1 // Copyright (c) 2006, Stephan Diederich
3 // This code may be used under either of the following two licences:
5 // Permission is hereby granted, free of charge, to any person
6 // obtaining a copy of this software and associated documentation
7 // files (the "Software"), to deal in the Software without
8 // restriction, including without limitation the rights to use,
9 // copy, modify, merge, publish, distribute, sublicense, and/or
10 // sell copies of the Software, and to permit persons to whom the
11 // Software is furnished to do so, subject to the following
14 // The above copyright notice and this permission notice shall be
15 // included in all copies or substantial portions of the Software.
17 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
18 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
19 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
20 // NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
21 // HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
22 // WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
23 // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
24 // OTHER DEALINGS IN THE SOFTWARE. OF SUCH DAMAGE.
28 // Distributed under the Boost Software License, Version 1.0.
29 // (See accompanying file LICENSE_1_0.txt or copy at
30 // http://www.boost.org/LICENSE_1_0.txt)
38 #include <boost/test/minimal.hpp>
39 #include <boost/graph/boykov_kolmogorov_max_flow.hpp>
41 #include <boost/graph/adjacency_list.hpp>
42 #include <boost/graph/adjacency_matrix.hpp>
43 #include <boost/graph/random.hpp>
44 #include <boost/property_map/property_map.hpp>
45 #include <boost/random/linear_congruential.hpp>
46 #include <boost/lexical_cast.hpp>
48 using namespace boost;
50 template <typename Graph, typename CapacityMap, typename ReverseEdgeMap>
51 std::pair< typename graph_traits<Graph>::vertex_descriptor,typename graph_traits<Graph>::vertex_descriptor>
52 fill_random_max_flow_graph(Graph& g, CapacityMap cap, ReverseEdgeMap rev, typename graph_traits<Graph>::vertices_size_type n_verts,
53 typename graph_traits<Graph>::edges_size_type n_edges, std::size_t seed)
55 typedef typename graph_traits<Graph>::edge_descriptor edge_descriptor;
56 typedef typename graph_traits<Graph>::vertex_descriptor vertex_descriptor;
57 const int cap_low = 1;
58 const int cap_high = 1000;
60 //init random numer generator
61 minstd_rand gen(seed);
63 generate_random_graph(g, n_verts, n_edges, gen);
65 //init an uniform distribution int generator
66 typedef variate_generator<minstd_rand, uniform_int<int> > tIntGen;
67 tIntGen int_gen(gen, uniform_int<int>(cap_low, cap_high));
68 //randomize edge-capacities
69 //randomize_property<edge_capacity, Graph, tIntGen> (g,int_gen); //we cannot use this, as we have no idea how properties are stored, right?
70 typename graph_traits<Graph>::edge_iterator ei, e_end;
71 for(boost::tie(ei,e_end) = edges(g); ei != e_end; ++ei)
74 //get source and sink node
75 vertex_descriptor s = random_vertex(g, gen);
76 vertex_descriptor t = graph_traits<Graph>::null_vertex();
77 while(t == graph_traits<Graph>::null_vertex() || t == s)
78 t = random_vertex(g, gen);
80 //add reverse edges (ugly... how to do better?!)
