[906] | 1 | /* -*- C++ -*- |
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[1435] | 2 | * lemon/kruskal.h - Part of LEMON, a generic C++ optimization library |
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[906] | 3 | * |
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[1164] | 4 | * Copyright (C) 2005 Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport |
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[1359] | 5 | * (Egervary Research Group on Combinatorial Optimization, EGRES). |
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[906] | 6 | * |
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| 7 | * Permission to use, modify and distribute this software is granted |
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| 8 | * provided that this copyright notice appears in all copies. For |
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| 9 | * precise terms see the accompanying LICENSE file. |
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| 10 | * |
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| 11 | * This software is provided "AS IS" with no warranty of any kind, |
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| 12 | * express or implied, and with no claim as to its suitability for any |
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| 13 | * purpose. |
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| 14 | * |
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| 15 | */ |
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| 16 | |
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[921] | 17 | #ifndef LEMON_KRUSKAL_H |
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| 18 | #define LEMON_KRUSKAL_H |
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[810] | 19 | |
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| 20 | #include <algorithm> |
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[921] | 21 | #include <lemon/unionfind.h> |
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[1449] | 22 | #include<lemon/utility.h> |
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[810] | 23 | |
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| 24 | /** |
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| 25 | @defgroup spantree Minimum Cost Spanning Tree Algorithms |
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| 26 | @ingroup galgs |
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| 27 | \brief This group containes the algorithms for finding a minimum cost spanning |
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| 28 | tree in a graph |
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| 29 | |
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| 30 | This group containes the algorithms for finding a minimum cost spanning |
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| 31 | tree in a graph |
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| 32 | */ |
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| 33 | |
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| 34 | ///\ingroup spantree |
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| 35 | ///\file |
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| 36 | ///\brief Kruskal's algorithm to compute a minimum cost tree |
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| 37 | /// |
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| 38 | ///Kruskal's algorithm to compute a minimum cost tree. |
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[1557] | 39 | /// |
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| 40 | ///\todo The file still needs some clean-up. |
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[810] | 41 | |
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[921] | 42 | namespace lemon { |
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[810] | 43 | |
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| 44 | /// \addtogroup spantree |
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| 45 | /// @{ |
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| 46 | |
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| 47 | /// Kruskal's algorithm to find a minimum cost tree of a graph. |
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| 48 | |
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| 49 | /// This function runs Kruskal's algorithm to find a minimum cost tree. |
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[1557] | 50 | /// Due to hard C++ hacking, it accepts various input and output types. |
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| 51 | /// |
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[1555] | 52 | /// \param g The graph the algorithm runs on. |
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| 53 | /// It can be either \ref concept::StaticGraph "directed" or |
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| 54 | /// \ref concept::UndirStaticGraph "undirected". |
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| 55 | /// If the graph is directed, the algorithm consider it to be |
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| 56 | /// undirected by disregarding the direction of the edges. |
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[810] | 57 | /// |
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[1557] | 58 | /// \param in This object is used to describe the edge costs. It can be one |
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| 59 | /// of the following choices. |
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| 60 | /// - An STL compatible 'Forward Container' |
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[824] | 61 | /// with <tt>std::pair<GR::Edge,X></tt> as its <tt>value_type</tt>, |
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[1557] | 62 | /// where \c X is the type of the costs. The pairs indicates the edges along |
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| 63 | /// with the assigned cost. <em>They must be in a |
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| 64 | /// cost-ascending order.</em> |
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| 65 | /// - Any readable Edge map. The values of the map indicate the edge costs. |
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[810] | 66 | /// |
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[1557] | 67 | /// \retval out Here we also have a choise. |
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| 68 | /// - Is can be a writable \c bool edge map. |
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[810] | 69 | /// After running the algorithm |
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| 70 | /// this will contain the found minimum cost spanning tree: the value of an |
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| 71 | /// edge will be set to \c true if it belongs to the tree, otherwise it will |
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| 72 | /// be set to \c false. The value of each edge will be set exactly once. |
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[1557] | 73 | /// - It can also be an iteraror of an STL Container with |
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| 74 | /// <tt>GR::Edge</tt> as its <tt>value_type</tt>. |
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| 75 | /// The algorithm copies the elements of the found tree into this sequence. |
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| 76 | /// For example, if we know that the spanning tree of the graph \c g has |
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[1603] | 77 | /// say 53 edges, then |
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[1557] | 78 | /// we can put its edges into a STL vector \c tree with a code like this. |
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| 79 | /// \code |
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| 80 | /// std::vector<Edge> tree(53); |
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| 81 | /// kruskal(g,cost,tree.begin()); |
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| 82 | /// \endcode |
