LEMON/LEMON-official Changeset - r437:6a2a33ad261b

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Changeset - r437:6a2a33ad261b

« 434:ad483a

438:0f2091 »

r437:6a2a33ad261b

Fri, 05 Dec 2008 00:22:47

[Not Reviewed]

0 comments (0 inline)

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

Add missing 'const' for query functions of algorithms

0 4 0

default

4 files changed with 10 insertions and 10 deletions:

lemon/bfs.h

lemon/circulation.h

lemon/dfs.h

lemon/preflow.h

↑ Collapse diff ↑

lemon/bfs.h

Show inline comments

@@ -1232,521 +1232,521 @@
 		    void start(const Node&) {}
 		    void reach(const Node&) {}
 		    void process(const Node&) {}
 		    void discover(const Arc&) {}
 		    void examine(const Arc&) {}
 		    template <typename _Visitor>
 		    struct Constraints {
 		      void constraints() {
 		        Arc arc;
 		        Node node;
 		        visitor.start(node);
 		        visitor.reach(node);
 		        visitor.process(node);
 		        visitor.discover(arc);
 		        visitor.examine(arc);
+		      }
 		      _Visitor& visitor;
 		    };
 		  };
 		#endif
 		  /// \brief Default traits class of BfsVisit class.
 		  ///
 		  /// Default traits class of BfsVisit class.
 		  /// \tparam _Digraph The type of the digraph the algorithm runs on.
 		  template<class _Digraph>
 		  struct BfsVisitDefaultTraits {
 		    /// \brief The type of the digraph the algorithm runs on.
 		    typedef _Digraph Digraph;
 		    /// \brief The type of the map that indicates which nodes are reached.
 		    ///
 		    /// The type of the map that indicates which nodes are reached.
 		    /// It must meet the \ref concepts::ReadWriteMap "ReadWriteMap" concept.
 		    typedef typename Digraph::template NodeMap<bool> ReachedMap;
 		    /// \brief Instantiates a ReachedMap.
 		    ///
 		    /// This function instantiates a ReachedMap.
 		    /// \param digraph is the digraph, to which
 		    /// we would like to define the ReachedMap.
 		    static ReachedMap *createReachedMap(const Digraph &digraph) {
 		      return new ReachedMap(digraph);
+		    }
 		  };
 		  /// \ingroup search
 		  ///
 		  /// \brief %BFS algorithm class with visitor interface.
 		  ///
 		  /// This class provides an efficient implementation of the %BFS algorithm
 		  /// with visitor interface.
 		  ///
 		  /// The %BfsVisit class provides an alternative interface to the Bfs
 		  /// class. It works with callback mechanism, the BfsVisit object calls
 		  /// the member functions of the \c Visitor class on every BFS event.
 		  ///
 		  /// This interface of the BFS algorithm should be used in special cases
 		  /// when extra actions have to be performed in connection with certain
 		  /// events of the BFS algorithm. Otherwise consider to use Bfs or bfs()
 		  /// instead.
 		  ///
 		  /// \tparam _Digraph The type of the digraph the algorithm runs on.
 		  /// The default value is
 		  /// \ref ListDigraph. The value of _Digraph is not used directly by
 		  /// \ref BfsVisit, it is only passed to \ref BfsVisitDefaultTraits.
 		  /// \tparam _Visitor The Visitor type that is used by the algorithm.
 		  /// \ref BfsVisitor "BfsVisitor<_Digraph>" is an empty visitor, which
 		  /// does not observe the BFS events. If you want to observe the BFS
 		  /// events, you should implement your own visitor class.
 		  /// \tparam _Traits Traits class to set various data types used by the
 		  /// algorithm. The default traits class is
 		  /// \ref BfsVisitDefaultTraits "BfsVisitDefaultTraits<_Digraph>".
 		  /// See \ref BfsVisitDefaultTraits for the documentation of
 		  /// a BFS visit traits class.
 		#ifdef DOXYGEN
 		  template <typename _Digraph, typename _Visitor, typename _Traits>
 		#else
 		  template <typename _Digraph = ListDigraph,
 		            typename _Visitor = BfsVisitor<_Digraph>,
 		            typename _Traits = BfsVisitDefaultTraits<_Digraph> >
 		#endif
 		  class BfsVisit {
 		  public:
 		    ///The traits class.
 		    typedef _Traits Traits;
 		    ///The type of the digraph the algorithm runs on.
 		    typedef typename Traits::Digraph Digraph;
 		    ///The visitor type used by the algorithm.
 		    typedef _Visitor Visitor;
 		    ///The type of the map that indicates which nodes are reached.
 		    typedef typename Traits::ReachedMap ReachedMap;
 		  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
 		    /// \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.
 		    /// It should be initially \c INVALID.
 		    ///
 		    /// \return The processed node.
 		    ///
 		    /// \pre The queue must not be empty.
 		    template <typename NM>
 		    Node processNextNode(const NM& nm, Node& rnode) {
 		      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;
 		          if (nm[m] && rnode == INVALID) rnode = m;
 		        } else {
 		          _visitor->examine(e);
+		        }
+		      }
 		      return n;
+		    }
 		    /// \brief The next node to be processed.
 		    ///
 		    /// Returns the next node to be processed or \c INVALID if the queue
 		    /// is empty.
 		    Node nextNode() const {
 		      return _list_front != _list_back ? _list[_list_front + 1] : 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.
 		    bool emptyQueue() const { return _list_front == _list_back; }
 		    /// \brief Returns the number of the nodes to be processed.
 		    ///
 		    /// Returns the number of the nodes to be processed in the queue.
 		    int queueSize() const { return _list_back - _list_front; }
 		    /// \brief Executes the algorithm.
 		    ///
 		    /// Executes the algorithm.
 		    ///
 		    /// This method runs the %BFS algorithm from the root node(s)
 		    /// in order to compute the shortest path to each node.
 		    ///
 		    /// The algorithm computes
 		    /// - the shortest path tree (forest),
 		    /// - the distance of each node from the root(s).
 		    ///
 		    /// \pre init() must be called and at least one root node should be added
 		    /// with addSource() before using this function.
 		    ///
 		    /// \note <tt>b.start()</tt> is just a shortcut of the following code.
 		    /// \code
 		    ///   while ( !b.emptyQueue() ) {
 		    ///     b.processNextNode();
 		    ///   }
 		    /// \endcode
 		    void start() {
 		      while ( !emptyQueue() ) processNextNode();
+		    }
 		    /// \brief Executes the algorithm until the given target node is reached.
 		    ///
 		    /// Executes the algorithm until the given target node is reached.
 		    ///
 		    /// This method runs the %BFS algorithm from the root node(s)
 		    /// in order to compute the shortest path to \c t.
 		    ///
 		    /// The algorithm computes
 		    /// - the shortest path to \c t,
 		    /// - the distance of \c t from the root(s).
 		    ///
 		    /// \pre init() must be called and at least one root node should be
 		    /// added with addSource() before using this function.
 		    ///
 		    /// \note <tt>b.start(t)</tt> is just a shortcut of the following code.
 		    /// \code
 		    ///   bool reach = false;
 		    ///   while ( !b.emptyQueue() && !reach ) {
 		    ///     b.processNextNode(t, reach);
 		    ///   }
 		    /// \endcode
 		    void start(Node t) {
 		      bool reach = false;
 		      while ( !emptyQueue() && !reach ) processNextNode(t, reach);
+		    }
 		    /// \brief Executes the algorithm until a condition is met.
 		    ///
 		    /// Executes the algorithm until a condition is met.
 		    ///
 		    /// This method runs the %BFS algorithm from the root node(s) in
 		    /// order to compute the shortest path to a node \c v with
 		    /// <tt>nm[v]</tt> true, if such a node can be found.
 		    ///
 		    /// \param nm must be a bool (or convertible) node map. The
 		    /// algorithm will stop when it reaches a node \c v with
 		    /// <tt>nm[v]</tt> true.
 		    ///
 		    /// \return The reached node \c v with <tt>nm[v]</tt> true or
 		    /// \c INVALID if no such node was found.
 		    ///
 		    /// \pre init() must be called and at least one root node should be
 		    /// added with addSource() before using this function.
 		    ///
 		    /// \note <tt>b.start(nm)</tt> is just a shortcut of the following code.
 		    /// \code
 		    ///   Node rnode = INVALID;
 		    ///   while ( !b.emptyQueue() && rnode == INVALID ) {
 		    ///     b.processNextNode(nm, rnode);
 		    ///   }
 		    ///   return rnode;
 		    /// \endcode
 		    template <typename NM>
 		    Node start(const NM &nm) {
 		      Node rnode = INVALID;
 		      while ( !emptyQueue() && rnode == INVALID ) {
 		        processNextNode(nm, rnode);
+		      }
 		      return rnode;
+		    }
 		    /// \brief Runs the algorithm from the given source node.
 		    ///
 		    /// This method runs the %BFS algorithm from node \c s
 		    /// in order to compute the shortest path to each node.
 		    ///
 		    /// The algorithm computes
 		    /// - the shortest path tree,
 		    /// - the distance of each node from the root.
 		    ///
 		    /// \note <tt>b.run(s)</tt> is just a shortcut of the following code.
 		    ///\code
 		    ///   b.init();
 		    ///   b.addSource(s);
 		    ///   b.start();
 		    ///\endcode
 		    void run(Node s) {
 		      init();
 		      addSource(s);
 		      start();
+		    }
 		    /// \brief Finds the shortest path between \c s and \c t.
 		    ///
 		    /// This method runs the %BFS algorithm from node \c s
 		    /// in order to compute the shortest path to node \c t
 		    /// (it stops searching when \c t is processed).
 		    ///
 		    /// \return \c true if \c t is reachable form \c s.
 		    ///
 		    /// \note Apart from the return value, <tt>b.run(s,t)</tt> is just a
 		    /// shortcut of the following code.
 		    ///\code
 		    ///   b.init();
 		    ///   b.addSource(s);
 		    ///   b.start(t);
 		    ///\endcode
 		    bool run(Node s,Node t) {
 		      init();
 		      addSource(s);
 		      start(t);
 		      return reached(t);
+		    }
 		    /// \brief Runs the algorithm to visit all nodes in the digraph.
 		    ///
 		    /// This method runs the %BFS algorithm in order to
 		    /// compute the shortest path to each node.
 		    ///
 		    /// The algorithm computes
 		    /// - the shortest path tree (forest),
 		    /// - the distance of each node from the root(s).
 		    ///
 		    /// \note <tt>b.run(s)</tt> is just a shortcut of the following code.
 		    ///\code
 		    ///  b.init();
 		    ///  for (NodeIt n(gr); n != INVALID; ++n) {
 		    ///    if (!b.reached(n)) {
 		    ///      b.addSource(n);
 		    ///      b.start();
 		    ///    }
 		    ///  }
 		    ///\endcode
 		    void run() {
 		      init();
 		      for (NodeIt it(*_digraph); it != INVALID; ++it) {
 		        if (!reached(it)) {
 		          addSource(it);
 		          start();
+		        }
+		      }
+		    }
 		    ///@}
 		    /// \name Query Functions
 		    /// The results of the BFS algorithm can be obtained using these
 		    /// functions.\n
 		    /// Either \ref run(Node) "run()" or \ref start() should be called
 		    /// before using them.
 		    ///@{
 		    /// \brief Checks if a node is reached from the root(s).
 		    ///
 		    /// Returns \c true if \c v is reached from the root(s).
 		    ///
 		    /// \pre Either \ref run(Node) "run()" or \ref init()
 		    /// must be called before using this function.
 		    bool reached(Node v) { return (*_reached)[v]; }
+		    bool reached(Node v) const { return (*_reached)[v]; }
 		    ///@}
 		  };
 		} //END OF NAMESPACE LEMON
 		#endif

