diff -r c35afa9e89e7 -r ef88c0a30f85 lemon/karp.h --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/lemon/karp.h Thu Nov 05 15:48:01 2009 +0100 @@ -0,0 +1,582 @@ +/* -*- C++ -*- + * + * This file is a part of LEMON, a generic C++ optimization library + * + * Copyright (C) 2003-2008 + * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport + * (Egervary Research Group on Combinatorial Optimization, EGRES). + * + * Permission to use, modify and distribute this software is granted + * provided that this copyright notice appears in all copies. For + * precise terms see the accompanying LICENSE file. + * + * This software is provided "AS IS" with no warranty of any kind, + * express or implied, and with no claim as to its suitability for any + * purpose. + * + */ + +#ifndef LEMON_KARP_H +#define LEMON_KARP_H + +/// \ingroup min_mean_cycle +/// +/// \file +/// \brief Karp's algorithm for finding a minimum mean cycle. + +#include +#include +#include +#include +#include +#include + +namespace lemon { + + /// \brief Default traits class of Karp algorithm. + /// + /// Default traits class of Karp algorithm. + /// \tparam GR The type of the digraph. + /// \tparam LEN The type of the length map. + /// It must conform to the \ref concepts::ReadMap "ReadMap" concept. +#ifdef DOXYGEN + template +#else + template ::is_integer> +#endif + struct KarpDefaultTraits + { + /// The type of the digraph + typedef GR Digraph; + /// The type of the length map + typedef LEN LengthMap; + /// The type of the arc lengths + typedef typename LengthMap::Value Value; + + /// \brief The large value type used for internal computations + /// + /// The large value type used for internal computations. + /// It is \c long \c long if the \c Value type is integer, + /// otherwise it is \c double. + /// \c Value must be convertible to \c LargeValue. + typedef double LargeValue; + + /// The tolerance type used for internal computations + typedef lemon::Tolerance Tolerance; + + /// \brief The path type of the found cycles + /// + /// The path type of the found cycles. + /// It must conform to the \ref lemon::concepts::Path "Path" concept + /// and it must have an \c addFront() function. + typedef lemon::Path Path; + }; + + // Default traits class for integer value types + template + struct KarpDefaultTraits + { + typedef GR Digraph; + typedef LEN LengthMap; + typedef typename LengthMap::Value Value; +#ifdef LEMON_HAVE_LONG_LONG + typedef long long LargeValue; +#else + typedef long LargeValue; +#endif + typedef lemon::Tolerance Tolerance; + typedef lemon::Path Path; + }; + + + /// \addtogroup min_mean_cycle + /// @{ + + /// \brief Implementation of Karp's algorithm for finding a minimum + /// mean cycle. + /// + /// This class implements Karp's algorithm for finding a directed + /// cycle of minimum mean length (cost) in a digraph + /// \ref amo93networkflows, \ref dasdan98minmeancycle. + /// It runs in time O(ne) and uses space O(n2+e). + /// + /// \tparam GR The type of the digraph the algorithm runs on. + /// \tparam LEN The type of the length map. The default + /// map type is \ref concepts::Digraph::ArcMap "GR::ArcMap". +#ifdef DOXYGEN + template +#else + template < typename GR, + typename LEN = typename GR::template ArcMap, + typename TR = KarpDefaultTraits > +#endif + class Karp + { + public: + + /// The type of the digraph + typedef typename TR::Digraph Digraph; + /// The type of the length map + typedef typename TR::LengthMap LengthMap; + /// The type of the arc lengths + typedef typename TR::Value Value; + + /// \brief The large value type + /// + /// The large value type used for internal computations. + /// Using the \ref KarpDefaultTraits "default traits class", + /// it is \c long \c long if the \c Value type is integer, + /// otherwise it is \c double. + typedef typename TR::LargeValue