diff -r a1a6f5b788bd -r cb7a6e0573bc lemon/graph_adaptor.h
--- a/lemon/graph_adaptor.h	Fri Feb 03 12:20:10 2006 +0000
+++ b/lemon/graph_adaptor.h	Fri Feb 03 14:07:52 2006 +0000
@@ -38,25 +38,25 @@
 
 namespace lemon {
 
-  //x\brief Base type for the Graph Adaptors
-  //x\ingroup graph_adaptors
-  //x    
-  //xBase type for the Graph Adaptors
-  //x    
-  //x\warning Graph adaptors are in even
-  //xmore experimental state than the other
-  //xparts of the lib. Use them at you own risk.
-  //x
-  //xThis is the base type for most of LEMON graph adaptors. 
-  //xThis class implements a trivial graph adaptor i.e. it only wraps the 
-  //xfunctions and types of the graph. The purpose of this class is to 
-  //xmake easier implementing graph adaptors. E.g. if an adaptor is 
-  //xconsidered which differs from the wrapped graph only in some of its 
-  //xfunctions or types, then it can be derived from GraphAdaptor,
-  //xand only the 
-  //xdifferences should be implemented.
-  //x
-  //xauthor Marton Makai 
+  ///\brief Base type for the Graph Adaptors
+  ///\ingroup graph_adaptors
+  ///
+  ///Base type for the Graph Adaptors
+  ///
+  ///\warning Graph adaptors are in even
+  ///more experimental state than the other
+  ///parts of the lib. Use them at you own risk.
+  ///
+  ///This is the base type for most of LEMON graph adaptors. 
+  ///This class implements a trivial graph adaptor i.e. it only wraps the 
+  ///functions and types of the graph. The purpose of this class is to 
+  ///make easier implementing graph adaptors. E.g. if an adaptor is 
+  ///considered which differs from the wrapped graph only in some of its 
+  ///functions or types, then it can be derived from GraphAdaptor,
+  ///and only the 
+  ///differences should be implemented.
+  ///
+  ///author Marton Makai 
   template<typename _Graph>
   class GraphAdaptorBase {
   public:
@@ -280,44 +280,44 @@
 	     || !(*node_filter_map)[Parent::target(i)])) Parent::nextOut(i); 
     }
 
-    //x\e
+    ///\e
 
-    //x This function hides \c n in the graph, i.e. the iteration 
-    //x jumps over it. This is done by simply setting the value of \c n  
-    //x to be false in the corresponding node-map.
+    /// This function hides \c n in the graph, i.e. the iteration 
+    /// jumps over it. This is done by simply setting the value of \c n  
+    /// to be false in the corresponding node-map.
     void hide(const Node& n) const { node_filter_map->set(n, false); }
 
-    //x\e
+    ///\e
 
-    //x This function hides \c e in the graph, i.e. the iteration 
-    //x jumps over it. This is done by simply setting the value of \c e  
-    //x to be false in the corresponding edge-map.
+    /// This function hides \c e in the graph, i.e. the iteration 
+    /// jumps over it. This is done by simply setting the value of \c e  
+    /// to be false in the corresponding edge-map.
     void hide(const Edge& e) const { edge_filter_map->set(e, false); }
 
-    //x\e
+    ///\e
 
-    //x The value of \c n is set to be true in the node-map which stores 
-    //x hide information. If \c n was hidden previuosly, then it is shown 
-    //x again
+    /// The value of \c n is set to be true in the node-map which stores 
+    /// hide information. If \c n was hidden previuosly, then it is shown 
+    /// again
      void unHide(const Node& n) const { node_filter_map->set(n, true); }
 
-    //x\e
+    ///\e
 
-    //x The value of \c e is set to be true in the edge-map which stores 
-    //x hide information. If \c e was hidden previuosly, then it is shown 
-    //x again
+    /// The value of \c e is set to be true in the edge-map which stores 
+    /// hide information. If \c e was hidden previuosly, then it is shown 
+    /// again
     void unHide(const Edge& e) const { edge_filter_map->set(e, true); }
 
-    //x Returns true if \c n is hidden.
+    /// Returns true if \c n is hidden.
     
