LEMON/LEMON-official Changeset - r760:4ac30454f1c1

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Changeset - r760:4ac30454f1c1

« 730:9f529a

761:98a308 »

r760:4ac30454f1c1

Fri, 24 Jul 2009 10:27:40

[Not Reviewed]

0 comments (0 inline)

kpeter (Peter Kovacs)
kpeter@inf.elte.hu

Small doc improvements

0 8 0

default

8 files changed with 42 insertions and 28 deletions:

doc/groups.dox

lemon/bfs.h

lemon/circulation.h

lemon/dfs.h

lemon/dijkstra.h

lemon/gomory_hu.h

lemon/min_cost_arborescence.h

lemon/preflow.h

↑ Collapse diff ↑

doc/groups.dox

Show inline comments

@@ -282,217 +282,217 @@
 		\brief Algorithms for finding shortest paths.
 		This group contains the algorithms for finding shortest paths in digraphs.
 		 - \ref Dijkstra algorithm for finding shortest paths from a source node
 		   when all arc lengths are non-negative.
 		 - \ref BellmanFord "Bellman-Ford" algorithm for finding shortest paths
 		   from a source node when arc lenghts can be either positive or negative,
 		   but the digraph should not contain directed cycles with negative total
 		   length.
 		 - \ref FloydWarshall "Floyd-Warshall" and \ref Johnson "Johnson" algorithms
 		   for solving the \e all-pairs \e shortest \e paths \e problem when arc
 		   lenghts can be either positive or negative, but the digraph should
 		   not contain directed cycles with negative total length.
 		 - \ref Suurballe A successive shortest path algorithm for finding
 		   arc-disjoint paths between two nodes having minimum total length.
 		*/
 		/**
 		@defgroup max_flow Maximum Flow Algorithms
 		@ingroup algs
 		\brief Algorithms for finding maximum flows.
 		This group contains the algorithms for finding maximum flows and
 		feasible circulations.
 		The \e maximum \e flow \e problem is to find a flow of maximum value between
 		a single source and a single target. Formally, there is a \f$G=(V,A)\f$
 		digraph, a \f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function and
 		\f$s, t \in V\f$ source and target nodes.
 		A maximum flow is an \f$f: A\rightarrow\mathbf{R}^+_0\f$ solution of the
 		following optimization problem.
 		\f[ \max\sum_{sv\in A} f(sv) - \sum_{vs\in A} f(vs) \f]
 		\f[ \sum_{uv\in A} f(uv) = \sum_{vu\in A} f(vu)
 		    \quad \forall u\in V\setminus\{s,t\} \f]
 		\f[ 0 \leq f(uv) \leq cap(uv) \quad \forall uv\in A \f]
 		LEMON contains several algorithms for solving maximum flow problems:
 		- \ref EdmondsKarp Edmonds-Karp algorithm.
 		- \ref Preflow Goldberg-Tarjan's preflow push-relabel algorithm.
 		- \ref DinitzSleatorTarjan Dinitz's blocking flow algorithm with dynamic trees.
 		- \ref GoldbergTarjan Preflow push-relabel algorithm with dynamic trees.
 		In most cases the \ref Preflow "Preflow" algorithm provides the
 		fastest method for computing a maximum flow. All implementations
 		also provide functions to query the minimum cut, which is the dual
 		problem of maximum flow.
 		\ref Circulation is a preflow push-relabel algorithm implemented directly
 		for finding feasible circulations, which is a somewhat different problem,
 		but it is strongly related to maximum flow.
 		For more information, see \ref Circulation.
 		*/
 		/**
 		@defgroup min_cost_flow_algs Minimum Cost Flow Algorithms
 		@ingroup algs
 		\brief Algorithms for finding minimum cost flows and circulations.
 		This group contains the algorithms for finding minimum cost flows and
 		circulations. For more information about this problem and its dual
 		solution see \ref min_cost_flow "Minimum Cost Flow Problem".
 		LEMON contains several algorithms for this problem.
 		 - \ref NetworkSimplex Primal Network Simplex algorithm with various
 		   pivot strategies.
 		 - \ref CostScaling Push-Relabel and Augment-Relabel algorithms based on
 		   cost scaling.
 		 - \ref CapacityScaling Successive Shortest %Path algorithm with optional
 		   capacity scaling.
 		 - \ref CancelAndTighten The Cancel and Tighten algorithm.
 		 - \ref CycleCanceling Cycle-Canceling algorithms.
 		In general NetworkSimplex is the most efficient implementation,
 		but in special cases other algorithms could be faster.
 		For example, if the total supply and/or capacities are rather small,
 		CapacityScaling is usually the fastest algorithm (without effective scaling).
 		*/
 		/**
 		@defgroup min_cut Minimum Cut Algorithms
 		@ingroup algs
 		\brief Algorithms for finding minimum cut in graphs.
 		This group contains the algorithms for finding minimum cut in graphs.
 		The \e minimum \e cut \e problem is to find a non-empty and non-complete
 		\f$X\f$ subset of the nodes with minimum overall capacity on
 		outgoing arcs. Formally, there is a \f$G=(V,A)\f$ digraph, a
 		\f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function. The minimum
 		cut is the \f$X\f$ solution of the next optimization problem:
 		\f[ \min_{X \subset V, X\not\in \{\emptyset, V\}}
-		    \sum_{uv\in A, u\in X, v\not\in X}cap(uv) \f]
+		    \sum_{uv\in A: u\in X, v\not\in X}cap(uv) \f]
 		LEMON contains several algorithms related to minimum cut problems:
 		- \ref HaoOrlin "Hao-Orlin algorithm" for calculating minimum cut
 		  in directed graphs.
 		- \ref NagamochiIbaraki "Nagamochi-Ibaraki algorithm" for
 		  calculating minimum cut in undirected graphs.
 		- \ref GomoryHu "Gomory-Hu tree computation" for calculating
 		  all-pairs minimum cut in undirected graphs.
 		If you want to find minimum cut just between two distinict nodes,
 		see the \ref max_flow "maximum flow problem".
 		*/
 		/**
 		@defgroup graph_properties Connectivity and Other Graph Properties
 		@ingroup algs
 		\brief Algorithms for discovering the graph properties
 		This group contains the algorithms for discovering the graph properties
 		like connectivity, bipartiteness, euler property, simplicity etc.
 		\image html edge_biconnected_components.png
 		\image latex edge_biconnected_components.eps "bi-edge-connected components" width=\textwidth
 		\image html connected_components.png
 		\image latex connected_components.eps "Connected components" width=\textwidth
 		*/
 		/**
 		@defgroup planar Planarity Embedding and Drawing
 		@ingroup algs
 		\brief Algorithms for planarity checking, embedding and drawing
 		This group contains the algorithms for planarity checking,
 		embedding and drawing.
 		\image html planar.png
 		\image latex planar.eps "Plane graph" width=\textwidth
 		*/
 		/**
 		@defgroup matching Matching Algorithms
 		@ingroup algs
 		\brief Algorithms for finding matchings in graphs and bipartite graphs.
 		This group contains the algorithms for calculating
 		matchings in graphs and bipartite graphs. The general matching problem is
 		finding a subset of the edges for which each node has at most one incident
 		edge.
 		There are several different algorithms for calculate matchings in
 		graphs.  The matching problems in bipartite graphs are generally
 		easier than in general graphs. The goal of the matching optimization
 		can be finding maximum cardinality, maximum weight or minimum cost
 		matching. The search can be constrained to find perfect or
 		maximum cardinality matching.
 		The matching algorithms implemented in LEMON:
 		- \ref MaxBipartiteMatching Hopcroft-Karp augmenting path algorithm
 		  for calculating maximum cardinality matching in bipartite graphs.
 		- \ref PrBipartiteMatching Push-relabel algorithm
 		  for calculating maximum cardinality matching in bipartite graphs.
 		- \ref MaxWeightedBipartiteMatching
 		  Successive shortest path algorithm for calculating maximum weighted
 		  matching and maximum weighted bipartite matching in bipartite graphs.
 		- \ref MinCostMaxBipartiteMatching
 		  Successive shortest path algorithm for calculating minimum cost maximum
 		  matching in bipartite graphs.
 		- \ref MaxMatching Edmond's blossom shrinking algorithm for calculating
 		  maximum cardinality matching in general graphs.
 		- \ref MaxWeightedMatching Edmond's blossom shrinking algorithm for calculating
 		  maximum weighted matching in general graphs.
 		- \ref MaxWeightedPerfectMatching
 		  Edmond's blossom shrinking algorithm for calculating maximum weighted
 		  perfect matching in general graphs.
 		\image html bipartite_matching.png
 		\image latex bipartite_matching.eps "Bipartite Matching" width=\textwidth
 		*/
 		/**
 		@defgroup spantree Minimum Spanning Tree Algorithms
 		@ingroup algs
 		\brief Algorithms for finding minimum cost spanning trees and arborescences.
 		This group contains the algorithms for finding minimum cost spanning
 		trees and arborescences.
 		*/
 		/**
 		@defgroup auxalg Auxiliary Algorithms
 		@ingroup algs
 		\brief Auxiliary algorithms implemented in LEMON.
 		This group contains some algorithms implemented in LEMON
 		in order to make it easier to implement complex algorithms.
 		*/
 		/**
 		@defgroup approx Approximation Algorithms
 		@ingroup algs
 		\brief Approximation algorithms.
 		This group contains the approximation and heuristic algorithms
 		implemented in LEMON.
 		*/
 		/**
 		@defgroup gen_opt_group General Optimization Tools
 		\brief This group contains some general optimization frameworks
 		implemented in LEMON.
 		This group contains some general optimization frameworks
 		implemented in LEMON.
 		*/
 		/**
 		@defgroup lp_group Lp and Mip Solvers
 		@ingroup gen_opt_group
 		\brief Lp and Mip solver interfaces for LEMON.
 		This group contains Lp and Mip solver interfaces for LEMON. The

