LEMON/LEMON-official Changeset - r760:4ac30454f1c1

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Changeset - r760:4ac30454f1c1

« 730:9f529a

761:98a308 »

r760:4ac30454f1c1

Fri, 24 Jul 2009 10:27:40

[Not Reviewed]

0 comments (0 inline)

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

Small doc improvements

0 8 0

default

8 files changed with 42 insertions and 28 deletions:

doc/groups.dox

lemon/bfs.h

lemon/circulation.h

lemon/dfs.h

lemon/dijkstra.h

lemon/gomory_hu.h

lemon/min_cost_arborescence.h

lemon/preflow.h

↑ Collapse diff ↑

doc/groups.dox

Show inline comments

@@ -186,409 +186,409 @@
 		    } else if (deg == 1) {
 		      return Color(1.0, 0.5, 1.0);
 		    } else {
 		      return Color(0.0, 0.0, 0.0);
+		    }
+		  }
 		  Digraph::NodeMap<int> degree_map(graph);
 		  graphToEps(graph, "graph.eps")
 		    .coords(coords).scaleToA4().undirected()
 		    .nodeColors(composeMap(functorToMap(nodeColor), degree_map))
 		    .run();
 		\endcode
 		The \c functorToMap() function makes an \c int to \c Color map from the
 		\c nodeColor() function. The \c composeMap() compose the \c degree_map
 		and the previously created map. The composed map is a proper function to
 		get the color of each node.
 		The usage with class type algorithms is little bit harder. In this
 		case the function type map adaptors can not be used, because the
 		function map adaptors give back temporary objects.
 		\code
 		  Digraph graph;
 		  typedef Digraph::ArcMap<double> DoubleArcMap;
 		  DoubleArcMap length(graph);
 		  DoubleArcMap speed(graph);
 		  typedef DivMap<DoubleArcMap, DoubleArcMap> TimeMap;
 		  TimeMap time(length, speed);
 		  Dijkstra<Digraph, TimeMap> dijkstra(graph, time);
 		  dijkstra.run(source, target);
 		\endcode
 		We have a length map and a maximum speed map on the arcs of a digraph.
 		The minimum time to pass the arc can be calculated as the division of
 		the two maps which can be done implicitly with the \c DivMap template
 		class. We use the implicit minimum time map as the length map of the
 		\c Dijkstra algorithm.
 		*/
 		/**
 		@defgroup matrices Matrices
 		@ingroup datas
 		\brief Two dimensional data storages implemented in LEMON.
 		This group contains two dimensional data storages implemented in LEMON.
 		*/
 		/**
 		@defgroup paths Path Structures
 		@ingroup datas
 		\brief %Path structures implemented in LEMON.
 		This group contains the path structures implemented in LEMON.
 		LEMON provides flexible data structures to work with paths.
 		All of them have similar interfaces and they can be copied easily with
 		assignment operators and copy constructors. This makes it easy and
 		efficient to have e.g. the Dijkstra algorithm to store its result in
 		any kind of path structure.
 		\sa lemon::concepts::Path
 		*/
 		/**
 		@defgroup auxdat Auxiliary Data Structures
 		@ingroup datas
 		\brief Auxiliary data structures implemented in LEMON.
 		This group contains some data structures implemented in LEMON in
 		order to make it easier to implement combinatorial algorithms.
 		*/
 		/**
 		@defgroup algs Algorithms
 		\brief This group contains the several algorithms
 		implemented in LEMON.
 		This group contains the several algorithms
 		implemented in LEMON.
 		*/
 		/**
 		@defgroup search Graph Search
 		@ingroup algs
 		\brief Common graph search algorithms.
 		This group contains the common graph search algorithms, namely
 		\e breadth-first \e search (BFS) and \e depth-first \e search (DFS).
 		*/
 		/**
 		@defgroup shortest_path Shortest Path Algorithms
 		@ingroup algs
 		\brief Algorithms for finding shortest paths.
 		This group contains the algorithms for finding shortest paths in digraphs.
 		 - \ref Dijkstra algorithm for finding shortest paths from a source node
 		   when all arc lengths are non-negative.
 		 - \ref BellmanFord "Bellman-Ford" algorithm for finding shortest paths
 		   from a source node when arc lenghts can be either positive or negative,
 		   but the digraph should not contain directed cycles with negative total
 		   length.
 		 - \ref FloydWarshall "Floyd-Warshall" and \ref Johnson "Johnson" algorithms
 		   for solving the \e all-pairs \e shortest \e paths \e problem when arc
 		   lenghts can be either positive or negative, but the digraph should
 		   not contain directed cycles with negative total length.
 		 - \ref Suurballe A successive shortest path algorithm for finding
 		   arc-disjoint paths between two nodes having minimum total length.
 		*/
 		/**
 		@defgroup max_flow Maximum Flow Algorithms
 		@ingroup algs
 		\brief Algorithms for finding maximum flows.
 		This group contains the algorithms for finding maximum flows and
 		feasible circulations.
 		The \e maximum \e flow \e problem is to find a flow of maximum value between
 		a single source and a single target. Formally, there is a \f$G=(V,A)\f$
 		digraph, a \f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function and
 		\f$s, t \in V\f$ source and target nodes.
 		A maximum flow is an \f$f: A\rightarrow\mathbf{R}^+_0\f$ solution of the
 		following optimization problem.
 		\f[ \max\sum_{sv\in A} f(sv) - \sum_{vs\in A} f(vs) \f]
 		\f[ \sum_{uv\in A} f(uv) = \sum_{vu\in A} f(vu)
 		    \quad \forall u\in V\setminus\{s,t\} \f]
 		\f[ 0 \leq f(uv) \leq cap(uv) \quad \forall uv\in A \f]
 		LEMON contains several algorithms for solving maximum flow problems:
 		- \ref EdmondsKarp Edmonds-Karp algorithm.
 		- \ref Preflow Goldberg-Tarjan's preflow push-relabel algorithm.
 		- \ref DinitzSleatorTarjan Dinitz's blocking flow algorithm with dynamic trees.
 		- \ref GoldbergTarjan Preflow push-relabel algorithm with dynamic trees.
 		In most cases the \ref Preflow "Preflow" algorithm provides the
 		fastest method for computing a maximum flow. All implementations
 		also provide functions to query the minimum cut, which is the dual
 		problem of maximum flow.
 		\ref Circulation is a preflow push-relabel algorithm implemented directly
 		for finding feasible circulations, which is a somewhat different problem,
 		but it is strongly related to maximum flow.
 		For more information, see \ref Circulation.
 		*/
 		/**
 		@defgroup min_cost_flow_algs Minimum Cost Flow Algorithms
 		@ingroup algs
 		\brief Algorithms for finding minimum cost flows and circulations.
 		This group contains the algorithms for finding minimum cost flows and
 		circulations. For more information about this problem and its dual
 		solution see \ref min_cost_flow "Minimum Cost Flow Problem".
 		LEMON contains several algorithms for this problem.
 		 - \ref NetworkSimplex Primal Network Simplex algorithm with various
 		   pivot strategies.
 		 - \ref CostScaling Push-Relabel and Augment-Relabel algorithms based on
 		   cost scaling.
 		 - \ref CapacityScaling Successive Shortest %Path algorithm with optional
 		   capacity scaling.
 		 - \ref CancelAndTighten The Cancel and Tighten algorithm.
 		 - \ref CycleCanceling Cycle-Canceling algorithms.
 		In general NetworkSimplex is the most efficient implementation,
 		but in special cases other algorithms could be faster.
 		For example, if the total supply and/or capacities are rather small,
 		CapacityScaling is usually the fastest algorithm (without effective scaling).
 		*/
 		/**
 		@defgroup min_cut Minimum Cut Algorithms
 		@ingroup algs
 		\brief Algorithms for finding minimum cut in graphs.
