// 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 #include #include #include #include #include //three max_flows we test here #include #include #include //boost utilities we use #include #include #include #include #include /*************** * test which compares results of the three different max_flow implementations * command line parameters: * number_of_vertices: defaults to 100 * number_of_edges: defaults to 1000 * seeed: defaults to 1 ***************/ using namespace boost; int test_main(int argc, char* argv[]) { typedef adjacency_list_traits < vecS, vecS, directedS > Traits; typedef adjacency_list < vecS, vecS, directedS, property < vertex_index_t, long, property < vertex_color_t, boost::default_color_type, property < vertex_distance_t, long, property < vertex_predecessor_t, Traits::edge_descriptor > > > >, property < edge_capacity_t, long, property < edge_residual_capacity_t, long, property < edge_reverse_t, Traits::edge_descriptor > > > > Graph; typedef graph_traits::edge_descriptor tEdge; typedef graph_traits::vertex_descriptor tVertex; graph_traits::vertices_size_type n_verts = 100; graph_traits::edges_size_type n_edges = 1000; std::size_t seed = 1; if (argc > 1) n_verts = lexical_cast(argv[1]); if (argc > 2) n_edges = lexical_cast(argv[2]); if (argc > 3) seed = lexical_cast(argv[3]); Graph g; 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 > tIntGen; tIntGen int_gen(gen, uniform_int(cap_low, cap_high)); //init edge-capacities randomize_property (g,int_gen); //get source and sink node tVertex source_vertex = random_vertex(g, gen); tVertex sink_vertex = graph_traits::null_vertex(); while(sink_vertex == graph_traits::null_vertex() || sink_vertex == source_vertex) sink_vertex = random_vertex(g, gen); //add reverse edges (ugly... how to do better?!) property_map < Graph, edge_reverse_t >::type rev = get(edge_reverse, g); property_map < Graph, edge_capacity_t >::type cap = get(edge_capacity, g); std::list edges_copy; graph_traits::edge_iterator ei, e_end; boost::tie(ei, e_end) = edges(g); std::copy(ei, e_end, std::back_insert_iterator< std::list >(edges_copy)); while( ! edges_copy.empty()){ tEdge old_edge=edges_copy.front(); edges_copy.pop_front(); tVertex source_vertex = target(old_edge, g); tVertex target_vertex = source(old_edge, g); bool inserted; tEdge 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; } typedef property_traits< property_map::const_type>::value_type tEdgeVal; tEdgeVal bk = boykov_kolmogorov_max_flow(g,source_vertex,sink_vertex); tEdgeVal push_relabel = push_relabel_max_flow(g,source_vertex,sink_vertex); tEdgeVal edmonds_karp = edmonds_karp_max_flow(g,source_vertex,sink_vertex); BOOST_REQUIRE( bk == push_relabel ); BOOST_REQUIRE( push_relabel == edmonds_karp ); return 0; }