[2528] | 1 | /* -*- C++ -*- |
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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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[2553] | 5 | * Copyright (C) 2003-2008 |
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[2528] | 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_GOMORY_HU_TREE_H |
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| 20 | #define LEMON_GOMORY_HU_TREE_H |
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| 21 | |
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| 22 | #include <lemon/preflow.h> |
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| 23 | #include <lemon/concept_check.h> |
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| 24 | #include <lemon/concepts/maps.h> |
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| 25 | |
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| 26 | /// \ingroup min_cut |
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| 27 | /// \file |
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| 28 | /// \brief Gomory-Hu cut tree in undirected graphs. |
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| 29 | |
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| 30 | namespace lemon { |
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| 31 | |
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| 32 | /// \ingroup min_cut |
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| 33 | /// |
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| 34 | /// \brief Gomory-Hu cut tree algorithm |
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| 35 | /// |
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| 36 | /// The Gomory-Hu tree is a tree on the nodeset of the graph, but it |
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| 37 | /// may contain edges which are not in the original graph. It helps |
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| 38 | /// to calculate the minimum cut between all pairs of nodes, because |
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| 39 | /// the minimum capacity edge on the tree path between two nodes has |
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| 40 | /// the same weight as the minimum cut in the graph between these |
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| 41 | /// nodes. Moreover this edge separates the nodes to two parts which |
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| 42 | /// determine this minimum cut. |
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| 43 | /// |
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| 44 | /// The algorithm calculates \e n-1 distinict minimum cuts with |
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| 45 | /// preflow algorithm, therefore the algorithm has |
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| 46 | /// \f$(O(n^3\sqrt{e})\f$ overall time complexity. It calculates a |
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| 47 | /// rooted Gomory-Hu tree, the structure of the tree and the weights |
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| 48 | /// can be obtained with \c predNode() and \c predValue() |
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| 49 | /// functions. The \c minCutValue() and \c minCutMap() calculates |
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| 50 | /// the minimum cut and the minimum cut value between any two node |
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| 51 | /// in the graph. |
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| 52 | template <typename _UGraph, |
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| 53 | typename _Capacity = typename _UGraph::template UEdgeMap<int> > |
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| 54 | class GomoryHuTree { |
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| 55 | public: |
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| 56 | |
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| 57 | /// The undirected graph type |
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| 58 | typedef _UGraph UGraph; |
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| 59 | /// The capacity on undirected edges |
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| 60 | typedef _Capacity Capacity; |
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| 61 | /// The value type of capacities |
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| 62 | typedef typename Capacity::Value Value; |
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| 63 | |
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| 64 | private: |
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| 65 | |
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| 66 | UGRAPH_TYPEDEFS(typename UGraph); |
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| 67 | |
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| 68 | const UGraph& _ugraph; |
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| 69 | const Capacity& _capacity; |
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| 70 | |
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| 71 | Node _root; |
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| 72 | typename UGraph::template NodeMap<Node>* _pred; |
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| 73 | typename UGraph::template NodeMap<Value>* _weight; |
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| 74 | typename UGraph::template NodeMap<int>* _order; |
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| 75 | |
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| 76 | void createStructures() { |
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| 77 | if (!_pred) { |
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| 78 | _pred = new typename UGraph::template NodeMap<Node>(_ugraph); |
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| 79 | } |
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| 80 | if (!_weight) { |
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| 81 | _weight = new typename UGraph::template NodeMap<Value>(_ugraph); |
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| 82 | } |
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| 83 | if (!_order) { |
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| 84 | _order = new typename UGraph::template NodeMap<int>(_ugraph); |
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| 85 | } |
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| 86 | } |
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| 87 | |
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| 88 | void destroyStructures() { |
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| 89 | if (_pred) { |
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| 90 | delete _pred; |
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| 91 | } |
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| 92 | if (_weight) { |
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| 93 | delete _weight; |
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| 94 | } |
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| 95 | if (_order) { |
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| 96 | delete _order; |
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| 97 | } |
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| 98 | } |
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| 99 | |
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| 100 | public: |
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| 101 | |
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| 102 | /// \brief Constructor |
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| 103 | /// |
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| 104 | /// Constructor |
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| 105 | /// \param ugraph The undirected graph type. |
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| 106 | /// \param capacity The capacity map. |
