alpar@906
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1 |
/* -*- C++ -*-
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alpar@906
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*
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alpar@1956
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* This file is a part of LEMON, a generic C++ optimization library
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alpar@1956
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*
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alpar@1956
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* Copyright (C) 2003-2006
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alpar@1956
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* Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
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alpar@1359
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* (Egervary Research Group on Combinatorial Optimization, EGRES).
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alpar@906
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*
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alpar@906
|
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* Permission to use, modify and distribute this software is granted
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alpar@906
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* provided that this copyright notice appears in all copies. For
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alpar@906
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* precise terms see the accompanying LICENSE file.
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alpar@906
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*
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alpar@906
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13 |
* This software is provided "AS IS" with no warranty of any kind,
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alpar@906
|
14 |
* express or implied, and with no claim as to its suitability for any
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alpar@906
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* purpose.
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alpar@906
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*
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alpar@906
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*/
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alpar@906
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alpar@921
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#ifndef LEMON_KRUSKAL_H
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alpar@921
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#define LEMON_KRUSKAL_H
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alpar@810
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alpar@810
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#include <algorithm>
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klao@1942
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#include <vector>
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alpar@921
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#include <lemon/unionfind.h>
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klao@1942
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#include <lemon/utility.h>
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alpar@810
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alpar@810
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/**
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alpar@810
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@defgroup spantree Minimum Cost Spanning Tree Algorithms
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alpar@810
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@ingroup galgs
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alpar@810
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\brief This group containes the algorithms for finding a minimum cost spanning
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alpar@810
|
31 |
tree in a graph
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alpar@810
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alpar@810
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This group containes the algorithms for finding a minimum cost spanning
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alpar@810
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tree in a graph
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alpar@810
|
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*/
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alpar@810
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alpar@810
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///\ingroup spantree
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alpar@810
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///\file
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alpar@810
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///\brief Kruskal's algorithm to compute a minimum cost tree
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alpar@810
|
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///
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alpar@810
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///Kruskal's algorithm to compute a minimum cost tree.
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alpar@1557
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///
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alpar@1557
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///\todo The file still needs some clean-up.
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alpar@810
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alpar@921
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namespace lemon {
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alpar@810
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alpar@810
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/// \addtogroup spantree
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alpar@810
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/// @{
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alpar@810
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alpar@810
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/// Kruskal's algorithm to find a minimum cost tree of a graph.
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alpar@810
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51 |
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alpar@810
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/// This function runs Kruskal's algorithm to find a minimum cost tree.
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alpar@1557
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53 |
/// Due to hard C++ hacking, it accepts various input and output types.
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alpar@1557
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///
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alpar@1555
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/// \param g The graph the algorithm runs on.
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alpar@1555
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/// It can be either \ref concept::StaticGraph "directed" or
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klao@1909
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/// \ref concept::UGraph "undirected".
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alpar@1555
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/// If the graph is directed, the algorithm consider it to be
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alpar@1555
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/// undirected by disregarding the direction of the edges.
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alpar@810
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///
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alpar@1557
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/// \param in This object is used to describe the edge costs. It can be one
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alpar@1557
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/// of the following choices.
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alpar@1557
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/// - An STL compatible 'Forward Container'
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alpar@824
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/// with <tt>std::pair<GR::Edge,X></tt> as its <tt>value_type</tt>,
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alpar@1557
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/// where \c X is the type of the costs. The pairs indicates the edges along
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alpar@1557
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/// with the assigned cost. <em>They must be in a
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alpar@1557
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/// cost-ascending order.</em>
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alpar@1557
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/// - Any readable Edge map. The values of the map indicate the edge costs.
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alpar@810
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///
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alpar@1557
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/// \retval out Here we also have a choise.
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alpar@1557
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/// - Is can be a writable \c bool edge map.
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alpar@810
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/// After running the algorithm
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alpar@810
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/// this will contain the found minimum cost spanning tree: the value of an
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alpar@810
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/// edge will be set to \c true if it belongs to the tree, otherwise it will
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alpar@810
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/// be set to \c false. The value of each edge will be set exactly once.
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alpar@1557
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/// - It can also be an iteraror of an STL Container with
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alpar@1557
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/// <tt>GR::Edge</tt> as its <tt>value_type</tt>.
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alpar@1557
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/// The algorithm copies the elements of the found tree into this sequence.
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alpar@1557
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/// For example, if we know that the spanning tree of the graph \c g has
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alpar@1603
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/// say 53 edges, then
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alpar@1557
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/// we can put its edges into a STL vector \c tree with a code like this.