 		This group contains the algorithms for finding minimum cut in graphs.
 		The \e minimum \e cut \e problem is to find a non-empty and non-complete
 		\f$X\f$ subset of the nodes with minimum overall capacity on
 		outgoing arcs. Formally, there is a \f$G=(V,A)\f$ digraph, a
 		\f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function. The minimum
 		cut is the \f$X\f$ solution of the next optimization problem:
 		\f[ \min_{X \subset V, X\not\in \{\emptyset, V\}}
-		    \sum_{uv\in A, u\in X, v\not\in X}cap(uv) \f]
+		    \sum_{uv\in A: u\in X, v\not\in X}cap(uv) \f]
 		LEMON contains several algorithms related to minimum cut problems:
 		- \ref HaoOrlin "Hao-Orlin algorithm" for calculating minimum cut
 		  in directed graphs.
 		- \ref NagamochiIbaraki "Nagamochi-Ibaraki algorithm" for
 		  calculating minimum cut in undirected graphs.
 		- \ref GomoryHu "Gomory-Hu tree computation" for calculating
 		  all-pairs minimum cut in undirected graphs.
 		If you want to find minimum cut just between two distinict nodes,
 		see the \ref max_flow "maximum flow problem".
 		*/
 		/**
 		@defgroup graph_properties Connectivity and Other Graph Properties
 		@ingroup algs
 		\brief Algorithms for discovering the graph properties
 		This group contains the algorithms for discovering the graph properties
 		like connectivity, bipartiteness, euler property, simplicity etc.
 		\image html edge_biconnected_components.png
 		\image latex edge_biconnected_components.eps "bi-edge-connected components" width=\textwidth
 		\image html connected_components.png
 		\image latex connected_components.eps "Connected components" width=\textwidth
 		*/
 		/**
 		@defgroup planar Planarity Embedding and Drawing
 		@ingroup algs
 		\brief Algorithms for planarity checking, embedding and drawing
 		This group contains the algorithms for planarity checking,
 		embedding and drawing.
 		\image html planar.png
 		\image latex planar.eps "Plane graph" width=\textwidth
 		*/
 		/**
 		@defgroup matching Matching Algorithms
 		@ingroup algs
 		\brief Algorithms for finding matchings in graphs and bipartite graphs.
 		This group contains the algorithms for calculating
 		matchings in graphs and bipartite graphs. The general matching problem is
 		finding a subset of the edges for which each node has at most one incident
 		edge.
 		There are several different algorithms for calculate matchings in
 		graphs.  The matching problems in bipartite graphs are generally
 		easier than in general graphs. The goal of the matching optimization
 		can be finding maximum cardinality, maximum weight or minimum cost
 		matching. The search can be constrained to find perfect or
 		maximum cardinality matching.
 		The matching algorithms implemented in LEMON:
 		- \ref MaxBipartiteMatching Hopcroft-Karp augmenting path algorithm
 		  for calculating maximum cardinality matching in bipartite graphs.
 		- \ref PrBipartiteMatching Push-relabel algorithm
 		  for calculating maximum cardinality matching in bipartite graphs.
 		- \ref MaxWeightedBipartiteMatching
 		  Successive shortest path algorithm for calculating maximum weighted
 		  matching and maximum weighted bipartite matching in bipartite graphs.
 		- \ref MinCostMaxBipartiteMatching
 		  Successive shortest path algorithm for calculating minimum cost maximum
 		  matching in bipartite graphs.
 		- \ref MaxMatching Edmond's blossom shrinking algorithm for calculating
 		  maximum cardinality matching in general graphs.
 		- \ref MaxWeightedMatching Edmond's blossom shrinking algorithm for calculating
 		  maximum weighted matching in general graphs.
 		- \ref MaxWeightedPerfectMatching
 		  Edmond's blossom shrinking algorithm for calculating maximum weighted
 		  perfect matching in general graphs.
 		\image html bipartite_matching.png
 		\image latex bipartite_matching.eps "Bipartite Matching" width=\textwidth
 		*/
 		/**
 		@defgroup spantree Minimum Spanning Tree Algorithms
 		@ingroup algs
 		\brief Algorithms for finding minimum cost spanning trees and arborescences.
 		This group contains the algorithms for finding minimum cost spanning
 		trees and arborescences.
 		*/
 		/**
 		@defgroup auxalg Auxiliary Algorithms
 		@ingroup algs
 		\brief Auxiliary algorithms implemented in LEMON.
 		This group contains some algorithms implemented in LEMON
 		in order to make it easier to implement complex algorithms.
 		*/
 		/**
 		@defgroup approx Approximation Algorithms
 		@ingroup algs
 		\brief Approximation algorithms.
 		This group contains the approximation and heuristic algorithms
 		implemented in LEMON.
 		*/
 		/**
 		@defgroup gen_opt_group General Optimization Tools
 		\brief This group contains some general optimization frameworks
 		implemented in LEMON.
 		This group contains some general optimization frameworks
 		implemented in LEMON.
 		*/
 		/**
 		@defgroup lp_group Lp and Mip Solvers
 		@ingroup gen_opt_group
 		\brief Lp and Mip solver interfaces for LEMON.
 		This group contains Lp and Mip solver interfaces for LEMON. The
 		various LP solvers could be used in the same manner with this
 		interface.
 		*/
 		/**
 		@defgroup lp_utils Tools for Lp and Mip Solvers
 		@ingroup lp_group
 		\brief Helper tools to the Lp and Mip solvers.
 		This group adds some helper tools to general optimization framework
 		implemented in LEMON.
 		*/
 		/**
 		@defgroup metah Metaheuristics
 		@ingroup gen_opt_group
 		\brief Metaheuristics for LEMON library.
 		This group contains some metaheuristic optimization tools.
 		*/
 		/**
 		@defgroup utils Tools and Utilities
 		\brief Tools and utilities for programming in LEMON
 		Tools and utilities for programming in LEMON.
 		*/
 		/**
 		@defgroup gutils Basic Graph Utilities
 		@ingroup utils
 		\brief Simple basic graph utilities.
 		This group contains some simple basic graph utilities.
 		*/
 		/**
 		@defgroup misc Miscellaneous Tools
 		@ingroup utils
 		\brief Tools for development, debugging and testing.
 		This group contains several useful tools for development,
 		debugging and testing.
 		*/
 		/**
 		@defgroup timecount Time Measuring and Counting
 		@ingroup misc
 		\brief Simple tools for measuring the performance of algorithms.
 		This group contains simple tools for measuring the performance
 		of algorithms.
 		*/
 		/**
 		@defgroup exceptions Exceptions
 		@ingroup utils
 		\brief Exceptions defined in LEMON.
 		This group contains the exceptions defined in LEMON.
 		*/
 		/**
 		@defgroup io_group Input-Output
 		\brief Graph Input-Output methods
 		This group contains the tools for importing and exporting graphs
 		and graph related data. Now it supports the \ref lgf-format
 		"LEMON Graph Format", the \c DIMACS format and the encapsulated
 		postscript (EPS) format.
 		*/
 		/**
 		@defgroup lemon_io LEMON Graph Format
 		@ingroup io_group
 		\brief Reading and writing LEMON Graph Format.
 		This group contains methods for reading and writing
 		\ref lgf-format "LEMON Graph Format".
 		*/
 		/**
 		@defgroup eps_io Postscript Exporting
 		@ingroup io_group
 		\brief General \c EPS drawer and graph exporter
 		This group contains general \c EPS drawing methods and special
 		graph exporting tools.
 		*/
 		/**
 		@defgroup dimacs_group DIMACS format
 		@ingroup io_group
 		\brief Read and write files in DIMACS format
 		Tools to read a digraph from or write it to a file in DIMACS format data.