lemon/bfs.h

Show inline comments

@@ -320,194 +320,194 @@
 		    ///\param g The digraph the algorithm runs on.
 		    Bfs(const Digraph &g) :
 		      G(&g),
 		      _pred(NULL), local_pred(false),
 		      _dist(NULL), local_dist(false),
 		      _reached(NULL), local_reached(false),
 		      _processed(NULL), local_processed(false)
 		    { }
 		    ///Destructor.
 		    ~Bfs()
+		    {
 		      if(local_pred) delete _pred;
 		      if(local_dist) delete _dist;
 		      if(local_reached) delete _reached;
 		      if(local_processed) delete _processed;
+		    }
 		    ///Sets the map that stores the predecessor arcs.
 		    ///Sets the map that stores the predecessor arcs.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Bfs &predMap(PredMap &m)
+		    {
 		      if(local_pred) {
 		        delete _pred;
 		        local_pred=false;
+		      }
 		      _pred = &m;
 		      return *this;
+		    }
 		    ///Sets the map that indicates which nodes are reached.
 		    ///Sets the map that indicates which nodes are reached.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Bfs &reachedMap(ReachedMap &m)
+		    {
 		      if(local_reached) {
 		        delete _reached;
 		        local_reached=false;
+		      }
 		      _reached = &m;
 		      return *this;
+		    }
 		    ///Sets the map that indicates which nodes are processed.
 		    ///Sets the map that indicates which nodes are processed.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Bfs &processedMap(ProcessedMap &m)
+		    {
 		      if(local_processed) {
 		        delete _processed;
 		        local_processed=false;
+		      }
 		      _processed = &m;
 		      return *this;
+		    }
 		    ///Sets the map that stores the distances of the nodes.
 		    ///Sets the map that stores the distances of the nodes calculated by
 		    ///the algorithm.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Bfs &distMap(DistMap &m)
+		    {
 		      if(local_dist) {
 		        delete _dist;
 		        local_dist=false;
+		      }
 		      _dist = &m;
 		      return *this;
+		    }
 		  public:
 		    ///\name Execution Control
 		    ///The simplest way to execute the BFS algorithm is to use one of the
 		    ///member functions called \ref run(Node) "run()".\n
 		    ///If you need more control on the execution, first you have to call
 		    ///\ref init(), then you can add several source nodes with
 		    ///If you need better control on the execution, you have to call
 		    ///\ref init() first, then you can add several source nodes with
 		    ///\ref addSource(). Finally the actual path computation can be
 		    ///performed with one of the \ref start() functions.
 		    ///@{
 		    ///\brief Initializes the internal data structures.
 		    ///
 		    ///Initializes the internal data structures.
 		    void init()
+		    {
 		      create_maps();
 		      _queue.resize(countNodes(*G));
 		      _queue_head=_queue_tail=0;
 		      _curr_dist=1;
 		      for ( NodeIt u(*G) ; u!=INVALID ; ++u ) {
 		        _pred->set(u,INVALID);
 		        _reached->set(u,false);
 		        _processed->set(u,false);
+		      }
+		    }
 		    ///Adds a new source node.
 		    ///Adds a new source node to the set of nodes to be processed.
 		    ///
 		    void addSource(Node s)
+		    {
 		      if(!(*_reached)[s])
+		        {
 		          _reached->set(s,true);
 		          _pred->set(s,INVALID);
 		          _dist->set(s,0);
 		          _queue[_queue_head++]=s;
 		          _queue_next_dist=_queue_head;
+		        }
+		    }
 		    ///Processes the next node.
 		    ///Processes the next node.
 		    ///
 		    ///\return The processed node.
 		    ///
 		    ///\pre The queue must not be empty.
 		    Node processNextNode()
+		    {
 		      if(_queue_tail==_queue_next_dist) {
 		        _curr_dist++;
 		        _queue_next_dist=_queue_head;
+		      }
 		      Node n=_queue[_queue_tail++];
 		      _processed->set(n,true);
 		      Node m;
 		      for(OutArcIt e(*G,n);e!=INVALID;++e)
 		        if(!(*_reached)[m=G->target(e)]) {
 		          _queue[_queue_head++]=m;
 		          _reached->set(m,true);
 		          _pred->set(m,e);
 		          _dist->set(m,_curr_dist);
+		        }
 		      return n;
+		    }
 		    ///Processes the next node.
 		    ///Processes the next node and checks if the given target node
 		    ///is reached. If the target node is reachable from the processed
 		    ///node, then the \c reach parameter will be set to \c true.
 		    ///
 		    ///\param target The target node.
 		    ///\retval reach Indicates if the target node is reached.
 		    ///It should be initially \c false.
 		    ///
 		    ///\return The processed node.
 		    ///
 		    ///\pre The queue must not be empty.
 		    Node processNextNode(Node target, bool& reach)
+		    {
 		      if(_queue_tail==_queue_next_dist) {
 		        _curr_dist++;
 		        _queue_next_dist=_queue_head;
+		      }
 		      Node n=_queue[_queue_tail++];
 		      _processed->set(n,true);
 		      Node m;
 		      for(OutArcIt e(*G,n);e!=INVALID;++e)
 		        if(!(*_reached)[m=G->target(e)]) {
 		          _queue[_queue_head++]=m;
 		          _reached->set(m,true);
 		          _pred->set(m,e);
 		          _dist->set(m,_curr_dist);
 		          reach = reach || (target == m);
+		        }
 		      return n;
+		    }
@@ -1332,194 +1332,194 @@
 		  private:
 		    typedef typename Digraph::Node Node;
 		    typedef typename Digraph::NodeIt NodeIt;
 		    typedef typename Digraph::Arc Arc;
 		    typedef typename Digraph::OutArcIt OutArcIt;
 		    //Pointer to the underlying digraph.
 		    const Digraph *_digraph;
 		    //Pointer to the visitor object.
 		    Visitor *_visitor;
 		    //Pointer to the map of reached status of the nodes.
 		    ReachedMap *_reached;
 		    //Indicates if _reached is locally allocated (true) or not.
 		    bool local_reached;
 		    std::vector<typename Digraph::Node> _list;
 		    int _list_front, _list_back;
 		    //Creates the maps if necessary.
 		    void create_maps() {
 		      if(!_reached) {
 		        local_reached = true;
 		        _reached = Traits::createReachedMap(*_digraph);
+		      }
+		    }
 		  protected:
 		    BfsVisit() {}
 		  public:
 		    typedef BfsVisit Create;
 		    /// \name Named Template Parameters
 		    ///@{
 		    template <class T>
 		    struct SetReachedMapTraits : public Traits {
 		      typedef T ReachedMap;
 		      static ReachedMap *createReachedMap(const Digraph &digraph) {
 		        LEMON_ASSERT(false, "ReachedMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for setting
 		    /// ReachedMap type.
 		    ///
 		    /// \ref named-templ-param "Named parameter" for setting ReachedMap type.
 		    template <class T>
 		    struct SetReachedMap : public BfsVisit< Digraph, Visitor,
 		                                            SetReachedMapTraits<T> > {
 		      typedef BfsVisit< Digraph, Visitor, SetReachedMapTraits<T> > Create;
 		    };
 		    ///@}
 		  public:
 		    /// \brief Constructor.
 		    ///
 		    /// Constructor.
 		    ///
 		    /// \param digraph The digraph the algorithm runs on.
 		    /// \param visitor The visitor object of the algorithm.
 		    BfsVisit(const Digraph& digraph, Visitor& visitor)
 		      : _digraph(&digraph), _visitor(&visitor),
 		        _reached(0), local_reached(false) {}
 		    /// \brief Destructor.
 		    ~BfsVisit() {
 		      if(local_reached) delete _reached;
+		    }
 		    /// \brief Sets the map that indicates which nodes are reached.
 		    ///
 		    /// Sets the map that indicates which nodes are reached.
 		    /// If you don't use this function before calling \ref run(Node) "run()"
 		    /// or \ref init(), an instance will be allocated automatically.
 		    /// The destructor deallocates this automatically allocated map,
 		    /// of course.
 		    /// \return <tt> (*this) </tt>
 		    BfsVisit &reachedMap(ReachedMap &m) {
 		      if(local_reached) {
 		        delete _reached;
 		        local_reached = false;
+		      }
 		      _reached = &m;
 		      return *this;
+		    }
 		  public:
 		    /// \name Execution Control
 		    /// The simplest way to execute the BFS algorithm is to use one of the
 		    /// member functions called \ref run(Node) "run()".\n
 		    /// If you need more control on the execution, first you have to call
 		    /// \ref init(), then you can add several source nodes with
 		    /// If you need better control on the execution, you have to call
 		    /// \ref init() first, then you can add several source nodes with
 		    /// \ref addSource(). Finally the actual path computation can be
 		    /// performed with one of the \ref start() functions.
 		    /// @{
 		    /// \brief Initializes the internal data structures.
 		    ///
 		    /// Initializes the internal data structures.
 		    void init() {
 		      create_maps();
 		      _list.resize(countNodes(*_digraph));
 		      _list_front = _list_back = -1;
 		      for (NodeIt u(*_digraph) ; u != INVALID ; ++u) {
 		        _reached->set(u, false);
+		      }
+		    }
 		    /// \brief Adds a new source node.
 		    ///
 		    /// Adds a new source node to the set of nodes to be processed.
 		    void addSource(Node s) {
 		      if(!(*_reached)[s]) {
 		          _reached->set(s,true);
 		          _visitor->start(s);
 		          _visitor->reach(s);
 		          _list[++_list_back] = s;
+		        }
+		    }
 		    /// \brief Processes the next node.
 		    ///
 		    /// Processes the next node.
 		    ///
 		    /// \return The processed node.
 		    ///
 		    /// \pre The queue must not be empty.
 		    Node processNextNode() {
 		      Node n = _list[++_list_front];
 		      _visitor->process(n);
 		      Arc e;
 		      for (_digraph->firstOut(e, n); e != INVALID; _digraph->nextOut(e)) {
 		        Node m = _digraph->target(e);
 		        if (!(*_reached)[m]) {
 		          _visitor->discover(e);
 		          _visitor->reach(m);
 		          _reached->set(m, true);
 		          _list[++_list_back] = m;
 		        } else {
 		          _visitor->examine(e);
+		        }
+		      }
 		      return n;
+		    }
 		    /// \brief Processes the next node.
 		    ///
 		    /// Processes the next node and checks if the given target node
 		    /// is reached. If the target node is reachable from the processed
 		    /// node, then the \c reach parameter will be set to \c true.
 		    ///
 		    /// \param target The target node.
 		    /// \retval reach Indicates if the target node is reached.
 		    /// It should be initially \c false.
 		    ///
 		    /// \return The processed node.
 		    ///
 		    /// \pre The queue must not be empty.
 		    Node processNextNode(Node target, bool& reach) {
 		      Node n = _list[++_list_front];
 		      _visitor->process(n);
 		      Arc e;
 		      for (_digraph->firstOut(e, n); e != INVALID; _digraph->nextOut(e)) {
 		        Node m = _digraph->target(e);
 		        if (!(*_reached)[m]) {
 		          _visitor->discover(e);
 		          _visitor->reach(m);
 		          _reached->set(m, true);
 		          _list[++_list_back] = m;
 		          reach = reach || (target == m);
 		        } else {
 		          _visitor->examine(e);
+		        }
+		      }
 		      return n;
+		    }
 		    /// \brief Processes the next node.
 		    ///
 		    /// Processes the next node and checks if at least one of reached
 		    /// nodes has \c true value in the \c nm node map. If one node
 		    /// with \c true value is reachable from the processed node, then the
 		    /// \c rnode parameter will be set to the first of such nodes.
 		    ///
 		    /// \param nm A \c bool (or convertible) node map that indicates the
 		    /// possible targets.
 		    /// \retval rnode The reached target node.