81 std::list<edge_descriptor> edges_copy;
82 boost::tie(ei, e_end) = edges(g);
83 std::copy(ei, e_end, std::back_insert_iterator< std::list<edge_descriptor> >(edges_copy));
84 while(!edges_copy.empty()){
85 edge_descriptor old_edge = edges_copy.front();
86 edges_copy.pop_front();
87 vertex_descriptor source_vertex = target(old_edge, g);
88 vertex_descriptor target_vertex = source(old_edge, g);
90 edge_descriptor new_edge;
91 boost::tie(new_edge,inserted) = add_edge(source_vertex, target_vertex, g);
93 rev[old_edge] = new_edge;
94 rev[new_edge] = old_edge ;
97 return std::make_pair(s,t);
100 long test_adjacency_list_vecS(int n_verts, int n_edges, std::size_t seed){
101 typedef adjacency_list_traits<vecS, vecS, directedS> tVectorTraits;
102 typedef adjacency_list<vecS, vecS, directedS,
103 property<vertex_index_t, long,
104 property<vertex_predecessor_t, tVectorTraits::edge_descriptor,
105 property<vertex_color_t, boost::default_color_type,
106 property<vertex_distance_t, long> > > >,
107 property<edge_capacity_t, long,
108 property<edge_residual_capacity_t, long,
109 property<edge_reverse_t, tVectorTraits::edge_descriptor > > > > tVectorGraph;
113 graph_traits<tVectorGraph>::vertex_descriptor src,sink;
114 boost::tie(src,sink) = fill_random_max_flow_graph(g, get(edge_capacity,g), get(edge_reverse, g), n_verts, n_edges, seed);
116 return boykov_kolmogorov_max_flow(g, get(edge_capacity, g),
117 get(edge_residual_capacity, g),
118 get(edge_reverse, g),
119 get(vertex_predecessor, g),
120 get(vertex_color, g),
121 get(vertex_distance, g),
122 get(vertex_index, g),
126 long test_adjacency_list_listS(int n_verts, int n_edges, std::size_t seed){
127 typedef adjacency_list_traits<listS, listS, directedS> tListTraits;
128 typedef adjacency_list<listS, listS, directedS,
129 property<vertex_index_t, long,
130 property<vertex_predecessor_t, tListTraits::edge_descriptor,
131 property<vertex_color_t, boost::default_color_type,
132 property<vertex_distance_t, long> > > >,
133 property<edge_capacity_t, long,
134 property<edge_residual_capacity_t, long,
135 property<edge_reverse_t, tListTraits::edge_descriptor > > > > tListGraph;
139 graph_traits<tListGraph>::vertex_descriptor src,sink;
140 boost::tie(src,sink) = fill_random_max_flow_graph(g, get(edge_capacity,g), get(edge_reverse, g), n_verts, n_edges, seed);
142 //initialize vertex indices
143 graph_traits<tListGraph>::vertex_iterator vi,v_end;
144 graph_traits<tListGraph>::vertices_size_type index = 0;
145 for(boost::tie(vi, v_end) = vertices(g); vi != v_end; ++vi){
146 put(vertex_index, g, *vi, index++);
148 return boykov_kolmogorov_max_flow(g, get(edge_capacity, g),
149 get(edge_residual_capacity, g),
150 get(edge_reverse, g),
151 get(vertex_predecessor, g),
152 get(vertex_color, g),
153 get(vertex_distance, g),
154 get(vertex_index, g),
158 template<typename EdgeDescriptor>
160 boost::default_color_type vertex_color;
161 long vertex_distance;
162 EdgeDescriptor vertex_predecessor;
165 template<typename EdgeDescriptor>
168 long edge_residual_capacity;
169 EdgeDescriptor edge_reverse;
172 long test_bundled_properties(int n_verts, int n_edges, std::size_t seed){
173 typedef adjacency_list_traits<vecS, vecS, directedS> tTraits;
174 typedef Node<tTraits::edge_descriptor> tVertex;
175 typedef Link<tTraits::edge_descriptor> tEdge;
176 typedef adjacency_list<vecS, vecS, directedS, tVertex, tEdge> tBundleGraph;
