| 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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| 5 | * Copyright (C) 2003-2008 | 
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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_PR_BIPARTITE_MATCHING | 
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| 20 | #define LEMON_PR_BIPARTITE_MATCHING | 
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| 21 |  | 
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| 22 | #include <lemon/graph_utils.h> | 
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| 23 | #include <lemon/iterable_maps.h> | 
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| 24 | #include <iostream> | 
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| 25 | #include <queue> | 
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| 26 | #include <lemon/elevator.h> | 
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| 27 |  | 
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| 28 | ///\ingroup matching | 
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| 29 | ///\file | 
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| 30 | ///\brief Push-prelabel maximum matching algorithms in bipartite graphs. | 
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| 31 | /// | 
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| 32 | namespace lemon { | 
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| 33 |  | 
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| 34 | ///Max cardinality matching algorithm based on push-relabel principle | 
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| 35 |  | 
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| 36 | ///\ingroup matching | 
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| 37 | ///Bipartite Max Cardinality Matching algorithm. This class uses the | 
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| 38 | ///push-relabel principle which in several cases has better runtime | 
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| 39 | ///performance than the augmenting path solutions. | 
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| 40 | /// | 
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| 41 | ///\author Alpar Juttner | 
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| 42 | template<class Graph> | 
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| 43 | class PrBipartiteMatching { | 
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| 44 | typedef typename Graph::Node Node; | 
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| 45 | typedef typename Graph::ANodeIt ANodeIt; | 
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| 46 | typedef typename Graph::BNodeIt BNodeIt; | 
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| 47 | typedef typename Graph::UEdge UEdge; | 
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| 48 | typedef typename Graph::UEdgeIt UEdgeIt; | 
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| 49 | typedef typename Graph::IncEdgeIt IncEdgeIt; | 
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| 50 |  | 
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| 51 | const Graph &_g; | 
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| 52 | int _node_num; | 
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| 53 | int _matching_size; | 
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| 54 | int _empty_level; | 
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| 55 |  | 
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| 56 | typename Graph::template ANodeMap<typename Graph::UEdge> _matching; | 
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| 57 | Elevator<Graph,typename Graph::BNode> _levels; | 
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| 58 | typename Graph::template BNodeMap<int> _cov; | 
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| 59 |  | 
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| 60 | public: | 
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| 61 |  | 
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| 62 | /// Constructor | 
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| 63 |  | 
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| 64 | /// Constructor | 
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| 65 | /// | 
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| 66 | PrBipartiteMatching(const Graph &g) : | 
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| 67 | _g(g), | 
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| 68 | _node_num(countBNodes(g)), | 
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| 69 | _matching(g), | 
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| 70 | _levels(g,_node_num), | 
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| 71 | _cov(g,0) | 
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| 72 | { | 
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| 73 | } | 
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| 74 |  | 
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| 75 | /// \name Execution control | 
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| 76 | /// The simplest way to execute the algorithm is to use one of the | 
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| 77 | /// member functions called \c run(). \n | 
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| 78 | /// If you need more control on the execution, first | 
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| 79 | /// you must call \ref init() and then one variant of the start() | 
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| 80 | /// member. | 
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| 81 |  | 
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| 82 | /// @{ | 
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| 83 |  | 
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| 84 | ///Initialize the data structures | 
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| 85 |  | 
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| 86 | ///This function constructs a prematching first, which is a | 
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| 87 | ///regular matching on the A-side of the graph, but on the B-side | 
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| 88 | ///each node could cover more matching edges. After that, the | 
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| 89 | ///B-nodes which multiple matched, will be pushed into the lowest | 
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| 90 | ///level of the Elevator. The remaning B-nodes will be pushed to | 
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| 91 | ///the consequent levels respect to a Bfs on following graph: the | 
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| 92 | ///nodes are the B-nodes of the original bipartite graph and two | 