lemon/bfs.h

Show inline comments

@@ -224,386 +224,386 @@
 		    ///\c PredMap type.
 		    ///
 		    ///\ref named-templ-param "Named parameter" for setting
 		    ///\c PredMap type.
 		    ///It must meet the \ref concepts::WriteMap "WriteMap" concept.
 		    template <class T>
 		    struct SetPredMap : public Bfs< Digraph, SetPredMapTraits<T> > {
 		      typedef Bfs< Digraph, SetPredMapTraits<T> > Create;
 		    };
 		    template <class T>
 		    struct SetDistMapTraits : public Traits {
 		      typedef T DistMap;
 		      static DistMap *createDistMap(const Digraph &)
+		      {
 		        LEMON_ASSERT(false, "DistMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    ///\brief \ref named-templ-param "Named parameter" for setting
 		    ///\c DistMap type.
 		    ///
 		    ///\ref named-templ-param "Named parameter" for setting
 		    ///\c DistMap type.
 		    ///It must meet the \ref concepts::WriteMap "WriteMap" concept.
 		    template <class T>
 		    struct SetDistMap : public Bfs< Digraph, SetDistMapTraits<T> > {
 		      typedef Bfs< Digraph, SetDistMapTraits<T> > Create;
 		    };
 		    template <class T>
 		    struct SetReachedMapTraits : public Traits {
 		      typedef T ReachedMap;
 		      static ReachedMap *createReachedMap(const Digraph &)
+		      {
 		        LEMON_ASSERT(false, "ReachedMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    ///\brief \ref named-templ-param "Named parameter" for setting
 		    ///\c ReachedMap type.
 		    ///
 		    ///\ref named-templ-param "Named parameter" for setting
 		    ///\c ReachedMap type.
 		    ///It must meet the \ref concepts::ReadWriteMap "ReadWriteMap" concept.
 		    template <class T>
 		    struct SetReachedMap : public Bfs< Digraph, SetReachedMapTraits<T> > {
 		      typedef Bfs< Digraph, SetReachedMapTraits<T> > Create;
 		    };
 		    template <class T>
 		    struct SetProcessedMapTraits : public Traits {
 		      typedef T ProcessedMap;
 		      static ProcessedMap *createProcessedMap(const Digraph &)
+		      {
 		        LEMON_ASSERT(false, "ProcessedMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    ///\brief \ref named-templ-param "Named parameter" for setting
 		    ///\c ProcessedMap type.
 		    ///
 		    ///\ref named-templ-param "Named parameter" for setting
 		    ///\c ProcessedMap type.
 		    ///It must meet the \ref concepts::WriteMap "WriteMap" concept.
 		    template <class T>
 		    struct SetProcessedMap : public Bfs< Digraph, SetProcessedMapTraits<T> > {
 		      typedef Bfs< Digraph, SetProcessedMapTraits<T> > Create;
 		    };
 		    struct SetStandardProcessedMapTraits : public Traits {
 		      typedef typename Digraph::template NodeMap<bool> ProcessedMap;
 		      static ProcessedMap *createProcessedMap(const Digraph &g)
+		      {
 		        return new ProcessedMap(g);
 		        return 0; // ignore warnings
+		      }
 		    };
 		    ///\brief \ref named-templ-param "Named parameter" for setting
 		    ///\c ProcessedMap type to be <tt>Digraph::NodeMap<bool></tt>.
 		    ///
 		    ///\ref named-templ-param "Named parameter" for setting
 		    ///\c ProcessedMap type to be <tt>Digraph::NodeMap<bool></tt>.
 		    ///If you don't set it explicitly, it will be automatically allocated.
 		    struct SetStandardProcessedMap :
 		      public Bfs< Digraph, SetStandardProcessedMapTraits > {
 		      typedef Bfs< Digraph, SetStandardProcessedMapTraits > Create;
 		    };
 		    ///@}
 		  public:
 		    ///Constructor.
 		    ///Constructor.
 		    ///\param g The digraph the algorithm runs on.
 		    Bfs(const Digraph &g) :
 		      G(&g),
 		      _pred(NULL), local_pred(false),
 		      _dist(NULL), local_dist(false),
 		      _reached(NULL), local_reached(false),
 		      _processed(NULL), local_processed(false)
 		    { }
 		    ///Destructor.
 		    ~Bfs()
+		    {
 		      if(local_pred) delete _pred;
 		      if(local_dist) delete _dist;
 		      if(local_reached) delete _reached;
 		      if(local_processed) delete _processed;
+		    }
 		    ///Sets the map that stores the predecessor arcs.
 		    ///Sets the map that stores the predecessor arcs.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Bfs &predMap(PredMap &m)
+		    {
 		      if(local_pred) {
 		        delete _pred;
 		        local_pred=false;
+		      }
 		      _pred = &m;
 		      return *this;
+		    }
 		    ///Sets the map that indicates which nodes are reached.
 		    ///Sets the map that indicates which nodes are reached.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Bfs &reachedMap(ReachedMap &m)
+		    {
 		      if(local_reached) {
 		        delete _reached;
 		        local_reached=false;
+		      }
 		      _reached = &m;
 		      return *this;
+		    }
 		    ///Sets the map that indicates which nodes are processed.
 		    ///Sets the map that indicates which nodes are processed.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Bfs &processedMap(ProcessedMap &m)
+		    {
 		      if(local_processed) {
 		        delete _processed;
 		        local_processed=false;
+		      }
 		      _processed = &m;
 		      return *this;
+		    }
 		    ///Sets the map that stores the distances of the nodes.
 		    ///Sets the map that stores the distances of the nodes calculated by
 		    ///the algorithm.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Bfs &distMap(DistMap &m)
+		    {
 		      if(local_dist) {
 		        delete _dist;
 		        local_dist=false;
+		      }
 		      _dist = &m;
 		      return *this;
+		    }
 		  public:
 		    ///\name Execution Control
 		    ///The simplest way to execute the BFS algorithm is to use one of the
 		    ///member functions called \ref run(Node) "run()".\n
 		    ///If you need more control on the execution, first you have to call
 		    ///\ref init(), then you can add several source nodes with
 		    ///If you need better control on the execution, you have to call
 		    ///\ref init() first, then you can add several source nodes with
 		    ///\ref addSource(). Finally the actual path computation can be
 		    ///performed with one of the \ref start() functions.
 		    ///@{
 		    ///\brief Initializes the internal data structures.
 		    ///
 		    ///Initializes the internal data structures.
 		    void init()
+		    {
 		      create_maps();
 		      _queue.resize(countNodes(*G));
 		      _queue_head=_queue_tail=0;
 		      _curr_dist=1;
 		      for ( NodeIt u(*G) ; u!=INVALID ; ++u ) {
 		        _pred->set(u,INVALID);
 		        _reached->set(u,false);
 		        _processed->set(u,false);
+		      }
+		    }
 		    ///Adds a new source node.
 		    ///Adds a new source node to the set of nodes to be processed.
 		    ///
 		    void addSource(Node s)
+		    {
 		      if(!(*_reached)[s])
+		        {
 		          _reached->set(s,true);
 		          _pred->set(s,INVALID);
 		          _dist->set(s,0);
 		          _queue[_queue_head++]=s;
 		          _queue_next_dist=_queue_head;
+		        }
+		    }
 		    ///Processes the next node.
 		    ///Processes the next node.
 		    ///
 		    ///\return The processed node.
 		    ///
 		    ///\pre The queue must not be empty.
 		    Node processNextNode()
+		    {
 		      if(_queue_tail==_queue_next_dist) {
 		        _curr_dist++;
 		        _queue_next_dist=_queue_head;
+		      }
 		      Node n=_queue[_queue_tail++];
 		      _processed->set(n,true);
 		      Node m;
 		      for(OutArcIt e(*G,n);e!=INVALID;++e)
 		        if(!(*_reached)[m=G->target(e)]) {
 		          _queue[_queue_head++]=m;
 		          _reached->set(m,true);
 		          _pred->set(m,e);
 		          _dist->set(m,_curr_dist);
+		        }
 		      return n;
+		    }
 		    ///Processes the next node.
 		    ///Processes the next node and checks if the given target node
 		    ///is reached. If the target node is reachable from the processed
 		    ///node, then the \c reach parameter will be set to \c true.
 		    ///
 		    ///\param target The target node.
 		    ///\retval reach Indicates if the target node is reached.
 		    ///It should be initially \c false.
 		    ///
 		    ///\return The processed node.
 		    ///
 		    ///\pre The queue must not be empty.
 		    Node processNextNode(Node target, bool& reach)
+		    {
 		      if(_queue_tail==_queue_next_dist) {
 		        _curr_dist++;
 		        _queue_next_dist=_queue_head;
+		      }
 		      Node n=_queue[_queue_tail++];
 		      _processed->set(n,true);
 		      Node m;
 		      for(OutArcIt e(*G,n);e!=INVALID;++e)
 		        if(!(*_reached)[m=G->target(e)]) {
 		          _queue[_queue_head++]=m;
 		          _reached->set(m,true);
 		          _pred->set(m,e);
 		          _dist->set(m,_curr_dist);
 		          reach = reach || (target == m);
+		        }
 		      return n;
+		    }
 		    ///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<class NM>
 		    Node processNextNode(const NM& nm, Node& rnode)
+		    {
 		      if(_queue_tail==_queue_next_dist) {
 		        _curr_dist++;
 		        _queue_next_dist=_queue_head;
+		      }
 		      Node n=_queue[_queue_tail++];
 		      _processed->set(n,true);
 		      Node m;
 		      for(OutArcIt e(*G,n);e!=INVALID;++e)
 		        if(!(*_reached)[m=G->target(e)]) {
 		          _queue[_queue_head++]=m;
 		          _reached->set(m,true);
 		          _pred->set(m,e);
 		          _dist->set(m,_curr_dist);
 		          if (nm[m] && rnode == INVALID) rnode = m;
+		        }
 		      return n;
+		    }
 		    ///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 _queue_tail<_queue_head?_queue[_queue_tail]:INVALID;
+		    }
 		    ///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 _queue_tail==_queue_head; }
 		    ///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 _queue_head-_queue_tail; }
 		    ///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();
+		    }
 		    ///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.
 		    ///
@@ -1236,386 +1236,386 @@
 		    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 GR The type of the digraph the algorithm runs on.
 		  template<class GR>
 		  struct BfsVisitDefaultTraits {
 		    /// \brief The type of the digraph the algorithm runs on.
 		    typedef GR 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 GR The type of the digraph the algorithm runs on.
 		  /// The default type is \ref ListDigraph.
 		  /// The value of GR is not used directly by \ref BfsVisit,
 		  /// it is only passed to \ref BfsVisitDefaultTraits.
 		  /// \tparam VS The Visitor type that is used by the algorithm.
 		  /// \ref BfsVisitor "BfsVisitor<GR>" 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 TR Traits class to set various data types used by the
 		  /// algorithm. The default traits class is
 		  /// \ref BfsVisitDefaultTraits "BfsVisitDefaultTraits<GR>".
 		  /// See \ref BfsVisitDefaultTraits for the documentation of
 		  /// a BFS visit traits class.
 		#ifdef DOXYGEN
 		  template <typename GR, typename VS, typename TR>
 		#else
 		  template <typename GR = ListDigraph,
 		            typename VS = BfsVisitor<GR>,
 		            typename TR = BfsVisitDefaultTraits<GR> >
 		#endif
 		  class BfsVisit {
 		  public:
 		    ///The traits class.
 		    typedef TR Traits;
 		    ///The type of the digraph the algorithm runs on.
 		    typedef typename Traits::Digraph Digraph;
 		    ///The visitor type used by the algorithm.
 		    typedef VS 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
 		    /// If you need better control on the execution, you have to call
 		    /// \ref init() first, then you can add several source nodes with
 		    /// \ref addSource(). Finally the actual path computation can be
 		    /// performed with one of the \ref start() functions.
 		    /// @{
 		    /// \brief Initializes the internal data structures.
 		    ///
 		    /// Initializes the internal data structures.
 		    void init() {
 		      create_maps();
 		      _list.resize(countNodes(*_digraph));
 		      _list_front = _list_back = -1;
 		      for (NodeIt u(*_digraph) ; u != INVALID ; ++u) {
 		        _reached->set(u, false);
+		      }
+		    }
 		    /// \brief Adds a new source node.
 		    ///
 		    /// Adds a new source node to the set of nodes to be processed.
 		    void addSource(Node s) {
 		      if(!(*_reached)[s]) {
 		          _reached->set(s,true);
 		          _visitor->start(s);
 		          _visitor->reach(s);
 		          _list[++_list_back] = s;
+		        }
+		    }
 		    /// \brief Processes the next node.
 		    ///
 		    /// Processes the next node.
 		    ///
 		    /// \return The processed node.
 		    ///
 		    /// \pre The queue must not be empty.
 		    Node processNextNode() {
 		      Node n = _list[++_list_front];
 		      _visitor->process(n);
 		      Arc e;
 		      for (_digraph->firstOut(e, n); e != INVALID; _digraph->nextOut(e)) {
 		        Node m = _digraph->target(e);
 		        if (!(*_reached)[m]) {
 		          _visitor->discover(e);
 		          _visitor->reach(m);
 		          _reached->set(m, true);
 		          _list[++_list_back] = m;
 		        } else {
 		          _visitor->examine(e);
+		        }
+		      }
 		      return n;
+		    }
 		    /// \brief Processes the next node.
 		    ///
 		    /// Processes the next node and checks if the given target node
 		    /// is reached. If the target node is reachable from the processed
 		    /// node, then the \c reach parameter will be set to \c true.
 		    ///
 		    /// \param target The target node.
 		    /// \retval reach Indicates if the target node is reached.
 		    /// It should be initially \c false.
 		    ///
 		    /// \return The processed node.
 		    ///
 		    /// \pre The queue must not be empty.
 		    Node processNextNode(Node target, bool& reach) {
 		      Node n = _list[++_list_front];
 		      _visitor->process(n);
 		      Arc e;
 		      for (_digraph->firstOut(e, n); e != INVALID; _digraph->nextOut(e)) {
 		        Node m = _digraph->target(e);
 		        if (!(*_reached)[m]) {
 		          _visitor->discover(e);
 		          _visitor->reach(m);
 		          _reached->set(m, true);
 		          _list[++_list_back] = m;
 		          reach = reach || (target == m);
 		        } else {
 		          _visitor->examine(e);
+		        }
+		      }
 		      return n;
+		    }
 		    /// \brief Processes the next node.
 		    ///
 		    /// Processes the next node and checks if at least one of reached
 		    /// nodes has \c true value in the \c nm node map. If one node
 		    /// with \c true value is reachable from the processed node, then the
 		    /// \c rnode parameter will be set to the first of such nodes.
 		    ///
 		    /// \param nm A \c bool (or convertible) node map that indicates the
 		    /// possible targets.
 		    /// \retval rnode The reached target node.
 		    /// 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.