180 graph_traits<tBundleGraph>::vertex_descriptor src,sink;
181 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);
182 return boykov_kolmogorov_max_flow(g, get(&tEdge::edge_capacity, g),
183 get(&tEdge::edge_residual_capacity, g),
184 get(&tEdge::edge_reverse, g),
185 get(&tVertex::vertex_predecessor, g),
186 get(&tVertex::vertex_color, g),
187 get(&tVertex::vertex_distance, g),
188 get(vertex_index, g),
192 long test_overloads(int n_verts, int n_edges, std::size_t seed){
193 typedef adjacency_list_traits<vecS, vecS, directedS> tTraits;
194 typedef property <edge_capacity_t, long,
195 property<edge_residual_capacity_t, long,
196 property<edge_reverse_t, tTraits::edge_descriptor> > >tEdgeProperty;
197 typedef adjacency_list<vecS, vecS, directedS, no_property, tEdgeProperty> tGraph;
201 graph_traits<tGraph>::vertex_descriptor src,sink;
202 boost::tie(src,sink) = fill_random_max_flow_graph(g, get(edge_capacity,g), get(edge_reverse, g), n_verts, n_edges, seed);
204 std::vector<graph_traits<tGraph>::edge_descriptor> predecessor_vec(n_verts);
205 std::vector<default_color_type> color_vec(n_verts);
206 std::vector<graph_traits<tGraph>::vertices_size_type> distance_vec(n_verts);
208 long flow_overload_1 =
209 boykov_kolmogorov_max_flow(g,
210 get(edge_capacity,g),
211 get(edge_residual_capacity,g),
216 long flow_overload_2 =
217 boykov_kolmogorov_max_flow(g,
218 get(edge_capacity,g),
219 get(edge_residual_capacity,g),
221 boost::make_iterator_property_map(
222 color_vec.begin(), get(vertex_index, g)),
226 BOOST_CHECK(flow_overload_1 == flow_overload_2);
227 return flow_overload_1;
230 template<class Graph,
231 class EdgeCapacityMap,
232 class ResidualCapacityEdgeMap,
233 class ReverseEdgeMap,
234 class PredecessorMap,
238 class boykov_kolmogorov_test
239 : public detail::bk_max_flow<
240 Graph, EdgeCapacityMap, ResidualCapacityEdgeMap, ReverseEdgeMap,
241 PredecessorMap, ColorMap, DistanceMap, IndexMap
245 typedef typename graph_traits<Graph>::edge_descriptor tEdge;
246 typedef typename graph_traits<Graph>::vertex_descriptor tVertex;
247 typedef typename property_traits< typename property_map<Graph, edge_capacity_t>::const_type>::value_type tEdgeVal;
248 typedef typename graph_traits<Graph>::vertex_iterator tVertexIterator;
249 typedef typename graph_traits<Graph>::out_edge_iterator tOutEdgeIterator;
250 typedef typename property_traits<ColorMap>::value_type tColorValue;
251 typedef color_traits<tColorValue> tColorTraits;
252 typedef typename property_traits<DistanceMap>::value_type tDistanceVal;
253 typedef typename detail::bk_max_flow<
254 Graph, EdgeCapacityMap, ResidualCapacityEdgeMap, ReverseEdgeMap,
255 PredecessorMap, ColorMap, DistanceMap, IndexMap
258 boykov_kolmogorov_test(Graph& g,
259 typename graph_traits<Graph>::vertex_descriptor src,
260 typename graph_traits<Graph>::vertex_descriptor sink)
261 : tSuper(g, get(edge_capacity,g), get(edge_residual_capacity,g),
262 get(edge_reverse, g), get(vertex_predecessor, g),
263 get(vertex_color, g), get(vertex_distance, g),
264 get(vertex_index, g), src, sink)
267 void invariant_four(tVertex v) const{
268 //passive nodes in S or T
269 if(v == tSuper::m_source || v == tSuper::m_sink)
271 typename std::list<tVertex>::const_iterator it = find(tSuper::m_orphans.begin(), tSuper::m_orphans.end(), v);
272 // 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)