-    //x\e
-    //x
+    ///\e
+    ///
     bool hidden(const Node& n) const { return !(*node_filter_map)[n]; }
 
-    //x Returns true if \c n is hidden.
+    /// Returns true if \c n is hidden.
     
-    //x\e
-    //x
+    ///\e
+    ///
     bool hidden(const Edge& e) const { return !(*edge_filter_map)[e]; }
 
     typedef False NodeNumTag;
@@ -386,111 +386,110 @@
       while (i!=INVALID && !(*edge_filter_map)[i]) Parent::nextOut(i); 
     }
 
-    //x\e
+    ///\e
 
-    //x This function hides \c n in the graph, i.e. the iteration 
-    //x jumps over it. This is done by simply setting the value of \c n  
-    //x to be false in the corresponding node-map.
+    /// This function hides \c n in the graph, i.e. the iteration 
+    /// jumps over it. This is done by simply setting the value of \c n  
+    /// to be false in the corresponding node-map.
     void hide(const Node& n) const { node_filter_map->set(n, false); }
 
-    //x\e
+    ///\e
 
-    //x This function hides \c e in the graph, i.e. the iteration 
-    //x jumps over it. This is done by simply setting the value of \c e  
-    //x to be false in the corresponding edge-map.
+    /// This function hides \c e in the graph, i.e. the iteration 
+    /// jumps over it. This is done by simply setting the value of \c e  
+    /// to be false in the corresponding edge-map.
     void hide(const Edge& e) const { edge_filter_map->set(e, false); }
 
-    //x\e
+    ///\e
 
-    //x The value of \c n is set to be true in the node-map which stores 
-    //x hide information. If \c n was hidden previuosly, then it is shown 
-    //x again
+    /// The value of \c n is set to be true in the node-map which stores 
+    /// hide information. If \c n was hidden previuosly, then it is shown 
+    /// again
      void unHide(const Node& n) const { node_filter_map->set(n, true); }
 
-    //x\e
+    ///\e
 
-    //x The value of \c e is set to be true in the edge-map which stores 
-    //x hide information. If \c e was hidden previuosly, then it is shown 
-    //x again
+    /// The value of \c e is set to be true in the edge-map which stores 
+    /// hide information. If \c e was hidden previuosly, then it is shown 
+    /// again
     void unHide(const Edge& e) const { edge_filter_map->set(e, true); }
 
-    //x Returns true if \c n is hidden.
+    /// Returns true if \c n is hidden.
     
-    //x\e
-    //x
+    ///\e
+    ///
     bool hidden(const Node& n) const { return !(*node_filter_map)[n]; }
 
-    //x Returns true if \c n is hidden.
+    /// Returns true if \c n is hidden.
     
-    //x\e
-    //x
+    ///\e
+    ///
     bool hidden(const Edge& e) const { return !(*edge_filter_map)[e]; }
 
     typedef False NodeNumTag;
     typedef False EdgeNumTag;
   };
 