lemon/circulation.h

Show inline comments

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

lemon/dfs.h

Show inline comments

@@ -222,386 +222,386 @@
 		    ///\brief \ref named-templ-param "Named parameter" for setting
 		    ///\c PredMap type.
 		    ///
 		    ///\ref named-templ-param "Named parameter" for setting
 		    ///\c PredMap type.
 		    ///It must meet the \ref concepts::WriteMap "WriteMap" concept.
 		    template <class T>
 		    struct SetPredMap : public Dfs<Digraph, SetPredMapTraits<T> > {
 		      typedef Dfs<Digraph, SetPredMapTraits<T> > Create;
 		    };
 		    template <class T>
 		    struct SetDistMapTraits : public Traits {
 		      typedef T DistMap;
 		      static DistMap *createDistMap(const Digraph &)
+		      {
 		        LEMON_ASSERT(false, "DistMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    ///\brief \ref named-templ-param "Named parameter" for setting
 		    ///\c DistMap type.
 		    ///
 		    ///\ref named-templ-param "Named parameter" for setting
 		    ///\c DistMap type.
 		    ///It must meet the \ref concepts::WriteMap "WriteMap" concept.
 		    template <class T>
 		    struct SetDistMap : public Dfs< Digraph, SetDistMapTraits<T> > {
 		      typedef Dfs<Digraph, SetDistMapTraits<T> > Create;
 		    };
 		    template <class T>
 		    struct SetReachedMapTraits : public Traits {
 		      typedef T ReachedMap;
 		      static ReachedMap *createReachedMap(const Digraph &)
+		      {
 		        LEMON_ASSERT(false, "ReachedMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    ///\brief \ref named-templ-param "Named parameter" for setting
 		    ///\c ReachedMap type.
 		    ///
 		    ///\ref named-templ-param "Named parameter" for setting
 		    ///\c ReachedMap type.
 		    ///It must meet the \ref concepts::ReadWriteMap "ReadWriteMap" concept.
 		    template <class T>
 		    struct SetReachedMap : public Dfs< Digraph, SetReachedMapTraits<T> > {
 		      typedef Dfs< Digraph, SetReachedMapTraits<T> > Create;
 		    };
 		    template <class T>
 		    struct SetProcessedMapTraits : public Traits {
 		      typedef T ProcessedMap;
 		      static ProcessedMap *createProcessedMap(const Digraph &)
+		      {
 		        LEMON_ASSERT(false, "ProcessedMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    ///\brief \ref named-templ-param "Named parameter" for setting
 		    ///\c ProcessedMap type.
 		    ///
 		    ///\ref named-templ-param "Named parameter" for setting
 		    ///\c ProcessedMap type.
 		    ///It must meet the \ref concepts::WriteMap "WriteMap" concept.
 		    template <class T>
 		    struct SetProcessedMap : public Dfs< Digraph, SetProcessedMapTraits<T> > {
 		      typedef Dfs< Digraph, SetProcessedMapTraits<T> > Create;
 		    };
 		    struct SetStandardProcessedMapTraits : public Traits {
 		      typedef typename Digraph::template NodeMap<bool> ProcessedMap;
 		      static ProcessedMap *createProcessedMap(const Digraph &g)
+		      {
 		        return new ProcessedMap(g);
+		      }
 		    };
 		    ///\brief \ref named-templ-param "Named parameter" for setting
 		    ///\c ProcessedMap type to be <tt>Digraph::NodeMap<bool></tt>.
 		    ///
 		    ///\ref named-templ-param "Named parameter" for setting
 		    ///\c ProcessedMap type to be <tt>Digraph::NodeMap<bool></tt>.
 		    ///If you don't set it explicitly, it will be automatically allocated.
 		    struct SetStandardProcessedMap :
 		      public Dfs< Digraph, SetStandardProcessedMapTraits > {
 		      typedef Dfs< Digraph, SetStandardProcessedMapTraits > Create;
 		    };
 		    ///@}
 		  public:
 		    ///Constructor.
 		    ///Constructor.
 		    ///\param g The digraph the algorithm runs on.
 		    Dfs(const Digraph &g) :
 		      G(&g),
 		      _pred(NULL), local_pred(false),
 		      _dist(NULL), local_dist(false),
 		      _reached(NULL), local_reached(false),
 		      _processed(NULL), local_processed(false)
 		    { }
 		    ///Destructor.
 		    ~Dfs()
+		    {
 		      if(local_pred) delete _pred;
 		      if(local_dist) delete _dist;
 		      if(local_reached) delete _reached;
 		      if(local_processed) delete _processed;
+		    }
 		    ///Sets the map that stores the predecessor arcs.
 		    ///Sets the map that stores the predecessor arcs.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dfs &predMap(PredMap &m)
+		    {
 		      if(local_pred) {
 		        delete _pred;
 		        local_pred=false;
+		      }
 		      _pred = &m;
 		      return *this;
+		    }
 		    ///Sets the map that indicates which nodes are reached.
 		    ///Sets the map that indicates which nodes are reached.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dfs &reachedMap(ReachedMap &m)
+		    {
 		      if(local_reached) {
 		        delete _reached;
 		        local_reached=false;
+		      }
 		      _reached = &m;
 		      return *this;
+		    }
 		    ///Sets the map that indicates which nodes are processed.
 		    ///Sets the map that indicates which nodes are processed.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dfs &processedMap(ProcessedMap &m)
+		    {
 		      if(local_processed) {
 		        delete _processed;
 		        local_processed=false;
+		      }
 		      _processed = &m;
 		      return *this;
+		    }
 		    ///Sets the map that stores the distances of the nodes.
 		    ///Sets the map that stores the distances of the nodes calculated by
 		    ///the algorithm.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dfs &distMap(DistMap &m)
+		    {
 		      if(local_dist) {
 		        delete _dist;
 		        local_dist=false;
+		      }
 		      _dist = &m;
 		      return *this;
+		    }
 		  public:
 		    ///\name Execution Control
 		    ///The simplest way to execute the DFS algorithm is to use one of the
 		    ///member functions called \ref run(Node) "run()".\n
 		    ///If you need more control on the execution, first you have to call
 		    ///\ref init(), then you can add a source node with \ref addSource()
 		    ///If you need better control on the execution, you have to call
 		    ///\ref init() first, then you can add a source node with \ref addSource()
 		    ///and perform the actual computation with \ref start().
 		    ///This procedure can be repeated if there are nodes that have not
 		    ///been reached.
 		    ///@{
 		    ///\brief Initializes the internal data structures.
 		    ///
 		    ///Initializes the internal data structures.
 		    void init()
+		    {
 		      create_maps();
 		      _stack.resize(countNodes(*G));
 		      _stack_head=-1;
 		      for ( NodeIt u(*G) ; u!=INVALID ; ++u ) {
 		        _pred->set(u,INVALID);
 		        _reached->set(u,false);
 		        _processed->set(u,false);
+		      }
+		    }
 		    ///Adds a new source node.
 		    ///Adds a new source node to the set of nodes to be processed.
 		    ///
 		    ///\pre The stack must be empty. Otherwise the algorithm gives
 		    ///wrong results. (One of the outgoing arcs of all the source nodes
 		    ///except for the last one will not be visited and distances will
 		    ///also be wrong.)
 		    void addSource(Node s)
+		    {
 		      LEMON_DEBUG(emptyQueue(), "The stack is not empty.");
 		      if(!(*_reached)[s])
+		        {
 		          _reached->set(s,true);
 		          _pred->set(s,INVALID);
 		          OutArcIt e(*G,s);
 		          if(e!=INVALID) {
 		            _stack[++_stack_head]=e;
 		            _dist->set(s,_stack_head);
+		          }
 		          else {
 		            _processed->set(s,true);
 		            _dist->set(s,0);
+		          }
+		        }
+		    }
 		    ///Processes the next arc.
 		    ///Processes the next arc.
 		    ///
 		    ///\return The processed arc.
 		    ///
 		    ///\pre The stack must not be empty.
 		    Arc processNextArc()
+		    {
 		      Node m;
 		      Arc e=_stack[_stack_head];
 		      if(!(*_reached)[m=G->target(e)]) {
 		        _pred->set(m,e);
 		        _reached->set(m,true);
 		        ++_stack_head;
 		        _stack[_stack_head] = OutArcIt(*G, m);
 		        _dist->set(m,_stack_head);
+		      }
 		      else {
 		        m=G->source(e);
 		        ++_stack[_stack_head];
+		      }
 		      while(_stack_head>=0 && _stack[_stack_head]==INVALID) {
 		        _processed->set(m,true);
 		        --_stack_head;
 		        if(_stack_head>=0) {
 		          m=G->source(_stack[_stack_head]);
 		          ++_stack[_stack_head];
+		        }
+		      }
 		      return e;
+		    }
 		    ///Next arc to be processed.
 		    ///Next arc to be processed.
 		    ///
 		    ///\return The next arc to be processed or \c INVALID if the stack
 		    ///is empty.
 		    OutArcIt nextArc() const
+		    {
 		      return _stack_head>=0?_stack[_stack_head]:INVALID;
+		    }
 		    ///Returns \c false if there are nodes to be processed.
 		    ///Returns \c false if there are nodes to be processed
 		    ///in the queue (stack).
 		    bool emptyQueue() const { return _stack_head<0; }
 		    ///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; }
 		    ///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();
+		    }
 		    ///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() && G->target(_stack[_stack_head])!=t )
 		        processNextArc();
+		    }
 		    ///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<class ArcBoolMap>
 		    Arc start(const ArcBoolMap &am)
+		    {
 		      while ( !emptyQueue() && !am[_stack[_stack_head]] )
 		        processNextArc();
 		      return emptyQueue() ? INVALID : _stack[_stack_head];
+		    }
 		    ///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);
@@ -1180,386 +1180,386 @@
 		    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 GR>
 		  struct DfsVisitDefaultTraits {
 		    /// \brief The type of the digraph the algorithm runs on.
 		    typedef GR 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 GR The type of the digraph the algorithm runs on.
 		  /// The default type is \ref ListDigraph.
 		  /// The value of GR is not used directly by \ref DfsVisit,
 		  /// it is only passed to \ref DfsVisitDefaultTraits.
 		  /// \tparam VS The Visitor type that is used by the algorithm.
 		  /// \ref DfsVisitor "DfsVisitor<GR>" 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 TR Traits class to set various data types used by the
 		  /// algorithm. The default traits class is
 		  /// \ref DfsVisitDefaultTraits "DfsVisitDefaultTraits<GR>".
 		  /// See \ref DfsVisitDefaultTraits for the documentation of
 		  /// a DFS visit traits class.
 		#ifdef DOXYGEN
 		  template <typename GR, typename VS, typename TR>
 		#else
 		  template <typename GR = ListDigraph,
 		            typename VS = DfsVisitor<GR>,
 		            typename TR = DfsVisitDefaultTraits<GR> >
 		#endif
 		  class DfsVisit {
 		  public:
 		    ///The traits class.
 		    typedef TR Traits;
 		    ///The type of the digraph the algorithm runs on.
 		    typedef typename Traits::Digraph Digraph;
 		    ///The visitor type used by the algorithm.
 		    typedef VS 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()
 		    /// If you need better control on the execution, you have to call
 		    /// \ref init() first, then you can add a source node with \ref addSource()
 		    /// and perform the actual computation with \ref start().
 		    /// This procedure can be repeated if there are nodes that have not
 		    /// been reached.
 		    /// @{
 		    /// \brief Initializes the internal data structures.
 		    ///
 		    /// Initializes the internal data structures.
 		    void init() {
 		      create_maps();
 		      _stack.resize(countNodes(*_digraph));
 		      _stack_head = -1;
 		      for (NodeIt u(*_digraph) ; u != INVALID ; ++u) {
 		        _reached->set(u, false);
+		      }
+		    }
 		    /// \brief Adds a new source node.
 		    ///
 		    /// Adds a new source node to the set of nodes to be processed.
 		    ///
 		    /// \pre The stack must be empty. Otherwise the algorithm gives
 		    /// wrong results. (One of the outgoing arcs of all the source nodes
 		    /// except for the last one will not be visited and distances will
 		    /// also be wrong.)
 		    void addSource(Node s)
+		    {
 		      LEMON_DEBUG(emptyQueue(), "The stack is not empty.");
 		      if(!(*_reached)[s]) {
 		          _reached->set(s,true);
 		          _visitor->start(s);
 		          _visitor->reach(s);
 		          Arc e;
 		          _digraph->firstOut(e, s);
 		          if (e != INVALID) {
 		            _stack[++_stack_head] = e;
 		          } else {
 		            _visitor->leave(s);
 		            _visitor->stop(s);
+		          }
+		        }
+		    }
 		    /// \brief Processes the next arc.
 		    ///
 		    /// Processes the next arc.
 		    ///
 		    /// \return The processed arc.
 		    ///
 		    /// \pre The stack must not be empty.
 		    Arc processNextArc() {
 		      Arc e = _stack[_stack_head];
 		      Node m = _digraph->target(e);
 		      if(!(*_reached)[m]) {
 		        _visitor->discover(e);
 		        _visitor->reach(m);
 		        _reached->set(m, true);
 		        _digraph->firstOut(_stack[++_stack_head], m);
 		      } else {
 		        _visitor->examine(e);
 		        m = _digraph->source(e);
 		        _digraph->nextOut(_stack[_stack_head]);
+		      }
 		      while (_stack_head>=0 && _stack[_stack_head] == INVALID) {
 		        _visitor->leave(m);
 		        --_stack_head;
 		        if (_stack_head >= 0) {
 		          _visitor->backtrack(_stack[_stack_head]);
 		          m = _digraph->source(_stack[_stack_head]);
 		          _digraph->nextOut(_stack[_stack_head]);
 		        } else {
 		          _visitor->stop(m);
+		        }
+		      }
 		      return e;
+		    }
 		    /// \brief Next arc to be processed.
 		    ///
 		    /// Next arc to be processed.
 		    ///
 		    /// \return The next arc to be processed or INVALID if the stack is
 		    /// empty.
 		    Arc nextArc() const {
 		      return _stack_head >= 0 ? _stack[_stack_head] : INVALID;
+		    }
 		    /// \brief Returns \c false if there are nodes
 		    /// to be processed.
 		    ///
 		    /// Returns \c false if there are nodes
 		    /// to be processed in the queue (stack).
 		    bool emptyQueue() const { return _stack_head < 0; }
 		    /// \brief Returns the number of the nodes to be processed.
 		    ///
 		    /// 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