273 bool is_active = (tSuper::m_in_active_list_map[v] && (tSuper::has_parent(v) || it != tSuper::m_orphans.end() ));
274 if(this->get_tree(v) != tColorTraits::gray() && !is_active){
275 typename graph_traits<Graph>::out_edge_iterator ei,e_end;
276 for(boost::tie(ei, e_end) = out_edges(v, tSuper::m_g); ei != e_end; ++ei){
277 const tVertex& other_node = target(*ei, tSuper::m_g);
278 if(this->get_tree(other_node) != this->get_tree(v)){
279 if(this->get_tree(v) == tColorTraits::black())
280 BOOST_CHECK(tSuper::m_res_cap_map[*ei] == 0);
282 BOOST_CHECK(tSuper::m_res_cap_map[tSuper::m_rev_edge_map[*ei]] == 0);
288 void invariant_five(const tVertex& v) const{
289 BOOST_CHECK(this->get_tree(v) != tColorTraits::gray() || tSuper::m_time_map[v] <= tSuper::m_time);
292 void invariant_six(const tVertex& v) const{
293 if(this->get_tree(v) == tColorTraits::gray() || tSuper::m_time_map[v] != tSuper::m_time)
296 tVertex current_node = v;
297 tDistanceVal distance = 0;
298 tColorValue color = this->get_tree(v);
299 tVertex terminal = (color == tColorTraits::black()) ? tSuper::m_source : tSuper::m_sink;
300 while(current_node != terminal){
301 BOOST_CHECK(tSuper::has_parent(current_node));
302 tEdge e = this->get_edge_to_parent(current_node);
304 current_node = (color == tColorTraits::black())? source(e, tSuper::m_g) : target(e, tSuper::m_g);
305 if(distance > tSuper::m_dist_map[v])
308 BOOST_CHECK(distance == tSuper::m_dist_map[v]);
312 void invariant_seven(const tVertex& v) const{
313 if(this->get_tree(v) == tColorTraits::gray())
316 tColorValue color = this->get_tree(v);
317 long time = tSuper::m_time_map[v];
318 tVertex current_node = v;
319 while(tSuper::has_parent(current_node)){
320 tEdge e = this->get_edge_to_parent(current_node);
321 current_node = (color == tColorTraits::black()) ? source(e, tSuper::m_g) : target(e, tSuper::m_g);
322 BOOST_CHECK(tSuper::m_time_map[current_node] >= time);
327 void invariant_eight(const tVertex& v) const{
328 if(this->get_tree(v) == tColorTraits::gray())
331 tColorValue color = this->get_tree(v);
332 long time = tSuper::m_time_map[v];
333 tDistanceVal distance = tSuper::m_dist_map[v];
334 tVertex current_node = v;
335 while(tSuper::has_parent(current_node)){
336 tEdge e = this->get_edge_to_parent(current_node);
337 current_node = (color == tColorTraits::black()) ? source(e, tSuper::m_g) : target(e, tSuper::m_g);
338 if(tSuper::m_time_map[current_node] == time)
339 BOOST_CHECK(tSuper::m_dist_map[current_node] < distance);
344 void check_invariants(){
345 tVertexIterator vi, v_end;
346 for(boost::tie(vi, v_end) = vertices(tSuper::m_g); vi != v_end; ++vi){
350 invariant_seven(*vi);
351 invariant_eight(*vi);
356 this->add_active_node(this->m_sink);
357 this->augment_direct_paths();
359 //start the main-loop
362 tEdge connecting_edge;
363 boost::tie(connecting_edge, path_found) = this->grow(); //find a path from source to sink
365 //we're finished, no more paths were found
370 this->augment(connecting_edge); //augment that path
372 this->adopt(); //rebuild search tree structure
376 //check if flow is the sum of outgoing edges of src
377 tOutEdgeIterator ei, e_end;
378 tEdgeVal src_sum = 0;
379 for(boost::tie(ei, e_end) = out_edges(this->m_source, this->m_g); ei != e_end; ++ei){
380 src_sum += this->m_cap_map[*ei] - this->m_res_cap_map[*ei];
382 BOOST_CHECK(this->m_flow == src_sum);
383 //check if flow is the sum of ingoing edges of sink