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| 83 | /// Or if we don't know in advance the size of the tree, we can write this. |
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| 84 | /// \code |
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| 85 | /// std::vector<Edge> tree; |
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| 86 | /// kruskal(g,cost,std::back_inserter(tree)); |
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| 87 | /// \endcode |
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[810] | 88 | /// |
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| 89 | /// \return The cost of the found tree. |
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[1449] | 90 | /// |
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[1603] | 91 | /// \warning If kruskal is run on an \ref undirected graph, be sure that the |
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| 92 | /// map storing the tree is also undirected |
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| 93 | /// (e.g. UndirListGraph::UndirEdgeMap<bool>, otherwise the values of the |
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| 94 | /// half of the edges will not be set. |
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| 95 | /// |
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[1449] | 96 | /// \todo Discuss the case of undirected graphs: In this case the algorithm |
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| 97 | /// also require <tt>Edge</tt>s instead of <tt>UndirEdge</tt>s, as some |
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| 98 | /// people would expect. So, one should be careful not to add both of the |
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| 99 | /// <tt>Edge</tt>s belonging to a certain <tt>UndirEdge</tt>. |
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[1570] | 100 | /// (\ref kruskal() and \ref KruskalMapInput are kind enough to do so.) |
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[810] | 101 | |
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[1557] | 102 | #ifdef DOXYGEN |
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[824] | 103 | template <class GR, class IN, class OUT> |
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| 104 | typename IN::value_type::second_type |
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[1547] | 105 | kruskal(GR const& g, IN const& in, |
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[1557] | 106 | OUT& out) |
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| 107 | #else |
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| 108 | template <class GR, class IN, class OUT> |
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| 109 | typename IN::value_type::second_type |
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| 110 | kruskal(GR const& g, IN const& in, |
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| 111 | OUT& out, |
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| 112 | // typename IN::value_type::first_type = typename GR::Edge() |
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| 113 | // ,typename OUT::Key = OUT::Key() |
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| 114 | // //,typename OUT::Key = typename GR::Edge() |
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| 115 | const typename IN::value_type::first_type * = |
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| 116 | (const typename IN::value_type::first_type *)(0), |
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| 117 | const typename OUT::Key * = (const typename OUT::Key *)(0) |
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| 118 | ) |
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| 119 | #endif |
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[810] | 120 | { |
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[824] | 121 | typedef typename IN::value_type::second_type EdgeCost; |
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| 122 | typedef typename GR::template NodeMap<int> NodeIntMap; |
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| 123 | typedef typename GR::Node Node; |
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[810] | 124 | |
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[1547] | 125 | NodeIntMap comp(g, -1); |
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[810] | 126 | UnionFind<Node,NodeIntMap> uf(comp); |
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| 127 | |
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| 128 | EdgeCost tot_cost = 0; |
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[824] | 129 | for (typename IN::const_iterator p = in.begin(); |
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[810] | 130 | p!=in.end(); ++p ) { |
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[1547] | 131 | if ( uf.join(g.target((*p).first), |
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| 132 | g.source((*p).first)) ) { |
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[810] | 133 | out.set((*p).first, true); |
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| 134 | tot_cost += (*p).second; |
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| 135 | } |
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| 136 | else { |
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| 137 | out.set((*p).first, false); |
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| 138 | } |
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| 139 | } |
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| 140 | return tot_cost; |
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| 141 | } |
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| 142 | |
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[1557] | 143 | |
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| 144 | /// @} |
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| 145 | |
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| 146 | |
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[810] | 147 | /* A work-around for running Kruskal with const-reference bool maps... */ |
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| 148 | |
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[885] | 149 | /// Helper class for calling kruskal with "constant" output map. |
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| 150 | |
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| 151 | /// Helper class for calling kruskal with output maps constructed |
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| 152 | /// on-the-fly. |
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[810] | 153 | /// |
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[885] | 154 | /// A typical examle is the following call: |
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[1547] | 155 | /// <tt>kruskal(g, some_input, makeSequenceOutput(iterator))</tt>. |
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[885] | 156 | /// Here, the third argument is a temporary object (which wraps around an |
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| 157 | /// iterator with a writable bool map interface), and thus by rules of C++ |
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| 158 | /// is a \c const object. To enable call like this exist this class and |
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| 159 | /// the prototype of the \ref kruskal() function with <tt>const& OUT</tt> |
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| 160 | /// third argument. |
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[824] | 161 | template<class Map> |
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[810] | 162 | class NonConstMapWr { |
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| 163 | const Map &m; |
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| 164 | public: |
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[1557] | 165 | typedef typename Map::Key Key; |
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[987] | 166 | typedef typename Map::Value Value; |
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[810] | 167 | |
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| 168 | NonConstMapWr(const Map &_m) : m(_m) {} |