lemon/dijkstra.h

Show inline comments

@@ -395,386 +395,386 @@
 		    ///using the \ref heap() function before calling \ref run(Node) "run()"
 		    ///or \ref init().
 		    ///\sa SetStandardHeap
 		    template <class H, class CR = typename Digraph::template NodeMap<int> >
 		    struct SetHeap
 		      : public Dijkstra< Digraph, LengthMap, SetHeapTraits<H, CR> > {
 		      typedef Dijkstra< Digraph, LengthMap, SetHeapTraits<H, CR> > Create;
 		    };
 		    template <class H, class CR>
 		    struct SetStandardHeapTraits : public Traits {
 		      typedef CR HeapCrossRef;
 		      typedef H Heap;
 		      static HeapCrossRef *createHeapCrossRef(const Digraph &G) {
 		        return new HeapCrossRef(G);
+		      }
 		      static Heap *createHeap(HeapCrossRef &R)
+		      {
 		        return new Heap(R);
+		      }
 		    };
 		    ///\brief \ref named-templ-param "Named parameter" for setting
 		    ///heap and cross reference types with automatic allocation
 		    ///
 		    ///\ref named-templ-param "Named parameter" for setting heap and cross
 		    ///reference types with automatic allocation.
 		    ///They should have standard constructor interfaces to be able to
 		    ///automatically created by the algorithm (i.e. the digraph should be
 		    ///passed to the constructor of the cross reference and the cross
 		    ///reference should be passed to the constructor of the heap).
 		    ///However external heap and cross reference objects could also be
 		    ///passed to the algorithm using the \ref heap() function before
 		    ///calling \ref run(Node) "run()" or \ref init().
 		    ///\sa SetHeap
 		    template <class H, class CR = typename Digraph::template NodeMap<int> >
 		    struct SetStandardHeap
 		      : public Dijkstra< Digraph, LengthMap, SetStandardHeapTraits<H, CR> > {
 		      typedef Dijkstra< Digraph, LengthMap, SetStandardHeapTraits<H, CR> >
 		      Create;
 		    };
 		    template <class T>
 		    struct SetOperationTraitsTraits : public Traits {
 		      typedef T OperationTraits;
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for setting
 		    ///\c OperationTraits type
 		    ///
 		    ///\ref named-templ-param "Named parameter" for setting
 		    ///\c OperationTraits type.
 		    template <class T>
 		    struct SetOperationTraits
 		      : public Dijkstra<Digraph, LengthMap, SetOperationTraitsTraits<T> > {
 		      typedef Dijkstra<Digraph, LengthMap, SetOperationTraitsTraits<T> >
 		      Create;
 		    };
 		    ///@}
 		  protected:
 		    Dijkstra() {}
 		  public:
 		    ///Constructor.
 		    ///Constructor.
 		    ///\param g The digraph the algorithm runs on.
 		    ///\param length The length map used by the algorithm.
 		    Dijkstra(const Digraph& g, const LengthMap& length) :
 		      G(&g), _length(&length),
 		      _pred(NULL), local_pred(false),
 		      _dist(NULL), local_dist(false),
 		      _processed(NULL), local_processed(false),
 		      _heap_cross_ref(NULL), local_heap_cross_ref(false),
 		      _heap(NULL), local_heap(false)
 		    { }
 		    ///Destructor.
 		    ~Dijkstra()
+		    {
 		      if(local_pred) delete _pred;
 		      if(local_dist) delete _dist;
 		      if(local_processed) delete _processed;
 		      if(local_heap_cross_ref) delete _heap_cross_ref;
 		      if(local_heap) delete _heap;
+		    }
 		    ///Sets the length map.
 		    ///Sets the length map.
 		    ///\return <tt> (*this) </tt>
 		    Dijkstra &lengthMap(const LengthMap &m)
+		    {
 		      _length = &m;
 		      return *this;
+		    }
 		    ///Sets the map that stores the predecessor arcs.
 		    ///Sets the map that stores the predecessor arcs.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dijkstra &predMap(PredMap &m)
+		    {
 		      if(local_pred) {
 		        delete _pred;
 		        local_pred=false;
+		      }
 		      _pred = &m;
 		      return *this;
+		    }
 		    ///Sets the map that indicates which nodes are processed.
 		    ///Sets the map that indicates which nodes are processed.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dijkstra &processedMap(ProcessedMap &m)
+		    {
 		      if(local_processed) {
 		        delete _processed;
 		        local_processed=false;
+		      }
 		      _processed = &m;
 		      return *this;
+		    }
 		    ///Sets the map that stores the distances of the nodes.
 		    ///Sets the map that stores the distances of the nodes calculated by the
 		    ///algorithm.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), an instance will be allocated automatically.
 		    ///The destructor deallocates this automatically allocated map,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dijkstra &distMap(DistMap &m)
+		    {
 		      if(local_dist) {
 		        delete _dist;
 		        local_dist=false;
+		      }
 		      _dist = &m;
 		      return *this;
+		    }
 		    ///Sets the heap and the cross reference used by algorithm.
 		    ///Sets the heap and the cross reference used by algorithm.
 		    ///If you don't use this function before calling \ref run(Node) "run()"
 		    ///or \ref init(), heap and cross reference instances will be
 		    ///allocated automatically.
 		    ///The destructor deallocates these automatically allocated objects,
 		    ///of course.
 		    ///\return <tt> (*this) </tt>
 		    Dijkstra &heap(Heap& hp, HeapCrossRef &cr)
+		    {
 		      if(local_heap_cross_ref) {
 		        delete _heap_cross_ref;
 		        local_heap_cross_ref=false;
+		      }
 		      _heap_cross_ref = &cr;
 		      if(local_heap) {
 		        delete _heap;
 		        local_heap=false;
+		      }
 		      _heap = &hp;
 		      return *this;
+		    }
 		  private:
 		    void finalizeNodeData(Node v,Value dst)
+		    {
 		      _processed->set(v,true);
 		      _dist->set(v, dst);
+		    }
 		  public:
 		    ///\name Execution Control
 		    ///The simplest way to execute the %Dijkstra algorithm is to use
 		    ///one of the member functions called \ref run(Node) "run()".\n
 		    ///If you need more control on the execution, first you have to call
 		    ///\ref init(), then you can add several source nodes with
 		    ///If you need better control on the execution, you have to call
 		    ///\ref init() first, then you can add several source nodes with
 		    ///\ref addSource(). Finally the actual path computation can be
 		    ///performed with one of the \ref start() functions.
 		    ///@{
 		    ///\brief Initializes the internal data structures.
 		    ///
 		    ///Initializes the internal data structures.
 		    void init()
+		    {
 		      create_maps();
 		      _heap->clear();
 		      for ( NodeIt u(*G) ; u!=INVALID ; ++u ) {
 		        _pred->set(u,INVALID);
 		        _processed->set(u,false);
 		        _heap_cross_ref->set(u,Heap::PRE_HEAP);
+		      }
+		    }
 		    ///Adds a new source node.
 		    ///Adds a new source node to the priority heap.
 		    ///The optional second parameter is the initial distance of the node.
 		    ///
 		    ///The function checks if the node has already been added to the heap and
 		    ///it is pushed to the heap only if either it was not in the heap
 		    ///or the shortest path found till then is shorter than \c dst.
 		    void addSource(Node s,Value dst=OperationTraits::zero())
+		    {
 		      if(_heap->state(s) != Heap::IN_HEAP) {
 		        _heap->push(s,dst);
 		      } else if(OperationTraits::less((*_heap)[s], dst)) {
 		        _heap->set(s,dst);
 		        _pred->set(s,INVALID);
+		      }
+		    }
 		    ///Processes the next node in the priority heap
 		    ///Processes the next node in the priority heap.
 		    ///
 		    ///\return The processed node.
 		    ///
 		    ///\warning The priority heap must not be empty.
 		    Node processNextNode()
+		    {
 		      Node v=_heap->top();
 		      Value oldvalue=_heap->prio();
 		      _heap->pop();
 		      finalizeNodeData(v,oldvalue);
 		      for(OutArcIt e(*G,v); e!=INVALID; ++e) {
 		        Node w=G->target(e);
 		        switch(_heap->state(w)) {
 		        case Heap::PRE_HEAP:
 		          _heap->push(w,OperationTraits::plus(oldvalue, (*_length)[e]));
 		          _pred->set(w,e);
 		          break;
 		        case Heap::IN_HEAP:
+		          {
 		            Value newvalue = OperationTraits::plus(oldvalue, (*_length)[e]);
 		            if ( OperationTraits::less(newvalue, (*_heap)[w]) ) {
 		              _heap->decrease(w, newvalue);
 		              _pred->set(w,e);
+		            }
+		          }
 		          break;
 		        case Heap::POST_HEAP:
 		          break;
+		        }
+		      }
 		      return v;
+		    }
 		    ///The next node to be processed.
 		    ///Returns the next node to be processed or \c INVALID if the
 		    ///priority heap is empty.
 		    Node nextNode() const
+		    {
 		      return !_heap->empty()?_heap->top():INVALID;
+		    }
 		    ///Returns \c false if there are nodes to be processed.
 		    ///Returns \c false if there are nodes to be processed
 		    ///in the priority heap.
 		    bool emptyQueue() const { return _heap->empty(); }
 		    ///Returns the number of the nodes to be processed.
 		    ///Returns the number of the nodes to be processed
 		    ///in the priority heap.
 		    int queueSize() const { return _heap->size(); }
 		    ///Executes the algorithm.
 		    ///Executes the algorithm.
 		    ///
 		    ///This method runs the %Dijkstra 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>d.start()</tt> is just a shortcut of the following code.
 		    ///\code
 		    ///  while ( !d.emptyQueue() ) {
 		    ///    d.processNextNode();
 		    ///  }
 		    ///\endcode
 		    void start()
+		    {
 		      while ( !emptyQueue() ) processNextNode();
+		    }
 		    ///Executes the algorithm until the given target node is processed.
 		    ///Executes the algorithm until the given target node is processed.
 		    ///
 		    ///This method runs the %Dijkstra 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.
 		    void start(Node t)
+		    {
 		      while ( !_heap->empty() && _heap->top()!=t ) processNextNode();
 		      if ( !_heap->empty() ) {
 		        finalizeNodeData(_heap->top(),_heap->prio());
 		        _heap->pop();
+		      }
+		    }
 		    ///Executes the algorithm until a condition is met.
 		    ///Executes the algorithm until a condition is met.
 		    ///
 		    ///This method runs the %Dijkstra 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 A \c 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.
 		    template<class NodeBoolMap>
 		    Node start(const NodeBoolMap &nm)
+		    {
 		      while ( !_heap->empty() && !nm[_heap->top()] ) processNextNode();
 		      if ( _heap->empty() ) return INVALID;
 		      finalizeNodeData(_heap->top(),_heap->prio());
 		      return _heap->top();
+		    }
 		    ///Runs the algorithm from the given source node.
 		    ///This method runs the %Dijkstra 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>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();
+		    }
 		    ///Finds the shortest path between \c s and \c t.
 		    ///This method runs the %Dijkstra algorithm from node \c s
 		    ///in order to compute the shortest path to node \c t