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) 2003-2008
 		 * 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_CIRCULATION_H
 		#define LEMON_CIRCULATION_H
 		#include <lemon/tolerance.h>
 		#include <lemon/elevator.h>
 		///\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 _Diraph Digraph type.
 		  /// \tparam _LCapMap Lower bound capacity map type.
 		  /// \tparam _UCapMap Upper bound capacity map type.
 		  /// \tparam _DeltaMap Delta map type.
 		  template <typename _Diraph, typename _LCapMap,
 		            typename _UCapMap, typename _DeltaMap>
 		  struct CirculationDefaultTraits {
 		    /// \brief The type of the digraph the algorithm runs on.
 		    typedef _Diraph Digraph;
 		    /// \brief The type of the map that stores the circulation lower
 		    /// bound.
 		    ///
 		    /// The type of the map that stores the circulation lower bound.
 		    /// It must meet the \ref concepts::ReadMap "ReadMap" concept.
 		    typedef _LCapMap LCapMap;
 		    /// \brief The type of the map that stores the circulation upper
 		    /// bound.
 		    ///
 		    /// The type of the map that stores the circulation upper bound.
 		    /// It must meet the \ref concepts::ReadMap "ReadMap" concept.
 		    typedef _UCapMap UCapMap;
 		    /// \brief The type of the map that stores the lower bound for
 		    /// the supply of the nodes.
 		    ///
 		    /// The type of the map that stores the lower bound for the supply
 		    /// of the nodes. It must meet the \ref concepts::ReadMap "ReadMap"
 		    /// concept.
 		    typedef _DeltaMap DeltaMap;
 		    /// \brief The type of the flow values.
 		    typedef typename DeltaMap::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.
 		    typedef typename Digraph::template ArcMap<Value> FlowMap;
 		    /// \brief Instantiates a FlowMap.
 		    ///
 		    /// This function instantiates a \ref FlowMap.
 		    /// \param digraph The digraph, to 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
 		    typedef lemon::Elevator<Digraph, typename Digraph::Node> Elevator;
 		    /// \brief Instantiates an Elevator.
 		    ///
 		    /// This function instantiates an \ref Elevator.
 		    /// \param digraph The digraph, to 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 network
 		     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 supply values of the nodes.
 		     The exact formulation of this problem is the following.
 		     Let \f$G=(V,A)\f$ be a digraph,
 		     \f$lower, upper: A\rightarrow\mathbf{R}^+_0\f$,
 		     \f$delta: V\rightarrow\mathbf{R}\f$. Find a feasible circulation
 		     \f$f: A\rightarrow\mathbf{R}^+_0\f$ so that
 		     \f[ \sum_{a\in\delta_{out}(v)} f(a) - \sum_{a\in\delta_{in}(v)} f(a)
 		     \geq delta(v) \quad \forall v\in V, \f]
 		     \f[ lower(a)\leq f(a) \leq upper(a) \quad \forall a\in A. \f]
 		     \note \f$delta(v)\f$ specifies a lower bound for the supply of node
 		     \f$v\f$. It can be either positive or negative, however note that
 		     \f$\sum_{v\in V}delta(v)\f$ should be zero or negative in order to
 		     have a feasible solution.
 		     \note A special case of this problem is when
 		     \f$\sum_{v\in V}delta(v) = 0\f$. Then the supply of each node \f$v\f$
 		     will be \e equal \e to \f$delta(v)\f$, if a circulation can be found.
 		     Thus a feasible solution for the
 		     \ref min_cost_flow "minimum cost flow" problem can be calculated
 		     in this way.
 		     \tparam _Digraph The type of the digraph the algorithm runs on.
 		     \tparam _LCapMap The type of the lower bound capacity map. The default
 		     map type is \ref concepts::Digraph::ArcMap "_Digraph::ArcMap<int>".
 		     \tparam _UCapMap The type of the upper bound capacity map. The default
 		     map type is \c _LCapMap.
 		     \tparam _DeltaMap The type of the map that stores the lower bound
 		     for the supply of the nodes. The default map type is
 		     \c _Digraph::ArcMap<_UCapMap::Value>.
 		  */
 		#ifdef DOXYGEN
 		template< typename _Digraph,
 		          typename _LCapMap,
 		          typename _UCapMap,
 		          typename _DeltaMap,
 		          typename _Traits >
 		#else
 		template< typename _Digraph,
 		          typename _LCapMap = typename _Digraph::template ArcMap<int>,
 		          typename _UCapMap = _LCapMap,
 		          typename _DeltaMap = typename _Digraph::
 		                               template NodeMap<typename _UCapMap::Value>,
 		          typename _Traits=CirculationDefaultTraits<_Digraph, _LCapMap,
 		                                                    _UCapMap, _DeltaMap> >
 		#endif
 		  class Circulation {
 		  public:
 		    ///The \ref CirculationDefaultTraits "traits class" of the algorithm.
 		    typedef _Traits Traits;
 		    ///The type of the digraph the algorithm runs on.
 		    typedef typename Traits::Digraph Digraph;
 		    ///The type of the flow values.
 		    typedef typename Traits::Value Value;
 		    /// The type of the lower bound capacity map.
 		    typedef typename Traits::LCapMap LCapMap;
 		    /// The type of the upper bound capacity map.
 		    typedef typename Traits::UCapMap UCapMap;
 		    /// \brief The type of the map that stores the lower bound for
 		    /// the supply of the nodes.
 		    typedef typename Traits::DeltaMap DeltaMap;
 		    ///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 &_g;
 		    int _node_num;
 		    const LCapMap *_lo;
 		    const UCapMap *_up;
 		    const DeltaMap *_delta;
 		    FlowMap *_flow;
 		    bool _local_flow;
 		    Elevator* _level;
 		    bool _local_level;
 		    typedef typename Digraph::template NodeMap<Value> ExcessMap;
 		    ExcessMap* _excess;
 		    Tolerance _tol;
 		    int _el;
 		  public:
 		    typedef Circulation Create;
 		    ///\name Named Template Parameters
 		    ///@{
 		    template <typename _FlowMap>
 		    struct SetFlowMapTraits : public Traits {
 		      typedef _FlowMap FlowMap;
 		      static FlowMap *createFlowMap(const Digraph&) {
 		        LEMON_ASSERT(false, "FlowMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for setting
 		    /// FlowMap type
 		    ///
 		    /// \ref named-templ-param "Named parameter" for setting FlowMap
 		    /// type.
 		    template <typename _FlowMap>
 		    struct SetFlowMap
 		      : public Circulation<Digraph, LCapMap, UCapMap, DeltaMap,
 		                           SetFlowMapTraits<_FlowMap> > {
 		      typedef Circulation<Digraph, LCapMap, UCapMap, DeltaMap,
 		                          SetFlowMapTraits<_FlowMap> > Create;
 		    };
 		    template <typename _Elevator>
