::type tEdgeCapMap; |
| typedef property_map<tVectorGraph, edge_residual_capacity_t>::type tEdgeResCapMap; |
| typedef property_map<tVectorGraph, edge_reverse_t>::type tRevEdgeMap; |
| typedef property_map<tVectorGraph, vertex_predecessor_t>::type tVertexPredMap; |
| typedef property_map<tVectorGraph, vertex_color_t>::type tVertexColorMap; |
| typedef property_map<tVectorGraph, vertex_distance_t>::type tDistanceMap; |
| typedef property_map<tVectorGraph, vertex_index_t>::type tIndexMap; |
| typedef boykov_kolmogorov_test< |
| tVectorGraph, tEdgeCapMap, tEdgeResCapMap, tRevEdgeMap, tVertexPredMap, |
| tVertexColorMap, tDistanceMap, tIndexMap |
| > tKolmo; |
| tKolmo instance(g, src, sink); |
| return instance.test(); |
| } |
| |
| int test_main(int argc, char* argv[]) |
| { |
| int n_verts = 10; |
| int n_edges = 500; |
| std::size_t seed = 1; |
| |
| if (argc > 1) n_verts = lexical_cast<int>(argv[1]); |
| if (argc > 2) n_edges = lexical_cast<int>(argv[2]); |
| if (argc > 3) seed = lexical_cast<std::size_t>(argv[3]); |
| |
| //we need at least 2 vertices to create src and sink in random graphs |
| //this case is also caught in boykov_kolmogorov_max_flow |
| if (n_verts<2) |
| n_verts = 2; |
| |
| // below are checks for different calls to boykov_kolmogorov_max_flow and different graph-types |
| |
| //checks support of vecS storage |
| long flow_vecS = test_adjacency_list_vecS(n_verts, n_edges, seed); |
| std::cout << "vecS flow: " << flow_vecS << std::endl; |
| //checks support of listS storage (especially problems with vertex indices) |
| long flow_listS = test_adjacency_list_listS(n_verts, n_edges, seed); |
| std::cout << "listS flow: " << flow_listS << std::endl; |
| BOOST_CHECK(flow_vecS == flow_listS); |
| //checks bundled properties |
| long flow_bundles = test_bundled_properties(n_verts, n_edges, seed); |
| std::cout << "bundles flow: " << flow_bundles << std::endl; |
| BOOST_CHECK(flow_listS == flow_bundles); |
| //checks overloads |
| long flow_overloads = test_overloads(n_verts, n_edges, seed); |
| std::cout << "overloads flow: " << flow_overloads << std::endl; |
| BOOST_CHECK(flow_bundles == flow_overloads); |
| |
| // excessive test version where Boykov-Kolmogorov's algorithm invariants are |
| // checked |
| long flow_invariants = test_algorithms_invariant(n_verts, n_edges, seed); |
| std::cout << "invariants flow: " << flow_invariants << std::endl; |
| BOOST_CHECK(flow_overloads == flow_invariants); |
| return 0; |
| } |