-  //x\brief A graph adaptor for hiding nodes and edges from a graph.
-  //x\ingroup graph_adaptors
-  //x
-  //x\warning Graph adaptors are in even more experimental
-  //xstate than the other
-  //xparts of the lib. Use them at you own risk.
-  //x
-  //xSubGraphAdaptor shows the graph with filtered node-set and 
-  //xedge-set. If the \c checked parameter is true then it filters the edgeset
-  //xto do not get invalid edges without source or target.
-  //xLet \f$G=(V, A)\f$ be a directed graph 
-  //xand suppose that the graph instance \c g of type ListGraph implements 
-  //x\f$G\f$. 
-  //x/Let moreover \f$b_V\f$ and 
-  //x\f$b_A\f$ be bool-valued functions resp. on the node-set and edge-set. 
-  //xSubGraphAdaptor<...>::NodeIt iterates 
-  //xon the node-set \f$\{v\in V : b_V(v)=true\}\f$ and 
-  //xSubGraphAdaptor<...>::EdgeIt iterates 
-  //xon the edge-set \f$\{e\in A : b_A(e)=true\}\f$. Similarly, 
-  //xSubGraphAdaptor<...>::OutEdgeIt and
-  //xSubGraphAdaptor<...>::InEdgeIt iterates 
-  //xonly on edges leaving and entering a specific node which have true value.
-  //x
-  //xIf the \c checked template parameter is false then we have to note that 
-  //xthe node-iterator cares only the filter on the node-set, and the 
-  //xedge-iterator cares only the filter on the edge-set.
-  //xThis way the edge-map
-  //xshould filter all edges which's source or target is filtered by the 
-  //xnode-filter.
-  //x\code
-  //xtypedef ListGraph Graph;
-  //xGraph g;
-  //xtypedef Graph::Node Node;
-  //xtypedef Graph::Edge Edge;
-  //xNode u=g.addNode(); //node of id 0
-  //xNode v=g.addNode(); //node of id 1
-  //xNode e=g.addEdge(u, v); //edge of id 0
-  //xNode f=g.addEdge(v, u); //edge of id 1
-  //xGraph::NodeMap<bool> nm(g, true);
-  //xnm.set(u, false);
-  //xGraph::EdgeMap<bool> em(g, true);
-  //xem.set(e, false);
-  //xtypedef SubGraphAdaptor<Graph, Graph::NodeMap<bool>, Graph::EdgeMap<bool> > SubGW;
-  //xSubGW gw(g, nm, em);
-  //xfor (SubGW::NodeIt n(gw); n!=INVALID; ++n) std::cout << g.id(n) << std::endl;
-  //xstd::cout << ":-)" << std::endl;
-  //xfor (SubGW::EdgeIt e(gw); e!=INVALID; ++e) std::cout << g.id(e) << std::endl;
-  //x\endcode
-  //xThe output of the above code is the following.
-  //x\code
-  //x1
-  //x:-)
-  //x1
-  //x\endcode
-  //xNote that \c n is of type \c SubGW::NodeIt, but it can be converted to
-  //x\c Graph::Node that is why \c g.id(n) can be applied.
-  //x
-  //xFor other examples see also the documentation of NodeSubGraphAdaptor and 
-  //xEdgeSubGraphAdaptor.
-  //x
-  //x\author Marton Makai
+  /// \brief A graph adaptor for hiding nodes and edges from a graph.
+  /// \ingroup graph_adaptors
+  /// 
+  /// \warning Graph adaptors are in even more experimental state than the
+  /// other parts of the lib. Use them at you own risk.
+  /// 
+  /// SubGraphAdaptor shows the graph with filtered node-set and 
+  /// edge-set. If the \c checked parameter is true then it filters the edgeset
+  /// to do not get invalid edges without source or target.
+  /// Let  \f$  G=(V, A)  \f$  be a directed graph
+  /// and suppose that the graph instance \c g of type ListGraph
+  /// implements  \f$  G  \f$ .
+  /// Let moreover  \f$  b_V  \f$  and  \f$  b_A  \f$  be bool-valued functions resp.
+  /// on the node-set and edge-set.
+  /// SubGraphAdaptor<...>::NodeIt iterates 
+  /// on the node-set  \f$ \{v\in V : b_V(v)=true\} \f$  and 
+  /// SubGraphAdaptor<...>::EdgeIt iterates 
+  /// on the edge-set  \f$ \{e\in A : b_A(e)=true\} \f$ . Similarly, 
+  /// SubGraphAdaptor<...>::OutEdgeIt and
+  /// SubGraphAdaptor<...>::InEdgeIt iterates 
+  /// only on edges leaving and entering a specific node which have true value.
+  /// 
+  /// If the \c checked template parameter is false then we have to note that 
+  /// the node-iterator cares only the filter on the node-set, and the 
+  /// edge-iterator cares only the filter on the edge-set.
+  /// This way the edge-map
+  /// should filter all edges which's source or target is filtered by the 
+  /// node-filter.
+  /// \code
+  /// typedef ListGraph Graph;
+  /// Graph g;
+  /// typedef Graph::Node Node;
+  /// typedef Graph::Edge Edge;
+  /// Node u=g.addNode(); //node of id 0
+  /// Node v=g.addNode(); //node of id 1
+  /// Node e=g.addEdge(u, v); //edge of id 0
+  /// Node f=g.addEdge(v, u); //edge of id 1
+  /// Graph::NodeMap<bool> nm(g, true);
+  /// nm.set(u, false);
+  /// Graph::EdgeMap<bool> em(g, true);
+  /// em.set(e, false);
+  /// typedef SubGraphAdaptor<Graph, Graph::NodeMap<bool>, Graph::EdgeMap<bool> > SubGW;
+  /// SubGW gw(g, nm, em);
+  /// for (SubGW::NodeIt n(gw); n!=INVALID; ++n) std::cout << g.id(n) << std::endl;
+  /// std::cout << ":-)" << std::endl;
+  /// for (SubGW::EdgeIt e(gw); e!=INVALID; ++e) std::cout << g.id(e) << std::endl;
+  /// \endcode
+  /// The output of the above code is the following.
+  /// \code
+  /// 1
+  /// :-)
+  /// 1
+  /// \endcode
+  /// Note that \c n is of type \c SubGW::NodeIt, but it can be converted to
+  /// \c Graph::Node that is why \c g.id(n) can be applied.
+  /// 
+  /// For other examples see also the documentation of NodeSubGraphAdaptor and 
+  /// EdgeSubGraphAdaptor.
+  /// 
+  /// \author Marton Makai
 