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alpar@1946
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///\code
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alpar@1557
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/// std::vector<Edge> tree(53);
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alpar@1557
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/// kruskal(g,cost,tree.begin());
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alpar@1946
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///\endcode
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alpar@1557
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/// Or if we don't know in advance the size of the tree, we can write this.
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alpar@1946
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///\code
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alpar@1557
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/// std::vector<Edge> tree;
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alpar@1557
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/// kruskal(g,cost,std::back_inserter(tree));
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alpar@1946
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///\endcode
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alpar@810
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///
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alpar@810
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/// \return The cost of the found tree.
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alpar@1449
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///
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alpar@1631
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/// \warning If kruskal is run on an
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klao@1909
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/// \ref lemon::concept::UGraph "undirected graph", be sure that the
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alpar@1603
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/// map storing the tree is also undirected
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klao@1909
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/// (e.g. ListUGraph::UEdgeMap<bool>, otherwise the values of the
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alpar@1603
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/// half of the edges will not be set.
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alpar@1603
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///
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alpar@1449
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/// \todo Discuss the case of undirected graphs: In this case the algorithm
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klao@1909
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/// also require <tt>Edge</tt>s instead of <tt>UEdge</tt>s, as some
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alpar@1449
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/// people would expect. So, one should be careful not to add both of the
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klao@1909
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/// <tt>Edge</tt>s belonging to a certain <tt>UEdge</tt>.
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alpar@1570
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/// (\ref kruskal() and \ref KruskalMapInput are kind enough to do so.)
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alpar@810
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alpar@1557
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#ifdef DOXYGEN
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alpar@824
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template <class GR, class IN, class OUT>
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alpar@824
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typename IN::value_type::second_type
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alpar@1547
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kruskal(GR const& g, IN const& in,
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alpar@1557
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OUT& out)
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alpar@1557
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#else
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alpar@1557
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template <class GR, class IN, class OUT>
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alpar@1557
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typename IN::value_type::second_type
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alpar@1557
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kruskal(GR const& g, IN const& in,
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alpar@1557
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OUT& out,
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alpar@1557
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// typename IN::value_type::first_type = typename GR::Edge()
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alpar@1557
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// ,typename OUT::Key = OUT::Key()
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alpar@1557
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// //,typename OUT::Key = typename GR::Edge()
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alpar@1557
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const typename IN::value_type::first_type * =
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alpar@1557
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(const typename IN::value_type::first_type *)(0),
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alpar@1557
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const typename OUT::Key * = (const typename OUT::Key *)(0)
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alpar@1557
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)
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alpar@1557
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#endif
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alpar@810
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{
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alpar@824
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125 |
typedef typename IN::value_type::second_type EdgeCost;
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alpar@824
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126 |
typedef typename GR::template NodeMap<int> NodeIntMap;
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alpar@824
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typedef typename GR::Node Node;
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alpar@810
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128 |
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alpar@1547
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129 |
NodeIntMap comp(g, -1);
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alpar@810
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UnionFind<Node,NodeIntMap> uf(comp);
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alpar@810
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alpar@810
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EdgeCost tot_cost = 0;
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alpar@824
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for (typename IN::const_iterator p = in.begin();
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alpar@810
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p!=in.end(); ++p ) {
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alpar@1547
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if ( uf.join(g.target((*p).first),
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alpar@1547
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g.source((*p).first)) ) {
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alpar@810
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out.set((*p).first, true);
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alpar@810
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138 |
tot_cost += (*p).second;
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alpar@810
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139 |
}
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alpar@810
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else {
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alpar@810
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out.set((*p).first, false);
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alpar@810
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}
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alpar@810
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143 |
}
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alpar@810
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144 |
return tot_cost;
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alpar@810
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}
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alpar@810
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alpar@1557
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alpar@1557
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/// @}
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alpar@1557
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alpar@1557
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alpar@810
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/* A work-around for running Kruskal with const-reference bool maps... */
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alpar@810
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152 |
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klao@885
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/// Helper class for calling kruskal with "constant" output map.
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klao@885
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klao@885
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/// Helper class for calling kruskal with output maps constructed
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klao@885
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/// on-the-fly.
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alpar@810
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157 |
///
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klao@885
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/// A typical examle is the following call:
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alpar@1547
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159 |
/// <tt>kruskal(g, some_input, makeSequenceOutput(iterator))</tt>.