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| 93 | ///nodes are adjacent if a node can pass over a matching edge to | 
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| 94 | ///an other node. The source of the Bfs are the lowest level | 
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| 95 | ///nodes. Last, the reached B-nodes without covered matching edge | 
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| 96 | ///becomes active. | 
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| 97 | void init() { | 
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| 98 | _matching_size=0; | 
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| 99 | _empty_level=_node_num; | 
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| 100 | for(ANodeIt n(_g);n!=INVALID;++n) | 
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| 101 | if((_matching[n]=IncEdgeIt(_g,n))!=INVALID) | 
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| 102 | ++_cov[_g.bNode(_matching[n])]; | 
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| 103 |  | 
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| 104 | std::queue<Node> q; | 
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| 105 | _levels.initStart(); | 
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| 106 | for(BNodeIt n(_g);n!=INVALID;++n) | 
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| 107 | if(_cov[n]>1) { | 
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| 108 | _levels.initAddItem(n); | 
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| 109 | q.push(n); | 
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| 110 | } | 
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| 111 | int hlev=0; | 
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| 112 | while(!q.empty()) { | 
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| 113 | Node n=q.front(); | 
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| 114 | q.pop(); | 
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| 115 | int nlev=_levels[n]+1; | 
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| 116 | for(IncEdgeIt e(_g,n);e!=INVALID;++e) { | 
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| 117 | Node m=_g.runningNode(e); | 
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| 118 | if(e==_matching[m]) { | 
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| 119 | for(IncEdgeIt f(_g,m);f!=INVALID;++f) { | 
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| 120 | Node r=_g.runningNode(f); | 
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| 121 | if(_levels[r]>nlev) { | 
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| 122 | for(;nlev>hlev;hlev++) | 
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| 123 | _levels.initNewLevel(); | 
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| 124 | _levels.initAddItem(r); | 
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| 125 | q.push(r); | 
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| 126 | } | 
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| 127 | } | 
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| 128 | } | 
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| 129 | } | 
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| 130 | } | 
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| 131 | _levels.initFinish(); | 
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| 132 | for(BNodeIt n(_g);n!=INVALID;++n) | 
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| 133 | if(_cov[n]<1&&_levels[n]<_node_num) | 
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| 134 | _levels.activate(n); | 
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| 135 | } | 
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| 136 |  | 
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| 137 | ///Start the main phase of the algorithm | 
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| 138 |  | 
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| 139 | ///This algorithm calculates the maximum matching with the | 
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| 140 | ///push-relabel principle. This function should be called just | 
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| 141 | ///after the init() function which already set the initial | 
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| 142 | ///prematching, the level function on the B-nodes and the active, | 
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| 143 | ///ie. unmatched B-nodes. | 
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| 144 | /// | 
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| 145 | ///The algorithm always takes highest active B-node, and it try to | 
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| 146 | ///find a B-node which is eligible to pass over one of it's | 
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| 147 | ///matching edge. This condition holds when the B-node is one | 
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| 148 | ///level lower, and the opposite node of it's matching edge is | 
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| 149 | ///adjacent to the highest active node. In this case the current | 
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| 150 | ///node steals the matching edge and becomes inactive. If there is | 
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| 151 | ///not eligible node then the highest active node should be lift | 
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| 152 | ///to the next proper level. | 
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| 153 | /// | 
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| 154 | ///The nodes should not lift higher than the number of the | 
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| 155 | ///B-nodes, if a node reach this level it remains unmatched. If | 
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| 156 | ///during the execution one level becomes empty the nodes above it | 
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| 157 | ///can be deactivated and lift to the highest level. | 
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| 158 | void start() { | 
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| 159 | Node act; | 
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| 160 | Node bact=INVALID; | 
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| 161 | Node last_activated=INVALID; | 
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| 162 | while((act=_levels.highestActive())!=INVALID) { | 
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| 163 | last_activated=INVALID; | 
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| 164 | int actlevel=_levels[act]; | 