 		    struct SetElevatorTraits : public Traits {
 		      typedef _Elevator Elevator;
 		      static Elevator *createElevator(const Digraph&, int) {
 		        LEMON_ASSERT(false, "Elevator is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for setting
 		    /// Elevator type
 		    ///
 		    /// \ref named-templ-param "Named parameter" for setting Elevator
 		    /// type. If this named parameter is used, then an external
 		    /// elevator object must be passed to the algorithm using the
 		    /// \ref elevator(Elevator&) "elevator()" function before calling
 		    /// \ref run() or \ref init().
 		    /// \sa SetStandardElevator
 		    template <typename _Elevator>
 		    struct SetElevator
 		      : public Circulation<Digraph, LCapMap, UCapMap, DeltaMap,
 		                           SetElevatorTraits<_Elevator> > {
 		      typedef Circulation<Digraph, LCapMap, UCapMap, DeltaMap,
 		                          SetElevatorTraits<_Elevator> > Create;
 		    };
 		    template <typename _Elevator>
 		    struct SetStandardElevatorTraits : public Traits {
 		      typedef _Elevator Elevator;
 		      static Elevator *createElevator(const Digraph& digraph, int max_level) {
 		        return new Elevator(digraph, max_level);
+		      }
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for setting
 		    /// Elevator type with automatic allocation
 		    ///
 		    /// \ref named-templ-param "Named parameter" for setting Elevator
 		    /// type with automatic allocation.
 		    /// The Elevator should have standard constructor interface to be
 		    /// able to automatically created by the algorithm (i.e. the
 		    /// digraph and the maximum level should be passed to it).
 		    /// However an external elevator object could also be passed to the
 		    /// algorithm with the \ref elevator(Elevator&) "elevator()" function
 		    /// before calling \ref run() or \ref init().
 		    /// \sa SetElevator
 		    template <typename _Elevator>
 		    struct SetStandardElevator
 		      : public Circulation<Digraph, LCapMap, UCapMap, DeltaMap,
 		                       SetStandardElevatorTraits<_Elevator> > {
 		      typedef Circulation<Digraph, LCapMap, UCapMap, DeltaMap,
 		                      SetStandardElevatorTraits<_Elevator> > Create;
 		    };
 		    /// @}
 		  protected:
 		    Circulation() {}
 		  public:
 		    /// The constructor of the class.
 		    /// The constructor of the class.
 		    /// \param g The digraph the algorithm runs on.
 		    /// \param lo The lower bound capacity of the arcs.
 		    /// \param up The upper bound capacity of the arcs.
 		    /// \param delta The lower bound for the supply of the nodes.
 		    Circulation(const Digraph &g,const LCapMap &lo,
 		                const UCapMap &up,const DeltaMap &delta)
 		      : _g(g), _node_num(),
 		        _lo(&lo),_up(&up),_delta(&delta),_flow(0),_local_flow(false),
 		        _level(0), _local_level(false), _excess(0), _el() {}
 		    /// Destructor.
 		    ~Circulation() {
 		      destroyStructures();
+		    }
 		  private:
 		    void createStructures() {
 		      _node_num = _el = countNodes(_g);
 		      if (!_flow) {
 		        _flow = Traits::createFlowMap(_g);
 		        _local_flow = true;
+		      }
 		      if (!_level) {
 		        _level = Traits::createElevator(_g, _node_num);
 		        _local_level = true;
+		      }
 		      if (!_excess) {
 		        _excess = new ExcessMap(_g);
+		      }
+		    }
 		    void destroyStructures() {
 		      if (_local_flow) {
 		        delete _flow;
+		      }
 		      if (_local_level) {
 		        delete _level;
+		      }
 		      if (_excess) {
 		        delete _excess;
+		      }
+		    }
 		  public:
 		    /// Sets the lower bound capacity map.
 		    /// Sets the lower bound capacity map.
 		    /// \return <tt>(*this)</tt>
 		    Circulation& lowerCapMap(const LCapMap& map) {
 		      _lo = &map;
 		      return *this;
+		    }
 		    /// Sets the upper bound capacity map.
 		    /// Sets the upper bound capacity map.
 		    /// \return <tt>(*this)</tt>
 		    Circulation& upperCapMap(const LCapMap& map) {
 		      _up = &map;
 		      return *this;
+		    }
 		    /// Sets the lower bound map for the supply of the nodes.
 		    /// Sets the lower bound map for the supply of the nodes.
 		    /// \return <tt>(*this)</tt>
 		    Circulation& deltaMap(const DeltaMap& map) {
 		      _delta = &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 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
 		    /// 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()
+		    {
 		      createStructures();
 		      for(NodeIt n(_g);n!=INVALID;++n) {
 		        _excess->set(n, (*_delta)[n]);
+		      }
 		      for (ArcIt e(_g);e!=INVALID;++e) {
 		        _flow->set(e, (*_lo)[e]);
 		        _excess->set(_g.target(e), (*_excess)[_g.target(e)] + (*_flow)[e]);
 		        _excess->set(_g.source(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()
+		    {
 		      createStructures();
 		      for(NodeIt n(_g);n!=INVALID;++n) {
 		        _excess->set(n, (*_delta)[n]);
+		      }
 		      for (ArcIt e(_g);e!=INVALID;++e) {
 		        if (!_tol.positive((*_excess)[_g.target(e)] + (*_up)[e])) {
 		          _flow->set(e, (*_up)[e]);
 		          _excess->set(_g.target(e), (*_excess)[_g.target(e)] + (*_up)[e]);
 		          _excess->set(_g.source(e), (*_excess)[_g.source(e)] - (*_up)[e]);
 		        } else if (_tol.positive((*_excess)[_g.target(e)] + (*_lo)[e])) {
 		          _flow->set(e, (*_lo)[e]);
 		          _excess->set(_g.target(e), (*_excess)[_g.target(e)] + (*_lo)[e]);
 		          _excess->set(_g.source(e), (*_excess)[_g.source(e)] - (*_lo)[e]);
 		        } else {
 		          Value fc = -(*_excess)[_g.target(e)];
 		          _flow->set(e, fc);
 		          _excess->set(_g.target(e), 0);
 		          _excess->set(_g.source(e), (*_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];
 		        for(OutArcIt e(_g,act);e!=INVALID; ++e) {
 		          Node v = _g.target(e);
 		          Value fc=(*_up)[e]-(*_flow)[e];
 		          if(!_tol.positive(fc)) continue;
 		          if((*_level)[v]<actlevel) {
 		            if(!_tol.less(fc, exc)) {
 		              _flow->set(e, (*_flow)[e] + exc);
 		              _excess->set(v, (*_excess)[v] + exc);
 		              if(!_level->active(v) && _tol.positive((*_excess)[v]))
 		                _level->activate(v);
 		              _excess->set(act,0);
 		              _level->deactivate(act);
 		              goto next_l;
+		            }
 		            else {
 		              _flow->set(e, (*_up)[e]);