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klao@885
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160 |
/// Here, the third argument is a temporary object (which wraps around an
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klao@885
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161 |
/// iterator with a writable bool map interface), and thus by rules of C++
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klao@885
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/// is a \c const object. To enable call like this exist this class and
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klao@885
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/// the prototype of the \ref kruskal() function with <tt>const& OUT</tt>
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klao@885
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/// third argument.
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alpar@824
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template<class Map>
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alpar@810
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166 |
class NonConstMapWr {
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alpar@810
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167 |
const Map &m;
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alpar@810
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168 |
public:
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alpar@1557
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169 |
typedef typename Map::Key Key;
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alpar@987
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typedef typename Map::Value Value;
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alpar@810
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alpar@810
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172 |
NonConstMapWr(const Map &_m) : m(_m) {}
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alpar@810
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alpar@987
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174 |
template<class Key>
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alpar@987
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void set(Key const& k, Value const &v) const { m.set(k,v); }
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alpar@810
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};
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alpar@810
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alpar@824
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template <class GR, class IN, class OUT>
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alpar@810
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inline
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klao@885
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typename IN::value_type::second_type
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alpar@1557
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181 |
kruskal(GR const& g, IN const& edges, OUT const& out_map,
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alpar@1557
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182 |
// typename IN::value_type::first_type = typename GR::Edge(),
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alpar@1557
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183 |
// typename OUT::Key = GR::Edge()
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alpar@1557
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184 |
const typename IN::value_type::first_type * =
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alpar@1557
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185 |
(const typename IN::value_type::first_type *)(0),
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alpar@1557
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186 |
const typename OUT::Key * = (const typename OUT::Key *)(0)
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alpar@1557
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)
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alpar@810
|
188 |
{
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alpar@824
|
189 |
NonConstMapWr<OUT> map_wr(out_map);
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alpar@1547
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190 |
return kruskal(g, edges, map_wr);
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alpar@810
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191 |
}
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alpar@810
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192 |
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alpar@810
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193 |
/* ** ** Input-objects ** ** */
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alpar@810
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194 |
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zsuzska@1274
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195 |
/// Kruskal's input source.
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alpar@1557
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196 |
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zsuzska@1274
|
197 |
/// Kruskal's input source.
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alpar@810
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198 |
///
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alpar@1570
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199 |
/// In most cases you possibly want to use the \ref kruskal() instead.
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alpar@810
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200 |
///
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alpar@810
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201 |
/// \sa makeKruskalMapInput()
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alpar@810
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202 |
///
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alpar@824
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203 |
