| 1 | /* -*- mode: C++; indent-tabs-mode: nil; -*- | 
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| 2 | * | 
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| 3 | * This file is a part of LEMON, a generic C++ optimization library. | 
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| 4 | * | 
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| 5 | * Copyright (C) 2003-2013 | 
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| 6 | * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport | 
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| 7 | * (Egervary Research Group on Combinatorial Optimization, EGRES). | 
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| 8 | * | 
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| 9 | * Permission to use, modify and distribute this software is granted | 
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| 10 | * provided that this copyright notice appears in all copies. For | 
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| 11 | * precise terms see the accompanying LICENSE file. | 
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| 12 | * | 
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| 13 | * This software is provided "AS IS" with no warranty of any kind, | 
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| 14 | * express or implied, and with no claim as to its suitability for any | 
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| 15 | * purpose. | 
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| 16 | * | 
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| 17 | */ | 
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| 18 |  | 
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| 19 | #ifndef LEMON_EDMONDS_KARP_H | 
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| 20 | #define LEMON_EDMONDS_KARP_H | 
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| 21 |  | 
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| 22 | /// \file | 
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| 23 | /// \ingroup max_flow | 
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| 24 | /// \brief Implementation of the Edmonds-Karp algorithm. | 
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| 25 |  | 
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| 26 | #include <lemon/tolerance.h> | 
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| 27 | #include <vector> | 
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| 28 |  | 
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| 29 | namespace lemon { | 
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| 30 |  | 
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| 31 | /// \brief Default traits class of EdmondsKarp class. | 
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| 32 | /// | 
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| 33 | /// Default traits class of EdmondsKarp class. | 
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| 34 | /// \param GR Digraph type. | 
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| 35 | /// \param CAP Type of capacity map. | 
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| 36 | template <typename GR, typename CAP> | 
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| 37 | struct EdmondsKarpDefaultTraits { | 
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| 38 |  | 
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| 39 | /// \brief The digraph type the algorithm runs on. | 
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| 40 | typedef GR Digraph; | 
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| 41 |  | 
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| 42 | /// \brief The type of the map that stores the arc capacities. | 
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| 43 | /// | 
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| 44 | /// The type of the map that stores the arc capacities. | 
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| 45 | /// It must meet the \ref concepts::ReadMap "ReadMap" concept. | 
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| 46 | typedef CAP CapacityMap; | 
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| 47 |  | 
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| 48 | /// \brief The type of the flow values. | 
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| 49 | typedef typename CapacityMap::Value Value; | 
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| 50 |  | 
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| 51 | /// \brief The type of the map that stores the flow values. | 
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| 52 | /// | 
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| 53 | /// The type of the map that stores the flow values. | 
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| 54 | /// It must meet the \ref concepts::ReadWriteMap "ReadWriteMap" concept. | 
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| 55 | #ifdef DOXYGEN | 
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| 56 | typedef GR::ArcMap<Value> FlowMap; | 
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| 57 | #else | 
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| 58 | typedef typename Digraph::template ArcMap<Value> FlowMap; | 
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| 59 | #endif | 
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| 60 |  | 
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| 61 | /// \brief Instantiates a FlowMap. | 
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| 62 | /// | 
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| 63 | /// This function instantiates a \ref FlowMap. | 
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| 64 | /// \param digraph The digraph for which we would like to define | 
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| 65 | /// the flow map. | 
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| 66 | static FlowMap* createFlowMap(const Digraph& digraph) { | 
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| 67 | return new FlowMap(digraph); | 
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| 68 | } | 
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| 69 |  | 
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| 70 | /// \brief The tolerance used by the algorithm | 
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| 71 | /// | 
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| 72 | /// The tolerance used by the algorithm to handle inexact computation. | 
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| 73 | typedef lemon::Tolerance<Value> Tolerance; | 
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| 74 |  | 
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| 75 | }; | 
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| 76 |  | 
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| 77 | /// \ingroup max_flow | 
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| 78 | /// | 
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| 79 | /// \brief Edmonds-Karp algorithms class. | 