   template<typename _Graph, typename NodeFilterMap, 
 	   typename EdgeFilterMap, bool checked = true>
@@ -514,20 +513,20 @@
 
 
 
-  //x\brief An adaptor for hiding nodes from a graph.
-  //x\ingroup graph_adaptors
-  //x
-  //x\warning Graph adaptors are in even more experimental state
-  //xthan the other
-  //xparts of the lib. Use them at you own risk.
-  //x
-  //xAn adaptor for hiding nodes from a graph.
-  //xThis adaptor specializes SubGraphAdaptor in the way that only
-  //xthe node-set 
-  //xcan be filtered. In usual case the checked parameter is true, we get the
-  //xinduced subgraph. But if the checked parameter is false then we can only
-  //xfilter only isolated nodes.
-  //x\author Marton Makai
+  ///\brief An adaptor for hiding nodes from a graph.
+  ///\ingroup graph_adaptors
+  ///
+  ///\warning Graph adaptors are in even more experimental state
+  ///than the other
+  ///parts of the lib. Use them at you own risk.
+  ///
+  ///An adaptor for hiding nodes from a graph.
+  ///This adaptor specializes SubGraphAdaptor in the way that only
+  ///the node-set 
+  ///can be filtered. In usual case the checked parameter is true, we get the
+  ///induced subgraph. But if the checked parameter is false then we can only
+  ///filter only isolated nodes.
+  ///\author Marton Makai
   template<typename Graph, typename NodeFilterMap, bool checked = true>
   class NodeSubGraphAdaptor : 
     public SubGraphAdaptor<Graph, NodeFilterMap, 
@@ -547,142 +546,142 @@
   };
 