///\param GR The type of the graph the algorithm runs on.
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alpar@810
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204 |
///\param Map An edge map containing the cost of the edges.
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alpar@810
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205 |
///\par
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alpar@810
|
206 |
///The cost type can be any type satisfying
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alpar@810
|
207 |
///the STL 'LessThan comparable'
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alpar@810
|
208 |
///concept if it also has an operator+() implemented. (It is necessary for
|
alpar@810
|
209 |
///computing the total cost of the tree).
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alpar@810
|
210 |
///
|
alpar@824
|
211 |
template<class GR, class Map>
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alpar@810
|
212 |
class KruskalMapInput
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alpar@824
|
213 |
: public std::vector< std::pair<typename GR::Edge,
|
alpar@987
|
214 |
typename Map::Value> > {
|
alpar@810
|
215 |
|
alpar@810
|
216 |
public:
|
alpar@824
|
217 |
typedef std::vector< std::pair<typename GR::Edge,
|
alpar@987
|
218 |
typename Map::Value> > Parent;
|
alpar@810
|
219 |
typedef typename Parent::value_type value_type;
|
alpar@810
|
220 |
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alpar@810
|
221 |
private:
|
alpar@810
|
222 |
class comparePair {
|
alpar@810
|
223 |
public:
|
alpar@810
|
224 |
bool operator()(const value_type& a,
|
alpar@810
|
225 |
const value_type& b) {
|
alpar@810
|
226 |
return a.second < b.second;
|
alpar@810
|
227 |
}
|
alpar@810
|
228 |
};
|
alpar@810
|
229 |
|
alpar@1449
|
230 |
template<class _GR>
|
klao@1909
|
231 |
typename enable_if<typename _GR::UTag,void>::type
|
alpar@1547
|
232 |
fillWithEdges(const _GR& g, const Map& m,dummy<0> = 0)
|
alpar@1449
|
233 |
{
|
klao@1909
|
234 |
for(typename GR::UEdgeIt e(g);e!=INVALID;++e)
|
deba@1679
|
235 |
push_back(value_type(g.direct(e, true), m[e]));
|
alpar@1449
|
236 |
}
|
alpar@1449
|
237 |
|
alpar@1449
|
238 |
template<class _GR>
|
klao@1909
|
239 |
typename disable_if<typename _GR::UTag,void>::type
|
alpar@1547
|
240 |
fillWithEdges(const _GR& g, const Map& m,dummy<1> = 1)
|
alpar@1449
|
241 |
{
|
alpar@1547
|
242 |
for(typename GR::EdgeIt e(g);e!=INVALID;++e)
|
alpar@1449
|
243 |
push_back(value_type(e, m[e]));
|
alpar@1449
|
244 |
}
|
alpar@1449
|
245 |
|
alpar@1449
|
246 |
|
alpar@810
|
247 |
public:
|
alpar@810
|
248 |
|
alpar@810
|
249 |
void sort() {
|
alpar@810
|
250 |
std::sort(this->begin(), this->end(), comparePair());
|
alpar@810
|
251 |
}
|
alpar@810
|
252 |
|
alpar@1547
|
253 |
KruskalMapInput(GR const& g, Map const& m) {
|
alpar@1547
|
254 |
fillWithEdges(g,m);
|
alpar@810
|
255 |
sort();
|
alpar@810
|
256 |
}
|
alpar@810
|
257 |
};
|
alpar@810
|
258 |
|
alpar@810
|
259 |
/// Creates a KruskalMapInput object for \ref kruskal()
|
alpar@810
|
260 |
|
zsuzska@1274
|
261 |
/// It makes easier to use
|
alpar@810
|
262 |
/// \ref KruskalMapInput by making it unnecessary
|
alpar@810
|
263 |
/// to explicitly give the type of the parameters.
|
alpar@810
|
264 |
///
|
alpar@810
|
265 |
/// In most cases you possibly
|
alpar@1570
|
266 |
/// want to use \ref kruskal() instead.
|
alpar@810
|
267 |
///
|
alpar@1547
|
268 |
///\param g The type of the graph the algorithm runs on.
|
alpar@810
|
269 |
///\param m An edge map containing the cost of the edges.
|
alpar@810
|
270 |
///\par
|
alpar@810
|
271 |
///The cost type can be any type satisfying the
|
alpar@810
|
272 |
///STL 'LessThan Comparable'
|
alpar@810
|
273 |
///concept if it also has an operator+() implemented. (It is necessary for
|
alpar@810
|
274 |
///computing the total cost of the tree).
|
alpar@810
|
275 |
///
|
alpar@810
|
276 |
///\return An appropriate input source for \ref kruskal().
|
alpar@810
|
277 |
///
|
alpar@824
|
278 |
template<class GR, class Map>
|
alpar@810
|
279 |
inline
|
alpar@1547
|
280 |
KruskalMapInput<GR,Map> makeKruskalMapInput(const GR &g,const Map &m)
|
alpar@810
|
281 |
{
|
alpar@1547
|
282 |
return KruskalMapInput<GR,Map>(g,m);
|
alpar@810
|
283 |
}
|
alpar@810
|
284 |
|
alpar@810
|
285 |
|
klao@885
|
286 |
|
klao@885
|
287 |
/* ** ** Output-objects: simple writable bool maps ** ** */
|
alpar@810
|
288 |
|
klao@885
|
289 |
|
klao@885
|
290 |
|
alpar@810
|
291 |
/// A writable bool-map that makes a sequence of "true" keys
|
alpar@810
|
292 |
|
alpar@810
|
293 |
/// A writable bool-map that creates a sequence out of keys that receives
|
alpar@810
|
294 |
/// the value "true".
|
klao@885
|
295 |
///
|
klao@885
|
296 |
/// \sa makeKruskalSequenceOutput()
|
klao@885
|
297 |
///
|
klao@885
|
298 |
/// Very often, when looking for a min cost spanning tree, we want as
|
klao@885
|
299 |
/// output a container containing the edges of the found tree. For this
|
klao@885
|
300 |
/// purpose exist this class that wraps around an STL iterator with a
|
klao@885
|
301 |
/// writable bool map interface. When a key gets value "true" this key
|
klao@885
|
302 |
/// is added to sequence pointed by the iterator.
|
klao@885
|
303 |
///
|
klao@885
|
304 |
/// A typical usage:
|
alpar@1946
|
305 |
///\code
|
klao@885
|
306 |
/// std::vector<Graph::Edge> v;
|
klao@885
|
307 |
/// kruskal(g, input, makeKruskalSequenceOutput(back_inserter(v)));
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///\endcode
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klao@885
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///
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klao@885
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/// For the most common case, when the input is given by a simple edge
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klao@885
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/// map and the output is a sequence of the tree edges, a special
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klao@885
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/// wrapper function exists: \ref kruskalEdgeMap_IteratorOut().