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| 80 | /// | 
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| 81 | /// This class provides an implementation of the \e Edmonds-Karp \e | 
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| 82 | /// algorithm producing a \ref max_flow "flow of maximum value" in a | 
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| 83 | /// digraph \cite clrs01algorithms, \cite amo93networkflows, | 
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| 84 | /// \cite edmondskarp72theoretical. | 
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| 85 | /// The Edmonds-Karp algorithm is slower than the Preflow | 
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| 86 | /// algorithm, but it has an advantage of the step-by-step execution | 
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| 87 | /// control with feasible flow solutions. The \e source node, the \e | 
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| 88 | /// target node, the \e capacity of the arcs and the \e starting \e | 
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| 89 | /// flow value of the arcs should be passed to the algorithm | 
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| 90 | /// through the constructor. | 
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| 91 | /// | 
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| 92 | /// The time complexity of the algorithm is \f$ O(nm^2) \f$ in | 
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| 93 | /// worst case. Always try the Preflow algorithm instead of this if | 
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| 94 | /// you just want to compute the optimal flow. | 
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| 95 | /// | 
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| 96 | /// \tparam GR The type of the digraph the algorithm runs on. | 
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| 97 | /// \tparam CAP The type of the capacity map. The default map | 
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| 98 | /// type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>". | 
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| 99 | /// \tparam TR The traits class that defines various types used by the | 
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| 100 | /// algorithm. By default, it is \ref EdmondsKarpDefaultTraits | 
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| 101 | /// "EdmondsKarpDefaultTraits<GR, CAP>". | 
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| 102 | /// In most cases, this parameter should not be set directly, | 
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| 103 | /// consider to use the named template parameters instead. | 
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| 104 |  | 
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| 105 | #ifdef DOXYGEN | 
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| 106 | template <typename GR, typename CAP, typename TR> | 
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| 107 | #else | 
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| 108 | template <typename GR, | 
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| 109 | typename CAP = typename GR::template ArcMap<int>, | 
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| 110 | typename TR = EdmondsKarpDefaultTraits<GR, CAP> > | 
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| 111 | #endif | 
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| 112 | class EdmondsKarp { | 
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| 113 | public: | 
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| 114 |  | 
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| 115 | /// \brief The \ref lemon::EdmondsKarpDefaultTraits "traits class" | 
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| 116 | /// of the algorithm. | 
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| 117 | typedef TR Traits; | 
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| 118 | /// The type of the digraph the algorithm runs on. | 
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| 119 | typedef typename Traits::Digraph Digraph; | 
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| 120 | /// The type of the capacity map. | 
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| 121 | typedef typename Traits::CapacityMap CapacityMap; | 
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| 122 | /// The type of the flow values. | 
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| 123 | typedef typename Traits::Value Value; | 
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| 124 |  | 
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| 125 | /// The type of the flow map. | 
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| 126 | typedef typename Traits::FlowMap FlowMap; | 
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| 127 | /// The type of the tolerance. | 
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| 128 | typedef typename Traits::Tolerance Tolerance; | 
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| 129 |  | 
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| 130 | private: | 
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| 131 |  | 
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| 132 | TEMPLATE_DIGRAPH_TYPEDEFS(Digraph); | 
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| 133 | typedef typename Digraph::template NodeMap<Arc> PredMap; | 
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| 134 |  | 
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| 135 | const Digraph& _graph; | 
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| 136 | const CapacityMap* _capacity; | 
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| 137 |  | 
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| 138 | Node _source, _target; | 
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| 139 |  | 
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| 140 | FlowMap* _flow; | 
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| 141 | bool _local_flow; | 
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| 142 |  | 
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| 143 | PredMap* _pred; | 
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| 144 | std::vector<Node> _queue; | 
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| 145 |  | 
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| 146 | Tolerance _tolerance; | 
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| 147 | Value _flow_value; | 
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| 148 |  | 
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| 149 | void createStructures() { | 
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| 150 | if (!_flow) { | 
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| 151 | _flow = Traits::createFlowMap(_graph); | 
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| 152 | _local_flow = true; | 
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| 153 | } | 
