[899] | 1 | // -*- c++ -*- |
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[901] | 2 | #ifndef HUGO_SUURBALLE_H |
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| 3 | #define HUGO_SUURBALLE_H |
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[899] | 4 | |
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| 5 | ///\ingroup flowalgs |
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| 6 | ///\file |
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| 7 | ///\brief An algorithm for finding k paths of minimal total length. |
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| 8 | |
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| 9 | |
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| 10 | #include <hugo/maps.h> |
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| 11 | #include <vector> |
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| 12 | #include <hugo/min_cost_flow.h> |
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| 13 | |
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| 14 | namespace hugo { |
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| 15 | |
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| 16 | /// \addtogroup flowalgs |
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| 17 | /// @{ |
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| 18 | |
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| 19 | ///\brief Implementation of an algorithm for finding k edge-disjoint paths between 2 nodes |
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| 20 | /// of minimal total length |
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| 21 | /// |
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| 22 | /// The class \ref hugo::Suurballe implements |
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| 23 | /// an algorithm for finding k edge-disjoint paths |
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| 24 | /// from a given source node to a given target node in an |
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| 25 | /// edge-weighted directed graph having minimal total weight (length). |
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| 26 | /// |
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| 27 | ///\warning Length values should be nonnegative. |
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| 28 | /// |
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| 29 | ///\param Graph The directed graph type the algorithm runs on. |
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| 30 | ///\param LengthMap The type of the length map (values should be nonnegative). |
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| 31 | /// |
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| 32 | ///\note It it questionable if it is correct to call this method after |
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| 33 | ///%Suurballe for it is just a special case of Edmond's and Karp's algorithm |
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| 34 | ///for finding minimum cost flows. In fact, this implementation is just |
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| 35 | ///wraps the MinCostFlow algorithms. The paper of both %Suurballe and |
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| 36 | ///Edmonds-Karp published in 1972, therefore it is possibly right to |
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| 37 | ///state that they are |
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| 38 | ///independent results. Most frequently this special case is referred as |
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| 39 | ///%Suurballe method in the literature, especially in communication |
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| 40 | ///network context. |
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| 41 | ///\author Attila Bernath |
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| 42 | template <typename Graph, typename LengthMap> |
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| 43 | class Suurballe{ |
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| 44 | |
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| 45 | |
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| 46 | typedef typename LengthMap::ValueType Length; |
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| 47 | |
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| 48 | typedef typename Graph::Node Node; |
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| 49 | typedef typename Graph::NodeIt NodeIt; |
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| 50 | typedef typename Graph::Edge Edge; |
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| 51 | typedef typename Graph::OutEdgeIt OutEdgeIt; |
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| 52 | typedef typename Graph::template EdgeMap<int> EdgeIntMap; |
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| 53 | |
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| 54 | typedef ConstMap<Edge,int> ConstMap; |
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| 55 | |
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| 56 | //Input |
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| 57 | const Graph& G; |
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| 58 | |
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| 59 | //Auxiliary variables |
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| 60 | //This is the capacity map for the mincostflow problem |
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| 61 | ConstMap const1map; |
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| 62 | //This MinCostFlow instance will actually solve the problem |
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| 63 | MinCostFlow<Graph, LengthMap, ConstMap> mincost_flow; |
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| 64 | |
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| 65 | //Container to store found paths |
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| 66 | std::vector< std::vector<Edge> > paths; |
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| 67 | |
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| 68 | public : |
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| 69 | |
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| 70 | |
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| 71 | /// The constructor of the class. |
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| 72 | |
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| 73 | ///\param _G The directed graph the algorithm runs on. |
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| 74 | ///\param _length The length (weight or cost) of the edges. |
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| 75 | Suurballe(Graph& _G, LengthMap& _length) : G(_G), |
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| 76 | const1map(1), mincost_flow(_G, _length, const1map){} |
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| 77 | |
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| 78 | ///Runs the algorithm. |
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| 79 | |
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| 80 | ///Runs the algorithm. |
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| 81 | ///Returns k if there are at least k edge-disjoint paths from s to t. |
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| 82 | ///Otherwise it returns the number of found edge-disjoint paths from s to t. |
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| 83 | /// |
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| 84 | ///\param s The source node. |
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| 85 | ///\param t The target node. |
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| 86 | ///\param k How many paths are we looking for? |
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| 87 | /// |
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| 88 | int run(Node s, Node t, int k) { |
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| 89 | |
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| 90 | int i = mincost_flow.run(s,t,k); |
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| 91 | |
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| 92 | |
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| 93 | //Let's find the paths |
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| 94 | //We put the paths into stl vectors (as an inner representation). |
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| 95 | //In the meantime we lose the information stored in 'reversed'. |
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| 96 | //We suppose the lengths to be positive now. |
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| 97 | |
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| 98 | //We don't want to change the flow of mincost_flow, so we make a copy |