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| 165 |  | 
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| 166 | UEdge bedge=INVALID; | 
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| 167 | int nlevel=_node_num; | 
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| 168 | { | 
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| 169 | int nnlevel; | 
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| 170 | for(IncEdgeIt tbedge(_g,act); | 
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| 171 | tbedge!=INVALID && nlevel>=actlevel; | 
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| 172 | ++tbedge) | 
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| 173 | if((nnlevel=_levels[_g.bNode(_matching[_g.runningNode(tbedge)])])< | 
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| 174 | nlevel) | 
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| 175 | { | 
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| 176 | nlevel=nnlevel; | 
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| 177 | bedge=tbedge; | 
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| 178 | } | 
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| 179 | } | 
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| 180 | if(nlevel<_node_num) { | 
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| 181 | if(nlevel>=actlevel) | 
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| 182 | _levels.liftHighestActive(nlevel+1); | 
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| 183 | bact=_g.bNode(_matching[_g.aNode(bedge)]); | 
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| 184 | if(--_cov[bact]<1) { | 
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| 185 | _levels.activate(bact); | 
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| 186 | last_activated=bact; | 
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| 187 | } | 
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| 188 | _matching[_g.aNode(bedge)]=bedge; | 
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| 189 | _cov[act]=1; | 
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| 190 | _levels.deactivate(act); | 
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| 191 | } | 
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| 192 | else { | 
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| 193 | _levels.liftHighestActiveToTop(); | 
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| 194 | } | 
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| 195 |  | 
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| 196 | if(_levels.emptyLevel(actlevel)) | 
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| 197 | _levels.liftToTop(actlevel); | 
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| 198 | } | 
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| 199 |  | 
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| 200 | for(ANodeIt n(_g);n!=INVALID;++n) { | 
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| 201 | if (_matching[n]==INVALID)continue; | 
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| 202 | if (_cov[_g.bNode(_matching[n])]>1) { | 
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| 203 | _cov[_g.bNode(_matching[n])]--; | 
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| 204 | _matching[n]=INVALID; | 
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| 205 | } else { | 
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| 206 | ++_matching_size; | 
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| 207 | } | 
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| 208 | } | 
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| 209 | } | 
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| 210 |  | 
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| 211 | ///Start the algorithm to find a perfect matching | 
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| 212 |  | 
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| 213 | ///This function is close to identical to the simple start() | 
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| 214 | ///member function but it calculates just perfect matching. | 
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| 215 | ///However, the perfect property is only checked on the B-side of | 
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| 216 | ///the graph | 
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| 217 | /// | 
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| 218 | ///The main difference between the two function is the handling of | 
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| 219 | ///the empty levels. The simple start() function let the nodes | 
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| 220 | ///above the empty levels unmatched while this variant if it find | 
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| 221 | ///an empty level immediately terminates and gives back false | 
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| 222 | ///return value. | 
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| 223 | bool startPerfect() { | 
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| 224 | Node act; | 
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| 225 | Node bact=INVALID; | 
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| 226 | Node last_activated=INVALID; | 
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| 227 | while((act=_levels.highestActive())!=INVALID) { | 
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| 228 | last_activated=INVALID; | 
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| 229 | int actlevel=_levels[act]; | 
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| 230 |  | 
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| 231 | UEdge bedge=INVALID; | 
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| 232 | int nlevel=_node_num; | 
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| 233 | { | 
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| 234 | int nnlevel; | 
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| 235 | for(IncEdgeIt tbedge(_g,act); | 
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| 236 | tbedge!=INVALID && nlevel>=actlevel; | 
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| 237 | ++tbedge) | 
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| 238 | if((nnlevel=_levels[_g.bNode(_matching[_g.runningNode(tbedge)])])< | 
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| 239 | nlevel) | 
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| 240 | { | 
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| 241 | nlevel=nnlevel; | 
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| 242 | bedge=tbedge; | 
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| 243 | } | 
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| 244 | } | 