 
-  //x\brief An adaptor for hiding edges from a graph.
-  //x
-  //x\warning Graph adaptors are in even more experimental state
-  //xthan the other parts of the lib. Use them at you own risk.
-  //x
-  //xAn adaptor for hiding edges from a graph.
-  //xThis adaptor specializes SubGraphAdaptor in the way that
-  //xonly the edge-set 
-  //xcan be filtered. The usefulness of this adaptor is demonstrated in the 
-  //xproblem of searching a maximum number of edge-disjoint shortest paths 
-  //xbetween 
-  //xtwo nodes \c s and \c t. Shortest here means being shortest w.r.t. 
-  //xnon-negative edge-lengths. Note that 
-  //xthe comprehension of the presented solution 
-  //xneed's some elementary knowledge from combinatorial optimization. 
-  //x
-  //xIf a single shortest path is to be 
-  //xsearched between \c s and \c t, then this can be done easily by 
-  //xapplying the Dijkstra algorithm. What happens, if a maximum number of 
-  //xedge-disjoint shortest paths is to be computed. It can be proved that an 
-  //xedge can be in a shortest path if and only
-  //xif it is tight with respect to 
-  //xthe potential function computed by Dijkstra.
-  //xMoreover, any path containing 
-  //xonly such edges is a shortest one.
-  //xThus we have to compute a maximum number 
-  //xof edge-disjoint paths between \c s and \c t in
-  //xthe graph which has edge-set 
-  //xall the tight edges. The computation will be demonstrated
-  //xon the following 
-  //xgraph, which is read from the dimacs file \c sub_graph_adaptor_demo.dim. 
-  //xThe full source code is available in \ref sub_graph_adaptor_demo.cc. 
-  //xIf you are interested in more demo programs, you can use 
-  //x\ref dim_to_dot.cc to generate .dot files from dimacs files. 
-  //xThe .dot file of the following figure was generated by  
-  //xthe demo program \ref dim_to_dot.cc.
-  //x
-  //x\dot
-  //xdigraph lemon_dot_example {
-  //xnode [ shape=ellipse, fontname=Helvetica, fontsize=10 ];
-  //xn0 [ label="0 (s)" ];
-  //xn1 [ label="1" ];
-  //xn2 [ label="2" ];
-  //xn3 [ label="3" ];
-  //xn4 [ label="4" ];
-  //xn5 [ label="5" ];
-  //xn6 [ label="6 (t)" ];
-  //xedge [ shape=ellipse, fontname=Helvetica, fontsize=10 ];
-  //xn5 ->  n6 [ label="9, length:4" ];
-  //xn4 ->  n6 [ label="8, length:2" ];
-  //xn3 ->  n5 [ label="7, length:1" ];
-  //xn2 ->  n5 [ label="6, length:3" ];
-  //xn2 ->  n6 [ label="5, length:5" ];
-  //xn2 ->  n4 [ label="4, length:2" ];
-  //xn1 ->  n4 [ label="3, length:3" ];
-  //xn0 ->  n3 [ label="2, length:1" ];
-  //xn0 ->  n2 [ label="1, length:2" ];
-  //xn0 ->  n1 [ label="0, length:3" ];
-  //x}
-  //x\enddot
-  //x
-  //x\code
-  //xGraph g;
-  //xNode s, t;
-  //xLengthMap length(g);
-  //x
-  //xreadDimacs(std::cin, g, length, s, t);
-  //x
-  //xcout << "edges with lengths (of form id, source--length->target): " << endl;
-  //xfor(EdgeIt e(g); e!=INVALID; ++e) 
-  //x  cout << g.id(e) << ", " << g.id(g.source(e)) << "--" 
-  //x       << length[e] << "->" << g.id(g.target(e)) << endl;
-  //x
-  //xcout << "s: " << g.id(s) << " t: " << g.id(t) << endl;
-  //x\endcode
-  //xNext, the potential function is computed with Dijkstra.
-  //x\code
-  //xtypedef Dijkstra<Graph, LengthMap> Dijkstra;
-  //xDijkstra dijkstra(g, length);
-  //xdijkstra.run(s);
-  //x\endcode
-  //xNext, we consrtruct a map which filters the edge-set to the tight edges.
-  //x\code
-  //xtypedef TightEdgeFilterMap<Graph, const Dijkstra::DistMap, LengthMap> 