 		              _excess->set(v, (*_excess)[v] + fc);
 		              if(!_level->active(v) && _tol.positive((*_excess)[v]))
 		                _level->activate(v);
 		              exc-=fc;
+		            }
+		          }
 		          else if((*_level)[v]<mlevel) mlevel=(*_level)[v];
+		        }
 		        for(InArcIt e(_g,act);e!=INVALID; ++e) {
 		          Node v = _g.source(e);
 		          Value fc=(*_flow)[e]-(*_lo)[e];
 		          if(!_tol.positive(fc)) continue;
 		          if((*_level)[v]<actlevel) {
 		            if(!_tol.less(fc, exc)) {
 		              _flow->set(e, (*_flow)[e] - exc);
 		              _excess->set(v, (*_excess)[v] + exc);
 		              if(!_level->active(v) && _tol.positive((*_excess)[v]))
 		                _level->activate(v);
 		              _excess->set(act,0);
 		              _level->deactivate(act);
 		              goto next_l;
+		            }
 		            else {
 		              _flow->set(e, (*_lo)[e]);
 		              _excess->set(v, (*_excess)[v] + fc);
 		              if(!_level->active(v) && _tol.positive((*_excess)[v]))
 		                _level->activate(v);
 		              exc-=fc;
+		            }
+		          }
 		          else if((*_level)[v]<mlevel) mlevel=(*_level)[v];
+		        }
 		        _excess->set(act, exc);
 		        if(!_tol.positive(exc)) _level->deactivate(act);
 		        else if(mlevel==_node_num) {
 		          _level->liftHighestActiveToTop();
 		          _el = _node_num;
 		          return false;
+		        }
 		        else {
 		          _level->liftHighestActive(mlevel+1);
 		          if(_level->onLevel(actlevel)==0) {
 		            _el = actlevel;
 		            return false;
+		          }
+		        }
 		      next_l:
+		        ;
+		      }
 		      return true;
+		    }
 		    /// Runs the algorithm.
 		    /// This function runs the algorithm.
 		    ///
 		    /// \return \c true if a feasible circulation is found.
 		    ///
 		    /// \note Apart from the return value, c.run() is just a shortcut of
 		    /// the following code.
 		    /// \code
 		    ///   c.greedyInit();
 		    ///   c.start();
 		    /// \endcode
 		    bool run() {
 		      greedyInit();
 		      return start();
+		    }
 		    /// @}
 		    /// \name Query Functions
 		    /// The results of the circulation algorithm can be obtained using
 		    /// these functions.\n
 		    /// Either \ref run() or \ref start() should be called before
 		    /// using them.
 		    ///@{
 		    /// \brief Returns the flow on the given arc.
 		    ///
 		    /// Returns the flow on the given arc.
 		    ///
 		    /// \pre Either \ref run() or \ref init() must be called before
 		    /// using this function.
 		    Value flow(const Arc& arc) const {
 		      return (*_flow)[arc];
+		    }
 		    /// \brief Returns a const reference to the flow map.
 		    ///
 		    /// Returns a const reference to the arc map storing the found flow.
 		    ///
 		    /// \pre Either \ref run() or \ref init() must be called before
 		    /// using this function.
 		    const FlowMap& flowMap() {
+		    const FlowMap& flowMap() const {
 		      return *_flow;
+		    }
 		    /**
 		       \brief Returns \c true if the given node is in a barrier.
 		       Barrier is a set \e B of nodes for which
 		       \f[ \sum_{a\in\delta_{out}(B)} upper(a) -
 		           \sum_{a\in\delta_{in}(B)} lower(a) < \sum_{v\in B}delta(v) \f]
 		       holds. The existence of a set with this property prooves that a
 		       feasible circualtion cannot exist.
 		       This function returns \c true if the given node is in the found
 		       barrier. If a feasible circulation is found, the function
 		       gives back \c false for every node.
 		       \pre Either \ref run() or \ref init() must be called before
 		       using this function.
 		       \sa barrierMap()
 		       \sa checkBarrier()
 		    */
 		    bool barrier(const Node& node)
+		    bool barrier(const Node& node) const
+		    {
 		      return (*_level)[node] >= _el;
+		    }
 		    /// \brief Gives back a barrier.
 		    ///
 		    /// This function sets \c bar to the characteristic vector of the
 		    /// found barrier. \c bar should be a \ref concepts::WriteMap "writable"
 		    /// node map with \c bool (or convertible) value type.
 		    ///
 		    /// If a feasible circulation is found, the function gives back an
 		    /// empty set, so \c bar[v] will be \c false for all nodes \c v.
 		    ///
 		    /// \note This function calls \ref barrier() for each node,
 		    /// so it runs in \f$O(n)\f$ time.
 		    ///
 		    /// \pre Either \ref run() or \ref init() must be called before
 		    /// using this function.
 		    ///
 		    /// \sa barrier()
 		    /// \sa checkBarrier()
 		    template<class BarrierMap>
 		    void barrierMap(BarrierMap &bar)
+		    void barrierMap(BarrierMap &bar) const
+		    {
 		      for(NodeIt n(_g);n!=INVALID;++n)
 		        bar.set(n, (*_level)[n] >= _el);
+		    }
 		    /// @}
 		    /// \name Checker Functions
 		    /// The feasibility of the results can be checked using
 		    /// these functions.\n
 		    /// Either \ref run() or \ref start() should be called before
 		    /// using them.
 		    ///@{
 		    ///Check if the found flow is a feasible circulation
 		    ///Check if the found flow is a feasible circulation,
 		    ///
 		    bool checkFlow() {
+		    bool checkFlow() const {
 		      for(ArcIt e(_g);e!=INVALID;++e)
 		        if((*_flow)[e]<(*_lo)[e]||(*_flow)[e]>(*_up)[e]) return false;
 		      for(NodeIt n(_g);n!=INVALID;++n)
+		        {
 		          Value dif=-(*_delta)[n];
 		          for(InArcIt e(_g,n);e!=INVALID;++e) dif-=(*_flow)[e];
 		          for(OutArcIt e(_g,n);e!=INVALID;++e) dif+=(*_flow)[e];
 		          if(_tol.negative(dif)) return false;
+		        }
 		      return true;
+		    }
 		    ///Check whether or not the last execution provides a barrier
 		    ///Check whether or not the last execution provides a barrier.
 		    ///\sa barrier()
 		    ///\sa barrierMap()
 		    bool checkBarrier()
+		    bool checkBarrier() const
+		    {
 		      Value delta=0;
 		      for(NodeIt n(_g);n!=INVALID;++n)
 		        if(barrier(n))
 		          delta-=(*_delta)[n];
 		      for(ArcIt e(_g);e!=INVALID;++e)
+		        {
 		          Node s=_g.source(e);
 		          Node t=_g.target(e);
 		          if(barrier(s)&&!barrier(t)) delta+=(*_up)[e];
 		          else if(barrier(t)&&!barrier(s)) delta-=(*_lo)[e];
+		        }
 		      return _tol.negative(delta);
+		    }
 		    /// @}
 		  };
+		}
 		#endif