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| 245 | if(nlevel<_node_num) { | 
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| 246 | if(nlevel>=actlevel) | 
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| 247 | _levels.liftHighestActive(nlevel+1); | 
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| 248 | bact=_g.bNode(_matching[_g.aNode(bedge)]); | 
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| 249 | if(--_cov[bact]<1) { | 
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| 250 | _levels.activate(bact); | 
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| 251 | last_activated=bact; | 
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| 252 | } | 
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| 253 | _matching[_g.aNode(bedge)]=bedge; | 
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| 254 | _cov[act]=1; | 
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| 255 | _levels.deactivate(act); | 
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| 256 | } | 
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| 257 | else { | 
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| 258 | _levels.liftHighestActiveToTop(); | 
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| 259 | } | 
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| 260 |  | 
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| 261 | if(_levels.emptyLevel(actlevel)) | 
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| 262 | _empty_level=actlevel; | 
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| 263 | return false; | 
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| 264 | } | 
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| 265 | _matching_size = _node_num; | 
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| 266 | return true; | 
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| 267 | } | 
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| 268 |  | 
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| 269 | ///Runs the algorithm | 
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| 270 |  | 
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| 271 | ///Just a shortcut for the next code: | 
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| 272 | ///\code | 
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| 273 | /// init(); | 
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| 274 | /// start(); | 
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| 275 | ///\endcode | 
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| 276 | void run() { | 
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| 277 | init(); | 
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| 278 | start(); | 
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| 279 | } | 
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| 280 |  | 
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| 281 | ///Runs the algorithm to find a perfect matching | 
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| 282 |  | 
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| 283 | ///Just a shortcut for the next code: | 
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| 284 | ///\code | 
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| 285 | /// init(); | 
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| 286 | /// startPerfect(); | 
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| 287 | ///\endcode | 
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| 288 | /// | 
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| 289 | ///\note If the two nodesets of the graph have different size then | 
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| 290 | ///this algorithm checks the perfect property on the B-side. | 
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| 291 | bool runPerfect() { | 
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| 292 | init(); | 
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| 293 | return startPerfect(); | 
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| 294 | } | 
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| 295 |  | 
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| 296 | ///Runs the algorithm to find a perfect matching | 
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| 297 |  | 
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| 298 | ///Just a shortcut for the next code: | 
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| 299 | ///\code | 
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| 300 | /// init(); | 
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| 301 | /// startPerfect(); | 
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| 302 | ///\endcode | 
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| 303 | /// | 
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| 304 | ///\note It checks that the size of the two nodesets are equal. | 
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| 305 | bool checkedRunPerfect() { | 
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| 306 | if (countANodes(_g) != _node_num) return false; | 
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| 307 | init(); | 
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| 308 | return startPerfect(); | 
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| 309 | } | 
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| 310 |  | 
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| 311 | ///@} | 
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| 312 |  | 
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| 313 | /// \name Query Functions | 
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| 314 | /// The result of the %Matching algorithm can be obtained using these | 
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| 315 | /// functions.\n | 
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| 316 | /// Before the use of these functions, | 
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| 317 | /// either run() or start() must be called. | 
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| 318 | ///@{ | 
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| 319 |  | 
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| 320 | ///Set true all matching uedge in the map. | 
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| 321 |  | 
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| 322 | ///Set true all matching uedge in the map. It does not change the | 
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| 323 | ///value mapped to the other uedges. | 
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| 324 | ///\return The number of the matching edges. | 
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| 325 | template <typename MatchingMap> | 