lemon/gomory_hu.h

Show inline comments

@@ -170,401 +170,401 @@
+			  }
+			}
 			if ((*_pred)[pn] != INVALID && fa.minCut((*_pred)[pn])) {
 			  (*_pred)[n] = (*_pred)[pn];
 			  (*_pred)[pn] = n;
 			  (*_weight)[n] = (*_weight)[pn];
 			  (*_weight)[pn] = fa.flowValue();
+			}
+		      }
 		      (*_order)[_root] = 0;
 		      int index = 1;
 		      for (NodeIt n(_graph); n != INVALID; ++n) {
 			std::vector<Node> st;
 			Node nn = n;
 			while ((*_order)[nn] == -1) {
 			  st.push_back(nn);
 			  nn = (*_pred)[nn];
+			}
 			while (!st.empty()) {
 			  (*_order)[st.back()] = index++;
 			  st.pop_back();
+			}
+		      }
+		    }
 		  public:
 		    ///\name Execution Control
 		    ///@{
 		    /// \brief Run the Gomory-Hu algorithm.
 		    ///
 		    /// This function runs the Gomory-Hu algorithm.
 		    void run() {
 		      init();
 		      start();
+		    }
 		    /// @}
 		    ///\name Query Functions
 		    ///The results of the algorithm can be obtained using these
 		    ///functions.\n
 		    ///\ref run() should be called before using them.\n
 		    ///See also \ref MinCutNodeIt and \ref MinCutEdgeIt.
 		    ///@{
 		    /// \brief Return the predecessor node in the Gomory-Hu tree.
 		    ///
 		    /// This function returns the predecessor node of the given node
 		    /// in the Gomory-Hu tree.
 		    /// If \c node is the root of the tree, then it returns \c INVALID.
 		    ///
 		    /// \pre \ref run() must be called before using this function.
 		    Node predNode(const Node& node) const {
 		      return (*_pred)[node];
+		    }
 		    /// \brief Return the weight of the predecessor edge in the
 		    /// Gomory-Hu tree.
 		    ///
 		    /// This function returns the weight of the predecessor edge of the
 		    /// given node in the Gomory-Hu tree.
 		    /// If \c node is the root of the tree, the result is undefined.
 		    ///
 		    /// \pre \ref run() must be called before using this function.
 		    Value predValue(const Node& node) const {
 		      return (*_weight)[node];
+		    }
 		    /// \brief Return the distance from the root node in the Gomory-Hu tree.
 		    ///
 		    /// This function returns the distance of the given node from the root
 		    /// node in the Gomory-Hu tree.
 		    ///
 		    /// \pre \ref run() must be called before using this function.
 		    int rootDist(const Node& node) const {
 		      return (*_order)[node];
+		    }
 		    /// \brief Return the minimum cut value between two nodes
 		    ///
 		    /// This function returns the minimum cut value between the nodes
 		    /// \c s and \c t.
 		    /// It finds the nearest common ancestor of the given nodes in the
 		    /// Gomory-Hu tree and calculates the minimum weight edge on the
 		    /// paths to the ancestor.
 		    ///
 		    /// \pre \ref run() must be called before using this function.
 		    Value minCutValue(const Node& s, const Node& t) const {
 		      Node sn = s, tn = t;
 		      Value value = std::numeric_limits<Value>::max();
 		      while (sn != tn) {
 			if ((*_order)[sn] < (*_order)[tn]) {
 			  if ((*_weight)[tn] <= value) value = (*_weight)[tn];
 			  tn = (*_pred)[tn];
 			} else {
 			  if ((*_weight)[sn] <= value) value = (*_weight)[sn];
 			  sn = (*_pred)[sn];
+			}
+		      }
 		      return value;
+		    }
 		    /// \brief Return the minimum cut between two nodes
 		    ///
 		    /// This function returns the minimum cut between the nodes \c s and \c t
 		    /// in the \c cutMap parameter by setting the nodes in the component of
 		    /// \c s to \c true and the other nodes to \c false.
 		    ///
 		    /// For higher level interfaces see MinCutNodeIt and MinCutEdgeIt.
 		    ///
 		    /// \param s The base node.
 		    /// \param t The node you want to separate from node \c s.
 		    /// \param cutMap The cut will be returned in this map.
 		    /// It must be a \c bool (or convertible) \ref concepts::ReadWriteMap
 		    /// "ReadWriteMap" on the graph nodes.
 		    ///
 		    /// \return The value of the minimum cut between \c s and \c t.
 		    ///
 		    /// \pre \ref run() must be called before using this function.
 		    template <typename CutMap>
 		    Value minCutMap(const Node& s, ///<
 		                    const Node& t,
 		                    ///<
 		                    CutMap& cutMap
 		                    ///<
 		                    ) const {
 		      Node sn = s, tn = t;
 		      bool s_root=false;
 		      Node rn = INVALID;
 		      Value value = std::numeric_limits<Value>::max();
 		      while (sn != tn) {
 			if ((*_order)[sn] < (*_order)[tn]) {
 			  if ((*_weight)[tn] <= value) {
 			    rn = tn;
 		            s_root = false;
 			    value = (*_weight)[tn];
+			  }
 			  tn = (*_pred)[tn];
 			} else {
 			  if ((*_weight)[sn] <= value) {
 			    rn = sn;
 		            s_root = true;
 			    value = (*_weight)[sn];
+			  }
 			  sn = (*_pred)[sn];
+			}
+		      }
 		      typename Graph::template NodeMap<bool> reached(_graph, false);
 		      reached[_root] = true;
 		      cutMap.set(_root, !s_root);
 		      reached[rn] = true;
 		      cutMap.set(rn, s_root);
 		      std::vector<Node> st;
 		      for (NodeIt n(_graph); n != INVALID; ++n) {
 			st.clear();
 		        Node nn = n;
 			while (!reached[nn]) {
 			  st.push_back(nn);
 			  nn = (*_pred)[nn];
+			}
 			while (!st.empty()) {
 			  cutMap.set(st.back(), cutMap[nn]);
 			  st.pop_back();
+			}
+		      }
 		      return value;
+		    }
 		    ///@}
 		    friend class MinCutNodeIt;
 		    /// Iterate on the nodes of a minimum cut
 		    /// This iterator class lists the nodes of a minimum cut found by
 		    /// GomoryHu. Before using it, you must allocate a GomoryHu class
 		    /// and call its \ref GomoryHu::run() "run()" method.
 		    ///
 		    /// This example counts the nodes in the minimum cut separating \c s from
 		    /// \c t.
 		    /// \code
-		    /// GomoruHu<Graph> gom(g, capacities);
+		    /// GomoryHu<Graph> gom(g, capacities);
 		    /// gom.run();
 		    /// int cnt=0;
-		    /// for(GomoruHu<Graph>::MinCutNodeIt n(gom,s,t); n!=INVALID; ++n) ++cnt;
+		    /// for(GomoryHu<Graph>::MinCutNodeIt n(gom,s,t); n!=INVALID; ++n) ++cnt;
 		    /// \endcode
 		    class MinCutNodeIt
+		    {
 		      bool _side;
 		      typename Graph::NodeIt _node_it;
 		      typename Graph::template NodeMap<bool> _cut;
 		    public:
 		      /// Constructor
 		      /// Constructor.
 		      ///
 		      MinCutNodeIt(GomoryHu const &gomory,
 		                   ///< The GomoryHu class. You must call its
 		                   ///  run() method
 		                   ///  before initializing this iterator.
 		                   const Node& s, ///< The base node.
 		                   const Node& t,
 		                   ///< The node you want to separate from node \c s.
 		                   bool side=true
 		                   ///< If it is \c true (default) then the iterator lists
 		                   ///  the nodes of the component containing \c s,
 		                   ///  otherwise it lists the other component.
 		                   /// \note As the minimum cut is not always unique,
 		                   /// \code
 		                   /// MinCutNodeIt(gomory, s, t, true);
 		                   /// \endcode
 		                   /// and
 		                   /// \code
 		                   /// MinCutNodeIt(gomory, t, s, false);
 		                   /// \endcode
 		                   /// does not necessarily give the same set of nodes.
 		                   /// However it is ensured that
 		                   /// \code
 		                   /// MinCutNodeIt(gomory, s, t, true);
 		                   /// \endcode
 		                   /// and
 		                   /// \code
 		                   /// MinCutNodeIt(gomory, s, t, false);
 		                   /// \endcode
 		                   /// together list each node exactly once.
+		                   )
 		        : _side(side), _cut(gomory._graph)
+		      {
 		        gomory.minCutMap(s,t,_cut);
 		        for(_node_it=typename Graph::NodeIt(gomory._graph);
 		            _node_it!=INVALID && _cut[_node_it]!=_side;
 		            ++_node_it) {}
+		      }
 		      /// Conversion to \c Node
 		      /// Conversion to \c Node.
 		      ///
 		      operator typename Graph::Node() const
+		      {
 		        return _node_it;
+		      }
 		      bool operator==(Invalid) { return _node_it==INVALID; }
 		      bool operator!=(Invalid) { return _node_it!=INVALID; }
 		      /// Next node
 		      /// Next node.
 		      ///
 		      MinCutNodeIt &operator++()
+		      {
 		        for(++_node_it;_node_it!=INVALID&&_cut[_node_it]!=_side;++_node_it) {}
 		        return *this;
+		      }
 		      /// Postfix incrementation
 		      /// Postfix incrementation.
 		      ///
 		      /// \warning This incrementation
 		      /// returns a \c Node, not a \c MinCutNodeIt, as one may
 		      /// expect.
 		      typename Graph::Node operator++(int)
+		      {
 		        typename Graph::Node n=*this;
 		        ++(*this);
 		        return n;
+		      }
 		    };
 		    friend class MinCutEdgeIt;
 		    /// Iterate on the edges of a minimum cut
 		    /// This iterator class lists the edges of a minimum cut found by
 		    /// GomoryHu. Before using it, you must allocate a GomoryHu class
 		    /// and call its \ref GomoryHu::run() "run()" method.
 		    ///
 		    /// This example computes the value of the minimum cut separating \c s from
 		    /// \c t.
 		    /// \code
-		    /// GomoruHu<Graph> gom(g, capacities);
+		    /// GomoryHu<Graph> gom(g, capacities);
 		    /// gom.run();
 		    /// int value=0;
-		    /// for(GomoruHu<Graph>::MinCutEdgeIt e(gom,s,t); e!=INVALID; ++e)
+		    /// for(GomoryHu<Graph>::MinCutEdgeIt e(gom,s,t); e!=INVALID; ++e)
 		    ///   value+=capacities[e];
 		    /// \endcode
 		    /// The result will be the same as the value returned by
 		    /// \ref GomoryHu::minCutValue() "gom.minCutValue(s,t)".
 		    class MinCutEdgeIt
+		    {
 		      bool _side;
 		      const Graph &_graph;
 		      typename Graph::NodeIt _node_it;
 		      typename Graph::OutArcIt _arc_it;
 		      typename Graph::template NodeMap<bool> _cut;
 		      void step()
+		      {
 		        ++_arc_it;
 		        while(_node_it!=INVALID && _arc_it==INVALID)
+		          {
 		            for(++_node_it;_node_it!=INVALID&&!_cut[_node_it];++_node_it) {}
 		            if(_node_it!=INVALID)
 		              _arc_it=typename Graph::OutArcIt(_graph,_node_it);
+		          }
+		      }
 		    public:
 		      /// Constructor
 		      /// Constructor.
 		      ///
 		      MinCutEdgeIt(GomoryHu const &gomory,
 		                   ///< The GomoryHu class. You must call its
 		                   ///  run() method
 		                   ///  before initializing this iterator.
 		                   const Node& s,  ///< The base node.
 		                   const Node& t,
 		                   ///< The node you want to separate from node \c s.
 		                   bool side=true
 		                   ///< If it is \c true (default) then the listed arcs
 		                   ///  will be oriented from the
 		                   ///  nodes of the component containing \c s,
 		                   ///  otherwise they will be oriented in the opposite
 		                   ///  direction.
+		                   )
 		        : _graph(gomory._graph), _cut(_graph)
+		      {
 		        gomory.minCutMap(s,t,_cut);
 		        if(!side)
 		          for(typename Graph::NodeIt n(_graph);n!=INVALID;++n)
 		            _cut[n]=!_cut[n];
 		        for(_node_it=typename Graph::NodeIt(_graph);
 		            _node_it!=INVALID && !_cut[_node_it];
 		            ++_node_it) {}
 		        _arc_it = _node_it!=INVALID ?
 		          typename Graph::OutArcIt(_graph,_node_it) : INVALID;
 		        while(_node_it!=INVALID && _arc_it == INVALID)
+		          {
 		            for(++_node_it; _node_it!=INVALID&&!_cut[_node_it]; ++_node_it) {}
 		            if(_node_it!=INVALID)
 		              _arc_it= typename Graph::OutArcIt(_graph,_node_it);
+		          }
 		        while(_arc_it!=INVALID && _cut[_graph.target(_arc_it)]) step();
+		      }
 		      /// Conversion to \c Arc
 		      /// Conversion to \c Arc.
 		      ///
 		      operator typename Graph::Arc() const
+		      {
 		        return _arc_it;
+		      }
 		      /// Conversion to \c Edge
 		      /// Conversion to \c Edge.
 		      ///
 		      operator typename Graph::Edge() const
+		      {
 		        return _arc_it;
+		      }
 		      bool operator==(Invalid) { return _node_it==INVALID; }
 		      bool operator!=(Invalid) { return _node_it!=INVALID; }
 		      /// Next edge
 		      /// Next edge.
 		      ///
 		      MinCutEdgeIt &operator++()
+		      {
 		        step();
 		        while(_arc_it!=INVALID && _cut[_graph.target(_arc_it)]) step();
 		        return *this;
+		      }
 		      /// Postfix incrementation
 		      /// Postfix incrementation.
 		      ///
 		      /// \warning This incrementation
 		      /// returns an \c Arc, not a \c MinCutEdgeIt, as one may expect.
 		      typename Graph::Arc operator++(int)
+		      {
 		        typename Graph::Arc e=*this;
 		        ++(*this);
 		        return e;
+		      }
 		    };
 		  };
+		}
 		#endif