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| 169 | |
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[987] | 170 | template<class Key> |
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| 171 | void set(Key const& k, Value const &v) const { m.set(k,v); } |
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[810] | 172 | }; |
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| 173 | |
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[824] | 174 | template <class GR, class IN, class OUT> |
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[810] | 175 | inline |
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[885] | 176 | typename IN::value_type::second_type |
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[1557] | 177 | kruskal(GR const& g, IN const& edges, OUT const& out_map, |
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| 178 | // typename IN::value_type::first_type = typename GR::Edge(), |
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| 179 | // typename OUT::Key = GR::Edge() |
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| 180 | const typename IN::value_type::first_type * = |
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| 181 | (const typename IN::value_type::first_type *)(0), |
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| 182 | const typename OUT::Key * = (const typename OUT::Key *)(0) |
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| 183 | ) |
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[810] | 184 | { |
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[824] | 185 | NonConstMapWr<OUT> map_wr(out_map); |
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[1547] | 186 | return kruskal(g, edges, map_wr); |
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[810] | 187 | } |
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| 188 | |
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| 189 | /* ** ** Input-objects ** ** */ |
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| 190 | |
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[1274] | 191 | /// Kruskal's input source. |
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[1557] | 192 | |
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[1274] | 193 | /// Kruskal's input source. |
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[810] | 194 | /// |
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[1570] | 195 | /// In most cases you possibly want to use the \ref kruskal() instead. |
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[810] | 196 | /// |
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| 197 | /// \sa makeKruskalMapInput() |
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| 198 | /// |
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[824] | 199 | ///\param GR The type of the graph the algorithm runs on. |
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[810] | 200 | ///\param Map An edge map containing the cost of the edges. |
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| 201 | ///\par |
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| 202 | ///The cost type can be any type satisfying |
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| 203 | ///the STL 'LessThan comparable' |
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| 204 | ///concept if it also has an operator+() implemented. (It is necessary for |
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| 205 | ///computing the total cost of the tree). |
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| 206 | /// |
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[824] | 207 | template<class GR, class Map> |
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[810] | 208 | class KruskalMapInput |
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[824] | 209 | : public std::vector< std::pair<typename GR::Edge, |
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[987] | 210 | typename Map::Value> > { |
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[810] | 211 | |
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| 212 | public: |
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[824] | 213 | typedef std::vector< std::pair<typename GR::Edge, |
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[987] | 214 | typename Map::Value> > Parent; |
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[810] | 215 | typedef typename Parent::value_type value_type; |
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| 216 | |
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| 217 | private: |
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| 218 | class comparePair { |
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| 219 | public: |
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| 220 | bool operator()(const value_type& a, |
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| 221 | const value_type& b) { |
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| 222 | return a.second < b.second; |
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| 223 | } |
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| 224 | }; |
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| 225 | |
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[1449] | 226 | template<class _GR> |
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| 227 | typename enable_if<typename _GR::UndirTag,void>::type |
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[1547] | 228 | fillWithEdges(const _GR& g, const Map& m,dummy<0> = 0) |
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[1449] | 229 | { |
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[1547] | 230 | for(typename GR::UndirEdgeIt e(g);e!=INVALID;++e) |
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[1449] | 231 | push_back(value_type(typename GR::Edge(e,true), m[e])); |
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| 232 | } |
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| 233 | |
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| 234 | template<class _GR> |
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| 235 | typename disable_if<typename _GR::UndirTag,void>::type |
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[1547] | 236 | fillWithEdges(const _GR& g, const Map& m,dummy<1> = 1) |
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[1449] | 237 | { |
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[1547] | 238 | for(typename GR::EdgeIt e(g);e!=INVALID;++e) |
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[1449] | 239 | push_back(value_type(e, m[e])); |
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| 240 | } |
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| 241 | |
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| 242 | |
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[810] | 243 | public: |
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| 244 | |
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| 245 | void sort() { |
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| 246 | std::sort(this->begin(), this->end(), comparePair()); |
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| 247 | } |
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| 248 | |
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[1547] | 249 | KruskalMapInput(GR const& g, Map const& m) { |
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| 250 | fillWithEdges(g,m); |
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[810] | 251 | sort(); |
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| 252 | } |
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| 253 | }; |
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| 254 | |
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| 255 | /// Creates a KruskalMapInput object for \ref kruskal() |
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| 256 | |
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[1274] | 257 | /// It makes easier to use |
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[810] | 258 | /// \ref KruskalMapInput by making it unnecessary |