lemon/circulation.h

Show inline comments

 		/* -*- mode: C++; indent-tabs-mode: nil; -*-
+		 *
 		 * This file is a part of LEMON, a generic C++ optimization library.
+		 *
 		 * Copyright (C) 2003-2009
 		 * 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_CIRCULATION_H
 		#define LEMON_CIRCULATION_H
 		#include <lemon/tolerance.h>
 		#include <lemon/elevator.h>
 		#include <limits>
 		///\ingroup max_flow
 		///\file
 		///\brief Push-relabel algorithm for finding a feasible circulation.
 		///
 		namespace lemon {
 		  /// \brief Default traits class of Circulation class.
 		  ///
 		  /// Default traits class of Circulation class.
 		  ///
 		  /// \tparam GR Type of the digraph the algorithm runs on.
 		  /// \tparam LM The type of the lower bound map.
 		  /// \tparam UM The type of the upper bound (capacity) map.
 		  /// \tparam SM The type of the supply map.
 		  template <typename GR, typename LM,
 		            typename UM, typename SM>
 		  struct CirculationDefaultTraits {
 		    /// \brief The type of the digraph the algorithm runs on.
 		    typedef GR Digraph;
 		    /// \brief The type of the lower bound map.
 		    ///
 		    /// The type of the map that stores the lower bounds on the arcs.
 		    /// It must conform to the \ref concepts::ReadMap "ReadMap" concept.
 		    typedef LM LowerMap;
 		    /// \brief The type of the upper bound (capacity) map.
 		    ///
 		    /// The type of the map that stores the upper bounds (capacities)
 		    /// on the arcs.
 		    /// It must conform to the \ref concepts::ReadMap "ReadMap" concept.
 		    typedef UM UpperMap;
 		    /// \brief The type of supply map.
 		    ///
 		    /// The type of the map that stores the signed supply values of the
 		    /// nodes.
 		    /// It must conform to the \ref concepts::ReadMap "ReadMap" concept.
 		    typedef SM SupplyMap;
 		    /// \brief The type of the flow and supply values.
 		    typedef typename SupplyMap::Value Value;
 		    /// \brief The type of the map that stores the flow values.
 		    ///
 		    /// The type of the map that stores the flow values.
 		    /// It must conform to the \ref concepts::ReadWriteMap "ReadWriteMap"
 		    /// concept.
 		#ifdef DOXYGEN
 		    typedef GR::ArcMap<Value> FlowMap;
 		#else
 		    typedef typename Digraph::template ArcMap<Value> FlowMap;
 		#endif
 		    /// \brief Instantiates a FlowMap.
 		    ///
 		    /// This function instantiates a \ref FlowMap.
 		    /// \param digraph The digraph for which we would like to define
 		    /// the flow map.
 		    static FlowMap* createFlowMap(const Digraph& digraph) {
 		      return new FlowMap(digraph);
+		    }
 		    /// \brief The elevator type used by the algorithm.
 		    ///
 		    /// The elevator type used by the algorithm.
 		    ///
 		    /// \sa Elevator
 		    /// \sa LinkedElevator
 		    /// \sa Elevator, LinkedElevator
 		#ifdef DOXYGEN
 		    typedef lemon::Elevator<GR, GR::Node> Elevator;
 		#else
 		    typedef lemon::Elevator<Digraph, typename Digraph::Node> Elevator;
 		#endif
 		    /// \brief Instantiates an Elevator.
 		    ///
 		    /// This function instantiates an \ref Elevator.
 		    /// \param digraph The digraph for which we would like to define
 		    /// the elevator.
 		    /// \param max_level The maximum level of the elevator.
 		    static Elevator* createElevator(const Digraph& digraph, int max_level) {
 		      return new Elevator(digraph, max_level);
+		    }
 		    /// \brief The tolerance used by the algorithm
 		    ///
 		    /// The tolerance used by the algorithm to handle inexact computation.
 		    typedef lemon::Tolerance<Value> Tolerance;
 		  };
 		  /**
 		     \brief Push-relabel algorithm for the network circulation problem.
 		     \ingroup max_flow
 		     This class implements a push-relabel algorithm for the \e network
 		     \e circulation problem.
 		     It is to find a feasible circulation when lower and upper bounds
 		     are given for the flow values on the arcs and lower bounds are
 		     given for the difference between the outgoing and incoming flow
 		     at the nodes.
 		     The exact formulation of this problem is the following.
 		     Let \f$G=(V,A)\f$ be a digraph, \f$lower: A\rightarrow\mathbf{R}\f$
 		     \f$upper: A\rightarrow\mathbf{R}\cup\{\infty\}\f$ denote the lower and
 		     upper bounds on the arcs, for which \f$lower(uv) \leq upper(uv)\f$
 		     holds for all \f$uv\in A\f$, and \f$sup: V\rightarrow\mathbf{R}\f$
 		     denotes the signed supply values of the nodes.
 		     If \f$sup(u)>0\f$, then \f$u\f$ is a supply node with \f$sup(u)\f$
 		     supply, if \f$sup(u)<0\f$, then \f$u\f$ is a demand node with
 		     \f$-sup(u)\f$ demand.
 		     A feasible circulation is an \f$f: A\rightarrow\mathbf{R}\f$
 		     solution of the following problem.
 		     \f[ \sum_{uv\in A} f(uv) - \sum_{vu\in A} f(vu)
 		     \geq sup(u) \quad \forall u\in V, \f]
 		     \f[ lower(uv) \leq f(uv) \leq upper(uv) \quad \forall uv\in A. \f]
 		     The sum of the supply values, i.e. \f$\sum_{u\in V} sup(u)\f$ must be
 		     zero or negative in order to have a feasible solution (since the sum
 		     of the expressions on the left-hand side of the inequalities is zero).
 		     It means that the total demand must be greater or equal to the total
 		     supply and all the supplies have to be carried out from the supply nodes,
 		     but there could be demands that are not satisfied.
 		     If \f$\sum_{u\in V} sup(u)\f$ is zero, then all the supply/demand
 		     constraints have to be satisfied with equality, i.e. all demands
 		     have to be satisfied and all supplies have to be used.
 		     If you need the opposite inequalities in the supply/demand constraints
 		     (i.e. the total demand is less than the total supply and all the demands
 		     have to be satisfied while there could be supplies that are not used),
 		     then you could easily transform the problem to the above form by reversing
 		     the direction of the arcs and taking the negative of the supply values
 		     (e.g. using \ref ReverseDigraph and \ref NegMap adaptors).
 		     This algorithm either calculates a feasible circulation, or provides
 		     a \ref barrier() "barrier", which prooves that a feasible soultion
 		     cannot exist.
 		     Note that this algorithm also provides a feasible solution for the
 		     \ref min_cost_flow "minimum cost flow problem".
 		     \tparam GR The type of the digraph the algorithm runs on.
 		     \tparam LM The type of the lower bound map. The default
 		     map type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
 		     \tparam UM The type of the upper bound (capacity) map.
 		     The default map type is \c LM.
 		     \tparam SM The type of the supply map. The default map type is
 		     \ref concepts::Digraph::NodeMap "GR::NodeMap<UM::Value>".
 		  */
 		#ifdef DOXYGEN
 		template< typename GR,
 		          typename LM,
 		          typename UM,
 		          typename SM,
 		          typename TR >
 		#else
 		template< typename GR,
 		          typename LM = typename GR::template ArcMap<int>,
 		          typename UM = LM,
 		          typename SM = typename GR::template NodeMap<typename UM::Value>,
 		          typename TR = CirculationDefaultTraits<GR, LM, UM, SM> >
 		#endif
 		  class Circulation {
 		  public:
 		    ///The \ref CirculationDefaultTraits "traits class" of the algorithm.
 		    typedef TR Traits;
 		    ///The type of the digraph the algorithm runs on.
@@ -374,194 +381,194 @@
+		      }
 		      if (_excess) {
 		        delete _excess;
+		      }
+		    }
 		  public:
 		    /// Sets the lower bound map.
 		    /// Sets the lower bound map.
 		    /// \return <tt>(*this)</tt>
 		    Circulation& lowerMap(const LowerMap& map) {
 		      _lo = &map;
 		      return *this;
+		    }
 		    /// Sets the upper bound (capacity) map.
 		    /// Sets the upper bound (capacity) map.
 		    /// \return <tt>(*this)</tt>
 		    Circulation& upperMap(const UpperMap& map) {
 		      _up = &map;
 		      return *this;
+		    }
 		    /// Sets the supply map.
 		    /// Sets the supply map.
 		    /// \return <tt>(*this)</tt>
 		    Circulation& supplyMap(const SupplyMap& map) {
 		      _supply = &map;
 		      return *this;
+		    }
 		    /// \brief Sets the flow map.
 		    ///
 		    /// Sets the flow map.
 		    /// If you don't use this function before calling \ref run() or
 		    /// \ref init(), an instance will be allocated automatically.
 		    /// The destructor deallocates this automatically allocated map,
 		    /// of course.
 		    /// \return <tt>(*this)</tt>
 		    Circulation& flowMap(FlowMap& map) {
 		      if (_local_flow) {
 		        delete _flow;
 		        _local_flow = false;
+		      }
 		      _flow = &map;
 		      return *this;
+		    }
 		    /// \brief Sets the elevator used by algorithm.
 		    ///
 		    /// Sets the elevator used by algorithm.
 		    /// If you don't use this function before calling \ref run() or
 		    /// \ref init(), an instance will be allocated automatically.
 		    /// The destructor deallocates this automatically allocated elevator,
 		    /// of course.
 		    /// \return <tt>(*this)</tt>
 		    Circulation& elevator(Elevator& elevator) {
 		      if (_local_level) {
 		        delete _level;
 		        _local_level = false;
+		      }
 		      _level = &elevator;
 		      return *this;
+		    }
 		    /// \brief Returns a const reference to the elevator.
 		    ///
 		    /// Returns a const reference to the elevator.
 		    ///
 		    /// \pre Either \ref run() or \ref init() must be called before
 		    /// using this function.
 		    const Elevator& elevator() const {
 		      return *_level;
+		    }
 		    /// \brief Sets the tolerance used by algorithm.
 		    ///
 		    /// Sets the tolerance used by algorithm.
 		    Circulation& tolerance(const Tolerance& tolerance) const {
 		      _tol = tolerance;
 		      return *this;
+		    }
 		    /// \brief Returns a const reference to the tolerance.
 		    ///
 		    /// Returns a const reference to the tolerance.
 		    const Tolerance& tolerance() const {
 		      return tolerance;
+		    }
 		    /// \name Execution Control
 		    /// The simplest way to execute the algorithm is to call \ref run().\n
 		    /// If you need more control on the initial solution or the execution,
 		    /// first you have to call one of the \ref init() functions, then
 		    /// If you need better control on the initial solution or the execution,
 		    /// you have to call one of the \ref init() functions first, then
 		    /// the \ref start() function.
 		    ///@{
 		    /// Initializes the internal data structures.
 		    /// Initializes the internal data structures and sets all flow values
 		    /// to the lower bound.
 		    void init()
+		    {
 		      LEMON_DEBUG(checkBoundMaps(),
 		        "Upper bounds must be greater or equal to the lower bounds");
 		      createStructures();
 		      for(NodeIt n(_g);n!=INVALID;++n) {
 		        (*_excess)[n] = (*_supply)[n];
+		      }
 		      for (ArcIt e(_g);e!=INVALID;++e) {
 		        _flow->set(e, (*_lo)[e]);
 		        (*_excess)[_g.target(e)] += (*_flow)[e];
 		        (*_excess)[_g.source(e)] -= (*_flow)[e];
+		      }
 		      // global relabeling tested, but in general case it provides
 		      // worse performance for random digraphs
 		      _level->initStart();
 		      for(NodeIt n(_g);n!=INVALID;++n)
 		        _level->initAddItem(n);
 		      _level->initFinish();
 		      for(NodeIt n(_g);n!=INVALID;++n)
 		        if(_tol.positive((*_excess)[n]))
 		          _level->activate(n);
+		    }
 		    /// Initializes the internal data structures using a greedy approach.
 		    /// Initializes the internal data structures using a greedy approach
 		    /// to construct the initial solution.
 		    void greedyInit()
+		    {
 		      LEMON_DEBUG(checkBoundMaps(),
 		        "Upper bounds must be greater or equal to the lower bounds");
 		      createStructures();
 		      for(NodeIt n(_g);n!=INVALID;++n) {
 		        (*_excess)[n] = (*_supply)[n];
+		      }
 		      for (ArcIt e(_g);e!=INVALID;++e) {
 		        if (!_tol.less(-(*_excess)[_g.target(e)], (*_up)[e])) {
 		          _flow->set(e, (*_up)[e]);
 		          (*_excess)[_g.target(e)] += (*_up)[e];
 		          (*_excess)[_g.source(e)] -= (*_up)[e];
 		        } else if (_tol.less(-(*_excess)[_g.target(e)], (*_lo)[e])) {
 		          _flow->set(e, (*_lo)[e]);
 		          (*_excess)[_g.target(e)] += (*_lo)[e];
 		          (*_excess)[_g.source(e)] -= (*_lo)[e];
 		        } else {
 		          Value fc = -(*_excess)[_g.target(e)];
 		          _flow->set(e, fc);
 		          (*_excess)[_g.target(e)] = 0;
 		          (*_excess)[_g.source(e)] -= fc;
+		        }
+		      }
 		      _level->initStart();
 		      for(NodeIt n(_g);n!=INVALID;++n)
 		        _level->initAddItem(n);
 		      _level->initFinish();
 		      for(NodeIt n(_g);n!=INVALID;++n)
 		        if(_tol.positive((*_excess)[n]))
 		          _level->activate(n);
+		    }
 		    ///Executes the algorithm
 		    ///This function executes the algorithm.
 		    ///
 		    ///\return \c true if a feasible circulation is found.
 		    ///
 		    ///\sa barrier()
 		    ///\sa barrierMap()
 		    bool start()
+		    {
 		      Node act;
 		      Node bact=INVALID;
 		      Node last_activated=INVALID;
 		      while((act=_level->highestActive())!=INVALID) {
 		        int actlevel=(*_level)[act];
 		        int mlevel=_node_num;
 		        Value exc=(*_excess)[act];