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| 99 | //The name here suggests that the flow has only 0/1 values. |
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| 100 | EdgeIntMap reversed(G); |
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| 101 | |
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| 102 | for(typename Graph::EdgeIt e(G); e!=INVALID; ++e) |
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| 103 | reversed[e] = mincost_flow.getFlow()[e]; |
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| 104 | |
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| 105 | paths.clear(); |
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| 106 | //total_length=0; |
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| 107 | paths.resize(k); |
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| 108 | for (int j=0; j<i; ++j){ |
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| 109 | Node n=s; |
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| 110 | OutEdgeIt e; |
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| 111 | |
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| 112 | while (n!=t){ |
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| 113 | |
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| 114 | |
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| 115 | G.first(e,n); |
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| 116 | |
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| 117 | while (!reversed[e]){ |
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| 118 | ++e; |
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| 119 | } |
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| 120 | n = G.head(e); |
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| 121 | paths[j].push_back(e); |
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| 122 | //total_length += length[e]; |
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| 123 | reversed[e] = 1-reversed[e]; |
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| 124 | } |
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| 125 | |
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| 126 | } |
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| 127 | return i; |
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| 128 | } |
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| 129 | |
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| 130 | |
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| 131 | ///Returns the total length of the paths |
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| 132 | |
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| 133 | ///This function gives back the total length of the found paths. |
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| 134 | ///\pre \ref run() must |
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| 135 | ///be called before using this function. |
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| 136 | Length totalLength(){ |
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| 137 | return mincost_flow.totalLength(); |
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| 138 | } |
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| 139 | |
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| 140 | ///Returns the found flow. |
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| 141 | |
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| 142 | ///This function returns a const reference to the EdgeMap \c flow. |
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| 143 | ///\pre \ref run() must |
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| 144 | ///be called before using this function. |
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| 145 | const EdgeIntMap &getFlow() const { return mincost_flow.flow;} |
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| 146 | |
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| 147 | /// Returns the optimal dual solution |
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| 148 | |
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| 149 | ///This function returns a const reference to the NodeMap |
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| 150 | ///\c potential (the dual solution). |
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| 151 | /// \pre \ref run() must be called before using this function. |
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| 152 | const EdgeIntMap &getPotential() const { return mincost_flow.potential;} |
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| 153 | |
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| 154 | ///Checks whether the complementary slackness holds. |
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| 155 | |
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| 156 | ///This function checks, whether the given solution is optimal. |
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| 157 | ///It should return true after calling \ref run() |
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| 158 | ///Currently this function only checks optimality, |
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| 159 | ///doesn't bother with feasibility |
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| 160 | ///It is meant for testing purposes. |
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| 161 | /// |
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| 162 | bool checkComplementarySlackness(){ |
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| 163 | return mincost_flow.checkComplementarySlackness(); |
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| 164 | } |
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| 165 | |
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| 166 | ///Read the found paths. |
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| 167 | |
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| 168 | ///This function gives back the \c j-th path in argument p. |
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| 169 | ///Assumes that \c run() has been run and nothing changed since then. |
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| 170 | /// \warning It is assumed that \c p is constructed to |
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| 171 | ///be a path of graph \c G. |
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| 172 | ///If \c j is not less than the result of previous \c run, |
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| 173 | ///then the result here will be an empty path (\c j can be 0 as well). |
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| 174 | /// |
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| 175 | ///\param Path The type of the path structure to put the result to (must meet hugo path concept). |
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| 176 | ///\param p The path to put the result to |
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| 177 | ///\param j Which path you want to get from the found paths (in a real application you would get the found paths iteratively) |
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| 178 | template<typename Path> |
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| 179 | void getPath(Path& p, size_t j){ |
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| 180 | |
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| 181 | p.clear(); |
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| 182 | if (j>paths.size()-1){ |
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| 183 | return; |
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| 184 | } |
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| 185 | typename Path::Builder B(p); |
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| 186 | for(typename std::vector<Edge>::iterator i=paths[j].begin(); |
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| 187 | i!=paths[j].end(); ++i ){ |
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| 188 | B.pushBack(*i); |
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| 189 | } |
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| 190 | |
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| 191 | B.commit(); |
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| 192 | } |
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| 193 | |
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| 194 | }; //class Suurballe |
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| 195 | |
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| 196 | ///@} |
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| 197 | |
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| 198 | } //namespace hugo |
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| 199 | |
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[901] | 200 | #endif //HUGO_SUURBALLE_H |
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