LargeValue; + + /// The tolerance type + typedef typename TR::Tolerance Tolerance; + + /// \brief The path type of the found cycles + /// + /// The path type of the found cycles. + /// Using the \ref KarpDefaultTraits "default traits class", + /// it is \ref lemon::Path "Path". + typedef typename TR::Path Path; + + /// The \ref KarpDefaultTraits "traits class" of the algorithm + typedef TR Traits; + + private: + + TEMPLATE_DIGRAPH_TYPEDEFS(Digraph); + + // Data sturcture for path data + struct PathData + { + LargeValue dist; + Arc pred; + PathData(LargeValue d, Arc p = INVALID) : + dist(d), pred(p) {} + }; + + typedef typename Digraph::template NodeMap > + PathDataNodeMap; + + private: + + // The digraph the algorithm runs on + const Digraph &_gr; + // The length of the arcs + const LengthMap &_length; + + // Data for storing the strongly connected components + int _comp_num; + typename Digraph::template NodeMap _comp; + std::vector > _comp_nodes; + std::vector* _nodes; + typename Digraph::template NodeMap > _out_arcs; + + // Data for the found cycle + LargeValue _cycle_length; + int _cycle_size; + Node _cycle_node; + + Path *_cycle_path; + bool _local_path; + + // Node map for storing path data + PathDataNodeMap _data; + // The processed nodes in the last round + std::vector _process; + + Tolerance _tolerance; + + // Infinite constant + const LargeValue INF; + + public: + + /// \name Named Template Parameters + /// @{ + + template + struct SetLargeValueTraits : public Traits { + typedef T LargeValue; + typedef lemon::Tolerance Tolerance; + }; + + /// \brief \ref named-templ-param "Named parameter" for setting + /// \c LargeValue type. + /// + /// \ref named-templ-param "Named parameter" for setting \c LargeValue + /// type. It is used for internal computations in the algorithm. + template + struct SetLargeValue + : public Karp > { + typedef Karp > Create; + }; + + template + struct SetPathTraits : public Traits { + typedef T Path; + }; + + /// \brief \ref named-templ-param "Named parameter" for setting + /// \c %Path type. + /// + /// \ref named-templ-param "Named parameter" for setting the \c %Path + /// type of the found cycles. + /// It must conform to the \ref lemon::concepts::Path "Path" concept + /// and it must have an \c addFront() function. + template + struct SetPath + : public Karp > { + typedef Karp > Create; + }; + + /// @} + + public: + + /// \brief Constructor. + /// + /// The constructor of the class. + /// + /// \param digraph The digraph the algorithm runs on. + /// \param length The lengths (costs) of the arcs. + Karp( const Digraph &digraph, + const LengthMap &length ) : + _gr(digraph), _length(length), _comp(digraph), _out_arcs(digraph), + _cycle_length(0), _cycle_size(1), _cycle_node(INVALID), + _cycle_path(NULL), _local_path(false), _data(digraph), + INF(std::numeric_limits::has_infinity ? + std::numeric_limits::infinity() : + std::numeric_limits::max()) + {} + + /// Destructor. + ~Karp() { + if (_local_path) delete _cycle_path; + } + + /// \brief Set the path structure for storing the found cycle. + /// + /// This function sets an external path structure for storing the + /// found cycle. + /// + /// If you don't call this function before calling \ref run() or + /// \ref findMinMean(), it will allocate a local \ref Path "path" + /// structure. The destuctor deallocates this automatically + /// allocated object, of course. + /// + /// \note The algorithm calls only the \ref lemon::Path::addFront() + /// "addFront()" function of the given path structure. + /// + /// \return (*this) + Karp& cycle(Path &path) { + if (_local_path) { + delete _cycle_path; + _local_path = false; + } + _cycle_path = &path; + return *this; + } + + /// \brief Set the tolerance used by the algorithm. + /// + /// This function sets the tolerance object used by the algorithm. + /// + /// \return (*this) + Karp& tolerance(const Tolerance& tolerance) { + _tolerance = tolerance; + return *this; + } + + /// \brief Return a const reference to the tolerance. + /// + /// This function returns a const reference to the tolerance object + /// used by the algorithm. + const Tolerance& tolerance() const { + return _tolerance; + } + + /// \name Execution control + /// The simplest way to execute the algorithm is to call the \ref run() + /// function.