lemon/dfs.h

Show inline comments

@@ -318,194 +318,194 @@
 		    ///\param g The digraph the algorithm runs on.
 		    Dfs(const Digraph &g) :
 		      G(&g),
 		      _pred(NULL), local_pred(false),
 		      _dist(NULL), local_dist(false),
 		      _reached(NULL), local_reached(false),
 		      _processed(NULL), local_processed(false)
 		    { }
 		    ///Destructor.
 		    ~Dfs()
+		    {
 		      if(local_pred) delete _pred;
 		      if(local_dist) delete _dist;
 		      if(local_reached) delete _reached;
 		      if(local_processed) delete _processed;
+		    }
 		    ///Sets the map that stores the predecessor arcs.
 		    ///Sets the map that stores the predecessor arcs.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dfs &predMap(PredMap &m)
+		    {
 		      if(local_pred) {
 		        delete _pred;
 		        local_pred=false;
+		      }
 		      _pred = &m;
 		      return *this;
+		    }
 		    ///Sets the map that indicates which nodes are reached.
 		    ///Sets the map that indicates which nodes are reached.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dfs &reachedMap(ReachedMap &m)
+		    {
 		      if(local_reached) {
 		        delete _reached;
 		        local_reached=false;
+		      }
 		      _reached = &m;
 		      return *this;
+		    }
 		    ///Sets the map that indicates which nodes are processed.
 		    ///Sets the map that indicates which nodes are processed.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dfs &processedMap(ProcessedMap &m)
+		    {
 		      if(local_processed) {
 		        delete _processed;
 		        local_processed=false;
+		      }
 		      _processed = &m;
 		      return *this;
+		    }
 		    ///Sets the map that stores the distances of the nodes.
 		    ///Sets the map that stores the distances of the nodes calculated by
 		    ///the algorithm.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dfs &distMap(DistMap &m)
+		    {
 		      if(local_dist) {
 		        delete _dist;
 		        local_dist=false;
+		      }
 		      _dist = &m;
 		      return *this;
+		    }
 		  public:
 		    ///\name Execution Control
 		    ///The simplest way to execute the DFS algorithm is to use one of the
 		    ///member functions called \ref run(Node) "run()".\n
 		    ///If you need more control on the execution, first you have to call
 		    ///\ref init(), then you can add a source node with \ref addSource()
 		    ///If you need better control on the execution, you have to call
 		    ///\ref init() first, then you can add a source node with \ref addSource()
 		    ///and perform the actual computation with \ref start().
 		    ///This procedure can be repeated if there are nodes that have not
 		    ///been reached.
 		    ///@{
 		    ///\brief Initializes the internal data structures.
 		    ///
 		    ///Initializes the internal data structures.
 		    void init()
+		    {
 		      create_maps();
 		      _stack.resize(countNodes(*G));
 		      _stack_head=-1;
 		      for ( NodeIt u(*G) ; u!=INVALID ; ++u ) {
 		        _pred->set(u,INVALID);
 		        _reached->set(u,false);
 		        _processed->set(u,false);
+		      }
+		    }
 		    ///Adds a new source node.
 		    ///Adds a new source node to the set of nodes to be processed.
 		    ///
 		    ///\pre The stack must be empty. Otherwise the algorithm gives
 		    ///wrong results. (One of the outgoing arcs of all the source nodes
 		    ///except for the last one will not be visited and distances will
 		    ///also be wrong.)
 		    void addSource(Node s)
+		    {
 		      LEMON_DEBUG(emptyQueue(), "The stack is not empty.");
 		      if(!(*_reached)[s])
+		        {
 		          _reached->set(s,true);
 		          _pred->set(s,INVALID);
 		          OutArcIt e(*G,s);
 		          if(e!=INVALID) {
 		            _stack[++_stack_head]=e;
 		            _dist->set(s,_stack_head);
+		          }
 		          else {
 		            _processed->set(s,true);
 		            _dist->set(s,0);
+		          }
+		        }
+		    }
 		    ///Processes the next arc.
 		    ///Processes the next arc.
 		    ///
 		    ///\return The processed arc.
 		    ///
 		    ///\pre The stack must not be empty.
 		    Arc processNextArc()
+		    {
 		      Node m;
 		      Arc e=_stack[_stack_head];
 		      if(!(*_reached)[m=G->target(e)]) {
 		        _pred->set(m,e);
 		        _reached->set(m,true);
 		        ++_stack_head;
 		        _stack[_stack_head] = OutArcIt(*G, m);
 		        _dist->set(m,_stack_head);
+		      }
 		      else {
 		        m=G->source(e);
 		        ++_stack[_stack_head];
+		      }
 		      while(_stack_head>=0 && _stack[_stack_head]==INVALID) {
 		        _processed->set(m,true);
 		        --_stack_head;
 		        if(_stack_head>=0) {
 		          m=G->source(_stack[_stack_head]);
 		          ++_stack[_stack_head];
+		        }
+		      }
 		      return e;
+		    }
 		    ///Next arc to be processed.
 		    ///Next arc to be processed.
 		    ///
 		    ///\return The next arc to be processed or \c INVALID if the stack
 		    ///is empty.
 		    OutArcIt nextArc() const
+		    {
 		      return _stack_head>=0?_stack[_stack_head]:INVALID;
+		    }
 		    ///Returns \c false if there are nodes to be processed.
 		    ///Returns \c false if there are nodes to be processed
 		    ///in the queue (stack).
@@ -1276,194 +1276,194 @@
 		  private:
 		    typedef typename Digraph::Node Node;
 		    typedef typename Digraph::NodeIt NodeIt;
 		    typedef typename Digraph::Arc Arc;
 		    typedef typename Digraph::OutArcIt OutArcIt;
 		    //Pointer to the underlying digraph.
 		    const Digraph *_digraph;
 		    //Pointer to the visitor object.
 		    Visitor *_visitor;
 		    //Pointer to the map of reached status of the nodes.
 		    ReachedMap *_reached;
 		    //Indicates if _reached is locally allocated (true) or not.
 		    bool local_reached;
 		    std::vector<typename Digraph::Arc> _stack;
 		    int _stack_head;
 		    //Creates the maps if necessary.
 		    void create_maps() {
 		      if(!_reached) {
 		        local_reached = true;
 		        _reached = Traits::createReachedMap(*_digraph);
+		      }
+		    }
 		  protected:
 		    DfsVisit() {}
 		  public:
 		    typedef DfsVisit Create;
 		    /// \name Named Template Parameters
 		    ///@{
 		    template <class T>
 		    struct SetReachedMapTraits : public Traits {
 		      typedef T ReachedMap;
 		      static ReachedMap *createReachedMap(const Digraph &digraph) {
 		        LEMON_ASSERT(false, "ReachedMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for setting
 		    /// ReachedMap type.
 		    ///
 		    /// \ref named-templ-param "Named parameter" for setting ReachedMap type.
 		    template <class T>
 		    struct SetReachedMap : public DfsVisit< Digraph, Visitor,
 		                                            SetReachedMapTraits<T> > {
 		      typedef DfsVisit< Digraph, Visitor, SetReachedMapTraits<T> > Create;
 		    };
 		    ///@}
 		  public:
 		    /// \brief Constructor.
 		    ///
 		    /// Constructor.
 		    ///
 		    /// \param digraph The digraph the algorithm runs on.
 		    /// \param visitor The visitor object of the algorithm.
 		    DfsVisit(const Digraph& digraph, Visitor& visitor)
 		      : _digraph(&digraph), _visitor(&visitor),
 		        _reached(0), local_reached(false) {}
 		    /// \brief Destructor.
 		    ~DfsVisit() {
 		      if(local_reached) delete _reached;
+		    }
 		    /// \brief Sets the map that indicates which nodes are reached.
 		    ///
 		    /// Sets the map that indicates which nodes are reached.
 		    /// If you don't use this function before calling \ref run(Node) "run()"
 		    /// or \ref init(), an instance will be allocated automatically.
 		    /// The destructor deallocates this automatically allocated map,
 		    /// of course.
 		    /// \return <tt> (*this) </tt>
 		    DfsVisit &reachedMap(ReachedMap &m) {
 		      if(local_reached) {
 		        delete _reached;
 		        local_reached=false;
+		      }
 		      _reached = &m;
 		      return *this;
+		    }
 		  public:
 		    /// \name Execution Control
 		    /// The simplest way to execute the DFS algorithm is to use one of the
 		    /// member functions called \ref run(Node) "run()".\n
 		    /// If you need more control on the execution, first you have to call
 		    /// \ref init(), then you can add a source node with \ref addSource()
 		    /// If you need better control on the execution, you have to call
 		    /// \ref init() first, then you can add a source node with \ref addSource()
 		    /// and perform the actual computation with \ref start().