lemon/min_cost_arborescence.h

Show inline comments

@@ -299,386 +299,386 @@
 		                       _dual_node_list.size(), minimum.value);
 		      _dual_variables.push_back(var);
 		      for (int i = 0; i < int(nodes.size()); ++i) {
 		        (*_cost_arcs)[nodes[i]].value -= minimum.value;
 		        level.arcs.push_back((*_cost_arcs)[nodes[i]]);
 		        (*_cost_arcs)[nodes[i]].arc = INVALID;
+		      }
 		      level_stack.push_back(level);
 		      return minimum.arc;
+		    }
 		    Arc contract(Node node) {
 		      int node_bottom = bottom(node);
 		      std::vector<Node> nodes;
 		      while (!level_stack.empty() &&
 		             level_stack.back().node_level >= node_bottom) {
 		        for (int i = 0; i < int(level_stack.back().arcs.size()); ++i) {
 		          Arc arc = level_stack.back().arcs[i].arc;
 		          Node source = _digraph->source(arc);
 		          Value value = level_stack.back().arcs[i].value;
 		          if ((*_node_order)[source] >= node_bottom) continue;
 		          if ((*_cost_arcs)[source].arc == INVALID) {
 		            (*_cost_arcs)[source].arc = arc;
 		            (*_cost_arcs)[source].value = value;
 		            nodes.push_back(source);
 		          } else {
 		            if ((*_cost_arcs)[source].value > value) {
 		              (*_cost_arcs)[source].arc = arc;
 		              (*_cost_arcs)[source].value = value;
+		            }
+		          }
+		        }
 		        level_stack.pop_back();
+		      }
 		      CostArc minimum = (*_cost_arcs)[nodes[0]];
 		      for (int i = 1; i < int(nodes.size()); ++i) {
 		        if ((*_cost_arcs)[nodes[i]].value < minimum.value) {
 		          minimum = (*_cost_arcs)[nodes[i]];
+		        }
+		      }
 		      (*_arc_order)[minimum.arc] = _dual_variables.size();
 		      DualVariable var(node_bottom, _dual_node_list.size(), minimum.value);
 		      _dual_variables.push_back(var);
 		      StackLevel level;
 		      level.node_level = node_bottom;
 		      for (int i = 0; i < int(nodes.size()); ++i) {
 		        (*_cost_arcs)[nodes[i]].value -= minimum.value;
 		        level.arcs.push_back((*_cost_arcs)[nodes[i]]);
 		        (*_cost_arcs)[nodes[i]].arc = INVALID;
+		      }
 		      level_stack.push_back(level);
 		      return minimum.arc;
+		    }
 		    int bottom(Node node) {
 		      int k = level_stack.size() - 1;
 		      while (level_stack[k].node_level > (*_node_order)[node]) {
 		        --k;
+		      }
 		      return level_stack[k].node_level;
+		    }
 		    void finalize(Arc arc) {
 		      Node node = _digraph->target(arc);
 		      _heap->push(node, (*_arc_order)[arc]);
 		      _pred->set(node, arc);
 		      while (!_heap->empty()) {
 		        Node source = _heap->top();
 		        _heap->pop();
 		        (*_node_order)[source] = -1;
 		        for (OutArcIt it(*_digraph, source); it != INVALID; ++it) {
 		          if ((*_arc_order)[it] < 0) continue;
 		          Node target = _digraph->target(it);
 		          switch(_heap->state(target)) {
 		          case Heap::PRE_HEAP:
 		            _heap->push(target, (*_arc_order)[it]);
 		            _pred->set(target, it);
 		            break;
 		          case Heap::IN_HEAP:
 		            if ((*_arc_order)[it] < (*_heap)[target]) {
 		              _heap->decrease(target, (*_arc_order)[it]);
 		              _pred->set(target, it);
+		            }
 		            break;
 		          case Heap::POST_HEAP:
 		            break;
+		          }
+		        }
 		        _arborescence->set((*_pred)[source], true);
+		      }
+		    }
 		  public:
 		    /// \name Named Template Parameters
 		    /// @{
 		    template <class T>
 		    struct SetArborescenceMapTraits : public Traits {
 		      typedef T ArborescenceMap;
 		      static ArborescenceMap *createArborescenceMap(const Digraph &)
+		      {
 		        LEMON_ASSERT(false, "ArborescenceMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for
 		    /// setting \c ArborescenceMap type
 		    ///
 		    /// \ref named-templ-param "Named parameter" for setting
 		    /// \c ArborescenceMap type.
 		    /// It must conform to the \ref concepts::WriteMap "WriteMap" concept,
 		    /// and its value type must be \c bool (or convertible).
 		    /// Initially it will be set to \c false on each arc,
 		    /// then it will be set on each arborescence arc once.
 		    template <class T>
 		    struct SetArborescenceMap
 		      : public MinCostArborescence<Digraph, CostMap,
 		                                   SetArborescenceMapTraits<T> > {
 		    };
 		    template <class T>
 		    struct SetPredMapTraits : public Traits {
 		      typedef T PredMap;
 		      static PredMap *createPredMap(const Digraph &)
+		      {
 		        LEMON_ASSERT(false, "PredMap is not initialized");
 		        return 0; // ignore warnings
+		      }
 		    };
 		    /// \brief \ref named-templ-param "Named parameter" for
 		    /// setting \c PredMap type
 		    ///
 		    /// \ref named-templ-param "Named parameter" for setting
 		    /// \c PredMap type.
 		    /// It must meet the \ref concepts::WriteMap "WriteMap" concept,
 		    /// and its value type must be the \c Arc type of the digraph.
 		    template <class T>
 		    struct SetPredMap
 		      : public MinCostArborescence<Digraph, CostMap, SetPredMapTraits<T> > {
 		    };
 		    /// @}
 		    /// \brief Constructor.
 		    ///
 		    /// \param digraph The digraph the algorithm will run on.
 		    /// \param cost The cost map used by the algorithm.
 		    MinCostArborescence(const Digraph& digraph, const CostMap& cost)
 		      : _digraph(&digraph), _cost(&cost), _pred(0), local_pred(false),
 		        _arborescence(0), local_arborescence(false),
 		        _arc_order(0), _node_order(0), _cost_arcs(0),
 		        _heap_cross_ref(0), _heap(0) {}
 		    /// \brief Destructor.
 		    ~MinCostArborescence() {
 		      destroyStructures();
+		    }
 		    /// \brief Sets the arborescence map.
 		    ///
 		    /// Sets the arborescence map.
 		    /// \return <tt>(*this)</tt>
 		    MinCostArborescence& arborescenceMap(ArborescenceMap& m) {
 		      if (local_arborescence) {
 		        delete _arborescence;
+		      }
 		      local_arborescence = false;
 		      _arborescence = &m;
 		      return *this;
+		    }
 		    /// \brief Sets the predecessor map.
 		    ///
 		    /// Sets the predecessor map.
 		    /// \return <tt>(*this)</tt>
 		    MinCostArborescence& predMap(PredMap& m) {
 		      if (local_pred) {
 		        delete _pred;
+		      }
 		      local_pred = false;
 		      _pred = &m;
 		      return *this;
+		    }
 		    /// \name Execution Control
 		    /// The simplest way to execute the algorithm is to use
 		    /// one of the member functions called \c run(...). \n
 		    /// If you need more control on the execution,
 		    /// first you must call \ref init(), then you can add several
 		    /// If you need better control on the execution,
 		    /// you have to call \ref init() first, then you can add several
 		    /// source nodes with \ref addSource().
 		    /// Finally \ref start() will perform the arborescence
 		    /// computation.
 		    ///@{
 		    /// \brief Initializes the internal data structures.
 		    ///
 		    /// Initializes the internal data structures.
 		    ///
 		    void init() {
 		      createStructures();
 		      _heap->clear();
 		      for (NodeIt it(*_digraph); it != INVALID; ++it) {
 		        (*_cost_arcs)[it].arc = INVALID;
 		        (*_node_order)[it] = -3;
 		        (*_heap_cross_ref)[it] = Heap::PRE_HEAP;
 		        _pred->set(it, INVALID);
+		      }
 		      for (ArcIt it(*_digraph); it != INVALID; ++it) {
 		        _arborescence->set(it, false);
 		        (*_arc_order)[it] = -1;
+		      }
 		      _dual_node_list.clear();
 		      _dual_variables.clear();
+		    }
 		    /// \brief Adds a new source node.
 		    ///
 		    /// Adds a new source node to the algorithm.
 		    void addSource(Node source) {
 		      std::vector<Node> nodes;
 		      nodes.push_back(source);
 		      while (!nodes.empty()) {
 		        Node node = nodes.back();
 		        nodes.pop_back();
 		        for (OutArcIt it(*_digraph, node); it != INVALID; ++it) {
 		          Node target = _digraph->target(it);
 		          if ((*_node_order)[target] == -3) {
 		            (*_node_order)[target] = -2;
 		            nodes.push_back(target);
 		            queue.push_back(target);
+		          }
+		        }
+		      }
 		      (*_node_order)[source] = -1;
+		    }
 		    /// \brief Processes the next node in the priority queue.
 		    ///
 		    /// Processes the next node in the priority queue.
 		    ///
 		    /// \return The processed node.
 		    ///
 		    /// \warning The queue must not be empty.
 		    Node processNextNode() {
 		      Node node = queue.back();
 		      queue.pop_back();
 		      if ((*_node_order)[node] == -2) {
 		        Arc arc = prepare(node);
 		        Node source = _digraph->source(arc);
 		        while ((*_node_order)[source] != -1) {
 		          if ((*_node_order)[source] >= 0) {
 		            arc = contract(source);
 		          } else {
 		            arc = prepare(source);
+		          }
 		          source = _digraph->source(arc);
+		        }
 		        finalize(arc);
 		        level_stack.clear();
+		      }
 		      return node;
+		    }
 		    /// \brief Returns the number of the nodes to be processed.
 		    ///
 		    /// Returns the number of the nodes to be processed in the priority
 		    /// queue.
 		    int queueSize() const {
 		      return queue.size();
+		    }
 		    /// \brief Returns \c false if there are nodes to be processed.
 		    ///
 		    /// Returns \c false if there are nodes to be processed.
 		    bool emptyQueue() const {
 		      return queue.empty();
+		    }
 		    /// \brief Executes the algorithm.
 		    ///
 		    /// Executes the algorithm.
 		    ///
 		    /// \pre init() must be called and at least one node should be added
 		    /// with addSource() before using this function.
 		    ///
 		    ///\note mca.start() is just a shortcut of the following code.
 		    ///\code
 		    ///while (!mca.emptyQueue()) {
 		    ///  mca.processNextNode();
 		    ///}
 		    ///\endcode
 		    void start() {
 		      while (!emptyQueue()) {
 		        processNextNode();
+		      }
+		    }
 		    /// \brief Runs %MinCostArborescence algorithm from node \c s.
 		    ///
 		    /// This method runs the %MinCostArborescence algorithm from
 		    /// a root node \c s.
 		    ///
 		    /// \note mca.run(s) is just a shortcut of the following code.
 		    /// \code
 		    /// mca.init();
 		    /// mca.addSource(s);
 		    /// mca.start();
 		    /// \endcode
 		    void run(Node s) {
 		      init();
 		      addSource(s);
 		      start();
+		    }
 		    ///@}
 		    /// \name Query Functions
 		    /// The result of the %MinCostArborescence algorithm can be obtained
 		    /// using these functions.\n
 		    /// Either run() or start() must be called before using them.
 		    /// @{
 		    /// \brief Returns the cost of the arborescence.
 		    ///
 		    /// Returns the cost of the arborescence.
 		    Value arborescenceCost() const {
 		      Value sum = 0;
 		      for (ArcIt it(*_digraph); it != INVALID; ++it) {
 		        if (arborescence(it)) {
 		          sum += (*_cost)[it];
+		        }
+		      }
 		      return sum;
+		    }
 		    /// \brief Returns \c true if the arc is in the arborescence.
 		    ///
 		    /// Returns \c true if the given arc is in the arborescence.
 		    /// \param arc An arc of the digraph.
 		    /// \pre \ref run() must be called before using this function.
 		    bool arborescence(Arc arc) const {
 		      return (*_pred)[_digraph->target(arc)] == arc;
+		    }
 		    /// \brief Returns a const reference to the arborescence map.
 		    ///
 		    /// Returns a const reference to the arborescence map.
 		    /// \pre \ref run() must be called before using this function.
 		    const ArborescenceMap& arborescenceMap() const {
 		      return *_arborescence;
+		    }
 		    /// \brief Returns the predecessor arc of the given node.
 		    ///
 		    /// Returns the predecessor arc of the given node.
 		    /// \pre \ref run() must be called before using this function.
 		    Arc pred(Node node) const {
 		      return (*_pred)[node];
+		    }
 		    /// \brief Returns a const reference to the pred map.
 		    ///
 		    /// Returns a const reference to the pred map.
 		    /// \pre \ref run() must be called before using this function.
 		    const PredMap& predMap() const {
 		      return *_pred;
+		    }
 		    /// \brief Indicates that a node is reachable from the sources.
 		    ///
 		    /// Indicates that a node is reachable from the sources.
 		    bool reached(Node node) const {
 		      return (*_node_order)[node] != -3;
+		    }
 		    /// \brief Indicates that a node is processed.
 		    ///
 		    /// Indicates that a node is processed. The arborescence path exists
 		    /// from the source to the given node.