\n + /// If you only need the minimum mean length, you may call + /// \ref findMinMean(). + + /// @{ + + /// \brief Run the algorithm. + /// + /// This function runs the algorithm. + /// It can be called more than once (e.g. if the underlying digraph + /// and/or the arc lengths have been modified). + /// + /// \return \c true if a directed cycle exists in the digraph. + /// + /// \note mmc.run() is just a shortcut of the following code. + /// \code + /// return mmc.findMinMean() && mmc.findCycle(); + /// \endcode + bool run() { + return findMinMean() && findCycle(); + } + + /// \brief Find the minimum cycle mean. + /// + /// This function finds the minimum mean length of the directed + /// cycles in the digraph. + /// + /// \return \c true if a directed cycle exists in the digraph. + bool findMinMean() { + // Initialization and find strongly connected components + init(); + findComponents(); + + // Find the minimum cycle mean in the components + for (int comp = 0; comp < _comp_num; ++comp) { + if (!initComponent(comp)) continue; + processRounds(); + updateMinMean(); + } + return (_cycle_node != INVALID); + } + + /// \brief Find a minimum mean directed cycle. + /// + /// This function finds a directed cycle of minimum mean length + /// in the digraph using the data computed by findMinMean(). + /// + /// \return \c true if a directed cycle exists in the digraph. + /// + /// \pre \ref findMinMean() must be called before using this function. + bool findCycle() { + if (_cycle_node == INVALID) return false; + IntNodeMap reached(_gr, -1); + int r = _data[_cycle_node].size(); + Node u = _cycle_node; + while (reached[u] < 0) { + reached[u] = --r; + u = _gr.source(_data[u][r].pred); + } + r = reached[u]; + Arc e = _data[u][r].pred; + _cycle_path->addFront(e); + _cycle_length = _length[e]; + _cycle_size = 1; + Node v; + while ((v = _gr.source(e)) != u) { + e = _data[v][--r].pred; + _cycle_path->addFront(e); + _cycle_length += _length[e]; + ++_cycle_size; + } + return true; + } + + /// @} + + /// \name Query Functions + /// The results of the algorithm can be obtained using these + /// functions.\n + /// The algorithm should be executed before using them. + + /// @{ + + /// \brief Return the total length of the found cycle. + /// + /// This function returns the total length of the found cycle. + /// + /// \pre \ref run() or \ref findMinMean() must be called before + /// using this function. + LargeValue cycleLength() const { + return _cycle_length; + } + + /// \brief Return the number of arcs on the found cycle. + /// + /// This function returns the number of arcs on the found cycle. + /// + /// \pre \ref run() or \ref findMinMean() must be called before + /// using this function. + int cycleArcNum() const { + return _cycle_size; + } + + /// \brief Return the mean length of the found cycle. + /// + /// This function returns the mean length of the found cycle. + /// + /// \note alg.cycleMean() is just a shortcut of the + /// following code. + /// \code + /// return static_cast(alg.cycleLength()) / alg.cycleArcNum(); + /// \endcode + /// + /// \pre \ref run() or \ref findMinMean() must be called before + /// using this function. + double cycleMean() const { + return static_cast(_cycle_length) / _cycle_size; + } + + /// \brief Return the found cycle. + /// + /// This function returns a const reference to the path structure + /// storing the found cycle. + /// + /// \pre \ref run() or \ref findCycle() must be called before using + /// this function. + const Path& cycle() const { + return *_cycle_path; + } + + ///@} + + private: + + // Initialization + void init() { + if (!