lemon/dfs.h

Show inline comments

@@ -1116,521 +1116,521 @@
 		  ///\sa Dfs
 		  template<class GR>
 		  DfsWizard<DfsWizardBase<GR> >
 		  dfs(const GR &digraph)
+		  {
 		    return DfsWizard<DfsWizardBase<GR> >(digraph);
+		  }
 		#ifdef DOXYGEN
 		  /// \brief Visitor class for DFS.
 		  ///
 		  /// This class defines the interface of the DfsVisit events, and
 		  /// it could be the base of a real visitor class.
 		  template <typename _Digraph>
 		  struct DfsVisitor {
 		    typedef _Digraph Digraph;
 		    typedef typename Digraph::Arc Arc;
 		    typedef typename Digraph::Node Node;
 		    /// \brief Called for the source node of the DFS.
 		    ///
 		    /// This function is called for the source node of the DFS.
 		    void start(const Node& node) {}
 		    /// \brief Called when the source node is leaved.
 		    ///
 		    /// This function is called when the source node is leaved.
 		    void stop(const Node& node) {}
 		    /// \brief Called when a node is reached first time.
 		    ///
 		    /// This function is called when a node is reached first time.
 		    void reach(const Node& node) {}
 		    /// \brief Called when an arc reaches a new node.
 		    ///
 		    /// This function is called when the DFS finds an arc whose target node
 		    /// is not reached yet.
 		    void discover(const Arc& arc) {}
 		    /// \brief Called when an arc is examined but its target node is
 		    /// already discovered.
 		    ///
 		    /// This function is called when an arc is examined but its target node is
 		    /// already discovered.
 		    void examine(const Arc& arc) {}
 		    /// \brief Called when the DFS steps back from a node.
 		    ///
 		    /// This function is called when the DFS steps back from a node.
 		    void leave(const Node& node) {}
 		    /// \brief Called when the DFS steps back on an arc.
 		    ///
 		    /// This function is called when the DFS steps back on an arc.
 		    void backtrack(const Arc& arc) {}
 		  };
 		#else
 		  template <typename _Digraph>
 		  struct DfsVisitor {
 		    typedef _Digraph Digraph;
 		    typedef typename Digraph::Arc Arc;
 		    typedef typename Digraph::Node Node;
 		    void start(const Node&) {}
 		    void stop(const Node&) {}
 		    void reach(const Node&) {}
 		    void discover(const Arc&) {}
 		    void examine(const Arc&) {}
 		    void leave(const Node&) {}
 		    void backtrack(const Arc&) {}
 		    template <typename _Visitor>
 		    struct Constraints {
 		      void constraints() {
 		        Arc arc;
 		        Node node;
 		        visitor.start(node);
 		        visitor.stop(arc);
 		        visitor.reach(node);
 		        visitor.discover(arc);
 		        visitor.examine(arc);
 		        visitor.leave(node);
 		        visitor.backtrack(arc);
+		      }
 		      _Visitor& visitor;
 		    };
 		  };
 		#endif
 		  /// \brief Default traits class of DfsVisit class.
 		  ///
 		  /// Default traits class of DfsVisit class.
 		  /// \tparam _Digraph The type of the digraph the algorithm runs on.
 		  template<class _Digraph>
 		  struct DfsVisitDefaultTraits {
 		    /// \brief The type of the digraph the algorithm runs on.
 		    typedef _Digraph Digraph;
 		    /// \brief The type of the map that indicates which nodes are reached.
 		    ///
 		    /// The type of the map that indicates which nodes are reached.
 		    /// It must meet the \ref concepts::ReadWriteMap "ReadWriteMap" concept.
 		    typedef typename Digraph::template NodeMap<bool> ReachedMap;
 		    /// \brief Instantiates a ReachedMap.
 		    ///
 		    /// This function instantiates a ReachedMap.
 		    /// \param digraph is the digraph, to which
 		    /// we would like to define the ReachedMap.
 		    static ReachedMap *createReachedMap(const Digraph &digraph) {
 		      return new ReachedMap(digraph);
+		    }
 		  };
 		  /// \ingroup search
 		  ///
 		  /// \brief %DFS algorithm class with visitor interface.
 		  ///
 		  /// This class provides an efficient implementation of the %DFS algorithm
 		  /// with visitor interface.
 		  ///
 		  /// The %DfsVisit class provides an alternative interface to the Dfs
 		  /// class. It works with callback mechanism, the DfsVisit object calls
 		  /// the member functions of the \c Visitor class on every DFS event.
 		  ///
 		  /// This interface of the DFS algorithm should be used in special cases
 		  /// when extra actions have to be performed in connection with certain
 		  /// events of the DFS algorithm. Otherwise consider to use Dfs or dfs()
 		  /// instead.
 		  ///
 		  /// \tparam _Digraph The type of the digraph the algorithm runs on.
 		  /// The default value is
 		  /// \ref ListDigraph. The value of _Digraph is not used directly by
 		  /// \ref DfsVisit, it is only passed to \ref DfsVisitDefaultTraits.
 		  /// \tparam _Visitor The Visitor type that is used by the algorithm.
 		  /// \ref DfsVisitor "DfsVisitor<_Digraph>" is an empty visitor, which
 		  /// does not observe the DFS events. If you want to observe the DFS
 		  /// events, you should implement your own visitor class.
 		  /// \tparam _Traits Traits class to set various data types used by the
 		  /// algorithm. The default traits class is
 		  /// \ref DfsVisitDefaultTraits "DfsVisitDefaultTraits<_Digraph>".
 		  /// See \ref DfsVisitDefaultTraits for the documentation of
 		  /// a DFS visit traits class.
 		#ifdef DOXYGEN
 		  template <typename _Digraph, typename _Visitor, typename _Traits>
 		#else
 		  template <typename _Digraph = ListDigraph,
 		            typename _Visitor = DfsVisitor<_Digraph>,
 		            typename _Traits = DfsVisitDefaultTraits<_Digraph> >
 		#endif
 		  class DfsVisit {
 		  public:
 		    ///The traits class.
 		    typedef _Traits Traits;
 		    ///The type of the digraph the algorithm runs on.
 		    typedef typename Traits::Digraph Digraph;
 		    ///The visitor type used by the algorithm.
 		    typedef _Visitor Visitor;
 		    ///The type of the map that indicates which nodes are reached.
 		    typedef typename Traits::ReachedMap ReachedMap;
 		  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()
 		    /// 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);
+		          }
+		        }
+		    }
 		    /// \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.
 		    ///
 		    /// Returns the number of the nodes to be processed in the queue (stack).
 		    int queueSize() const { return _stack_head + 1; }
 		    /// \brief Executes the algorithm.
 		    ///
 		    /// Executes the algorithm.
 		    ///
 		    /// This method runs the %DFS algorithm from the root node
 		    /// in order to compute the %DFS path to each node.
 		    ///
 		    /// The algorithm computes
 		    /// - the %DFS tree,
 		    /// - the distance of each node from the root in the %DFS tree.
 		    ///
 		    /// \pre init() must be called and a root node should be
 		    /// added with addSource() before using this function.
 		    ///
 		    /// \note <tt>d.start()</tt> is just a shortcut of the following code.
 		    /// \code
 		    ///   while ( !d.emptyQueue() ) {
 		    ///     d.processNextArc();
 		    ///   }
 		    /// \endcode
 		    void start() {
 		      while ( !emptyQueue() ) processNextArc();
+		    }
 		    /// \brief Executes the algorithm until the given target node is reached.
 		    ///
 		    /// Executes the algorithm until the given target node is reached.
 		    ///
 		    /// This method runs the %DFS algorithm from the root node
 		    /// in order to compute the DFS path to \c t.
 		    ///
 		    /// The algorithm computes
 		    /// - the %DFS path to \c t,
 		    /// - the distance of \c t from the root in the %DFS tree.
 		    ///
 		    /// \pre init() must be called and a root node should be added
 		    /// with addSource() before using this function.
 		    void start(Node t) {
 		      while ( !emptyQueue() && _digraph->target(_stack[_stack_head]) != t )
 		        processNextArc();
+		    }
 		    /// \brief Executes the algorithm until a condition is met.
 		    ///
 		    /// Executes the algorithm until a condition is met.
 		    ///
 		    /// This method runs the %DFS algorithm from the root node
 		    /// until an arc \c a with <tt>am[a]</tt> true is found.
 		    ///
 		    /// \param am A \c bool (or convertible) arc map. The algorithm
 		    /// will stop when it reaches an arc \c a with <tt>am[a]</tt> true.
 		    ///
 		    /// \return The reached arc \c a with <tt>am[a]</tt> true or
 		    /// \c INVALID if no such arc was found.
 		    ///
 		    /// \pre init() must be called and a root node should be added
 		    /// with addSource() before using this function.
 		    ///
 		    /// \warning Contrary to \ref Bfs and \ref Dijkstra, \c am is an arc map,
 		    /// not a node map.
 		    template <typename AM>
 		    Arc start(const AM &am) {
 		      while ( !emptyQueue() && !am[_stack[_stack_head]] )
 		        processNextArc();
 		      return emptyQueue() ? INVALID : _stack[_stack_head];
+		    }
 		    /// \brief Runs the algorithm from the given source node.
 		    ///
 		    /// This method runs the %DFS algorithm from node \c s.
 		    /// in order to compute the DFS path to each node.
 		    ///
 		    /// The algorithm computes
 		    /// - the %DFS tree,
 		    /// - the distance of each node from the root in the %DFS tree.
 		    ///
 		    /// \note <tt>d.run(s)</tt> is just a shortcut of the following code.
 		    ///\code
 		    ///   d.init();
 		    ///   d.addSource(s);
 		    ///   d.start();
 		    ///\endcode
 		    void run(Node s) {
 		      init();
 		      addSource(s);
 		      start();
+		    }
 		    /// \brief Finds the %DFS path between \c s and \c t.
 		    /// This method runs the %DFS algorithm from node \c s
 		    /// in order to compute the DFS path to node \c t
 		    /// (it stops searching when \c t is processed).
 		    ///
 		    /// \return \c true if \c t is reachable form \c s.
 		    ///
 		    /// \note Apart from the return value, <tt>d.run(s,t)</tt> is
 		    /// just a shortcut of the following code.
 		    ///\code
 		    ///   d.init();
 		    ///   d.addSource(s);
 		    ///   d.start(t);
 		    ///\endcode
 		    bool run(Node s,Node t) {
 		      init();
 		      addSource(s);
 		      start(t);
 		      return reached(t);
+		    }
 		    /// \brief Runs the algorithm to visit all nodes in the digraph.
 		    /// This method runs the %DFS algorithm in order to
 		    /// compute the %DFS path to each node.
 		    ///
 		    /// The algorithm computes
 		    /// - the %DFS tree (forest),
 		    /// - the distance of each node from the root(s) in the %DFS tree.
 		    ///
 		    /// \note <tt>d.run()</tt> is just a shortcut of the following code.
 		    ///\code
 		    ///   d.init();
 		    ///   for (NodeIt n(digraph); n != INVALID; ++n) {
 		    ///     if (!d.reached(n)) {
 		    ///       d.addSource(n);
 		    ///       d.start();
 		    ///     }
 		    ///   }
 		    ///\endcode
 		    void run() {
 		      init();
 		      for (NodeIt it(*_digraph); it != INVALID; ++it) {
 		        if (!reached(it)) {
 		          addSource(it);
 		          start();
+		        }
+		      }
+		    }
 		    ///@}
 		    /// \name Query Functions
 		    /// The results of the DFS algorithm can be obtained using these
 		    /// functions.\n
 		    /// Either \ref run(Node) "run()" or \ref start() should be called
 		    /// before using them.
 		    ///@{
 		    /// \brief Checks if a node is reached from the root(s).
 		    ///
 		    /// Returns \c true if \c v is reached from the root(s).
 		    ///
 		    /// \pre Either \ref run(Node) "run()" or \ref init()
 		    /// must be called before using this function.
 		    bool reached(Node v) { return (*_reached)[v]; }
+		    bool reached(Node v) const { return (*_reached)[v]; }
 		    ///@}
 		  };
 		} //END OF NAMESPACE LEMON
 		#endif

