466 lines
20 KiB
C++
466 lines
20 KiB
C++
// Copyright (c) 2006, Stephan Diederich
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//
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// This code may be used under either of the following two licences:
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//
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
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// files (the "Software"), to deal in the Software without
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// restriction, including without limitation the rights to use,
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// copy, modify, merge, publish, distribute, sublicense, and/or
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// sell copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following
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// conditions:
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//
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE. OF SUCH DAMAGE.
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//
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// Or:
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//
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// Distributed under the Boost Software License, Version 1.0.
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// (See accompanying file LICENSE_1_0.txt or copy at
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// http://www.boost.org/LICENSE_1_0.txt)
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#include <vector>
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#include <iterator>
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#include <iostream>
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#include <algorithm>
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#include <fstream>
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#include <boost/test/minimal.hpp>
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#include <boost/graph/boykov_kolmogorov_max_flow.hpp>
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#include <boost/graph/adjacency_list.hpp>
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#include <boost/graph/adjacency_matrix.hpp>
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#include <boost/graph/random.hpp>
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#include <boost/property_map/property_map.hpp>
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#include <boost/random/linear_congruential.hpp>
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#include <boost/lexical_cast.hpp>
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using namespace boost;
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template <typename Graph, typename CapacityMap, typename ReverseEdgeMap>
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std::pair< typename graph_traits<Graph>::vertex_descriptor,typename graph_traits<Graph>::vertex_descriptor>
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fill_random_max_flow_graph(Graph& g, CapacityMap cap, ReverseEdgeMap rev, typename graph_traits<Graph>::vertices_size_type n_verts,
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typename graph_traits<Graph>::edges_size_type n_edges, std::size_t seed)
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{
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typedef typename graph_traits<Graph>::edge_descriptor edge_descriptor;
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typedef typename graph_traits<Graph>::vertex_descriptor vertex_descriptor;
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const int cap_low = 1;
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const int cap_high = 1000;
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//init random numer generator
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minstd_rand gen(seed);
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//generate graph
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generate_random_graph(g, n_verts, n_edges, gen);
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//init an uniform distribution int generator
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typedef variate_generator<minstd_rand, uniform_int<int> > tIntGen;
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tIntGen int_gen(gen, uniform_int<int>(cap_low, cap_high));
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//randomize edge-capacities
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//randomize_property<edge_capacity, Graph, tIntGen> (g,int_gen); //we cannot use this, as we have no idea how properties are stored, right?
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typename graph_traits<Graph>::edge_iterator ei, e_end;
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for(boost::tie(ei,e_end) = edges(g); ei != e_end; ++ei)
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cap[*ei] = int_gen();
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//get source and sink node
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vertex_descriptor s = random_vertex(g, gen);
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vertex_descriptor t = graph_traits<Graph>::null_vertex();
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while(t == graph_traits<Graph>::null_vertex() || t == s)
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t = random_vertex(g, gen);
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//add reverse edges (ugly... how to do better?!)
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std::list<edge_descriptor> edges_copy;
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boost::tie(ei, e_end) = edges(g);
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std::copy(ei, e_end, std::back_insert_iterator< std::list<edge_descriptor> >(edges_copy));
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while(!edges_copy.empty()){
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edge_descriptor old_edge = edges_copy.front();
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edges_copy.pop_front();
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vertex_descriptor source_vertex = target(old_edge, g);
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vertex_descriptor target_vertex = source(old_edge, g);
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bool inserted;
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edge_descriptor new_edge;
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boost::tie(new_edge,inserted) = add_edge(source_vertex, target_vertex, g);
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assert(inserted);
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rev[old_edge] = new_edge;
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rev[new_edge] = old_edge ;
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cap[new_edge] = 0;
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}
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return std::make_pair(s,t);
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}
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long test_adjacency_list_vecS(int n_verts, int n_edges, std::size_t seed){
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typedef adjacency_list_traits<vecS, vecS, directedS> tVectorTraits;
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typedef adjacency_list<vecS, vecS, directedS,
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property<vertex_index_t, long,
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property<vertex_predecessor_t, tVectorTraits::edge_descriptor,
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property<vertex_color_t, boost::default_color_type,
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property<vertex_distance_t, long> > > >,
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property<edge_capacity_t, long,
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property<edge_residual_capacity_t, long,
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property<edge_reverse_t, tVectorTraits::edge_descriptor > > > > tVectorGraph;
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tVectorGraph g;
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graph_traits<tVectorGraph>::vertex_descriptor src,sink;
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boost::tie(src,sink) = fill_random_max_flow_graph(g, get(edge_capacity,g), get(edge_reverse, g), n_verts, n_edges, seed);
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return boykov_kolmogorov_max_flow(g, get(edge_capacity, g),
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get(edge_residual_capacity, g),