 		    /// This procedure can be repeated if there are nodes that have not
 		    /// been reached.
 		    /// @{
 		    /// \brief Initializes the internal data structures.
 		    ///
 		    /// Initializes the internal data structures.
 		    void init() {
 		      create_maps();
 		      _stack.resize(countNodes(*_digraph));
 		      _stack_head = -1;
 		      for (NodeIt u(*_digraph) ; u != INVALID ; ++u) {
 		        _reached->set(u, false);
+		      }
+		    }
 		    /// \brief Adds a new source node.
 		    ///
 		    /// Adds a new source node to the set of nodes to be processed.
 		    ///
 		    /// \pre The stack must be empty. Otherwise the algorithm gives
 		    /// wrong results. (One of the outgoing arcs of all the source nodes
 		    /// except for the last one will not be visited and distances will
 		    /// also be wrong.)
 		    void addSource(Node s)
+		    {
 		      LEMON_DEBUG(emptyQueue(), "The stack is not empty.");
 		      if(!(*_reached)[s]) {
 		          _reached->set(s,true);
 		          _visitor->start(s);
 		          _visitor->reach(s);
 		          Arc e;
 		          _digraph->firstOut(e, s);
 		          if (e != INVALID) {
 		            _stack[++_stack_head] = e;
 		          } else {
 		            _visitor->leave(s);
 		            _visitor->stop(s);
+		          }
+		        }
+		    }
 		    /// \brief Processes the next arc.
 		    ///
 		    /// Processes the next arc.
 		    ///
 		    /// \return The processed arc.
 		    ///
 		    /// \pre The stack must not be empty.
 		    Arc processNextArc() {
 		      Arc e = _stack[_stack_head];
 		      Node m = _digraph->target(e);
 		      if(!(*_reached)[m]) {
 		        _visitor->discover(e);
 		        _visitor->reach(m);
 		        _reached->set(m, true);
 		        _digraph->firstOut(_stack[++_stack_head], m);
 		      } else {
 		        _visitor->examine(e);
 		        m = _digraph->source(e);
 		        _digraph->nextOut(_stack[_stack_head]);
+		      }
 		      while (_stack_head>=0 && _stack[_stack_head] == INVALID) {
 		        _visitor->leave(m);
 		        --_stack_head;
 		        if (_stack_head >= 0) {
 		          _visitor->backtrack(_stack[_stack_head]);
 		          m = _digraph->source(_stack[_stack_head]);
 		          _digraph->nextOut(_stack[_stack_head]);
 		        } else {
 		          _visitor->stop(m);
+		        }
+		      }
 		      return e;
+		    }
 		    /// \brief Next arc to be processed.
 		    ///
 		    /// Next arc to be processed.
 		    ///
 		    /// \return The next arc to be processed or INVALID if the stack is
 		    /// empty.
 		    Arc nextArc() const {
 		      return _stack_head >= 0 ? _stack[_stack_head] : INVALID;
+		    }
 		    /// \brief Returns \c false if there are nodes
 		    /// to be processed.
 		    ///
 		    /// Returns \c false if there are nodes
 		    /// to be processed in the queue (stack).
 		    bool emptyQueue() const { return _stack_head < 0; }
 		    /// \brief Returns the number of the nodes to be processed.

lemon/dijkstra.h

Show inline comments

@@ -491,194 +491,194 @@
 		      _length = &m;
 		      return *this;
+		    }
 		    ///Sets the map that stores the predecessor arcs.
 		    ///Sets the map that stores the predecessor arcs.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dijkstra &predMap(PredMap &m)
+		    {
 		      if(local_pred) {
 		        delete _pred;
 		        local_pred=false;
+		      }
 		      _pred = &m;
 		      return *this;
+		    }
 		    ///Sets the map that indicates which nodes are processed.
 		    ///Sets the map that indicates which nodes are processed.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dijkstra &processedMap(ProcessedMap &m)
+		    {
 		      if(local_processed) {
 		        delete _processed;
 		        local_processed=false;
+		      }
 		      _processed = &m;
 		      return *this;
+		    }
 		    ///Sets the map that stores the distances of the nodes.
 		    ///Sets the map that stores the distances of the nodes calculated by the
 		    ///algorithm.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dijkstra &distMap(DistMap &m)
+		    {
 		      if(local_dist) {
 		        delete _dist;
 		        local_dist=false;
+		      }
 		      _dist = &m;
 		      return *this;
+		    }
 		    ///Sets the heap and the cross reference used by algorithm.
 		    ///Sets the heap and the cross reference used by algorithm.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), heap and cross reference instances will be
 		    ///allocated automatically.
 		    ///The destructor deallocates these automatically allocated objects,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dijkstra &heap(Heap& hp, HeapCrossRef &cr)
+		    {
 		      if(local_heap_cross_ref) {
 		        delete _heap_cross_ref;
 		        local_heap_cross_ref=false;
+		      }
 		      _heap_cross_ref = &cr;
 		      if(local_heap) {
 		        delete _heap;
 		        local_heap=false;
+		      }
 		      _heap = &hp;
 		      return *this;
+		    }
 		  private:
 		    void finalizeNodeData(Node v,Value dst)
+		    {
 		      _processed->set(v,true);
 		      _dist->set(v, dst);
+		    }
 		  public:
 		    ///\name Execution Control
 		    ///The simplest way to execute the %Dijkstra algorithm is to use
 		    ///one of the member functions called \ref run(Node) "run()".\n
 		    ///If you need more control on the execution, first you have to call
 		    ///\ref init(), then you can add several source nodes with
 		    ///If you need better control on the execution, you have to call
 		    ///\ref init() first, then you can add several source nodes with
 		    ///\ref addSource(). Finally the actual path computation can be
 		    ///performed with one of the \ref start() functions.
 		    ///@{
 		    ///\brief Initializes the internal data structures.
 		    ///
 		    ///Initializes the internal data structures.
 		    void init()
+		    {
 		      create_maps();
 		      _heap->clear();
 		      for ( NodeIt u(*G) ; u!=INVALID ; ++u ) {
 		        _pred->set(u,INVALID);
 		        _processed->set(u,false);
 		        _heap_cross_ref->set(u,Heap::PRE_HEAP);
+		      }
+		    }
 		    ///Adds a new source node.
 		    ///Adds a new source node to the priority heap.
 		    ///The optional second parameter is the initial distance of the node.
 		    ///
 		    ///The function checks if the node has already been added to the heap and
 		    ///it is pushed to the heap only if either it was not in the heap
 		    ///or the shortest path found till then is shorter than \c dst.
 		    void addSource(Node s,Value dst=OperationTraits::zero())
+		    {
 		      if(_heap->state(s) != Heap::IN_HEAP) {
 		        _heap->push(s,dst);
 		      } else if(OperationTraits::less((*_heap)[s], dst)) {
 		        _heap->set(s,dst);
 		        _pred->set(s,INVALID);
+		      }
+		    }
 		    ///Processes the next node in the priority heap
 		    ///Processes the next node in the priority heap.
 		    ///
 		    ///\return The processed node.
 		    ///
 		    ///\warning The priority heap must not be empty.
 		    Node processNextNode()
+		    {
 		      Node v=_heap->top();
 		      Value oldvalue=_heap->prio();
 		      _heap->pop();
 		      finalizeNodeData(v,oldvalue);
 		      for(OutArcIt e(*G,v); e!=INVALID; ++e) {
 		        Node w=G->target(e);
 		        switch(_heap->state(w)) {
 		        case Heap::PRE_HEAP:
 		          _heap->push(w,OperationTraits::plus(oldvalue, (*_length)[e]));
 		          _pred->set(w,e);
 		          break;
 		        case Heap::IN_HEAP:
+		          {
 		            Value newvalue = OperationTraits::plus(oldvalue, (*_length)[e]);
 		            if ( OperationTraits::less(newvalue, (*_heap)[w]) ) {
 		              _heap->decrease(w, newvalue);
 		              _pred->set(w,e);
+		            }
+		          }
 		          break;
 		        case Heap::POST_HEAP:
 		          break;
+		        }
+		      }
 		      return v;
+		    }
 		    ///The next node to be processed.
 		    ///Returns the next node to be processed or \c INVALID if the
 		    ///priority heap is empty.
 		    Node nextNode() const
+		    {
 		      return !_heap->empty()?_heap->top():INVALID;
+		    }
 		    ///Returns \c false if there are nodes to be processed.
 		    ///Returns \c false if there are nodes to be processed
 		    ///in the priority heap.
 		    bool emptyQueue() const { return _heap->empty(); }
 		    ///Returns the number of the nodes to be processed.
 		    ///Returns the number of the nodes to be processed
 		    ///in the priority heap.
 		    int queueSize() const { return _heap->size(); }
 		    ///Executes the algorithm.