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| 107 | GomoryHuTree(const UGraph& ugraph, const Capacity& capacity) |
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| 108 | : _ugraph(ugraph), _capacity(capacity), |
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| 109 | _pred(0), _weight(0), _order(0) |
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| 110 | { |
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| 111 | checkConcept<concepts::ReadMap<UEdge, Value>, Capacity>(); |
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| 112 | } |
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| 113 | |
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| 114 | |
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| 115 | /// \brief Destructor |
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| 116 | /// |
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| 117 | /// Destructor |
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| 118 | ~GomoryHuTree() { |
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| 119 | destroyStructures(); |
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| 120 | } |
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| 121 | |
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| 122 | /// \brief Initializes the internal data structures. |
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| 123 | /// |
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| 124 | /// Initializes the internal data structures. |
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| 125 | /// |
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| 126 | void init() { |
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| 127 | createStructures(); |
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| 128 | |
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| 129 | _root = NodeIt(_ugraph); |
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| 130 | for (NodeIt n(_ugraph); n != INVALID; ++n) { |
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| 131 | _pred->set(n, _root); |
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| 132 | _order->set(n, -1); |
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| 133 | } |
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| 134 | _pred->set(_root, INVALID); |
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| 135 | _weight->set(_root, std::numeric_limits<Value>::max()); |
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| 136 | } |
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| 137 | |
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| 138 | |
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| 139 | /// \brief Starts the algorithm |
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| 140 | /// |
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| 141 | /// Starts the algorithm. |
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| 142 | void start() { |
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| 143 | Preflow<UGraph, Capacity> fa(_ugraph, _capacity, _root, INVALID); |
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| 144 | |
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| 145 | for (NodeIt n(_ugraph); n != INVALID; ++n) { |
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| 146 | if (n == _root) continue; |
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| 147 | |
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| 148 | Node pn = (*_pred)[n]; |
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| 149 | fa.source(n); |
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| 150 | fa.target(pn); |
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| 151 | |
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| 152 | fa.runMinCut(); |
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| 153 | |
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| 154 | _weight->set(n, fa.flowValue()); |
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| 155 | |
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| 156 | for (NodeIt nn(_ugraph); nn != INVALID; ++nn) { |
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| 157 | if (nn != n && fa.minCut(nn) && (*_pred)[nn] == pn) { |
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| 158 | _pred->set(nn, n); |
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| 159 | } |
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| 160 | } |
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| 161 | if ((*_pred)[pn] != INVALID && fa.minCut((*_pred)[pn])) { |
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| 162 | _pred->set(n, (*_pred)[pn]); |
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| 163 | _pred->set(pn, n); |
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| 164 | _weight->set(n, (*_weight)[pn]); |
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| 165 | _weight->set(pn, fa.flowValue()); |
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| 166 | } |
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| 167 | } |
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| 168 | |
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| 169 | _order->set(_root, 0); |
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| 170 | int index = 1; |
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| 171 | |
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| 172 | for (NodeIt n(_ugraph); n != INVALID; ++n) { |
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| 173 | std::vector<Node> st; |
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| 174 | Node nn = n; |
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| 175 | while ((*_order)[nn] == -1) { |
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| 176 | st.push_back(nn); |
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| 177 | nn = (*_pred)[nn]; |
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| 178 | } |
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| 179 | while (!st.empty()) { |
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| 180 | _order->set(st.back(), index++); |
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| 181 | st.pop_back(); |
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| 182 | } |
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| 183 | } |
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| 184 | } |
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| 185 | |
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| 186 | /// \brief Runs the Gomory-Hu algorithm. |
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| 187 | /// |
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| 188 | /// Runs the Gomory-Hu algorithm. |
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| 189 | /// \note gh.run() is just a shortcut of the following code. |
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| 190 | /// \code |
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| 191 | /// ght.init(); |
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| 192 | /// ght.start(); |
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| 193 | /// \endcode |
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| 194 | void run() { |
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| 195 | init(); |
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| 196 | start(); |
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| 197 | } |
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| 198 | |
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| 199 | /// \brief Returns the predecessor node in the Gomory-Hu tree. |
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| 200 | /// |
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| 201 | /// Returns the predecessor node in the Gomory-Hu tree. If the node is |
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| 202 | /// the root of the Gomory-Hu tree, then it returns \c INVALID. |
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| 203 | Node predNode(const Node& node) { |