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| 326 | int quickMatching(MatchingMap& mm) const { | 
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| 327 | for (ANodeIt n(_g);n!=INVALID;++n) { | 
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| 328 | if (_matching[n]!=INVALID) mm.set(_matching[n],true); | 
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| 329 | } | 
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| 330 | return _matching_size; | 
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| 331 | } | 
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| 332 |  | 
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| 333 | ///Set true all matching uedge in the map and the others to false. | 
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| 334 |  | 
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| 335 | ///Set true all matching uedge in the map and the others to false. | 
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| 336 | ///\return The number of the matching edges. | 
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| 337 | template<class MatchingMap> | 
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| 338 | int matching(MatchingMap& mm) const { | 
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| 339 | for (UEdgeIt e(_g);e!=INVALID;++e) { | 
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| 340 | mm.set(e,e==_matching[_g.aNode(e)]); | 
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| 341 | } | 
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| 342 | return _matching_size; | 
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| 343 | } | 
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| 344 |  | 
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| 345 | ///Gives back the matching in an ANodeMap. | 
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| 346 |  | 
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| 347 | ///Gives back the matching in an ANodeMap. The parameter should | 
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| 348 | ///be a write ANodeMap of UEdge values. | 
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| 349 | ///\return The number of the matching edges. | 
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| 350 | template<class MatchingMap> | 
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| 351 | int aMatching(MatchingMap& mm) const { | 
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| 352 | for (ANodeIt n(_g);n!=INVALID;++n) { | 
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| 353 | mm.set(n,_matching[n]); | 
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| 354 | } | 
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| 355 | return _matching_size; | 
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| 356 | } | 
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| 357 |  | 
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| 358 | ///Gives back the matching in a BNodeMap. | 
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| 359 |  | 
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| 360 | ///Gives back the matching in a BNodeMap. The parameter should | 
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| 361 | ///be a write BNodeMap of UEdge values. | 
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| 362 | ///\return The number of the matching edges. | 
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| 363 | template<class MatchingMap> | 
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| 364 | int bMatching(MatchingMap& mm) const { | 
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| 365 | for (BNodeIt n(_g);n!=INVALID;++n) { | 
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| 366 | mm.set(n,INVALID); | 
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| 367 | } | 
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| 368 | for (ANodeIt n(_g);n!=INVALID;++n) { | 
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| 369 | if (_matching[n]!=INVALID) | 
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| 370 | mm.set(_g.bNode(_matching[n]),_matching[n]); | 
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| 371 | } | 
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| 372 | return _matching_size; | 
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| 373 | } | 
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| 374 |  | 
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| 375 |  | 
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| 376 | ///Returns true if the given uedge is in the matching. | 
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| 377 |  | 
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| 378 | ///It returns true if the given uedge is in the matching. | 
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| 379 | /// | 
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| 380 | bool matchingEdge(const UEdge& e) const { | 
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| 381 | return _matching[_g.aNode(e)]==e; | 
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| 382 | } | 
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| 383 |  | 
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| 384 | ///Returns the matching edge from the node. | 
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| 385 |  | 
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| 386 | ///Returns the matching edge from the node. If there is not such | 
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| 387 | ///edge it gives back \c INVALID. | 
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| 388 | ///\note If the parameter node is a B-node then the running time is | 
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| 389 | ///propotional to the degree of the node. | 
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| 390 | UEdge matchingEdge(const Node& n) const { | 
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| 391 | if (_g.aNode(n)) { | 
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| 392 | return _matching[n]; | 
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| 393 | } else { | 
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| 394 | for (IncEdgeIt e(_g,n);e!=INVALID;++e) | 
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| 395 | if (e==_matching[_g.aNode(e)]) return e; | 
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| 396 | return INVALID; | 
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| 397 | } | 
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| 398 | } | 
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| 399 |  | 
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| 400 | ///Gives back the number of the matching edges. | 
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| 401 |  | 