-  //x  TightEdgeFilter;
-  //xTightEdgeFilter tight_edge_filter(g, dijkstra.distMap(), length);
-  //x
-  //xtypedef EdgeSubGraphAdaptor<Graph, TightEdgeFilter> SubGW;
-  //xSubGW gw(g, tight_edge_filter);
-  //x\endcode
-  //xThen, the maximum nimber of edge-disjoint \c s-\c t paths are computed 
-  //xwith a max flow algorithm Preflow.
-  //x\code
-  //xConstMap<Edge, int> const_1_map(1);
-  //xGraph::EdgeMap<int> flow(g, 0);
-  //x
-  //xPreflow<SubGW, int, ConstMap<Edge, int>, Graph::EdgeMap<int> > 
-  //x  preflow(gw, s, t, const_1_map, flow);
-  //xpreflow.run();
-  //x\endcode
-  //xLast, the output is:
-  //x\code  
-  //xcout << "maximum number of edge-disjoint shortest path: " 
-  //x     << preflow.flowValue() << endl;
-  //xcout << "edges of the maximum number of edge-disjoint shortest s-t paths: " 
-  //x     << endl;
-  //xfor(EdgeIt e(g); e!=INVALID; ++e) 
-  //x  if (flow[e])
-  //x    cout << " " << g.id(g.source(e)) << "--"
-  //x         << length[e] << "->" << g.id(g.target(e)) << endl;
-  //x\endcode
-  //xThe program has the following (expected :-)) output:
-  //x\code
-  //xedges with lengths (of form id, source--length->target):
-  //x 9, 5--4->6
-  //x 8, 4--2->6
-  //x 7, 3--1->5
-  //x 6, 2--3->5
-  //x 5, 2--5->6
-  //x 4, 2--2->4
-  //x 3, 1--3->4
-  //x 2, 0--1->3
-  //x 1, 0--2->2
-  //x 0, 0--3->1
-  //xs: 0 t: 6
-  //xmaximum number of edge-disjoint shortest path: 2
-  //xedges of the maximum number of edge-disjoint shortest s-t paths:
-  //x 9, 5--4->6
-  //x 8, 4--2->6
-  //x 7, 3--1->5
-  //x 4, 2--2->4
-  //x 2, 0--1->3
-  //x 1, 0--2->2
-  //x\endcode
-  //x
-  //x\author Marton Makai
+  ///\brief An adaptor for hiding edges from a graph.
+  ///
+  ///\warning Graph adaptors are in even more experimental state
+  ///than the other parts of the lib. Use them at you own risk.
+  ///
+  ///An adaptor for hiding edges from a graph.
+  ///This adaptor specializes SubGraphAdaptor in the way that
+  ///only the edge-set 
+  ///can be filtered. The usefulness of this adaptor is demonstrated in the 
+  ///problem of searching a maximum number of edge-disjoint shortest paths 
+  ///between 
+  ///two nodes \c s and \c t. Shortest here means being shortest w.r.t. 
+  ///non-negative edge-lengths. Note that 
+  ///the comprehension of the presented solution 
+  ///need's some elementary knowledge from combinatorial optimization. 
+  ///
+  ///If a single shortest path is to be 
+  ///searched between \c s and \c t, then this can be done easily by 
+  ///applying the Dijkstra algorithm. What happens, if a maximum number of 
+  ///edge-disjoint shortest paths is to be computed. It can be proved that an 
+  ///edge can be in a shortest path if and only
+  ///if it is tight with respect to 
+  ///the potential function computed by Dijkstra.
+  ///Moreover, any path containing 
+  ///only such edges is a shortest one.
+  ///Thus we have to compute a maximum number 
+  ///of edge-disjoint paths between \c s and \c t in
+  ///the graph which has edge-set 
+  ///all the tight edges. The computation will be demonstrated
+  ///on the following 
+  ///graph, which is read from the dimacs file \c sub_graph_adaptor_demo.dim. 
+  ///The full source code is available in \ref sub_graph_adaptor_demo.cc. 
+  ///If you are interested in more demo programs, you can use 
+  ///\ref dim_to_dot.cc to generate .dot files from dimacs files. 
+  ///The .dot file of the following figure was generated by  