lemon/gomory_hu.h

Show inline comments

@@ -266,293 +266,293 @@
 		      while (sn != tn) {
 			if ((*_order)[sn] < (*_order)[tn]) {
 			  if ((*_weight)[tn] <= value) value = (*_weight)[tn];
 			  tn = (*_pred)[tn];
 			} else {
 			  if ((*_weight)[sn] <= value) value = (*_weight)[sn];
 			  sn = (*_pred)[sn];
+			}
+		      }
 		      return value;
+		    }
 		    /// \brief Return the minimum cut between two nodes
 		    ///
 		    /// This function returns the minimum cut between the nodes \c s and \c t
 		    /// in the \c cutMap parameter by setting the nodes in the component of
 		    /// \c s to \c true and the other nodes to \c false.
 		    ///
 		    /// For higher level interfaces see MinCutNodeIt and MinCutEdgeIt.
 		    ///
 		    /// \param s The base node.
 		    /// \param t The node you want to separate from node \c s.
 		    /// \param cutMap The cut will be returned in this map.
 		    /// It must be a \c bool (or convertible) \ref concepts::ReadWriteMap
 		    /// "ReadWriteMap" on the graph nodes.
 		    ///
 		    /// \return The value of the minimum cut between \c s and \c t.
 		    ///
 		    /// \pre \ref run() must be called before using this function.
 		    template <typename CutMap>
 		    Value minCutMap(const Node& s, ///<
 		                    const Node& t,
 		                    ///<
 		                    CutMap& cutMap
 		                    ///<
 		                    ) const {
 		      Node sn = s, tn = t;
 		      bool s_root=false;
 		      Node rn = INVALID;
 		      Value value = std::numeric_limits<Value>::max();
 		      while (sn != tn) {
 			if ((*_order)[sn] < (*_order)[tn]) {
 			  if ((*_weight)[tn] <= value) {
 			    rn = tn;
 		            s_root = false;
 			    value = (*_weight)[tn];
+			  }
 			  tn = (*_pred)[tn];
 			} else {
 			  if ((*_weight)[sn] <= value) {
 			    rn = sn;
 		            s_root = true;
 			    value = (*_weight)[sn];
+			  }
 			  sn = (*_pred)[sn];
+			}
+		      }
 		      typename Graph::template NodeMap<bool> reached(_graph, false);
 		      reached[_root] = true;
 		      cutMap.set(_root, !s_root);
 		      reached[rn] = true;
 		      cutMap.set(rn, s_root);
 		      std::vector<Node> st;
 		      for (NodeIt n(_graph); n != INVALID; ++n) {
 			st.clear();
 		        Node nn = n;
 			while (!reached[nn]) {
 			  st.push_back(nn);
 			  nn = (*_pred)[nn];
+			}
 			while (!st.empty()) {
 			  cutMap.set(st.back(), cutMap[nn]);
 			  st.pop_back();
+			}
+		      }
 		      return value;
+		    }
 		    ///@}
 		    friend class MinCutNodeIt;
 		    /// Iterate on the nodes of a minimum cut
 		    /// This iterator class lists the nodes of a minimum cut found by
 		    /// GomoryHu. Before using it, you must allocate a GomoryHu class
 		    /// and call its \ref GomoryHu::run() "run()" method.
 		    ///
 		    /// This example counts the nodes in the minimum cut separating \c s from
 		    /// \c t.
 		    /// \code
-		    /// GomoruHu<Graph> gom(g, capacities);
+		    /// GomoryHu<Graph> gom(g, capacities);
 		    /// gom.run();
 		    /// int cnt=0;
-		    /// for(GomoruHu<Graph>::MinCutNodeIt n(gom,s,t); n!=INVALID; ++n) ++cnt;
+		    /// for(GomoryHu<Graph>::MinCutNodeIt n(gom,s,t); n!=INVALID; ++n) ++cnt;
 		    /// \endcode
 		    class MinCutNodeIt
+		    {
 		      bool _side;
 		      typename Graph::NodeIt _node_it;
 		      typename Graph::template NodeMap<bool> _cut;
 		    public:
 		      /// Constructor
 		      /// Constructor.
 		      ///
 		      MinCutNodeIt(GomoryHu const &gomory,
 		                   ///< The GomoryHu class. You must call its
 		                   ///  run() method
 		                   ///  before initializing this iterator.
 		                   const Node& s, ///< The base node.
 		                   const Node& t,
 		                   ///< The node you want to separate from node \c s.
 		                   bool side=true
 		                   ///< If it is \c true (default) then the iterator lists
 		                   ///  the nodes of the component containing \c s,
 		                   ///  otherwise it lists the other component.
 		                   /// \note As the minimum cut is not always unique,
 		                   /// \code
 		                   /// MinCutNodeIt(gomory, s, t, true);
 		                   /// \endcode
 		                   /// and
 		                   /// \code
 		                   /// MinCutNodeIt(gomory, t, s, false);
 		                   /// \endcode
 		                   /// does not necessarily give the same set of nodes.
 		                   /// However it is ensured that
 		                   /// \code
 		                   /// MinCutNodeIt(gomory, s, t, true);
 		                   /// \endcode
 		                   /// and
 		                   /// \code
 		                   /// MinCutNodeIt(gomory, s, t, false);
 		                   /// \endcode
 		                   /// together list each node exactly once.
+		                   )
 		        : _side(side), _cut(gomory._graph)
+		      {
 		        gomory.minCutMap(s,t,_cut);
 		        for(_node_it=typename Graph::NodeIt(gomory._graph);
 		            _node_it!=INVALID && _cut[_node_it]!=_side;
 		            ++_node_it) {}
+		      }
 		      /// Conversion to \c Node
 		      /// Conversion to \c Node.
 		      ///
 		      operator typename Graph::Node() const
+		      {
 		        return _node_it;
+		      }
 		      bool operator==(Invalid) { return _node_it==INVALID; }
 		      bool operator!=(Invalid) { return _node_it!=INVALID; }
 		      /// Next node
 		      /// Next node.
 		      ///
 		      MinCutNodeIt &operator++()
+		      {
 		        for(++_node_it;_node_it!=INVALID&&_cut[_node_it]!=_side;++_node_it) {}
 		        return *this;
+		      }
 		      /// Postfix incrementation
 		      /// Postfix incrementation.
 		      ///
 		      /// \warning This incrementation
 		      /// returns a \c Node, not a \c MinCutNodeIt, as one may
 		      /// expect.
 		      typename Graph::Node operator++(int)
+		      {
 		        typename Graph::Node n=*this;
 		        ++(*this);
 		        return n;
+		      }
 		    };
 		    friend class MinCutEdgeIt;
 		    /// Iterate on the edges of a minimum cut
 		    /// This iterator class lists the edges of a minimum cut found by
 		    /// GomoryHu. Before using it, you must allocate a GomoryHu class
 		    /// and call its \ref GomoryHu::run() "run()" method.
 		    ///
 		    /// This example computes the value of the minimum cut separating \c s from
 		    /// \c t.
 		    /// \code
-		    /// GomoruHu<Graph> gom(g, capacities);
+		    /// GomoryHu<Graph> gom(g, capacities);
 		    /// gom.run();
 		    /// int value=0;
-		    /// for(GomoruHu<Graph>::MinCutEdgeIt e(gom,s,t); e!=INVALID; ++e)
+		    /// for(GomoryHu<Graph>::MinCutEdgeIt e(gom,s,t); e!=INVALID; ++e)
 		    ///   value+=capacities[e];
 		    /// \endcode
 		    /// The result will be the same as the value returned by
 		    /// \ref GomoryHu::minCutValue() "gom.minCutValue(s,t)".
 		    class MinCutEdgeIt
+		    {
 		      bool _side;
 		      const Graph &_graph;
 		      typename Graph::NodeIt _node_it;
 		      typename Graph::OutArcIt _arc_it;
 		      typename Graph::template NodeMap<bool> _cut;
 		      void step()
+		      {
 		        ++_arc_it;
 		        while(_node_it!=INVALID && _arc_it==INVALID)
+		          {
 		            for(++_node_it;_node_it!=INVALID&&!_cut[_node_it];++_node_it) {}
 		            if(_node_it!=INVALID)
 		              _arc_it=typename Graph::OutArcIt(_graph,_node_it);
+		          }
+		      }
 		    public:
 		      /// Constructor
 		      /// Constructor.
 		      ///
 		      MinCutEdgeIt(GomoryHu const &gomory,
 		                   ///< The GomoryHu class. You must call its
 		                   ///  run() method
 		                   ///  before initializing this iterator.
 		                   const Node& s,  ///< The base node.
 		                   const Node& t,
 		                   ///< The node you want to separate from node \c s.
 		                   bool side=true
 		                   ///< If it is \c true (default) then the listed arcs
 		                   ///  will be oriented from the
 		                   ///  nodes of the component containing \c s,
 		                   ///  otherwise they will be oriented in the opposite
 		                   ///  direction.
+		                   )
 		        : _graph(gomory._graph), _cut(_graph)
+		      {
 		        gomory.minCutMap(s,t,_cut);
 		        if(!side)
 		          for(typename Graph::NodeIt n(_graph);n!=INVALID;++n)
 		            _cut[n]=!_cut[n];
 		        for(_node_it=typename Graph::NodeIt(_graph);
 		            _node_it!=INVALID && !_cut[_node_it];
 		            ++_node_it) {}
 		        _arc_it = _node_it!=INVALID ?
 		          typename Graph::OutArcIt(_graph,_node_it) : INVALID;
 		        while(_node_it!=INVALID && _arc_it == INVALID)
+		          {
 		            for(++_node_it; _node_it!=INVALID&&!_cut[_node_it]; ++_node_it) {}
 		            if(_node_it!=INVALID)
 		              _arc_it= typename Graph::OutArcIt(_graph,_node_it);
+		          }
 		        while(_arc_it!=INVALID && _cut[_graph.target(_arc_it)]) step();
+		      }
 		      /// Conversion to \c Arc
 		      /// Conversion to \c Arc.
 		      ///
 		      operator typename Graph::Arc() const
+		      {
 		        return _arc_it;
+		      }
 		      /// Conversion to \c Edge
 		      /// Conversion to \c Edge.
 		      ///
 		      operator typename Graph::Edge() const
+		      {
 		        return _arc_it;
+		      }
 		      bool operator==(Invalid) { return _node_it==INVALID; }
 		      bool operator!=(Invalid) { return _node_it!=INVALID; }
 		      /// Next edge
 		      /// Next edge.
 		      ///
 		      MinCutEdgeIt &operator++()
+		      {
 		        step();
 		        while(_arc_it!=INVALID && _cut[_graph.target(_arc_it)]) step();
 		        return *this;
+		      }
 		      /// Postfix incrementation
 		      /// Postfix incrementation.
 		      ///
 		      /// \warning This incrementation
 		      /// returns an \c Arc, not a \c MinCutEdgeIt, as one may expect.
 		      typename Graph::Arc operator++(int)