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///
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alpar@987
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314 |
/// \warning Not a regular property map, as it doesn't know its Key
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klao@885
|
315 |
|
alpar@824
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316 |
template<class Iterator>
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317 |
class KruskalSequenceOutput {
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alpar@810
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318 |
mutable Iterator it;
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alpar@810
|
319 |
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alpar@810
|
320 |
public:
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klao@1942
|
321 |
typedef typename std::iterator_traits<Iterator>::value_type Key;
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alpar@987
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322 |
typedef bool Value;
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alpar@810
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323 |
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klao@885
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324 |
KruskalSequenceOutput(Iterator const &_it) : it(_it) {}
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alpar@810
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325 |
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alpar@987
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326 |
template<typename Key>
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alpar@987
|
327 |
void set(Key const& k, bool v) const { if(v) {*it=k; ++it;} }
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alpar@810
|
328 |
};
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alpar@810
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329 |
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alpar@824
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330 |
template<class Iterator>
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331 |
inline
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KruskalSequenceOutput<Iterator>
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klao@885
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makeKruskalSequenceOutput(Iterator it) {
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klao@885
|
334 |
return KruskalSequenceOutput<Iterator>(it);
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alpar@810
|
335 |
}
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alpar@810
|
336 |
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klao@885
|
337 |
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klao@885
|
338 |
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alpar@810
|
339 |
/* ** ** Wrapper funtions ** ** */
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alpar@810
|
340 |
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alpar@1557
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// \brief Wrapper function to kruskal().
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alpar@1557
|
342 |
// Input is from an edge map, output is a plain bool map.
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alpar@1557
|
343 |
//
|
alpar@1557
|
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// Wrapper function to kruskal().
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alpar@1557
|
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// Input is from an edge map, output is a plain bool map.
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alpar@1557
|
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//
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alpar@1557
|
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// \param g The type of the graph the algorithm runs on.
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alpar@1557
|
348 |
// \param in An edge map containing the cost of the edges.
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alpar@1557
|
349 |
// \par
|
alpar@1557
|
350 |
// The cost type can be any type satisfying the
|
alpar@1557
|
351 |
// STL 'LessThan Comparable'
|
alpar@1557
|
352 |
// concept if it also has an operator+() implemented. (It is necessary for
|
alpar@1557
|
353 |
// computing the total cost of the tree).
|
alpar@1557
|
354 |
//
|
alpar@1557
|
355 |
// \retval out This must be a writable \c bool edge map.
|
alpar@1557
|
356 |
// After running the algorithm
|
alpar@1557
|
357 |
// this will contain the found minimum cost spanning tree: the value of an
|
alpar@1557
|
358 |
// edge will be set to \c true if it belongs to the tree, otherwise it will
|
alpar@1557
|
359 |
// be set to \c false. The value of each edge will be set exactly once.
|
alpar@1557
|
360 |
//
|
alpar@1557
|
361 |
// \return The cost of the found tree.
|
alpar@810
|
362 |
|
alpar@824
|
363 |
template <class GR, class IN, class RET>
|
alpar@810
|
364 |
inline
|
alpar@987
|
365 |
typename IN::Value
|
alpar@1557
|
366 |
kruskal(GR const& g,
|
alpar@1557
|
367 |
IN const& in,
|
alpar@1557
|
368 |
RET &out,
|
alpar@1557
|
369 |
// typename IN::Key = typename GR::Edge(),
|
alpar@1557
|
370 |
//typename IN::Key = typename IN::Key (),
|
alpar@1557
|
371 |
// typename RET::Key = typename GR::Edge()
|
alpar@1557
|
372 |
const typename IN::Key * = (const typename IN::Key *)(0),
|
alpar@1557
|
373 |
const typename RET::Key * = (const typename RET::Key *)(0)
|
alpar@1557
|
374 |
)
|
alpar@1557
|
375 |
{
|
alpar@1547
|
376 |
return kruskal(g,
|
alpar@1547
|
377 |
KruskalMapInput<GR,IN>(g,in),
|
alpar@810
|
378 |
out);
|
alpar@810
|
379 |
}
|
alpar@810
|
380 |
|
alpar@1557
|
381 |
// \brief Wrapper function to kruskal().