+  ///the demo program \ref dim_to_dot.cc.
+  ///
+  ///\dot
+  ///digraph lemon_dot_example {
+  ///node [ shape=ellipse, fontname=Helvetica, fontsize=10 ];
+  ///n0 [ label="0 (s)" ];
+  ///n1 [ label="1" ];
+  ///n2 [ label="2" ];
+  ///n3 [ label="3" ];
+  ///n4 [ label="4" ];
+  ///n5 [ label="5" ];
+  ///n6 [ label="6 (t)" ];
+  ///edge [ shape=ellipse, fontname=Helvetica, fontsize=10 ];
+  ///n5 ->  n6 [ label="9, length:4" ];
+  ///n4 ->  n6 [ label="8, length:2" ];
+  ///n3 ->  n5 [ label="7, length:1" ];
+  ///n2 ->  n5 [ label="6, length:3" ];
+  ///n2 ->  n6 [ label="5, length:5" ];
+  ///n2 ->  n4 [ label="4, length:2" ];
+  ///n1 ->  n4 [ label="3, length:3" ];
+  ///n0 ->  n3 [ label="2, length:1" ];
+  ///n0 ->  n2 [ label="1, length:2" ];
+  ///n0 ->  n1 [ label="0, length:3" ];
+  ///}
+  ///\enddot
+  ///
+  ///\code
+  ///Graph g;
+  ///Node s, t;
+  ///LengthMap length(g);
+  ///
+  ///readDimacs(std::cin, g, length, s, t);
+  ///
+  ///cout << "edges with lengths (of form id, source--length->target): " << endl;
+  ///for(EdgeIt e(g); e!=INVALID; ++e) 
+  ///  cout << g.id(e) << ", " << g.id(g.source(e)) << "--" 
+  ///       << length[e] << "->" << g.id(g.target(e)) << endl;
+  ///
+  ///cout << "s: " << g.id(s) << " t: " << g.id(t) << endl;
+  ///\endcode
+  ///Next, the potential function is computed with Dijkstra.
+  ///\code
+  ///typedef Dijkstra<Graph, LengthMap> Dijkstra;
+  ///Dijkstra dijkstra(g, length);
+  ///dijkstra.run(s);
+  ///\endcode
+  ///Next, we consrtruct a map which filters the edge-set to the tight edges.
+  ///\code
+  ///typedef TightEdgeFilterMap<Graph, const Dijkstra::DistMap, LengthMap> 
+  ///  TightEdgeFilter;
+  ///TightEdgeFilter tight_edge_filter(g, dijkstra.distMap(), length);
+  ///
+  ///typedef EdgeSubGraphAdaptor<Graph, TightEdgeFilter> SubGW;
+  ///SubGW gw(g, tight_edge_filter);
+  ///\endcode
+  ///Then, the maximum nimber of edge-disjoint \c s-\c t paths are computed 
+  ///with a max flow algorithm Preflow.
+  ///\code
+  ///ConstMap<Edge, int> const_1_map(1);
+  ///Graph::EdgeMap<int> flow(g, 0);
+  ///
+  ///Preflow<SubGW, int, ConstMap<Edge, int>, Graph::EdgeMap<int> > 
+  ///  preflow(gw, s, t, const_1_map, flow);
+  ///preflow.run();
+  ///\endcode
+  ///Last, the output is:
+  ///\code  
+  ///cout << "maximum number of edge-disjoint shortest path: " 
+  ///     << preflow.flowValue() << endl;
+  ///cout << "edges of the maximum number of edge-disjoint shortest s-t paths: " 
+  ///     << endl;
+  ///for(EdgeIt e(g); e!=INVALID; ++e) 
+  ///  if (flow[e])
+  ///    cout << " " << g.id(g.source(e)) << "--"
+  ///         << length[e] << "->" << g.id(g.target(e)) << endl;
+  ///\endcode
+  ///The program has the following (expected :-)) output:
+  ///\code
+  ///edges with lengths (of form id, source--length->target):
+  /// 9, 5--4->6
+  /// 8, 4--2->6
+  /// 7, 3--1->5
+  /// 6, 2--3->5
+  /// 5, 2--5->6
+  /// 4, 2--2->4
+  /// 3, 1--3->4
+  /// 2, 0--1->3
+  /// 1, 0--2->2
+  /// 0, 0--3->1
+  ///s: 0 t: 6
+  ///maximum number of edge-disjoint shortest path: 2
+  ///edges of the maximum number of edge-disjoint shortest s-t paths:
+  /// 9, 5--4->6
+  /// 8, 4--2->6
+  /// 7, 3--1->5
+  /// 4, 2--2->4
+  /// 2, 0--1->3
+  /// 1, 0--2->2
+  ///\endcode
+  ///
+  ///\author Marton Makai
   template<typename Graph, typename EdgeFilterMap>
   class EdgeSubGraphAdaptor : 
     public SubGraphAdaptor<Graph, ConstMap<typename Graph::Node,bool>, 
@@ -769,13 +768,13 @@
       