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| 259 | /// to explicitly give the type of the parameters. |
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| 260 | /// |
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| 261 | /// In most cases you possibly |
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[1570] | 262 | /// want to use \ref kruskal() instead. |
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[810] | 263 | /// |
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[1547] | 264 | ///\param g The type of the graph the algorithm runs on. |
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[810] | 265 | ///\param m An edge map containing the cost of the edges. |
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| 266 | ///\par |
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| 267 | ///The cost type can be any type satisfying the |
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| 268 | ///STL 'LessThan Comparable' |
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| 269 | ///concept if it also has an operator+() implemented. (It is necessary for |
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| 270 | ///computing the total cost of the tree). |
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| 271 | /// |
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| 272 | ///\return An appropriate input source for \ref kruskal(). |
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| 273 | /// |
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[824] | 274 | template<class GR, class Map> |
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[810] | 275 | inline |
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[1547] | 276 | KruskalMapInput<GR,Map> makeKruskalMapInput(const GR &g,const Map &m) |
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[810] | 277 | { |
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[1547] | 278 | return KruskalMapInput<GR,Map>(g,m); |
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[810] | 279 | } |
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| 280 | |
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| 281 | |
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[885] | 282 | |
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| 283 | /* ** ** Output-objects: simple writable bool maps ** ** */ |
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[810] | 284 | |
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[885] | 285 | |
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| 286 | |
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[810] | 287 | /// A writable bool-map that makes a sequence of "true" keys |
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| 288 | |
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| 289 | /// A writable bool-map that creates a sequence out of keys that receives |
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| 290 | /// the value "true". |
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[885] | 291 | /// |
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| 292 | /// \sa makeKruskalSequenceOutput() |
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| 293 | /// |
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| 294 | /// Very often, when looking for a min cost spanning tree, we want as |
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| 295 | /// output a container containing the edges of the found tree. For this |
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| 296 | /// purpose exist this class that wraps around an STL iterator with a |
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| 297 | /// writable bool map interface. When a key gets value "true" this key |
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| 298 | /// is added to sequence pointed by the iterator. |
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| 299 | /// |
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| 300 | /// A typical usage: |
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| 301 | /// \code |
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| 302 | /// std::vector<Graph::Edge> v; |
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| 303 | /// kruskal(g, input, makeKruskalSequenceOutput(back_inserter(v))); |
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| 304 | /// \endcode |
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| 305 | /// |
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| 306 | /// For the most common case, when the input is given by a simple edge |
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| 307 | /// map and the output is a sequence of the tree edges, a special |
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| 308 | /// wrapper function exists: \ref kruskalEdgeMap_IteratorOut(). |
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| 309 | /// |
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[987] | 310 | /// \warning Not a regular property map, as it doesn't know its Key |
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[885] | 311 | |
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[824] | 312 | template<class Iterator> |
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[885] | 313 | class KruskalSequenceOutput { |
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[810] | 314 | mutable Iterator it; |
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| 315 | |
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| 316 | public: |
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[1557] | 317 | typedef typename Iterator::value_type Key; |
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[987] | 318 | typedef bool Value; |
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[810] | 319 | |
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[885] | 320 | KruskalSequenceOutput(Iterator const &_it) : it(_it) {} |
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[810] | 321 | |
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[987] | 322 | template<typename Key> |
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| 323 | void set(Key const& k, bool v) const { if(v) {*it=k; ++it;} } |
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[810] | 324 | }; |
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| 325 | |
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[824] | 326 | template<class Iterator> |
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[810] | 327 | inline |
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[885] | 328 | KruskalSequenceOutput<Iterator> |
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| 329 | makeKruskalSequenceOutput(Iterator it) { |
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| 330 | return KruskalSequenceOutput<Iterator>(it); |
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[810] | 331 | } |
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| 332 | |
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[885] | 333 | |
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| 334 | |
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[810] | 335 | /* ** ** Wrapper funtions ** ** */ |
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| 336 | |
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[1557] | 337 | // \brief Wrapper function to kruskal(). |
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| 338 | // Input is from an edge map, output is a plain bool map. |
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| 339 | // |
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| 340 | // Wrapper function to kruskal(). |
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| 341 | // Input is from an edge map, output is a plain bool map. |
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| 342 | // |
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| 343 | // \param g The type of the graph the algorithm runs on. |
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| 344 | // \param in An edge map containing the cost of the edges. |
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| 345 | // \par |
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| 346 | // The cost type can be any type satisfying the |