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| 154 | if (!_pred) { | 
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| 155 | _pred = new PredMap(_graph); | 
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| 156 | } | 
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| 157 | _queue.resize(countNodes(_graph)); | 
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| 158 | } | 
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| 159 |  | 
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| 160 | void destroyStructures() { | 
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| 161 | if (_local_flow) { | 
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| 162 | delete _flow; | 
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| 163 | } | 
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| 164 | if (_pred) { | 
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| 165 | delete _pred; | 
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| 166 | } | 
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| 167 | } | 
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| 168 |  | 
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| 169 | public: | 
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| 170 |  | 
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| 171 | typedef EdmondsKarp Create; | 
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| 172 |  | 
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| 173 | ///\name Named template parameters | 
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| 174 |  | 
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| 175 | ///@{ | 
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| 176 |  | 
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| 177 | template <typename T> | 
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| 178 | struct SetFlowMapTraits : public Traits { | 
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| 179 | typedef T FlowMap; | 
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| 180 | static FlowMap *createFlowMap(const Digraph&) { | 
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| 181 | LEMON_ASSERT(false, "FlowMap is not initialized"); | 
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| 182 | return 0; | 
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| 183 | } | 
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| 184 | }; | 
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| 185 |  | 
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| 186 | /// \brief \ref named-templ-param "Named parameter" for setting | 
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| 187 | /// FlowMap type | 
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| 188 | /// | 
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| 189 | /// \ref named-templ-param "Named parameter" for setting FlowMap | 
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| 190 | /// type | 
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| 191 | template <typename T> | 
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| 192 | struct SetFlowMap | 
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| 193 | : public EdmondsKarp<Digraph, CapacityMap, SetFlowMapTraits<T> > { | 
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| 194 | typedef EdmondsKarp<Digraph, CapacityMap, SetFlowMapTraits<T> > Create; | 
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| 195 | }; | 
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| 196 |  | 
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| 197 | /// @} | 
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| 198 |  | 
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| 199 | protected: | 
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| 200 |  | 
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| 201 | EdmondsKarp() {} | 
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| 202 |  | 
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| 203 | public: | 
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| 204 |  | 
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| 205 | /// \brief The constructor of the class. | 
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| 206 | /// | 
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| 207 | /// The constructor of the class. | 
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| 208 | /// \param digraph The digraph the algorithm runs on. | 
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| 209 | /// \param capacity The capacity of the arcs. | 
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| 210 | /// \param source The source node. | 
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| 211 | /// \param target The target node. | 
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| 212 | EdmondsKarp(const Digraph& digraph, const CapacityMap& capacity, | 
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| 213 | Node source, Node target) | 
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| 214 | : _graph(digraph), _capacity(&capacity), _source(source), _target(target), | 
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| 215 | _flow(0), _local_flow(false), _pred(0), _tolerance(), _flow_value() | 
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| 216 | { | 
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| 217 | LEMON_ASSERT(_source != _target, | 
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| 218 | "Flow source and target are the same nodes."); | 
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| 219 | } | 
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| 220 |  | 
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| 221 | /// \brief Destructor. | 
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| 222 | /// | 
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| 223 | /// Destructor. | 
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| 224 | ~EdmondsKarp() { | 
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| 225 | destroyStructures(); | 
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| 226 | } | 
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| 227 |  | 
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| 228 | /// \brief Sets the capacity map. | 
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| 229 | /// | 
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| 230 | /// Sets the capacity map. | 
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| 231 | /// \return <tt>(*this)</tt> | 
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| 232 | EdmondsKarp& capacityMap(const CapacityMap& map) { | 
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| 233 | _capacity = ↦ | 
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| 234 | return *this; | 
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| 235 | } | 
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| 236 |  | 
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| 237 | /// \brief Sets the flow map. | 
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| 238 | /// | 