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) 2003-2008
 		 * 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_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 _Digraph Digraph type.
 		  /// \tparam _CapacityMap Capacity map type.
 		  template <typename _Digraph, typename _CapacityMap>
 		  struct PreflowDefaultTraits {
 		    /// \brief The type of the digraph the algorithm runs on.
 		    typedef _Digraph 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 _CapacityMap 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.
 		    typedef typename Digraph::template ArcMap<Value> FlowMap;
 		    /// \brief Instantiates a FlowMap.
 		    ///
 		    /// This function instantiates a \ref FlowMap.
 		    /// \param digraph The digraph, to 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;
 		    /// \brief Instantiates an Elevator.
 		    ///
 		    /// This function instantiates an \ref Elevator.
 		    /// \param digraph The digraph, to 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 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 _Digraph The type of the digraph the algorithm runs on.
 		  /// \tparam _CapacityMap The type of the capacity map. The default map
 		  /// type is \ref concepts::Digraph::ArcMap "_Digraph::ArcMap<int>".
 		#ifdef DOXYGEN
 		  template <typename _Digraph, typename _CapacityMap, typename _Traits>
 		#else
 		  template <typename _Digraph,
 		            typename _CapacityMap = typename _Digraph::template ArcMap<int>,
 		            typename _Traits = PreflowDefaultTraits<_Digraph, _CapacityMap> >
 		#endif
 		  class Preflow {
 		  public:
 		    ///The \ref PreflowDefaultTraits "traits class" of the algorithm.
 		    typedef _Traits 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;
+		      }
 		      if (!_level) {
 		        _level = Traits::createElevator(_graph, _node_num);
 		        _local_level = true;
+		      }
 		      if (!_excess) {
 		        _excess = new ExcessMap(_graph);
+		      }
+		    }
 		    void destroyStructures() {
 		      if (_local_flow) {
 		        delete _flow;
+		      }
 		      if (_local_level) {
 		        delete _level;
+		      }
 		      if (_excess) {
 		        delete _excess;
+		      }
+		    }
 		  public:
 		    typedef Preflow Create;
 		    ///\name Named Template Parameters
 		    ///@{
 		    template <typename _FlowMap>
 		    struct SetFlowMapTraits : public Traits {
 		      typedef _FlowMap FlowMap;
 		      static FlowMap *createFlowMap(const Digraph&) {
 		        LEMON_ASSERT(false, "FlowMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for setting
 		    /// FlowMap type
 		    ///
 		    /// \ref named-templ-param "Named parameter" for setting FlowMap
 		    /// type.
 		    template <typename _FlowMap>
 		    struct SetFlowMap
 		      : public Preflow<Digraph, CapacityMap, SetFlowMapTraits<_FlowMap> > {
 		      typedef Preflow<Digraph, CapacityMap,
 		                      SetFlowMapTraits<_FlowMap> > Create;
 		    };
 		    template <typename _Elevator>
 		    struct SetElevatorTraits : public Traits {
 		      typedef _Elevator Elevator;
 		      static Elevator *createElevator(const Digraph&, int) {
 		        LEMON_ASSERT(false, "Elevator is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for setting
 		    /// Elevator type
 		    ///
 		    /// \ref named-templ-param "Named parameter" for setting Elevator
 		    /// type. If this named parameter is used, then an external
 		    /// elevator object must be passed to the algorithm using the
 		    /// \ref elevator(Elevator&) "elevator()" function before calling
 		    /// \ref run() or \ref init().
 		    /// \sa SetStandardElevator
 		    template <typename _Elevator>
 		    struct SetElevator
 		      : public Preflow<Digraph, CapacityMap, SetElevatorTraits<_Elevator> > {
 		      typedef Preflow<Digraph, CapacityMap,
 		                      SetElevatorTraits<_Elevator> > Create;
 		    };
 		    template <typename _Elevator>
 		    struct SetStandardElevatorTraits : public Traits {
 		      typedef _Elevator Elevator;
 		      static Elevator *createElevator(const Digraph& digraph, int max_level) {
 		        return new Elevator(digraph, max_level);
+		      }
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for setting
 		    /// Elevator type with automatic allocation
 		    ///
 		    /// \ref named-templ-param "Named parameter" for setting Elevator
 		    /// type with automatic allocation.
 		    /// The Elevator should have standard constructor interface to be
 		    /// able to automatically created by the algorithm (i.e. the
 		    /// digraph and the maximum level should be passed to it).
 		    /// However an external elevator object could also be passed to the
 		    /// algorithm with the \ref elevator(Elevator&) "elevator()" function
 		    /// before calling \ref run() or \ref init().
 		    /// \sa SetElevator
 		    template <typename _Elevator>
 		    struct SetStandardElevator
 		      : public Preflow<Digraph, CapacityMap,
 		                       SetStandardElevatorTraits<_Elevator> > {
 		      typedef Preflow<Digraph, CapacityMap,
 		                      SetStandardElevatorTraits<_Elevator> > Create;
 		    };
 		    /// @}
 		  protected:
 		    Preflow() {}
 		  public:
 		    /// \brief The constructor of the class.
 		    ///
 		    /// The constructor of the class.
 		    /// \param digraph The digraph the algorithm runs on.
 		    /// \param capacity The capacity of the arcs.
 		    /// \param source The source node.
 		    /// \param target The target node.
 		    Preflow(const Digraph& digraph, const CapacityMap& capacity,
 		            Node source, Node target)
 		      : _graph(digraph), _capacity(&capacity),
 		        _node_num(0), _source(source), _target(target),
 		        _flow(0), _local_flow(false),
 		        _level(0), _local_level(false),
 		        _excess(0), _tolerance(), _phase() {}
 		    /// \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 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
 		    /// \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->set(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.set(_source, true);
 		      queue.push_back(_target);
 		      reached.set(_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.set(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->set(u, (*_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->set(n, excess);
+		      }
 		      typename Digraph::template NodeMap<bool> reached(_graph, false);
 		      _level->initStart();
 		      _level->initAddItem(_target);
 		      std::vector<Node> queue;
 		      reached.set(_source, true);
 		      queue.push_back(_target);
 		      reached.set(_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] - (*_flow)[e])) {
 		              reached.set(u, true);
 		              _level->initAddItem(u);
 		              nqueue.push_back(u);
+		            }
+		          }
 		          for (OutArcIt e(_graph, n); e != INVALID; ++e) {
 		            Node v = _graph.target(e);
 		            if (!reached[v] && _tolerance.positive((*_flow)[e])) {
 		              reached.set(v, true);
 		              _level->initAddItem(v);
 		              nqueue.push_back(v);
+		            }
+		          }
+		        }
 		        queue.swap(nqueue);
+		      }
 		      _level->initFinish();
 		      for (OutArcIt e(_graph, _source); e != INVALID; ++e) {
 		        Value rem = (*_capacity)[e] - (*_flow)[e];
 		        if (_tolerance.positive(rem)) {
 		          Node u = _graph.target(e);
 		          if ((*_level)[u] == _level->maxLevel()) continue;
 		          _flow->set(e, (*_capacity)[e]);
 		          _excess->set(u, (*_excess)[u] + rem);
 		          if (u != _target && !_level->active(u)) {