lemon/min_cost_arborescence.h

Show inline comments

@@ -395,194 +395,194 @@
 		    /// @{
 		    template <class T>
 		    struct SetArborescenceMapTraits : public Traits {
 		      typedef T ArborescenceMap;
 		      static ArborescenceMap *createArborescenceMap(const Digraph &)
+		      {
 		        LEMON_ASSERT(false, "ArborescenceMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for
 		    /// setting \c ArborescenceMap type
 		    ///
 		    /// \ref named-templ-param "Named parameter" for setting
 		    /// \c ArborescenceMap type.
 		    /// It must conform to the \ref concepts::WriteMap "WriteMap" concept,
 		    /// and its value type must be \c bool (or convertible).
 		    /// Initially it will be set to \c false on each arc,
 		    /// then it will be set on each arborescence arc once.
 		    template <class T>
 		    struct SetArborescenceMap
 		      : public MinCostArborescence<Digraph, CostMap,
 		                                   SetArborescenceMapTraits<T> > {
 		    };
 		    template <class T>
 		    struct SetPredMapTraits : public Traits {
 		      typedef T PredMap;
 		      static PredMap *createPredMap(const Digraph &)
+		      {
 		        LEMON_ASSERT(false, "PredMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for
 		    /// setting \c PredMap type
 		    ///
 		    /// \ref named-templ-param "Named parameter" for setting
 		    /// \c PredMap type.
 		    /// It must meet the \ref concepts::WriteMap "WriteMap" concept,
 		    /// and its value type must be the \c Arc type of the digraph.
 		    template <class T>
 		    struct SetPredMap
 		      : public MinCostArborescence<Digraph, CostMap, SetPredMapTraits<T> > {
 		    };
 		    /// @}
 		    /// \brief Constructor.
 		    ///
 		    /// \param digraph The digraph the algorithm will run on.
 		    /// \param cost The cost map used by the algorithm.
 		    MinCostArborescence(const Digraph& digraph, const CostMap& cost)
 		      : _digraph(&digraph), _cost(&cost), _pred(0), local_pred(false),
 		        _arborescence(0), local_arborescence(false),
 		        _arc_order(0), _node_order(0), _cost_arcs(0),
 		        _heap_cross_ref(0), _heap(0) {}
 		    /// \brief Destructor.
 		    ~MinCostArborescence() {
 		      destroyStructures();
+		    }
 		    /// \brief Sets the arborescence map.
 		    ///
 		    /// Sets the arborescence map.
 		    /// \return <tt>(*this)</tt>
 		    MinCostArborescence& arborescenceMap(ArborescenceMap& m) {
 		      if (local_arborescence) {
 		        delete _arborescence;
+		      }
 		      local_arborescence = false;
 		      _arborescence = &m;
 		      return *this;
+		    }
 		    /// \brief Sets the predecessor map.
 		    ///
 		    /// Sets the predecessor map.
 		    /// \return <tt>(*this)</tt>
 		    MinCostArborescence& predMap(PredMap& m) {
 		      if (local_pred) {
 		        delete _pred;
+		      }
 		      local_pred = false;
 		      _pred = &m;
 		      return *this;
+		    }
 		    /// \name Execution Control
 		    /// The simplest way to execute the algorithm is to use
 		    /// one of the member functions called \c run(...). \n
 		    /// If you need more control on the execution,
 		    /// first you must call \ref init(), then you can add several
 		    /// If you need better control on the execution,
 		    /// you have to call \ref init() first, then you can add several
 		    /// source nodes with \ref addSource().
 		    /// Finally \ref start() will perform the arborescence
 		    /// computation.
 		    ///@{
 		    /// \brief Initializes the internal data structures.
 		    ///
 		    /// Initializes the internal data structures.
 		    ///
 		    void init() {
 		      createStructures();
 		      _heap->clear();
 		      for (NodeIt it(*_digraph); it != INVALID; ++it) {
 		        (*_cost_arcs)[it].arc = INVALID;
 		        (*_node_order)[it] = -3;
 		        (*_heap_cross_ref)[it] = Heap::PRE_HEAP;
 		        _pred->set(it, INVALID);
+		      }
 		      for (ArcIt it(*_digraph); it != INVALID; ++it) {
 		        _arborescence->set(it, false);
 		        (*_arc_order)[it] = -1;
+		      }
 		      _dual_node_list.clear();
 		      _dual_variables.clear();
+		    }
 		    /// \brief Adds a new source node.
 		    ///
 		    /// Adds a new source node to the algorithm.
 		    void addSource(Node source) {
 		      std::vector<Node> nodes;
 		      nodes.push_back(source);
 		      while (!nodes.empty()) {
 		        Node node = nodes.back();
 		        nodes.pop_back();
 		        for (OutArcIt it(*_digraph, node); it != INVALID; ++it) {
 		          Node target = _digraph->target(it);
 		          if ((*_node_order)[target] == -3) {
 		            (*_node_order)[target] = -2;
 		            nodes.push_back(target);
 		            queue.push_back(target);
+		          }
+		        }
+		      }
 		      (*_node_order)[source] = -1;
+		    }
 		    /// \brief Processes the next node in the priority queue.
 		    ///
 		    /// Processes the next node in the priority queue.
 		    ///
 		    /// \return The processed node.
 		    ///
 		    /// \warning The queue must not be empty.
 		    Node processNextNode() {
 		      Node node = queue.back();
 		      queue.pop_back();
 		      if ((*_node_order)[node] == -2) {
 		        Arc arc = prepare(node);
 		        Node source = _digraph->source(arc);
 		        while ((*_node_order)[source] != -1) {
 		          if ((*_node_order)[source] >= 0) {
 		            arc = contract(source);
 		          } else {
 		            arc = prepare(source);
+		          }
 		          source = _digraph->source(arc);
+		        }
 		        finalize(arc);
 		        level_stack.clear();
+		      }
 		      return node;
+		    }
 		    /// \brief Returns the number of the nodes to be processed.
 		    ///
 		    /// Returns the number of the nodes to be processed in the priority
 		    /// queue.
 		    int queueSize() const {
 		      return queue.size();
+		    }
 		    /// \brief Returns \c false if there are nodes to be processed.
 		    ///
 		    /// Returns \c false if there are nodes to be processed.
 		    bool emptyQueue() const {
 		      return queue.empty();
+		    }
 		    /// \brief Executes the algorithm.
 		    ///
 		    /// Executes the algorithm.
 		    ///
 		    /// \pre init() must be called and at least one node should be added
 		    /// with addSource() before using this function.