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| 239 | /// Sets the flow map. | 
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| 240 | /// If you don't use this function before calling \ref run() or | 
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| 241 | /// \ref init(), an instance will be allocated automatically. | 
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| 242 | /// The destructor deallocates this automatically allocated map, | 
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| 243 | /// of course. | 
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| 244 | /// \return <tt>(*this)</tt> | 
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| 245 | EdmondsKarp& flowMap(FlowMap& map) { | 
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| 246 | if (_local_flow) { | 
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| 247 | delete _flow; | 
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| 248 | _local_flow = false; | 
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| 249 | } | 
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| 250 | _flow = ↦ | 
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| 251 | return *this; | 
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| 252 | } | 
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| 253 |  | 
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| 254 | /// \brief Sets the source node. | 
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| 255 | /// | 
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| 256 | /// Sets the source node. | 
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| 257 | /// \return <tt>(*this)</tt> | 
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| 258 | EdmondsKarp& source(const Node& node) { | 
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| 259 | _source = node; | 
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| 260 | return *this; | 
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| 261 | } | 
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| 262 |  | 
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| 263 | /// \brief Sets the target node. | 
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| 264 | /// | 
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| 265 | /// Sets the target node. | 
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| 266 | /// \return <tt>(*this)</tt> | 
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| 267 | EdmondsKarp& target(const Node& node) { | 
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| 268 | _target = node; | 
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| 269 | return *this; | 
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| 270 | } | 
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| 271 |  | 
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| 272 | /// \brief Sets the tolerance used by algorithm. | 
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| 273 | /// | 
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| 274 | /// Sets the tolerance used by algorithm. | 
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| 275 | /// \return <tt>(*this)</tt> | 
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| 276 | EdmondsKarp& tolerance(const Tolerance& tolerance) { | 
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| 277 | _tolerance = tolerance; | 
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| 278 | return *this; | 
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| 279 | } | 
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| 280 |  | 
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| 281 | /// \brief Returns a const reference to the tolerance. | 
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| 282 | /// | 
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| 283 | /// Returns a const reference to the tolerance object used by | 
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| 284 | /// the algorithm. | 
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| 285 | const Tolerance& tolerance() const { | 
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| 286 | return _tolerance; | 
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| 287 | } | 
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| 288 |  | 
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| 289 | /// \name Execution control | 
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| 290 | /// The simplest way to execute the algorithm is to use \ref run().\n | 
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| 291 | /// If you need better control on the initial solution or the execution, | 
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| 292 | /// you have to call one of the \ref init() functions first, then | 
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| 293 | /// \ref start() or multiple times the \ref augment() function. | 
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| 294 |  | 
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| 295 | ///@{ | 
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| 296 |  | 
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| 297 | /// \brief Initializes the algorithm. | 
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| 298 | /// | 
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| 299 | /// Initializes the internal data structures and sets the initial | 
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| 300 | /// flow to zero on each arc. | 
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| 301 | void init() { | 
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| 302 | createStructures(); | 
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| 303 | for (ArcIt it(_graph); it != INVALID; ++it) { | 
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| 304 | _flow->set(it, 0); | 
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| 305 | } | 
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| 306 | _flow_value = 0; | 
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| 307 | } | 
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| 308 |  | 
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| 309 | /// \brief Initializes the algorithm using the given flow map. | 
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| 310 | /// | 
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| 311 | /// Initializes the internal data structures and sets the initial | 
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| 312 | /// flow to the given \c flowMap. The \c flowMap should | 
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| 313 | /// contain a feasible flow, i.e. at each node excluding the source | 
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| 314 | /// and the target, the incoming flow should be equal to the | 
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| 315 | /// outgoing flow. | 
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| 316 | template <typename FlowMap> | 
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| 317 | void init(const FlowMap& flowMap) { | 