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get(edge_reverse, g),
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get(vertex_predecessor, g),
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get(vertex_color, g),
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get(vertex_distance, g),
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get(vertex_index, g),
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src, sink);
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}
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long test_adjacency_list_listS(int n_verts, int n_edges, std::size_t seed){
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typedef adjacency_list_traits<listS, listS, directedS> tListTraits;
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typedef adjacency_list<listS, listS, directedS,
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property<vertex_index_t, long,
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property<vertex_predecessor_t, tListTraits::edge_descriptor,
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property<vertex_color_t, boost::default_color_type,
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property<vertex_distance_t, long> > > >,
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property<edge_capacity_t, long,
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property<edge_residual_capacity_t, long,
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property<edge_reverse_t, tListTraits::edge_descriptor > > > > tListGraph;
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tListGraph g;
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graph_traits<tListGraph>::vertex_descriptor src,sink;
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boost::tie(src,sink) = fill_random_max_flow_graph(g, get(edge_capacity,g), get(edge_reverse, g), n_verts, n_edges, seed);
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//initialize vertex indices
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graph_traits<tListGraph>::vertex_iterator vi,v_end;
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graph_traits<tListGraph>::vertices_size_type index = 0;
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for(boost::tie(vi, v_end) = vertices(g); vi != v_end; ++vi){
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put(vertex_index, g, *vi, index++);
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}
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return boykov_kolmogorov_max_flow(g, get(edge_capacity, g),
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get(edge_residual_capacity, g),
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get(edge_reverse, g),
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get(vertex_predecessor, g),
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get(vertex_color, g),
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get(vertex_distance, g),
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get(vertex_index, g),
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src, sink);
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}
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template<typename EdgeDescriptor>
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struct Node{
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boost::default_color_type vertex_color;
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long vertex_distance;
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EdgeDescriptor vertex_predecessor;
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};
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template<typename EdgeDescriptor>
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struct Link{
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long edge_capacity;
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long edge_residual_capacity;
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EdgeDescriptor edge_reverse;
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};
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long test_bundled_properties(int n_verts, int n_edges, std::size_t seed){
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typedef adjacency_list_traits<vecS, vecS, directedS> tTraits;
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typedef Node<tTraits::edge_descriptor> tVertex;
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typedef Link<tTraits::edge_descriptor> tEdge;
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typedef adjacency_list<vecS, vecS, directedS, tVertex, tEdge> tBundleGraph;
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tBundleGraph g;
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graph_traits<tBundleGraph>::vertex_descriptor src,sink;
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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);
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return boykov_kolmogorov_max_flow(g, get(&tEdge::edge_capacity, g),
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get(&tEdge::edge_residual_capacity, g),
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get(&tEdge::edge_reverse, g),
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get(&tVertex::vertex_predecessor, g),
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get(&tVertex::vertex_color, g),
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get(&tVertex::vertex_distance, g),
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get(vertex_index, g),
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src, sink);
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}
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long test_overloads(int n_verts, int n_edges, std::size_t seed){
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typedef adjacency_list_traits<vecS, vecS, directedS> tTraits;
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typedef property <edge_capacity_t, long,
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property<edge_residual_capacity_t, long,
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property<edge_reverse_t, tTraits::edge_descriptor> > >tEdgeProperty;
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typedef adjacency_list<vecS, vecS, directedS, no_property, tEdgeProperty> tGraph;
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tGraph g;
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graph_traits<tGraph>::vertex_descriptor src,sink;
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boost::tie(src,sink) = fill_random_max_flow_graph(g, get(edge_capacity,g), get(edge_reverse, g), n_verts, n_edges, seed);
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std::vector<graph_traits<tGraph>::edge_descriptor> predecessor_vec(n_verts);
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std::vector<default_color_type> color_vec(n_verts);
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std::vector<graph_traits<tGraph>::vertices_size_type> distance_vec(n_verts);
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long flow_overload_1 =
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boykov_kolmogorov_max_flow(g,
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get(edge_capacity,g),
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get(edge_residual_capacity,g),
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get(edge_reverse,g),
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get(vertex_index,g),
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src, sink);
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long flow_overload_2 =
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boykov_kolmogorov_max_flow(g,
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get(edge_capacity,g),
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get(edge_residual_capacity,g),
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get(edge_reverse,g),
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boost::make_iterator_property_map(
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color_vec.begin(), get(vertex_index, g)),
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get(vertex_index,g),
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src, sink);
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BOOST_CHECK(flow_overload_1 == flow_overload_2);
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return flow_overload_1;
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}
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template<class Graph,
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class EdgeCapacityMap,