|
alpar@1557
|
382 |
// Input is from an edge map, output is an STL Sequence.
|
alpar@1557
|
383 |
//
|
alpar@1557
|
384 |
// Wrapper function to kruskal().
|
alpar@1557
|
385 |
// Input is from an edge map, output is an STL Sequence.
|
alpar@1557
|
386 |
//
|
alpar@1557
|
387 |
// \param g The type of the graph the algorithm runs on.
|
alpar@1557
|
388 |
// \param in An edge map containing the cost of the edges.
|
alpar@1557
|
389 |
// \par
|
alpar@1557
|
390 |
// The cost type can be any type satisfying the
|
alpar@1557
|
391 |
// STL 'LessThan Comparable'
|
alpar@1557
|
392 |
// concept if it also has an operator+() implemented. (It is necessary for
|
alpar@1557
|
393 |
// computing the total cost of the tree).
|
alpar@1557
|
394 |
//
|
alpar@1557
|
395 |
// \retval out This must be an iteraror of an STL Container with
|
alpar@1557
|
396 |
// <tt>GR::Edge</tt> as its <tt>value_type</tt>.
|
alpar@1557
|
397 |
// The algorithm copies the elements of the found tree into this sequence.
|
alpar@1557
|
398 |
// For example, if we know that the spanning tree of the graph \c g has
|
alpar@1603
|
399 |
// say 53 edges, then
|
alpar@1557
|
400 |
// we can put its edges into a STL vector \c tree with a code like this.
|
alpar@1946
|
401 |
//\code
|
alpar@1557
|
402 |
// std::vector<Edge> tree(53);
|
alpar@1570
|
403 |
// kruskal(g,cost,tree.begin());
|
alpar@1946
|
404 |
//\endcode
|
alpar@1557
|
405 |
// Or if we don't know in advance the size of the tree, we can write this.
|
alpar@1946
|
406 |
//\code
|
alpar@1557
|
407 |
// std::vector<Edge> tree;
|
alpar@1570
|
408 |
// kruskal(g,cost,std::back_inserter(tree));
|
alpar@1946
|
409 |
//\endcode
|
alpar@1557
|
410 |
//
|
alpar@1557
|
411 |
// \return The cost of the found tree.
|
alpar@1557
|
412 |
//
|
alpar@1557
|
413 |
// \bug its name does not follow the coding style.
|
klao@885
|
414 |
|
alpar@824
|
415 |
template <class GR, class IN, class RET>
|
alpar@810
|
416 |
inline
|
alpar@987
|
417 |
typename IN::Value
|
alpar@1557
|
418 |
kruskal(const GR& g,
|
alpar@1557
|
419 |
const IN& in,
|
alpar@1557
|
420 |
RET out,
|
alpar@1557
|
421 |
const typename RET::value_type * =
|
alpar@1557
|
422 |
(const typename RET::value_type *)(0)
|
alpar@1557
|
423 |
)
|
alpar@810
|
424 |
{
|
klao@885
|
425 |
KruskalSequenceOutput<RET> _out(out);
|
alpar@1547
|
426 |
return kruskal(g, KruskalMapInput<GR,IN>(g, in), _out);
|
alpar@810
|
427 |
}
|
alpar@1557
|
428 |
|
klao@1942
|
429 |
template <class GR, class IN, class RET>
|
klao@1942
|
430 |
inline
|
klao@1942
|
431 |
typename IN::Value
|
klao@1942
|
432 |
kruskal(const GR& g,
|
klao@1942
|
433 |
const IN& in,
|
klao@1942
|
434 |
RET *out
|
klao@1942
|
435 |
)
|
klao@1942
|
436 |
{
|
klao@1942
|
437 |
KruskalSequenceOutput<RET*> _out(out);
|
klao@1942
|
438 |
return kruskal(g, KruskalMapInput<GR,IN>(g, in), _out);
|
klao@1942
|
439 |
}
|
klao@1942
|
440 |
|
alpar@810
|
441 |
/// @}
|
alpar@810
|
442 |
|
alpar@921
|
443 |
} //namespace lemon
|
alpar@810
|
444 |
|
alpar@921
|
445 |
#endif //LEMON_KRUSKAL_H
|