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| 318 | createStructures(); | 
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| 319 | for (ArcIt e(_graph); e != INVALID; ++e) { | 
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| 320 | _flow->set(e, flowMap[e]); | 
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| 321 | } | 
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| 322 | _flow_value = 0; | 
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| 323 | for (OutArcIt jt(_graph, _source); jt != INVALID; ++jt) { | 
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| 324 | _flow_value += (*_flow)[jt]; | 
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| 325 | } | 
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| 326 | for (InArcIt jt(_graph, _source); jt != INVALID; ++jt) { | 
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| 327 | _flow_value -= (*_flow)[jt]; | 
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| 328 | } | 
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| 329 | } | 
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| 330 |  | 
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| 331 | /// \brief Initializes the algorithm using the given flow map. | 
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| 332 | /// | 
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| 333 | /// Initializes the internal data structures and sets the initial | 
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| 334 | /// flow to the given \c flowMap. The \c flowMap should | 
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| 335 | /// contain a feasible flow, i.e. at each node excluding the source | 
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| 336 | /// and the target, the incoming flow should be equal to the | 
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| 337 | /// outgoing flow. | 
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| 338 | /// \return \c false when the given \c flowMap does not contain a | 
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| 339 | /// feasible flow. | 
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| 340 | template <typename FlowMap> | 
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| 341 | bool checkedInit(const FlowMap& flowMap) { | 
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| 342 | createStructures(); | 
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| 343 | for (ArcIt e(_graph); e != INVALID; ++e) { | 
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| 344 | _flow->set(e, flowMap[e]); | 
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| 345 | } | 
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| 346 | for (NodeIt it(_graph); it != INVALID; ++it) { | 
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| 347 | if (it == _source || it == _target) continue; | 
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| 348 | Value outFlow = 0; | 
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| 349 | for (OutArcIt jt(_graph, it); jt != INVALID; ++jt) { | 
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| 350 | outFlow += (*_flow)[jt]; | 
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| 351 | } | 
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| 352 | Value inFlow = 0; | 
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| 353 | for (InArcIt jt(_graph, it); jt != INVALID; ++jt) { | 
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| 354 | inFlow += (*_flow)[jt]; | 
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| 355 | } | 
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| 356 | if (_tolerance.different(outFlow, inFlow)) { | 
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| 357 | return false; | 
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| 358 | } | 
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| 359 | } | 
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| 360 | for (ArcIt it(_graph); it != INVALID; ++it) { | 
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| 361 | if (_tolerance.less((*_flow)[it], 0)) return false; | 
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| 362 | if (_tolerance.less((*_capacity)[it], (*_flow)[it])) return false; | 
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| 363 | } | 
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| 364 | _flow_value = 0; | 
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| 365 | for (OutArcIt jt(_graph, _source); jt != INVALID; ++jt) { | 
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| 366 | _flow_value += (*_flow)[jt]; | 
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| 367 | } | 
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| 368 | for (InArcIt jt(_graph, _source); jt != INVALID; ++jt) { | 
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| 369 | _flow_value -= (*_flow)[jt]; | 
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| 370 | } | 
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| 371 | return true; | 
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| 372 | } | 
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| 373 |  | 
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| 374 | /// \brief Augments the solution along a shortest path. | 
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| 375 | /// | 
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| 376 | /// Augments the solution along a shortest path. This function searches a | 
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| 377 | /// shortest path between the source and the target | 
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| 378 | /// in the residual digraph by the Bfs algoritm. | 
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| 379 | /// Then it increases the flow on this path with the minimal residual | 
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| 380 | /// capacity on the path. If there is no such path, it gives back | 
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| 381 | /// false. | 
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| 382 | /// \return \c false when the augmenting did not success, i.e. the | 
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| 383 | /// current flow is a feasible and optimal solution. | 
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| 384 | bool augment() { | 
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| 385 | for (NodeIt n(_graph); n != INVALID; ++n) { | 
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| 386 | _pred->set(n, INVALID); | 
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| 387 | } | 
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| 388 |  | 
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| 389 | int first = 0, last = 1; | 
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| 390 |  | 
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| 391 | _queue[0] = _source; | 
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| 392 | _pred->set(_source, OutArcIt(_graph, _source)); | 