lemon/preflow.h

Show inline comments

 		/* -*- mode: C++; indent-tabs-mode: nil; -*-
+		 *
 		 * This file is a part of LEMON, a generic C++ optimization library.
+		 *
 		 * Copyright (C) 2003-2009
 		 * 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_PREFLOW_H
 		#define LEMON_PREFLOW_H
 		#include <lemon/tolerance.h>
 		#include <lemon/elevator.h>
 		/// \file
 		/// \ingroup max_flow
 		/// \brief Implementation of the preflow algorithm.
 		namespace lemon {
 		  /// \brief Default traits class of Preflow class.
 		  ///
 		  /// Default traits class of Preflow class.
 		  /// \tparam GR Digraph type.
 		  /// \tparam CAP Capacity map type.
 		  template <typename GR, typename CAP>
 		  struct PreflowDefaultTraits {
 		    /// \brief The type of the digraph the algorithm runs on.
 		    typedef GR Digraph;
 		    /// \brief The type of the map that stores the arc capacities.
 		    ///
 		    /// The type of the map that stores the arc capacities.
 		    /// It must meet the \ref concepts::ReadMap "ReadMap" concept.
 		    typedef CAP CapacityMap;
 		    /// \brief The type of the flow values.
 		    typedef typename CapacityMap::Value Value;
 		    /// \brief The type of the map that stores the flow values.
 		    ///
 		    /// The type of the map that stores the flow values.
 		    /// It must meet the \ref concepts::ReadWriteMap "ReadWriteMap" concept.
 		#ifdef DOXYGEN
 		    typedef GR::ArcMap<Value> FlowMap;
 		#else
 		    typedef typename Digraph::template ArcMap<Value> FlowMap;
 		#endif
 		    /// \brief Instantiates a FlowMap.
 		    ///
 		    /// This function instantiates a \ref FlowMap.
 		    /// \param digraph The digraph for which we would like to define
 		    /// the flow map.
 		    static FlowMap* createFlowMap(const Digraph& digraph) {
 		      return new FlowMap(digraph);
+		    }
 		    /// \brief The elevator type used by Preflow algorithm.
 		    ///
 		    /// The elevator type used by Preflow algorithm.
 		    ///
 		    /// \sa Elevator
 		    /// \sa LinkedElevator
-		    typedef LinkedElevator<Digraph, typename Digraph::Node> Elevator;
+		    /// \sa Elevator, LinkedElevator
 		#ifdef DOXYGEN
 		    typedef lemon::Elevator<GR, GR::Node> Elevator;
 		#else
 		    typedef lemon::Elevator<Digraph, typename Digraph::Node> Elevator;
 		#endif
 		    /// \brief Instantiates an Elevator.
 		    ///
 		    /// This function instantiates an \ref Elevator.
 		    /// \param digraph The digraph for which we would like to define
 		    /// the elevator.
 		    /// \param max_level The maximum level of the elevator.
 		    static Elevator* createElevator(const Digraph& digraph, int max_level) {
 		      return new Elevator(digraph, max_level);
+		    }
 		    /// \brief The tolerance used by the algorithm
 		    ///
 		    /// The tolerance used by the algorithm to handle inexact computation.
 		    typedef lemon::Tolerance<Value> Tolerance;
 		  };
 		  /// \ingroup max_flow
 		  ///
 		  /// \brief %Preflow algorithm class.
 		  ///
 		  /// This class provides an implementation of Goldberg-Tarjan's \e preflow
 		  /// \e push-relabel algorithm producing a \ref max_flow
 		  /// "flow of maximum value" in a digraph.
 		  /// The preflow algorithms are the fastest known maximum
 		  /// flow algorithms. The current implementation use a mixture of the
 		  /// \e "highest label" and the \e "bound decrease" heuristics.
 		  /// The worst case time complexity of the algorithm is \f$O(n^2\sqrt{e})\f$.
 		  ///
 		  /// The algorithm consists of two phases. After the first phase
 		  /// the maximum flow value and the minimum cut is obtained. The
 		  /// second phase constructs a feasible maximum flow on each arc.
 		  ///
 		  /// \tparam GR The type of the digraph the algorithm runs on.
 		  /// \tparam CAP The type of the capacity map. The default map
 		  /// type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
 		#ifdef DOXYGEN
 		  template <typename GR, typename CAP, typename TR>
 		#else
 		  template <typename GR,
 		            typename CAP = typename GR::template ArcMap<int>,
 		            typename TR = PreflowDefaultTraits<GR, CAP> >
 		#endif
 		  class Preflow {
 		  public:
 		    ///The \ref PreflowDefaultTraits "traits class" of the algorithm.
 		    typedef TR Traits;
 		    ///The type of the digraph the algorithm runs on.
 		    typedef typename Traits::Digraph Digraph;
 		    ///The type of the capacity map.
 		    typedef typename Traits::CapacityMap CapacityMap;
 		    ///The type of the flow values.
 		    typedef typename Traits::Value Value;
 		    ///The type of the flow map.
 		    typedef typename Traits::FlowMap FlowMap;
 		    ///The type of the elevator.
 		    typedef typename Traits::Elevator Elevator;
 		    ///The type of the tolerance.
 		    typedef typename Traits::Tolerance Tolerance;
 		  private:
 		    TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
 		    const Digraph& _graph;
 		    const CapacityMap* _capacity;
 		    int _node_num;
 		    Node _source, _target;
 		    FlowMap* _flow;
 		    bool _local_flow;
 		    Elevator* _level;
 		    bool _local_level;
 		    typedef typename Digraph::template NodeMap<Value> ExcessMap;
 		    ExcessMap* _excess;
 		    Tolerance _tolerance;
 		    bool _phase;
 		    void createStructures() {
 		      _node_num = countNodes(_graph);
 		      if (!_flow) {
 		        _flow = Traits::createFlowMap(_graph);
 		        _local_flow = true;
+		      }
@@ -296,194 +303,194 @@
 		    /// \brief Destructor.
 		    ///
 		    /// Destructor.
 		    ~Preflow() {
 		      destroyStructures();
+		    }
 		    /// \brief Sets the capacity map.
 		    ///
 		    /// Sets the capacity map.
 		    /// \return <tt>(*this)</tt>
 		    Preflow& capacityMap(const CapacityMap& map) {
 		      _capacity = &map;
 		      return *this;
+		    }
 		    /// \brief Sets the flow map.
 		    ///
 		    /// Sets the flow map.
 		    /// If you don't use this function before calling \ref run() or
 		    /// \ref init(), an instance will be allocated automatically.
 		    /// The destructor deallocates this automatically allocated map,
 		    /// of course.
 		    /// \return <tt>(*this)</tt>
 		    Preflow& flowMap(FlowMap& map) {
 		      if (_local_flow) {
 		        delete _flow;
 		        _local_flow = false;
+		      }
 		      _flow = &map;
 		      return *this;
+		    }
 		    /// \brief Sets the source node.
 		    ///
 		    /// Sets the source node.
 		    /// \return <tt>(*this)</tt>
 		    Preflow& source(const Node& node) {
 		      _source = node;
 		      return *this;
+		    }
 		    /// \brief Sets the target node.
 		    ///
 		    /// Sets the target node.
 		    /// \return <tt>(*this)</tt>
 		    Preflow& target(const Node& node) {
 		      _target = node;
 		      return *this;
+		    }
 		    /// \brief Sets the elevator used by algorithm.
 		    ///
 		    /// Sets the elevator used by algorithm.
 		    /// If you don't use this function before calling \ref run() or
 		    /// \ref init(), an instance will be allocated automatically.
 		    /// The destructor deallocates this automatically allocated elevator,
 		    /// of course.
 		    /// \return <tt>(*this)</tt>
 		    Preflow& elevator(Elevator& elevator) {
 		      if (_local_level) {
 		        delete _level;
 		        _local_level = false;
+		      }
 		      _level = &elevator;
 		      return *this;
+		    }
 		    /// \brief Returns a const reference to the elevator.
 		    ///
 		    /// Returns a const reference to the elevator.
 		    ///
 		    /// \pre Either \ref run() or \ref init() must be called before
 		    /// using this function.
 		    const Elevator& elevator() const {
 		      return *_level;
+		    }
 		    /// \brief Sets the tolerance used by algorithm.
 		    ///
 		    /// Sets the tolerance used by algorithm.
 		    Preflow& tolerance(const Tolerance& tolerance) const {
 		      _tolerance = tolerance;
 		      return *this;
+		    }
 		    /// \brief Returns a const reference to the tolerance.
 		    ///
 		    /// Returns a const reference to the tolerance.
 		    const Tolerance& tolerance() const {
 		      return tolerance;
+		    }
 		    /// \name Execution Control
 		    /// The simplest way to execute the preflow algorithm is to use
 		    /// \ref run() or \ref runMinCut().\n
 		    /// If you need more control on the initial solution or the execution,
 		    /// first you have to call one of the \ref init() functions, then
 		    /// If you need better control on the initial solution or the execution,
 		    /// you have to call one of the \ref init() functions first, then
 		    /// \ref startFirstPhase() and if you need it \ref startSecondPhase().
 		    ///@{
 		    /// \brief Initializes the internal data structures.
 		    ///
 		    /// Initializes the internal data structures and sets the initial
 		    /// flow to zero on each arc.
 		    void init() {
 		      createStructures();
 		      _phase = true;
 		      for (NodeIt n(_graph); n != INVALID; ++n) {
 		        (*_excess)[n] = 0;
+		      }
 		      for (ArcIt e(_graph); e != INVALID; ++e) {
 		        _flow->set(e, 0);
+		      }
 		      typename Digraph::template NodeMap<bool> reached(_graph, false);
 		      _level->initStart();
 		      _level->initAddItem(_target);
 		      std::vector<Node> queue;
 		      reached[_source] = true;
 		      queue.push_back(_target);
 		      reached[_target] = true;
 		      while (!queue.empty()) {
 		        _level->initNewLevel();
 		        std::vector<Node> nqueue;
 		        for (int i = 0; i < int(queue.size()); ++i) {
 		          Node n = queue[i];
 		          for (InArcIt e(_graph, n); e != INVALID; ++e) {
 		            Node u = _graph.source(e);
 		            if (!reached[u] && _tolerance.positive((*_capacity)[e])) {
 		              reached[u] = true;
 		              _level->initAddItem(u);
 		              nqueue.push_back(u);
+		            }
+		          }
+		        }
 		        queue.swap(nqueue);
+		      }
 		      _level->initFinish();
 		      for (OutArcIt e(_graph, _source); e != INVALID; ++e) {
 		        if (_tolerance.positive((*_capacity)[e])) {
 		          Node u = _graph.target(e);
 		          if ((*_level)[u] == _level->maxLevel()) continue;
 		          _flow->set(e, (*_capacity)[e]);
 		          (*_excess)[u] += (*_capacity)[e];
 		          if (u != _target && !_level->active(u)) {
 		            _level->activate(u);
+		          }
+		        }
+		      }
+		    }
 		    /// \brief Initializes the internal data structures using the
 		    /// given flow map.
 		    ///
 		    /// Initializes the internal data structures and sets the initial
 		    /// flow to the given \c flowMap. The \c flowMap should contain a
 		    /// flow or at least a preflow, i.e. at each node excluding the
 		    /// source node the incoming flow should greater or equal to the
 		    /// outgoing flow.
 		    /// \return \c false if the given \c flowMap is not a preflow.
 		    template <typename FlowMap>
 		    bool init(const FlowMap& flowMap) {
 		      createStructures();
 		      for (ArcIt e(_graph); e != INVALID; ++e) {
 		        _flow->set(e, flowMap[e]);
+		      }
 		      for (NodeIt n(_graph); n != INVALID; ++n) {
 		        Value excess = 0;
 		        for (InArcIt e(_graph, n); e != INVALID; ++e) {
 		          excess += (*_flow)[e];
+		        }
 		        for (OutArcIt e(_graph, n); e != INVALID; ++e) {
 		          excess -= (*_flow)[e];
+		        }
 		        if (excess < 0 && n != _source) return false;
 		        (*_excess)[n] = excess;
+		      }
 		      typename Digraph::template NodeMap<bool> reached(_graph, false);
 		      _level->initStart();
 		      _level->initAddItem(_target);
 		      std::vector<Node> queue;

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