384 tEdgeVal sink_sum = 0;
385 for(boost::tie(ei, e_end) = out_edges(this->m_sink, this->m_g); ei != e_end; ++ei){
386 tEdge in_edge = this->m_rev_edge_map[*ei];
387 sink_sum += this->m_cap_map[in_edge] - this->m_res_cap_map[in_edge];
389 BOOST_CHECK(this->m_flow == sink_sum);
394 long test_algorithms_invariant(int n_verts, int n_edges, std::size_t seed)
396 typedef adjacency_list_traits<vecS, vecS, directedS> tVectorTraits;
397 typedef adjacency_list<vecS, vecS, directedS,
398 property<vertex_index_t, long,
399 property<vertex_predecessor_t, tVectorTraits::edge_descriptor,
400 property<vertex_color_t, default_color_type,
401 property<vertex_distance_t, long> > > >,
402 property<edge_capacity_t, long,
403 property<edge_residual_capacity_t, long,
404 property<edge_reverse_t, tVectorTraits::edge_descriptor > > > > tVectorGraph;
408 graph_traits<tVectorGraph>::vertex_descriptor src, sink;
409 boost::tie(src,sink) = fill_random_max_flow_graph(g, get(edge_capacity,g), get(edge_reverse, g), n_verts, n_edges, seed);
411 typedef property_map<tVectorGraph, edge_capacity_t>::type tEdgeCapMap;
412 typedef property_map<tVectorGraph, edge_residual_capacity_t>::type tEdgeResCapMap;
413 typedef property_map<tVectorGraph, edge_reverse_t>::type tRevEdgeMap;
414 typedef property_map<tVectorGraph, vertex_predecessor_t>::type tVertexPredMap;
415 typedef property_map<tVectorGraph, vertex_color_t>::type tVertexColorMap;
416 typedef property_map<tVectorGraph, vertex_distance_t>::type tDistanceMap;
417 typedef property_map<tVectorGraph, vertex_index_t>::type tIndexMap;
418 typedef boykov_kolmogorov_test<
419 tVectorGraph, tEdgeCapMap, tEdgeResCapMap, tRevEdgeMap, tVertexPredMap,
420 tVertexColorMap, tDistanceMap, tIndexMap
422 tKolmo instance(g, src, sink);
423 return instance.test();
426 int test_main(int argc, char* argv[])
430 std::size_t seed = 1;
432 if (argc > 1) n_verts = lexical_cast<int>(argv[1]);
433 if (argc > 2) n_edges = lexical_cast<int>(argv[2]);
434 if (argc > 3) seed = lexical_cast<std::size_t>(argv[3]);
436 //we need at least 2 vertices to create src and sink in random graphs
437 //this case is also caught in boykov_kolmogorov_max_flow
441 // below are checks for different calls to boykov_kolmogorov_max_flow and different graph-types
443 //checks support of vecS storage
444 long flow_vecS = test_adjacency_list_vecS(n_verts, n_edges, seed);
445 std::cout << "vecS flow: " << flow_vecS << std::endl;
446 //checks support of listS storage (especially problems with vertex indices)
447 long flow_listS = test_adjacency_list_listS(n_verts, n_edges, seed);
448 std::cout << "listS flow: " << flow_listS << std::endl;
449 BOOST_CHECK(flow_vecS == flow_listS);
450 //checks bundled properties
451 long flow_bundles = test_bundled_properties(n_verts, n_edges, seed);
452 std::cout << "bundles flow: " << flow_bundles << std::endl;
453 BOOST_CHECK(flow_listS == flow_bundles);
455 long flow_overloads = test_overloads(n_verts, n_edges, seed);
456 std::cout << "overloads flow: " << flow_overloads << std::endl;
457 BOOST_CHECK(flow_bundles == flow_overloads);
459 // excessive test version where Boykov-Kolmogorov's algorithm invariants are
461 long flow_invariants = test_algorithms_invariant(n_verts, n_edges, seed);
462 std::cout << "invariants flow: " << flow_invariants << std::endl;
463 BOOST_CHECK(flow_overloads == flow_invariants);