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class ResidualCapacityEdgeMap,
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class ReverseEdgeMap,
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class PredecessorMap,
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class ColorMap,
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class DistanceMap,
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class IndexMap>
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class boykov_kolmogorov_test
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: public detail::bk_max_flow<
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Graph, EdgeCapacityMap, ResidualCapacityEdgeMap, ReverseEdgeMap,
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PredecessorMap, ColorMap, DistanceMap, IndexMap
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>
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{
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typedef typename graph_traits<Graph>::edge_descriptor tEdge;
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typedef typename graph_traits<Graph>::vertex_descriptor tVertex;
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typedef typename property_traits< typename property_map<Graph, edge_capacity_t>::const_type>::value_type tEdgeVal;
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typedef typename graph_traits<Graph>::vertex_iterator tVertexIterator;
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typedef typename graph_traits<Graph>::out_edge_iterator tOutEdgeIterator;
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typedef typename property_traits<ColorMap>::value_type tColorValue;
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typedef color_traits<tColorValue> tColorTraits;
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typedef typename property_traits<DistanceMap>::value_type tDistanceVal;
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typedef typename detail::bk_max_flow<
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Graph, EdgeCapacityMap, ResidualCapacityEdgeMap, ReverseEdgeMap,
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PredecessorMap, ColorMap, DistanceMap, IndexMap
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> tSuper;
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public:
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boykov_kolmogorov_test(Graph& g,
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typename graph_traits<Graph>::vertex_descriptor src,
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typename graph_traits<Graph>::vertex_descriptor sink)
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: tSuper(g, get(edge_capacity,g), get(edge_residual_capacity,g),
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get(edge_reverse, g), get(vertex_predecessor, g),
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get(vertex_color, g), get(vertex_distance, g),
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get(vertex_index, g), src, sink)
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{ }
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void invariant_four(tVertex v) const{
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//passive nodes in S or T
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if(v == tSuper::m_source || v == tSuper::m_sink)
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return;
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typename std::list<tVertex>::const_iterator it = find(tSuper::m_orphans.begin(), tSuper::m_orphans.end(), v);
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// 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)
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bool is_active = (tSuper::m_in_active_list_map[v] && (tSuper::has_parent(v) || it != tSuper::m_orphans.end() ));
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if(this->get_tree(v) != tColorTraits::gray() && !is_active){
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typename graph_traits<Graph>::out_edge_iterator ei,e_end;
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for(boost::tie(ei, e_end) = out_edges(v, tSuper::m_g); ei != e_end; ++ei){
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const tVertex& other_node = target(*ei, tSuper::m_g);
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if(this->get_tree(other_node) != this->get_tree(v)){
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if(this->get_tree(v) == tColorTraits::black())
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BOOST_CHECK(tSuper::m_res_cap_map[*ei] == 0);
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else
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BOOST_CHECK(tSuper::m_res_cap_map[tSuper::m_rev_edge_map[*ei]] == 0);
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}
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}
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}
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}
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void invariant_five(const tVertex& v) const{
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BOOST_CHECK(this->get_tree(v) != tColorTraits::gray() || tSuper::m_time_map[v] <= tSuper::m_time);
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}
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void invariant_six(const tVertex& v) const{
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if(this->get_tree(v) == tColorTraits::gray() || tSuper::m_time_map[v] != tSuper::m_time)
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return;
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else{
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tVertex current_node = v;
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tDistanceVal distance = 0;
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tColorValue color = this->get_tree(v);
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tVertex terminal = (color == tColorTraits::black()) ? tSuper::m_source : tSuper::m_sink;
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while(current_node != terminal){
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BOOST_CHECK(tSuper::has_parent(current_node));
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tEdge e = this->get_edge_to_parent(current_node);
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++distance;
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current_node = (color == tColorTraits::black())? source(e, tSuper::m_g) : target(e, tSuper::m_g);
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if(distance > tSuper::m_dist_map[v])
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break;
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}
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BOOST_CHECK(distance == tSuper::m_dist_map[v]);
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}
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}
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void invariant_seven(const tVertex& v) const{
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if(this->get_tree(v) == tColorTraits::gray())
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return;
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else{
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tColorValue color = this->get_tree(v);
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long time = tSuper::m_time_map[v];
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tVertex current_node = v;
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while(tSuper::has_parent(current_node)){
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tEdge e = this->get_edge_to_parent(current_node);
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current_node = (color == tColorTraits::black()) ? source(e, tSuper::m_g) : target(e, tSuper::m_g);
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BOOST_CHECK(tSuper::m_time_map[current_node] >= time);
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}
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}
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}//invariant_seven
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void invariant_eight(const tVertex& v) const{
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if(this->get_tree(v) == tColorTraits::gray())
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return;
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else{
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tColorValue color = this->get_tree(v);
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long time = tSuper::m_time_map[v];