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| 402 | ///Gives back the number of the matching edges. | 
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| 403 | int matchingSize() const { | 
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| 404 | return _matching_size; | 
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| 405 | } | 
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| 406 |  | 
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| 407 | ///Gives back a barrier on the A-nodes | 
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| 408 |  | 
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| 409 | ///The barrier is s subset of the nodes on the same side of the | 
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| 410 | ///graph. If we tried to find a perfect matching and it failed | 
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| 411 | ///then the barrier size will be greater than its neighbours. If | 
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| 412 | ///the maximum matching searched then the barrier size minus its | 
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| 413 | ///neighbours will be exactly the unmatched nodes on the A-side. | 
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| 414 | ///\retval bar A WriteMap on the ANodes with bool value. | 
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| 415 | template<class BarrierMap> | 
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| 416 | void aBarrier(BarrierMap &bar) const | 
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| 417 | { | 
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| 418 | for(ANodeIt n(_g);n!=INVALID;++n) | 
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| 419 | bar.set(n,_matching[n]==INVALID || | 
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| 420 | _levels[_g.bNode(_matching[n])]<_empty_level); | 
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| 421 | } | 
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| 422 |  | 
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| 423 | ///Gives back a barrier on the B-nodes | 
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| 424 |  | 
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| 425 | ///The barrier is s subset of the nodes on the same side of the | 
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| 426 | ///graph. If we tried to find a perfect matching and it failed | 
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| 427 | ///then the barrier size will be greater than its neighbours. If | 
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| 428 | ///the maximum matching searched then the barrier size minus its | 
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| 429 | ///neighbours will be exactly the unmatched nodes on the B-side. | 
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| 430 | ///\retval bar A WriteMap on the BNodes with bool value. | 
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| 431 | template<class BarrierMap> | 
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| 432 | void bBarrier(BarrierMap &bar) const | 
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| 433 | { | 
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| 434 | for(BNodeIt n(_g);n!=INVALID;++n) bar.set(n,_levels[n]>=_empty_level); | 
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| 435 | } | 
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| 436 |  | 
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| 437 | ///Returns a minimum covering of the nodes. | 
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| 438 |  | 
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| 439 | ///The minimum covering set problem is the dual solution of the | 
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| 440 | ///maximum bipartite matching. It provides a solution for this | 
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| 441 | ///problem what is proof of the optimality of the matching. | 
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| 442 | ///\param covering NodeMap of bool values, the nodes of the cover | 
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| 443 | ///set will set true while the others false. | 
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| 444 | ///\return The size of the cover set. | 
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| 445 | ///\note This function can be called just after the algorithm have | 
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| 446 | ///already found a matching. | 
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| 447 | template<class CoverMap> | 
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| 448 | int coverSet(CoverMap& covering) const { | 
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| 449 | int ret=0; | 
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| 450 | for(BNodeIt n(_g);n!=INVALID;++n) { | 
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| 451 | if (_levels[n]<_empty_level) { covering.set(n,true); ++ret; } | 
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| 452 | else covering.set(n,false); | 
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| 453 | } | 
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| 454 | for(ANodeIt n(_g);n!=INVALID;++n) { | 
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| 455 | if (_matching[n]!=INVALID && | 
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| 456 | _levels[_g.bNode(_matching[n])]>=_empty_level) | 
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| 457 | { covering.set(n,true); ++ret; } | 
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| 458 | else covering.set(n,false); | 
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| 459 | } | 
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| 460 | return ret; | 
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| 461 | } | 
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| 462 |  | 
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| 463 |  | 
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| 464 | /// @} | 
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| 465 |  | 
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| 466 | }; | 
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| 467 |  | 
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| 468 |  | 
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| 469 | ///Maximum cardinality of the matchings in a bipartite graph | 
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| 470 |  | 
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| 471 | ///\ingroup matching | 
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| 472 | ///This function finds the maximum cardinality of the matchings | 
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| 473 | ///in a bipartite graph \c g. | 