lemon/preflow.h

Show inline comments

 		/* -*- mode: C++; indent-tabs-mode: nil; -*-
+		 *
 		 * This file is a part of LEMON, a generic C++ optimization library.
+		 *
 		 * Copyright (C) 2003-2009
 		 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
 		 * (Egervary Research Group on Combinatorial Optimization, EGRES).
+		 *
 		 * Permission to use, modify and distribute this software is granted
 		 * provided that this copyright notice appears in all copies. For
 		 * precise terms see the accompanying LICENSE file.
+		 *
 		 * This software is provided "AS IS" with no warranty of any kind,
 		 * express or implied, and with no claim as to its suitability for any
 		 * purpose.
+		 *
 		 */
 		#ifndef LEMON_PREFLOW_H
 		#define LEMON_PREFLOW_H
 		#include <lemon/tolerance.h>
 		#include <lemon/elevator.h>
 		/// \file
 		/// \ingroup max_flow
 		/// \brief Implementation of the preflow algorithm.
 		namespace lemon {
 		  /// \brief Default traits class of Preflow class.
 		  ///
 		  /// Default traits class of Preflow class.
 		  /// \tparam GR Digraph type.
 		  /// \tparam CAP Capacity map type.
 		  template <typename GR, typename CAP>
 		  struct PreflowDefaultTraits {
 		    /// \brief The type of the digraph the algorithm runs on.
 		    typedef GR Digraph;
 		    /// \brief The type of the map that stores the arc capacities.
 		    ///
 		    /// The type of the map that stores the arc capacities.
 		    /// It must meet the \ref concepts::ReadMap "ReadMap" concept.
 		    typedef CAP CapacityMap;
 		    /// \brief The type of the flow values.
 		    typedef typename CapacityMap::Value Value;
 		    /// \brief The type of the map that stores the flow values.
 		    ///
 		    /// The type of the map that stores the flow values.
 		    /// It must meet the \ref concepts::ReadWriteMap "ReadWriteMap" concept.
 		#ifdef DOXYGEN
 		    typedef GR::ArcMap<Value> FlowMap;
 		#else
 		    typedef typename Digraph::template ArcMap<Value> FlowMap;
 		#endif
 		    /// \brief Instantiates a FlowMap.
 		    ///
 		    /// This function instantiates a \ref FlowMap.
 		    /// \param digraph The digraph for which we would like to define
 		    /// the flow map.
 		    static FlowMap* createFlowMap(const Digraph& digraph) {
 		      return new FlowMap(digraph);
+		    }
 		    /// \brief The elevator type used by Preflow algorithm.
 		    ///
 		    /// The elevator type used by Preflow algorithm.
 		    ///
 		    /// \sa Elevator
 		    /// \sa LinkedElevator
-		    typedef LinkedElevator<Digraph, typename Digraph::Node> Elevator;
+		    /// \sa Elevator, LinkedElevator
 		#ifdef DOXYGEN
 		    typedef lemon::Elevator<GR, GR::Node> Elevator;
 		#else
 		    typedef lemon::Elevator<Digraph, typename Digraph::Node> Elevator;
 		#endif
 		    /// \brief Instantiates an Elevator.
 		    ///
 		    /// This function instantiates an \ref Elevator.
 		    /// \param digraph The digraph for which we would like to define
 		    /// the elevator.
 		    /// \param max_level The maximum level of the elevator.
 		    static Elevator* createElevator(const Digraph& digraph, int max_level) {
 		      return new Elevator(digraph, max_level);
+		    }
 		    /// \brief The tolerance used by the algorithm
 		    ///
 		    /// The tolerance used by the algorithm to handle inexact computation.
 		    typedef lemon::Tolerance<Value> Tolerance;
 		  };
 		  /// \ingroup max_flow
 		  ///
 		  /// \brief %Preflow algorithm class.
 		  ///
 		  /// This class provides an implementation of Goldberg-Tarjan's \e preflow
 		  /// \e push-relabel algorithm producing a \ref max_flow
 		  /// "flow of maximum value" in a digraph.
 		  /// The preflow algorithms are the fastest known maximum
 		  /// flow algorithms. The current implementation use a mixture of the
 		  /// \e "highest label" and the \e "bound decrease" heuristics.
 		  /// The worst case time complexity of the algorithm is \f$O(n^2\sqrt{e})\f$.
 		  ///
 		  /// The algorithm consists of two phases. After the first phase
 		  /// the maximum flow value and the minimum cut is obtained. The
 		  /// second phase constructs a feasible maximum flow on each arc.
 		  ///
 		  /// \tparam GR The type of the digraph the algorithm runs on.
 		  /// \tparam CAP The type of the capacity map. The default map
 		  /// type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
 		#ifdef DOXYGEN
 		  template <typename GR, typename CAP, typename TR>
 		#else
 		  template <typename GR,
 		            typename CAP = typename GR::template ArcMap<int>,
 		            typename TR = PreflowDefaultTraits<GR, CAP> >
 		#endif
 		  class Preflow {
 		  public:
 		    ///The \ref PreflowDefaultTraits "traits class" of the algorithm.
 		    typedef TR Traits;
 		    ///The type of the digraph the algorithm runs on.
 		    typedef typename Traits::Digraph Digraph;
 		    ///The type of the capacity map.
 		    typedef typename Traits::CapacityMap CapacityMap;
 		    ///The type of the flow values.
 		    typedef typename Traits::Value Value;
 		    ///The type of the flow map.
 		    typedef typename Traits::FlowMap FlowMap;
 		    ///The type of the elevator.
 		    typedef typename Traits::Elevator Elevator;
 		    ///The type of the tolerance.
 		    typedef typename Traits::Tolerance Tolerance;
 		  private:
 		    TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
 		    const Digraph& _graph;
 		    const CapacityMap* _capacity;
 		    int _node_num;
 		    Node _source, _target;
 		    FlowMap* _flow;
 		    bool _local_flow;
 		    Elevator* _level;
 		    bool _local_level;
 		    typedef typename Digraph::template NodeMap<Value> ExcessMap;
 		    ExcessMap* _excess;
 		    Tolerance _tolerance;
 		    bool _phase;
 		    void createStructures() {
 		      _node_num = countNodes(_graph);
 		      if (!_flow) {
 		        _flow = Traits::createFlowMap(_graph);
 		        _local_flow = true;
+		      }
 		      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 T>
 		    struct SetFlowMapTraits : public Traits {
 		      typedef T 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 T>
 		    struct SetFlowMap
 		      : public Preflow<Digraph, CapacityMap, SetFlowMapTraits<T> > {
 		      typedef Preflow<Digraph, CapacityMap,
 		                      SetFlowMapTraits<T> > Create;
 		    };
 		    template <typename T>
 		    struct SetElevatorTraits : public Traits {
 		      typedef T 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 T>
 		    struct SetElevator
 		      : public Preflow<Digraph, CapacityMap, SetElevatorTraits<T> > {
 		      typedef Preflow<Digraph, CapacityMap,
 		                      SetElevatorTraits<T> > Create;
 		    };
 		    template <typename T>
 		    struct SetStandardElevatorTraits : public Traits {
 		      typedef T 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 T>
 		    struct SetStandardElevator
 		      : public Preflow<Digraph, CapacityMap,
 		                       SetStandardElevatorTraits<T> > {
 		      typedef Preflow<Digraph, CapacityMap,
 		                      SetStandardElevatorTraits<T> > 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 {
 		      return *_level;
+		    }
 		    /// \brief Sets the tolerance used by algorithm.
 		    ///
 		    /// Sets the tolerance used by algorithm.
 		    Preflow& tolerance(const Tolerance& tolerance) const {
 		      _tolerance = tolerance;
 		      return *this;
+		    }
 		    /// \brief Returns a const reference to the tolerance.
 		    ///
 		    /// Returns a const reference to the tolerance.
 		    const Tolerance& tolerance() const {
 		      return tolerance;
+		    }
 		    /// \name Execution Control
 		    /// The simplest way to execute the preflow algorithm is to use
 		    /// \ref run() or \ref runMinCut().\n
 		    /// If you need more control on the initial solution or the execution,
 		    /// first you have to call one of the \ref init() functions, then
 		    /// If you need better control on the initial solution or the execution,
 		    /// you have to call one of the \ref init() functions first, then
 		    /// \ref startFirstPhase() and if you need it \ref startSecondPhase().
 		    ///@{
 		    /// \brief Initializes the internal data structures.
 		    ///
 		    /// Initializes the internal data structures and sets the initial
 		    /// flow to zero on each arc.
 		    void init() {
 		      createStructures();
 		      _phase = true;
 		      for (NodeIt n(_graph); n != INVALID; ++n) {
 		        (*_excess)[n] = 0;
+		      }
 		      for (ArcIt e(_graph); e != INVALID; ++e) {
 		        _flow->set(e, 0);
+		      }
 		      typename Digraph::template NodeMap<bool> reached(_graph, false);
 		      _level->initStart();
 		      _level->initAddItem(_target);
 		      std::vector<Node> queue;
 		      reached[_source] = true;
 		      queue.push_back(_target);
 		      reached[_target] = true;
 		      while (!queue.empty()) {
 		        _level->initNewLevel();
 		        std::vector<Node> nqueue;
 		        for (int i = 0; i < int(queue.size()); ++i) {
 		          Node n = queue[i];
 		          for (InArcIt e(_graph, n); e != INVALID; ++e) {
 		            Node u = _graph.source(e);
 		            if (!reached[u] && _tolerance.positive((*_capacity)[e])) {
 		              reached[u] = true;
 		              _level->initAddItem(u);
 		              nqueue.push_back(u);
+		            }
+		          }
+		        }
 		        queue.swap(nqueue);
+		      }
 		      _level->initFinish();
 		      for (OutArcIt e(_graph, _source); e != INVALID; ++e) {
 		        if (_tolerance.positive((*_capacity)[e])) {
 		          Node u = _graph.target(e);
 		          if ((*_level)[u] == _level->maxLevel()) continue;
 		          _flow->set(e, (*_capacity)[e]);
 		          (*_excess)[u] += (*_capacity)[e];
 		          if (u != _target && !_level->active(u)) {
 		            _level->activate(u);
+		          }
+		        }
+		      }
+		    }
 		    /// \brief Initializes the internal data structures using the
 		    /// given flow map.
 		    ///
 		    /// Initializes the internal data structures and sets the initial
 		    /// flow to the given \c flowMap. The \c flowMap should contain a
 		    /// flow or at least a preflow, i.e. at each node excluding the
 		    /// source node the incoming flow should greater or equal to the
 		    /// outgoing flow.
 		    /// \return \c false if the given \c flowMap is not a preflow.
 		    template <typename FlowMap>
 		    bool init(const FlowMap& flowMap) {
 		      createStructures();
 		      for (ArcIt e(_graph); e != INVALID; ++e) {
 		        _flow->set(e, flowMap[e]);
+		      }
 		      for (NodeIt n(_graph); n != INVALID; ++n) {
 		        Value excess = 0;
 		        for (InArcIt e(_graph, n); e != INVALID; ++e) {
 		          excess += (*_flow)[e];
+		        }
 		        for (OutArcIt e(_graph, n); e != INVALID; ++e) {
 		          excess -= (*_flow)[e];
+		        }
 		        if (excess < 0 && n != _source) return false;
 		        (*_excess)[n] = excess;
+		      }
 		      typename Digraph::template NodeMap<bool> reached(_graph, false);
 		      _level->initStart();
 		      _level->initAddItem(_target);
 		      std::vector<Node> queue;
 		      reached[_source] = true;
 		      queue.push_back(_target);
 		      reached[_target] = true;
 		      while (!queue.empty()) {
 		        _level->initNewLevel();
 		        std::vector<Node> nqueue;
 		        for (int i = 0; i < int(queue.size()); ++i) {
 		          Node n = queue[i];
 		          for (InArcIt e(_graph, n); e != INVALID; ++e) {
 		            Node u = _graph.source(e);
 		            if (!reached[u] &&
 		                _tolerance.positive((*_capacity)[e] - (*_flow)[e])) {
 		              reached[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[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)[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)[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)[v] += excess;
 		                excess = 0;
 		                goto no_more_push_1;
 		              } else {
 		                excess -= rem;
 		                (*_excess)[v] += rem;

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