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| 393 |  | 
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| 394 | while (first != last && (*_pred)[_target] == INVALID) { | 
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| 395 | Node n = _queue[first++]; | 
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| 396 |  | 
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| 397 | for (OutArcIt e(_graph, n); e != INVALID; ++e) { | 
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| 398 | Value rem = (*_capacity)[e] - (*_flow)[e]; | 
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| 399 | Node t = _graph.target(e); | 
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| 400 | if (_tolerance.positive(rem) && (*_pred)[t] == INVALID) { | 
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| 401 | _pred->set(t, e); | 
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| 402 | _queue[last++] = t; | 
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| 403 | } | 
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| 404 | } | 
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| 405 | for (InArcIt e(_graph, n); e != INVALID; ++e) { | 
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| 406 | Value rem = (*_flow)[e]; | 
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| 407 | Node t = _graph.source(e); | 
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| 408 | if (_tolerance.positive(rem) && (*_pred)[t] == INVALID) { | 
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| 409 | _pred->set(t, e); | 
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| 410 | _queue[last++] = t; | 
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| 411 | } | 
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| 412 | } | 
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| 413 | } | 
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| 414 |  | 
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| 415 | if ((*_pred)[_target] != INVALID) { | 
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| 416 | Node n = _target; | 
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| 417 | Arc e = (*_pred)[n]; | 
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| 418 |  | 
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| 419 | Value prem = (*_capacity)[e] - (*_flow)[e]; | 
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| 420 | n = _graph.source(e); | 
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| 421 | while (n != _source) { | 
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| 422 | e = (*_pred)[n]; | 
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| 423 | if (_graph.target(e) == n) { | 
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| 424 | Value rem = (*_capacity)[e] - (*_flow)[e]; | 
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| 425 | if (rem < prem) prem = rem; | 
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| 426 | n = _graph.source(e); | 
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| 427 | } else { | 
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| 428 | Value rem = (*_flow)[e]; | 
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| 429 | if (rem < prem) prem = rem; | 
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| 430 | n = _graph.target(e); | 
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| 431 | } | 
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| 432 | } | 
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| 433 |  | 
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| 434 | n = _target; | 
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| 435 | e = (*_pred)[n]; | 
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| 436 |  | 
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| 437 | _flow->set(e, (*_flow)[e] + prem); | 
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| 438 | n = _graph.source(e); | 
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| 439 | while (n != _source) { | 
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| 440 | e = (*_pred)[n]; | 
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| 441 | if (_graph.target(e) == n) { | 
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| 442 | _flow->set(e, (*_flow)[e] + prem); | 
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| 443 | n = _graph.source(e); | 
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| 444 | } else { | 
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| 445 | _flow->set(e, (*_flow)[e] - prem); | 
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| 446 | n = _graph.target(e); | 
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| 447 | } | 
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| 448 | } | 
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| 449 |  | 
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| 450 | _flow_value += prem; | 
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| 451 | return true; | 
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| 452 | } else { | 
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| 453 | return false; | 
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| 454 | } | 
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| 455 | } | 
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| 456 |  | 
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| 457 | /// \brief Executes the algorithm | 
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| 458 | /// | 
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| 459 | /// Executes the algorithm by performing augmenting phases until the | 
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| 460 | /// optimal solution is reached. | 
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| 461 | /// \pre One of the \ref init() functions must be called before | 
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| 462 | /// using this function. | 
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| 463 | void start() { | 
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| 464 | while (augment()) {} | 
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| 465 | } | 
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| 466 |  | 
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| 467 | /// \brief Runs the algorithm. | 
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| 468 | /// | 
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| 469 | /// Runs the Edmonds-Karp algorithm. | 
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| 470 | /// \note ek.run() is just a shortcut of the following code. | 
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| 471 | ///\code | 
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| 472 | /// ek.init(); | 
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| 473 | /// ek.start(); | 
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| 474 | ///\endcode | 
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| 475 | void run() { | 
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| 476 | init(); | 