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| 474 | ///\param g An undirected bipartite graph. | 
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| 475 | ///\return The cardinality of the maximum matching. | 
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| 476 | /// | 
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| 477 | ///\note The the implementation is based | 
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| 478 | ///on the push-relabel principle. | 
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| 479 | template<class Graph> | 
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| 480 | int prBipartiteMatching(const Graph &g) | 
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| 481 | { | 
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| 482 | PrBipartiteMatching<Graph> bpm(g); | 
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| 483 | bpm.run(); | 
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| 484 | return bpm.matchingSize(); | 
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| 485 | } | 
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| 486 |  | 
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| 487 | ///Maximum cardinality matching in a bipartite graph | 
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| 488 |  | 
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| 489 | ///\ingroup matching | 
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| 490 | ///This function finds a maximum cardinality matching | 
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| 491 | ///in a bipartite graph \c g. | 
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| 492 | ///\param g An undirected bipartite graph. | 
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| 493 | ///\retval matching A write ANodeMap of value type \c UEdge. | 
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| 494 | /// The found edges will be returned in this map, | 
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| 495 | /// i.e. for an \c ANode \c n the edge <tt>matching[n]</tt> is the one | 
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| 496 | /// that covers the node \c n. | 
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| 497 | ///\return The cardinality of the maximum matching. | 
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| 498 | /// | 
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| 499 | ///\note The the implementation is based | 
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| 500 | ///on the push-relabel principle. | 
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| 501 | template<class Graph,class MT> | 
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| 502 | int prBipartiteMatching(const Graph &g,MT &matching) | 
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| 503 | { | 
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| 504 | PrBipartiteMatching<Graph> bpm(g); | 
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| 505 | bpm.run(); | 
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| 506 | bpm.aMatching(matching); | 
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| 507 | return bpm.matchingSize(); | 
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| 508 | } | 
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| 509 |  | 
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| 510 | ///Maximum cardinality matching in a bipartite graph | 
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| 511 |  | 
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| 512 | ///\ingroup matching | 
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| 513 | ///This function finds a maximum cardinality matching | 
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| 514 | ///in a bipartite graph \c g. | 
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| 515 | ///\param g An undirected bipartite graph. | 
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| 516 | ///\retval matching A write ANodeMap of value type \c UEdge. | 
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| 517 | /// The found edges will be returned in this map, | 
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| 518 | /// i.e. for an \c ANode \c n the edge <tt>matching[n]</tt> is the one | 
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| 519 | /// that covers the node \c n. | 
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| 520 | ///\retval barrier A \c bool WriteMap on the BNodes. The map will be set | 
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| 521 | /// exactly once for each BNode. The nodes with \c true value represent | 
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| 522 | /// a barrier \e B, i.e. the cardinality of \e B minus the number of its | 
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| 523 | /// neighbor is equal to the number of the <tt>BNode</tt>s minus the | 
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| 524 | /// cardinality of the maximum matching. | 
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| 525 | ///\return The cardinality of the maximum matching. | 
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| 526 | /// | 
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| 527 | ///\note The the implementation is based | 
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| 528 | ///on the push-relabel principle. | 
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| 529 | template<class Graph,class MT, class GT> | 
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| 530 | int prBipartiteMatching(const Graph &g,MT &matching,GT &barrier) | 
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| 531 | { | 
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| 532 | PrBipartiteMatching<Graph> bpm(g); | 
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| 533 | bpm.run(); | 
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| 534 | bpm.aMatching(matching); | 
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| 535 | bpm.bBarrier(barrier); | 
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| 536 | return bpm.matchingSize(); | 
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| 537 | } | 
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| 538 |  | 
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| 539 | ///Perfect matching in a bipartite graph | 
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| 540 |  | 
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| 541 | ///\ingroup matching | 
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| 542 | ///This function checks whether the bipartite graph \c g | 
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| 543 | ///has a perfect matching. | 
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| 544 | ///\param g An undirected bipartite graph. | 