 		            _level->activate(u);
+		          }
+		        }
+		      }
 		      for (InArcIt e(_graph, _source); e != INVALID; ++e) {
 		        Value rem = (*_flow)[e];
 		        if (_tolerance.positive(rem)) {
 		          Node v = _graph.source(e);
 		          if ((*_level)[v] == _level->maxLevel()) continue;
 		          _flow->set(e, 0);
 		          _excess->set(v, (*_excess)[v] + rem);
 		          if (v != _target && !_level->active(v)) {
 		            _level->activate(v);
+		          }
+		        }
+		      }
 		      return true;
+		    }
 		    /// \brief Starts the first phase of the preflow algorithm.
 		    ///
 		    /// The preflow algorithm consists of two phases, this method runs
 		    /// the first phase. After the first phase the maximum flow value
 		    /// and a minimum value cut can already be computed, although a
 		    /// maximum flow is not yet obtained. So after calling this method
 		    /// \ref flowValue() returns the value of a maximum flow and \ref
 		    /// minCut() returns a minimum cut.
 		    /// \pre One of the \ref init() functions must be called before
 		    /// using this function.
 		    void startFirstPhase() {
 		      _phase = true;
 		      Node n = _level->highestActive();
 		      int level = _level->highestActiveLevel();
 		      while (n != INVALID) {
 		        int num = _node_num;
 		        while (num > 0 && n != INVALID) {
 		          Value excess = (*_excess)[n];
 		          int new_level = _level->maxLevel();
 		          for (OutArcIt e(_graph, n); e != INVALID; ++e) {
 		            Value rem = (*_capacity)[e] - (*_flow)[e];
 		            if (!_tolerance.positive(rem)) continue;
 		            Node v = _graph.target(e);
 		            if ((*_level)[v] < level) {
 		              if (!_level->active(v) && v != _target) {
 		                _level->activate(v);
+		              }
 		              if (!_tolerance.less(rem, excess)) {
 		                _flow->set(e, (*_flow)[e] + excess);
 		                _excess->set(v, (*_excess)[v] + excess);
 		                excess = 0;
 		                goto no_more_push_1;
 		              } else {
 		                excess -= rem;
 		                _excess->set(v, (*_excess)[v] + rem);
 		                _flow->set(e, (*_capacity)[e]);
+		              }
 		            } else if (new_level > (*_level)[v]) {
 		              new_level = (*_level)[v];
+		            }
+		          }
 		          for (InArcIt e(_graph, n); e != INVALID; ++e) {
 		            Value rem = (*_flow)[e];
 		            if (!_tolerance.positive(rem)) continue;
 		            Node v = _graph.source(e);
 		            if ((*_level)[v] < level) {
 		              if (!_level->active(v) && v != _target) {
 		                _level->activate(v);
+		              }
 		              if (!_tolerance.less(rem, excess)) {
 		                _flow->set(e, (*_flow)[e] - excess);
 		                _excess->set(v, (*_excess)[v] + excess);
 		                excess = 0;
 		                goto no_more_push_1;
 		              } else {
 		                excess -= rem;
 		                _excess->set(v, (*_excess)[v] + rem);
 		                _flow->set(e, 0);
+		              }
 		            } else if (new_level > (*_level)[v]) {
 		              new_level = (*_level)[v];
+		            }
+		          }
 		        no_more_push_1:
 		          _excess->set(n, excess);
 		          if (excess != 0) {
 		            if (new_level + 1 < _level->maxLevel()) {
 		              _level->liftHighestActive(new_level + 1);
 		            } else {
 		              _level->liftHighestActiveToTop();
+		            }
 		            if (_level->emptyLevel(level)) {
 		              _level->liftToTop(level);
+		            }
 		          } else {
 		            _level->deactivate(n);
+		          }
 		          n = _level->highestActive();
 		          level = _level->highestActiveLevel();
 		          --num;
+		        }
 		        num = _node_num * 20;
 		        while (num > 0 && n != INVALID) {
 		          Value excess = (*_excess)[n];
 		          int new_level = _level->maxLevel();
 		          for (OutArcIt e(_graph, n); e != INVALID; ++e) {
 		            Value rem = (*_capacity)[e] - (*_flow)[e];
 		            if (!_tolerance.positive(rem)) continue;
 		            Node v = _graph.target(e);
 		            if ((*_level)[v] < level) {
 		              if (!_level->active(v) && v != _target) {
 		                _level->activate(v);
+		              }
 		              if (!_tolerance.less(rem, excess)) {
 		                _flow->set(e, (*_flow)[e] + excess);
 		                _excess->set(v, (*_excess)[v] + excess);
 		                excess = 0;
 		                goto no_more_push_2;
 		              } else {
 		                excess -= rem;
 		                _excess->set(v, (*_excess)[v] + rem);
 		                _flow->set(e, (*_capacity)[e]);
+		              }
 		            } else if (new_level > (*_level)[v]) {
 		              new_level = (*_level)[v];
+		            }
+		          }
 		          for (InArcIt e(_graph, n); e != INVALID; ++e) {
 		            Value rem = (*_flow)[e];
 		            if (!_tolerance.positive(rem)) continue;
 		            Node v = _graph.source(e);
 		            if ((*_level)[v] < level) {
 		              if (!_level->active(v) && v != _target) {
 		                _level->activate(v);
+		              }
 		              if (!_tolerance.less(rem, excess)) {
 		                _flow->set(e, (*_flow)[e] - excess);
 		                _excess->set(v, (*_excess)[v] + excess);
 		                excess = 0;
 		                goto no_more_push_2;
 		              } else {
 		                excess -= rem;
 		                _excess->set(v, (*_excess)[v] + rem);
 		                _flow->set(e, 0);
+		              }
 		            } else if (new_level > (*_level)[v]) {
 		              new_level = (*_level)[v];
+		            }
+		          }
 		        no_more_push_2:
 		          _excess->set(n, excess);
 		          if (excess != 0) {
 		            if (new_level + 1 < _level->maxLevel()) {
 		              _level->liftActiveOn(level, new_level + 1);
 		            } else {
 		              _level->liftActiveToTop(level);
+		            }
 		            if (_level->emptyLevel(level)) {
 		              _level->liftToTop(level);
+		            }
 		          } else {
 		            _level->deactivate(n);
+		          }
 		          while (level >= 0 && _level->activeFree(level)) {
 		            --level;
+		          }
 		          if (level == -1) {
 		            n = _level->highestActive();
 		            level = _level->highestActiveLevel();
 		          } else {
 		            n = _level->activeOn(level);
+		          }
 		          --num;
+		        }
+		      }
+		    }
 		    /// \brief Starts the second phase of the preflow algorithm.
 		    ///
 		    /// The preflow algorithm consists of two phases, this method runs
 		    /// the second phase. After calling one of the \ref init() functions
 		    /// and \ref startFirstPhase() and then \ref startSecondPhase(),
 		    /// \ref flowMap() returns a maximum flow, \ref flowValue() returns the
 		    /// value of a maximum flow, \ref minCut() returns a minimum cut
 		    /// \pre One of the \ref init() functions and \ref startFirstPhase()
 		    /// must be called before using this function.
 		    void startSecondPhase() {
 		      _phase = false;
 		      typename Digraph::template NodeMap<bool> reached(_graph);
 		      for (NodeIt n(_graph); n != INVALID; ++n) {
 		        reached.set(n, (*_level)[n] < _level->maxLevel());
+		      }
 		      _level->initStart();
 		      _level->initAddItem(_source);
 		      std::vector<Node> queue;
 		      queue.push_back(_source);