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| 477 | start(); | 
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| 478 | } | 
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| 479 |  | 
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| 480 | /// @} | 
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| 481 |  | 
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| 482 | /// \name Query Functions | 
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| 483 | /// The result of the Edmonds-Karp algorithm can be obtained using these | 
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| 484 | /// functions.\n | 
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| 485 | /// Either \ref run() or \ref start() should be called before using them. | 
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| 486 |  | 
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| 487 | ///@{ | 
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| 488 |  | 
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| 489 | /// \brief Returns the value of the maximum flow. | 
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| 490 | /// | 
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| 491 | /// Returns the value of the maximum flow found by the algorithm. | 
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| 492 | /// | 
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| 493 | /// \pre Either \ref run() or \ref init() must be called before | 
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| 494 | /// using this function. | 
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| 495 | Value flowValue() const { | 
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| 496 | return _flow_value; | 
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| 497 | } | 
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| 498 |  | 
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| 499 | /// \brief Returns the flow value on the given arc. | 
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| 500 | /// | 
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| 501 | /// Returns the flow value on the given arc. | 
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| 502 | /// | 
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| 503 | /// \pre Either \ref run() or \ref init() must be called before | 
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| 504 | /// using this function. | 
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| 505 | Value flow(const Arc& arc) const { | 
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| 506 | return (*_flow)[arc]; | 
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| 507 | } | 
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| 508 |  | 
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| 509 | /// \brief Returns a const reference to the flow map. | 
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| 510 | /// | 
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| 511 | /// Returns a const reference to the arc map storing the found flow. | 
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| 512 | /// | 
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| 513 | /// \pre Either \ref run() or \ref init() must be called before | 
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| 514 | /// using this function. | 
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| 515 | const FlowMap& flowMap() const { | 
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| 516 | return *_flow; | 
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| 517 | } | 
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| 518 |  | 
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| 519 | /// \brief Returns \c true when the node is on the source side of the | 
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| 520 | /// minimum cut. | 
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| 521 | /// | 
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| 522 | /// Returns true when the node is on the source side of the found | 
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| 523 | /// minimum cut. | 
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| 524 | /// | 
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| 525 | /// \pre Either \ref run() or \ref init() must be called before | 
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| 526 | /// using this function. | 
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| 527 | bool minCut(const Node& node) const { | 
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| 528 | return ((*_pred)[node] != INVALID) || node == _source; | 
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| 529 | } | 
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| 530 |  | 
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| 531 | /// \brief Gives back a minimum value cut. | 
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| 532 | /// | 
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| 533 | /// Sets \c cutMap to the characteristic vector of a minimum value | 
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| 534 | /// cut. \c cutMap should be a \ref concepts::WriteMap "writable" | 
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| 535 | /// node map with \c bool (or convertible) value type. | 
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| 536 | /// | 
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| 537 | /// \note This function calls \ref minCut() for each node, so it runs in | 
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| 538 | /// O(n) time. | 
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| 539 | /// | 
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| 540 | /// \pre Either \ref run() or \ref init() must be called before | 
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| 541 | /// using this function. | 
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| 542 | template <typename CutMap> | 
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| 543 | void minCutMap(CutMap& cutMap) const { | 
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| 544 | for (NodeIt n(_graph); n != INVALID; ++n) { | 
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| 545 | cutMap.set(n, (*_pred)[n] != INVALID); | 
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| 546 | } | 
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| 547 | cutMap.set(_source, true); | 
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| 548 | } | 
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| 549 |  | 
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| 550 | /// @} | 
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| 551 |  | 
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| 552 | }; | 
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| 553 |  | 
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| 554 | } | 
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| 555 |  | 
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| 556 | #endif | 
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