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| 545 | ///\return \c true iff \c g has a perfect matching. | 
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| 546 | /// | 
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| 547 | ///\note The the implementation is based | 
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| 548 | ///on the push-relabel principle. | 
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| 549 | template<class Graph> | 
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| 550 | bool prPerfectBipartiteMatching(const Graph &g) | 
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| 551 | { | 
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| 552 | PrBipartiteMatching<Graph> bpm(g); | 
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| 553 | bpm.run(); | 
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| 554 | return bpm.checkedRunPerfect(); | 
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| 555 | } | 
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| 556 |  | 
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| 557 | ///Perfect matching in a bipartite graph | 
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| 558 |  | 
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| 559 | ///\ingroup matching | 
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| 560 | ///This function finds a perfect matching in a bipartite graph \c g. | 
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| 561 | ///\param g An undirected bipartite graph. | 
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| 562 | ///\retval matching A write ANodeMap of value type \c UEdge. | 
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| 563 | /// The found edges will be returned in this map, | 
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| 564 | /// i.e. for an \c ANode \c n the edge <tt>matching[n]</tt> is the one | 
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| 565 | /// that covers the node \c n. | 
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| 566 | /// The values are unchanged if the graph | 
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| 567 | /// has no perfect matching. | 
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| 568 | ///\return \c true iff \c g has a perfect matching. | 
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| 569 | /// | 
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| 570 | ///\note The the implementation is based | 
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| 571 | ///on the push-relabel principle. | 
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| 572 | template<class Graph,class MT> | 
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| 573 | bool prPerfectBipartiteMatching(const Graph &g,MT &matching) | 
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| 574 | { | 
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| 575 | PrBipartiteMatching<Graph> bpm(g); | 
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| 576 | bool ret = bpm.checkedRunPerfect(); | 
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| 577 | if (ret) bpm.aMatching(matching); | 
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| 578 | return ret; | 
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| 579 | } | 
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| 580 |  | 
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| 581 | ///Perfect matching in a bipartite graph | 
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| 582 |  | 
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| 583 | ///\ingroup matching | 
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| 584 | ///This function finds a perfect matching in a bipartite graph \c g. | 
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| 585 | ///\param g An undirected bipartite graph. | 
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| 586 | ///\retval matching A write ANodeMap of value type \c UEdge. | 
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| 587 | /// The found edges will be returned in this map, | 
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| 588 | /// i.e. for an \c ANode \c n the edge <tt>matching[n]</tt> is the one | 
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| 589 | /// that covers the node \c n. | 
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| 590 | /// The values are unchanged if the graph | 
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| 591 | /// has no perfect matching. | 
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| 592 | ///\retval barrier A \c bool WriteMap on the BNodes. The map will only | 
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| 593 | /// be set if \c g has no perfect matching. In this case it is set | 
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| 594 | /// exactly once for each BNode. The nodes with \c true value represent | 
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| 595 | /// a barrier, i.e. a subset \e B a of BNodes with the property that | 
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| 596 | /// the cardinality of \e B is greater than the number of its neighbors. | 
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| 597 | ///\return \c true iff \c g has a perfect matching. | 
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| 598 | /// | 
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| 599 | ///\note The the implementation is based | 
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| 600 | ///on the push-relabel principle. | 
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| 601 | template<class Graph,class MT, class GT> | 
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| 602 | bool prPerfectBipartiteMatching(const Graph &g,MT &matching,GT &barrier) | 
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| 603 | { | 
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| 604 | PrBipartiteMatching<Graph> bpm(g); | 
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| 605 | bool ret=bpm.checkedRunPerfect(); | 
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| 606 | if(ret) | 
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| 607 | bpm.aMatching(matching); | 
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| 608 | else | 
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| 609 | bpm.bBarrier(barrier); | 
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| 610 | return ret; | 
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| 611 | } | 
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| 612 | } | 
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| 613 |  | 
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| 614 | #endif | 
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