 		      reached.set(_source, true);
 		      while (!queue.empty()) {
 		        _level->initNewLevel();
 		        std::vector<Node> nqueue;
 		        for (int i = 0; i < int(queue.size()); ++i) {
 		          Node n = queue[i];
 		          for (OutArcIt e(_graph, n); e != INVALID; ++e) {
 		            Node v = _graph.target(e);
 		            if (!reached[v] && _tolerance.positive((*_flow)[e])) {
 		              reached.set(v, true);
 		              _level->initAddItem(v);
 		              nqueue.push_back(v);
+		            }
+		          }
 		          for (InArcIt e(_graph, n); e != INVALID; ++e) {
 		            Node u = _graph.source(e);
 		            if (!reached[u] &&
 		                _tolerance.positive((*_capacity)[e] - (*_flow)[e])) {
 		              reached.set(u, true);
 		              _level->initAddItem(u);
 		              nqueue.push_back(u);
+		            }
+		          }
+		        }
 		        queue.swap(nqueue);
+		      }
 		      _level->initFinish();
 		      for (NodeIt n(_graph); n != INVALID; ++n) {
 		        if (!reached[n]) {
 		          _level->dirtyTopButOne(n);
 		        } else if ((*_excess)[n] > 0 && _target != n) {
 		          _level->activate(n);
+		        }
+		      }
 		      Node n;
 		      while ((n = _level->highestActive()) != INVALID) {
 		        Value excess = (*_excess)[n];
 		        int level = _level->highestActiveLevel();
 		        int new_level = _level->maxLevel();
 		        for (OutArcIt e(_graph, n); e != INVALID; ++e) {
 		          Value rem = (*_capacity)[e] - (*_flow)[e];
 		          if (!_tolerance.positive(rem)) continue;
 		          Node v = _graph.target(e);
 		          if ((*_level)[v] < level) {
 		            if (!_level->active(v) && v != _source) {
 		              _level->activate(v);
+		            }
 		            if (!_tolerance.less(rem, excess)) {
 		              _flow->set(e, (*_flow)[e] + excess);
 		              _excess->set(v, (*_excess)[v] + excess);
 		              excess = 0;
 		              goto no_more_push;
 		            } else {
 		              excess -= rem;
 		              _excess->set(v, (*_excess)[v] + rem);
 		              _flow->set(e, (*_capacity)[e]);
+		            }
 		          } else if (new_level > (*_level)[v]) {
 		            new_level = (*_level)[v];
+		          }
+		        }
 		        for (InArcIt e(_graph, n); e != INVALID; ++e) {
 		          Value rem = (*_flow)[e];
 		          if (!_tolerance.positive(rem)) continue;
 		          Node v = _graph.source(e);
 		          if ((*_level)[v] < level) {
 		            if (!_level->active(v) && v != _source) {
 		              _level->activate(v);
+		            }
 		            if (!_tolerance.less(rem, excess)) {
 		              _flow->set(e, (*_flow)[e] - excess);
 		              _excess->set(v, (*_excess)[v] + excess);
 		              excess = 0;
 		              goto no_more_push;
 		            } else {
 		              excess -= rem;
 		              _excess->set(v, (*_excess)[v] + rem);
 		              _flow->set(e, 0);
+		            }
 		          } else if (new_level > (*_level)[v]) {
 		            new_level = (*_level)[v];
+		          }
+		        }
 		      no_more_push:
 		        _excess->set(n, excess);
 		        if (excess != 0) {
 		          if (new_level + 1 < _level->maxLevel()) {
 		            _level->liftHighestActive(new_level + 1);
 		          } else {
 		            // Calculation error
 		            _level->liftHighestActiveToTop();
+		          }
 		          if (_level->emptyLevel(level)) {
 		            // Calculation error
 		            _level->liftToTop(level);
+		          }
 		        } else {
 		          _level->deactivate(n);
+		        }
+		      }
+		    }
 		    /// \brief Runs the preflow algorithm.
 		    ///
 		    /// Runs the preflow algorithm.
 		    /// \note pf.run() is just a shortcut of the following code.
 		    /// \code
 		    ///   pf.init();
 		    ///   pf.startFirstPhase();
 		    ///   pf.startSecondPhase();
 		    /// \endcode
 		    void run() {
 		      init();
 		      startFirstPhase();
 		      startSecondPhase();
+		    }
 		    /// \brief Runs the preflow algorithm to compute the minimum cut.
 		    ///
 		    /// Runs the preflow algorithm to compute the minimum cut.
 		    /// \note pf.runMinCut() is just a shortcut of the following code.
 		    /// \code
 		    ///   pf.init();
 		    ///   pf.startFirstPhase();
 		    /// \endcode
 		    void runMinCut() {
 		      init();
 		      startFirstPhase();
+		    }
 		    /// @}
 		    /// \name Query Functions
 		    /// The results of the preflow algorithm can be obtained using these
 		    /// functions.\n
 		    /// Either one of the \ref run() "run*()" functions or one of the
 		    /// \ref startFirstPhase() "start*()" functions should be called
 		    /// before using them.
 		    ///@{
 		    /// \brief Returns the value of the maximum flow.
 		    ///
 		    /// Returns the value of the maximum flow by returning the excess
 		    /// of the target node. This value equals to the value of
 		    /// the maximum flow already after the first phase of the algorithm.
 		    ///
 		    /// \pre Either \ref run() or \ref init() must be called before
 		    /// using this function.
 		    Value flowValue() const {
 		      return (*_excess)[_target];
+		    }
 		    /// \brief Returns the flow on the given arc.
 		    ///
 		    /// Returns the flow on the given arc. This method can
 		    /// be called after the second phase of the algorithm.
 		    ///
 		    /// \pre Either \ref run() or \ref init() must be called before
 		    /// using this function.
 		    Value flow(const Arc& arc) const {
 		      return (*_flow)[arc];
+		    }
 		    /// \brief Returns a const reference to the flow map.
 		    ///
 		    /// Returns a const reference to the arc map storing the found flow.
 		    /// This method can be called after the second phase of the algorithm.
 		    ///
 		    /// \pre Either \ref run() or \ref init() must be called before
 		    /// using this function.
 		    const FlowMap& flowMap() {
+		    const FlowMap& flowMap() const {
 		      return *_flow;
+		    }
 		    /// \brief Returns \c true when the node is on the source side of the
 		    /// minimum cut.
 		    ///
 		    /// Returns true when the node is on the source side of the found
 		    /// minimum cut. This method can be called both after running \ref
 		    /// startFirstPhase() and \ref startSecondPhase().
 		    ///
 		    /// \pre Either \ref run() or \ref init() must be called before
 		    /// using this function.
 		    bool minCut(const Node& node) const {
 		      return ((*_level)[node] == _level->maxLevel()) == _phase;
+		    }
 		    /// \brief Gives back a minimum value cut.
 		    ///
 		    /// Sets \c cutMap to the characteristic vector of a minimum value
 		    /// cut. \c cutMap should be a \ref concepts::WriteMap "writable"
 		    /// node map with \c bool (or convertible) value type.
 		    ///
 		    /// This method can be called both after running \ref startFirstPhase()
 		    /// and \ref startSecondPhase(). The result after the second phase
 		    /// could be slightly different if inexact computation is used.
 		    ///
 		    /// \note This function calls \ref minCut() for each node, so it runs in
 		    /// \f$O(n)\f$ time.
 		    ///
 		    /// \pre Either \ref run() or \ref init() must be called before
 		    /// using this function.
 		    template <typename CutMap>
 		    void minCutMap(CutMap& cutMap) const {
 		      for (NodeIt n(_graph); n != INVALID; ++n) {
 		        cutMap.set(n, minCut(n));
+		      }
+		    }
 		    /// @}
 		  };
+		}
 		#endif

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