_cycle_path) { + _local_path = true; + _cycle_path = new Path; + } + _cycle_path->clear(); + _cycle_length = 0; + _cycle_size = 1; + _cycle_node = INVALID; + for (NodeIt u(_gr); u != INVALID; ++u) + _data[u].clear(); + } + + // Find strongly connected components and initialize _comp_nodes + // and _out_arcs + void findComponents() { + _comp_num = stronglyConnectedComponents(_gr, _comp); + _comp_nodes.resize(_comp_num); + if (_comp_num == 1) { + _comp_nodes[0].clear(); + for (NodeIt n(_gr); n != INVALID; ++n) { + _comp_nodes[0].push_back(n); + _out_arcs[n].clear(); + for (OutArcIt a(_gr, n); a != INVALID; ++a) { + _out_arcs[n].push_back(a); + } + } + } else { + for (int i = 0; i < _comp_num; ++i) + _comp_nodes[i].clear(); + for (NodeIt n(_gr); n != INVALID; ++n) { + int k = _comp[n]; + _comp_nodes[k].push_back(n); + _out_arcs[n].clear(); + for (OutArcIt a(_gr, n); a != INVALID; ++a) { + if (_comp[_gr.target(a)] == k) _out_arcs[n].push_back(a); + } + } + } + } + + // Initialize path data for the current component + bool initComponent(int comp) { + _nodes = &(_comp_nodes[comp]); + int n = _nodes->size(); + if (n < 1 || (n == 1 && _out_arcs[(*_nodes)[0]].size() == 0)) { + return false; + } + for (int i = 0; i < n; ++i) { + _data[(*_nodes)[i]].resize(n + 1, PathData(INF)); + } + return true; + } + + // Process all rounds of computing path data for the current component. + // _data[v][k] is the length of a shortest directed walk from the root + // node to node v containing exactly k arcs. + void processRounds() { + Node start = (*_nodes)[0]; + _data[start][0] = PathData(0); + _process.clear(); + _process.push_back(start); + + int k, n = _nodes->size(); + for (k = 1; k <= n && int(_process.size()) < n; ++k) { + processNextBuildRound(k); + } + for ( ; k <= n; ++k) { + processNextFullRound(k); + } + } + + // Process one round and rebuild _process + void processNextBuildRound(int k) { + std::vector next; + Node u, v; + Arc e; + LargeValue d; + for (int i = 0; i < int(_process.size()); ++i) { + u = _process[i]; + for (int j = 0; j < int(_out_arcs[u].size()); ++j) { + e = _out_arcs[u][j]; + v = _gr.target(e); + d = _data[u][k-1].dist + _length[e]; + if (_tolerance.less(d, _data[v][k].dist)) { + if (_data[v][k].dist == INF) next.push_back(v); + _data[v][k] = PathData(d, e); + } + } + } + _process.swap(next); + } + + // Process one round using _nodes instead of _process + void processNextFullRound(int k) { + Node u, v; + Arc e; + LargeValue d; + for (int i = 0; i < int(_nodes->size()); ++i) { + u = (*_nodes)[i]; + for (int j = 0; j < int(_out_arcs[u].size()); ++j) { + e = _out_arcs[u][j]; + v = _gr.target(e); + d = _data[u][k-1].dist + _length[e]; + if (_tolerance.less(d, _data[v][k].dist)) { + _data[v][k] = PathData(d, e); + } + } + } + } + + // Update the minimum cycle mean + void updateMinMean() { + int n = _nodes->size(); + for (int i = 0; i < n; ++i) { + Node u = (*_nodes)[i]; + if (_data[u][n].dist == INF) continue; + LargeValue length, max_length = 0; + int size, max_size = 1; + bool found_curr = false; + for (int k = 0; k < n; ++k) { + if (_data[u][k].dist == INF) continue; + length = _data[u][n].dist - _data[u][k].dist; + size = n - k; + if (!found_curr || length * max_size > max_length * size) { + found_curr = true; + max_length = length; + max_size = size; + } + } + if ( found_curr && (_cycle_node == INVALID || + max_length * _cycle_size < _cycle_length * max_size) ) { + _cycle_length = max_length; + _cycle_size = max_size; + _cycle_node = u; + } + } + } + + }; //class Karp + + ///@} + +} //namespace lemon + +#endif //LEMON_KARP_H