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| 204 | return (*_pred)[node]; |
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| 205 | } |
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| 206 | |
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| 207 | /// \brief Returns the weight of the predecessor edge in the |
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| 208 | /// Gomory-Hu tree. |
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| 209 | /// |
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| 210 | /// Returns the weight of the predecessor edge in the Gomory-Hu |
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| 211 | /// tree. If the node is the root of the Gomory-Hu tree, the |
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| 212 | /// result is undefined. |
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| 213 | Value predValue(const Node& node) { |
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| 214 | return (*_weight)[node]; |
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| 215 | } |
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| 216 | |
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| 217 | /// \brief Returns the minimum cut value between two nodes |
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| 218 | /// |
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| 219 | /// Returns the minimum cut value between two nodes. The |
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| 220 | /// algorithm finds the nearest common ancestor in the Gomory-Hu |
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| 221 | /// tree and calculates the minimum weight edge on the paths to |
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| 222 | /// the ancestor. |
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| 223 | Value minCutValue(const Node& s, const Node& t) const { |
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| 224 | Node sn = s, tn = t; |
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| 225 | Value value = std::numeric_limits<Value>::max(); |
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| 226 | |
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| 227 | while (sn != tn) { |
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| 228 | if ((*_order)[sn] < (*_order)[tn]) { |
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| 229 | if ((*_weight)[tn] < value) value = (*_weight)[tn]; |
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| 230 | tn = (*_pred)[tn]; |
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| 231 | } else { |
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| 232 | if ((*_weight)[sn] < value) value = (*_weight)[sn]; |
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| 233 | sn = (*_pred)[sn]; |
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| 234 | } |
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| 235 | } |
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| 236 | return value; |
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| 237 | } |
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| 238 | |
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| 239 | /// \brief Returns the minimum cut between two nodes |
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| 240 | /// |
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| 241 | /// Returns the minimum cut value between two nodes. The |
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| 242 | /// algorithm finds the nearest common ancestor in the Gomory-Hu |
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| 243 | /// tree and calculates the minimum weight edge on the paths to |
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| 244 | /// the ancestor. Then it sets all nodes to the cut determined by |
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| 245 | /// this edge. The \c cutMap should be \ref concepts::ReadWriteMap |
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| 246 | /// "ReadWriteMap". |
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| 247 | template <typename CutMap> |
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| 248 | Value minCutMap(const Node& s, const Node& t, CutMap& cutMap) const { |
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| 249 | Node sn = s, tn = t; |
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| 250 | |
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| 251 | Node rn = INVALID; |
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| 252 | Value value = std::numeric_limits<Value>::max(); |
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| 253 | |
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| 254 | while (sn != tn) { |
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| 255 | if ((*_order)[sn] < (*_order)[tn]) { |
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| 256 | if ((*_weight)[tn] < value) { |
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| 257 | rn = tn; |
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| 258 | value = (*_weight)[tn]; |
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| 259 | } |
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| 260 | tn = (*_pred)[tn]; |
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| 261 | } else { |
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| 262 | if ((*_weight)[sn] < value) { |
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| 263 | rn = sn; |
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| 264 | value = (*_weight)[sn]; |
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| 265 | } |
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| 266 | sn = (*_pred)[sn]; |
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| 267 | } |
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| 268 | } |
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| 269 | |
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| 270 | typename UGraph::template NodeMap<bool> reached(_ugraph, false); |
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| 271 | reached.set(_root, true); |
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| 272 | cutMap.set(_root, false); |
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| 273 | reached.set(rn, true); |
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| 274 | cutMap.set(rn, true); |
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| 275 | |
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| 276 | for (NodeIt n(_ugraph); n != INVALID; ++n) { |
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| 277 | std::vector<Node> st; |
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| 278 | Node nn = n; |
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| 279 | while (!reached[nn]) { |
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| 280 | st.push_back(nn); |
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| 281 | nn = (*_pred)[nn]; |
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| 282 | } |
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| 283 | while (!st.empty()) { |
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| 284 | cutMap.set(st.back(), cutMap[nn]); |
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| 285 | st.pop_back(); |
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| 286 | } |
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| 287 | } |
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| 288 | |
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| 289 | return value; |
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| 290 | } |
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| 291 | |
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| 292 | }; |
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| 293 | |
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| 294 | } |
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| 295 | |
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| 296 | #endif |
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