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tDistanceVal distance = tSuper::m_dist_map[v];
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tVertex current_node = v;
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while(tSuper::has_parent(current_node)){
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tEdge e = this->get_edge_to_parent(current_node);
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current_node = (color == tColorTraits::black()) ? source(e, tSuper::m_g) : target(e, tSuper::m_g);
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if(tSuper::m_time_map[current_node] == time)
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BOOST_CHECK(tSuper::m_dist_map[current_node] < distance);
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}
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}
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}//invariant_eight
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void check_invariants(){
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tVertexIterator vi, v_end;
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for(boost::tie(vi, v_end) = vertices(tSuper::m_g); vi != v_end; ++vi){
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invariant_four(*vi);
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invariant_five(*vi);
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invariant_six(*vi);
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invariant_seven(*vi);
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invariant_eight(*vi);
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}
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}
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tEdgeVal test(){
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this->add_active_node(this->m_sink);
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this->augment_direct_paths();
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check_invariants();
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//start the main-loop
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while(true){
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bool path_found;
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tEdge connecting_edge;
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boost::tie(connecting_edge, path_found) = this->grow(); //find a path from source to sink
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if(!path_found){
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//we're finished, no more paths were found
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break;
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}
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check_invariants();
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this->m_time++;
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this->augment(connecting_edge); //augment that path
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check_invariants();
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this->adopt(); //rebuild search tree structure
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check_invariants();
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}
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//check if flow is the sum of outgoing edges of src
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tOutEdgeIterator ei, e_end;
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tEdgeVal src_sum = 0;
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for(boost::tie(ei, e_end) = out_edges(this->m_source, this->m_g); ei != e_end; ++ei){
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src_sum += this->m_cap_map[*ei] - this->m_res_cap_map[*ei];
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}
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BOOST_CHECK(this->m_flow == src_sum);
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//check if flow is the sum of ingoing edges of sink
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tEdgeVal sink_sum = 0;
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for(boost::tie(ei, e_end) = out_edges(this->m_sink, this->m_g); ei != e_end; ++ei){
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tEdge in_edge = this->m_rev_edge_map[*ei];
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sink_sum += this->m_cap_map[in_edge] - this->m_res_cap_map[in_edge];
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}
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BOOST_CHECK(this->m_flow == sink_sum);
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return this->m_flow;
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}
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};
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long test_algorithms_invariant(int n_verts, int n_edges, std::size_t seed)
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{
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typedef adjacency_list_traits<vecS, vecS, directedS> tVectorTraits;
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typedef adjacency_list<vecS, vecS, directedS,
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property<vertex_index_t, long,
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property<vertex_predecessor_t, tVectorTraits::edge_descriptor,
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property<vertex_color_t, default_color_type,
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property<vertex_distance_t, long> > > >,
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property<edge_capacity_t, long,
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property<edge_residual_capacity_t, long,
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property<edge_reverse_t, tVectorTraits::edge_descriptor > > > > tVectorGraph;
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tVectorGraph g;
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graph_traits<tVectorGraph>::vertex_descriptor src, sink;
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boost::tie(src,sink) = fill_random_max_flow_graph(g, get(edge_capacity,g), get(edge_reverse, g), n_verts, n_edges, seed);
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typedef property_map<tVectorGraph, edge_capacity_t>::type tEdgeCapMap;
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typedef property_map<tVectorGraph, edge_residual_capacity_t>::type tEdgeResCapMap;
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typedef property_map<tVectorGraph, edge_reverse_t>::type tRevEdgeMap;
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typedef property_map<tVectorGraph, vertex_predecessor_t>::type tVertexPredMap;
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typedef property_map<tVectorGraph, vertex_color_t>::type tVertexColorMap;
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typedef property_map<tVectorGraph, vertex_distance_t>::type tDistanceMap;
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typedef property_map<tVectorGraph, vertex_index_t>::type tIndexMap;
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typedef boykov_kolmogorov_test<
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tVectorGraph, tEdgeCapMap, tEdgeResCapMap, tRevEdgeMap, tVertexPredMap,
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tVertexColorMap, tDistanceMap, tIndexMap
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> tKolmo;
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tKolmo instance(g, src, sink);
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return instance.test();
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}
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|
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int test_main(int argc, char* argv[])
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|
{
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int n_verts = 10;
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int n_edges = 500;
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|
std::size_t seed = 1;
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|
|
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if (argc > 1) n_verts = lexical_cast<int>(argv[1]);
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|
if (argc > 2) n_edges = lexical_cast<int>(argv[2]);
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|
if (argc > 3) seed = lexical_cast<std::size_t>(argv[3]);
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|
|
|
//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);
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|
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;
|
|
}
|