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| 347 | // STL 'LessThan Comparable' |
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| 348 | // concept if it also has an operator+() implemented. (It is necessary for |
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| 349 | // computing the total cost of the tree). |
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| 350 | // |
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| 351 | // \retval out This must be a writable \c bool edge map. |
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| 352 | // After running the algorithm |
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| 353 | // this will contain the found minimum cost spanning tree: the value of an |
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| 354 | // edge will be set to \c true if it belongs to the tree, otherwise it will |
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| 355 | // be set to \c false. The value of each edge will be set exactly once. |
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| 356 | // |
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| 357 | // \return The cost of the found tree. |
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[810] | 358 | |
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[824] | 359 | template <class GR, class IN, class RET> |
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[810] | 360 | inline |
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[987] | 361 | typename IN::Value |
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[1557] | 362 | kruskal(GR const& g, |
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| 363 | IN const& in, |
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| 364 | RET &out, |
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| 365 | // typename IN::Key = typename GR::Edge(), |
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| 366 | //typename IN::Key = typename IN::Key (), |
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| 367 | // typename RET::Key = typename GR::Edge() |
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| 368 | const typename IN::Key * = (const typename IN::Key *)(0), |
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| 369 | const typename RET::Key * = (const typename RET::Key *)(0) |
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| 370 | ) |
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| 371 | { |
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[1547] | 372 | return kruskal(g, |
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| 373 | KruskalMapInput<GR,IN>(g,in), |
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[810] | 374 | out); |
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| 375 | } |
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| 376 | |
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[1557] | 377 | // \brief Wrapper function to kruskal(). |
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| 378 | // Input is from an edge map, output is an STL Sequence. |
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| 379 | // |
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| 380 | // Wrapper function to kruskal(). |
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| 381 | // Input is from an edge map, output is an STL Sequence. |
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| 382 | // |
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| 383 | // \param g The type of the graph the algorithm runs on. |
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| 384 | // \param in An edge map containing the cost of the edges. |
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| 385 | // \par |
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| 386 | // The cost type can be any type satisfying the |
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| 387 | // STL 'LessThan Comparable' |
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| 388 | // concept if it also has an operator+() implemented. (It is necessary for |
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| 389 | // computing the total cost of the tree). |
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| 390 | // |
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| 391 | // \retval out This must be an iteraror of an STL Container with |
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| 392 | // <tt>GR::Edge</tt> as its <tt>value_type</tt>. |
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| 393 | // The algorithm copies the elements of the found tree into this sequence. |
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| 394 | // For example, if we know that the spanning tree of the graph \c g has |
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[1603] | 395 | // say 53 edges, then |
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[1557] | 396 | // we can put its edges into a STL vector \c tree with a code like this. |
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| 397 | // \code |
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| 398 | // std::vector<Edge> tree(53); |
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[1570] | 399 | // kruskal(g,cost,tree.begin()); |
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[1557] | 400 | // \endcode |
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| 401 | // Or if we don't know in advance the size of the tree, we can write this. |
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| 402 | // \code |
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| 403 | // std::vector<Edge> tree; |
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[1570] | 404 | // kruskal(g,cost,std::back_inserter(tree)); |
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[1557] | 405 | // \endcode |
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| 406 | // |
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| 407 | // \return The cost of the found tree. |
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| 408 | // |
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| 409 | // \bug its name does not follow the coding style. |
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[885] | 410 | |
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[824] | 411 | template <class GR, class IN, class RET> |
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[810] | 412 | inline |
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[987] | 413 | typename IN::Value |
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[1557] | 414 | kruskal(const GR& g, |
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| 415 | const IN& in, |
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| 416 | RET out, |
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| 417 | //,typename RET::value_type = typename GR::Edge() |
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| 418 | //,typename RET::value_type = typename RET::value_type() |
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| 419 | const typename RET::value_type * = |
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| 420 | (const typename RET::value_type *)(0) |
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| 421 | ) |
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[810] | 422 | { |
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[885] | 423 | KruskalSequenceOutput<RET> _out(out); |
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[1547] | 424 | return kruskal(g, KruskalMapInput<GR,IN>(g, in), _out); |
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[810] | 425 | } |
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[1557] | 426 | |
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[810] | 427 | /// @} |
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| 428 | |
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[921] | 429 | } //namespace lemon |
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[810] | 430 | |
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[921] | 431 | #endif //LEMON_KRUSKAL_H |
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