   };
 
-  //x\brief An undirected graph is made from a directed graph by an adaptor
-  //x\ingroup graph_adaptors
-  //x
-  //x Undocumented, untested!!!
-  //x If somebody knows nice demo application, let's polulate it.
-  //x 
-  //x \author Marton Makai
+  ///\brief An undirected graph is made from a directed graph by an adaptor
+  ///\ingroup graph_adaptors
+  ///
+  /// Undocumented, untested!!!
+  /// If somebody knows nice demo application, let's polulate it.
+  /// 
+  /// \author Marton Makai
   template<typename _Graph>
   class UGraphAdaptor : 
     public IterableUGraphExtender<
@@ -961,21 +960,21 @@
     Node target(Edge e) const { 
       return ((!e.backward) ? this->graph->target(e) : this->graph->source(e)); }
 
-    //x Gives back the opposite edge.
+    /// Gives back the opposite edge.
 
-    //x\e
-    //x
+    ///\e
+    ///
     Edge opposite(const Edge& e) const { 
       Edge f=e;
       f.backward=!f.backward;
       return f;
     }
 
-    //x\e
+    ///\e
 
-    //x \warning This is a linear time operation and works only if 
-    //x \c Graph::EdgeIt is defined.
-    //x \todo hmm
+    /// \warning This is a linear time operation and works only if 
+    /// \c Graph::EdgeIt is defined.
+    /// \todo hmm
     int edgeNum() const { 
       int i=0;
       Edge e;
@@ -986,11 +985,11 @@
     bool forward(const Edge& e) const { return !e.backward; }
     bool backward(const Edge& e) const { return e.backward; }
 
-    //x\e
+    ///\e
 
-    //x \c SubBidirGraphAdaptorBase<..., ..., ...>::EdgeMap contains two 
-    //x _Graph::EdgeMap one for the forward edges and 
-    //x one for the backward edges.
+    /// \c SubBidirGraphAdaptorBase<..., ..., ...>::EdgeMap contains two 
+    /// _Graph::EdgeMap one for the forward edges and 
+    /// one for the backward edges.
     template <typename T>
     class EdgeMap {
       template <typename TT> friend class EdgeMap;
@@ -1039,46 +1038,46 @@
   };
 
 
-  //x\brief An adaptor for composing a subgraph of a 
-  //x bidirected graph made from a directed one. 
-  //x\ingroup graph_adaptors
-  //x
-  //x An adaptor for composing a subgraph of a 
-  //x bidirected graph made from a directed one. 
-  //x
-  //x\warning Graph adaptors are in even more experimental state
-  //xthan the other
-  //xparts of the lib. Use them at you own risk.
-  //x
-  //x Let \f$G=(V, A)\f$ be a directed graph and for each directed edge 
-  //x \f$e\in A\f$, let \f$\bar e\f$ denote the edge obtained by
-  //x reversing its orientation. We are given moreover two bool valued 
-  //x maps on the edge-set, 
-  //x \f$forward\_filter\f$, and \f$backward\_filter\f$. 
-  //x SubBidirGraphAdaptor implements the graph structure with node-set 
-  //x \f$V\f$ and edge-set 
-  //x \f$\{e : e\in A \mbox{ and } forward\_filter(e) \mbox{ is true}\}+\{\bar e : e\in A \mbox{ and } backward\_filter(e) \mbox{ is true}\}\f$. 
-  //x The purpose of writing + instead of union is because parallel 
-  //x edges can arise. (Similarly, antiparallel edges also can arise).
-  //x In other words, a subgraph of the bidirected graph obtained, which 
-  //x is given by orienting the edges of the original graph in both directions.
-  //x As the oppositely directed edges are logically different, 
-  //x the maps are able to attach different values for them. 
-  //x
-  //x An example for such a construction is \c RevGraphAdaptor where the 
-  //x forward_filter is everywhere false and the backward_filter is 
-  //x everywhere true. We note that for sake of efficiency, 
-  //x \c RevGraphAdaptor is implemented in a different way. 
-  //x But BidirGraphAdaptor is obtained from 
-  //x SubBidirGraphAdaptor by considering everywhere true 
-  //x valued maps both for forward_filter and backward_filter. 
-  //x
-  //x The most important application of SubBidirGraphAdaptor 
-  //x is ResGraphAdaptor, which stands for the residual graph in directed 
-  //x flow and circulation problems. 
-  //x As adaptors usually, the SubBidirGraphAdaptor implements the 
-  //x above mentioned graph structure without its physical storage, 
-  //x that is the whole stuff is stored in constant memory. 
+  ///\brief An adaptor for composing a subgraph of a 
+  /// bidirected graph made from a directed one. 
+  ///\ingroup graph_adaptors
+  ///
+  /// An adaptor for composing a subgraph of a 
+  /// bidirected graph made from a directed one. 
+  ///
+  ///\warning Graph adaptors are in even more experimental state
+  ///than the other
+  ///parts of the lib. Use them at you own risk.
+  ///
+  /// Let  \f$  G=(V, A)  \f$  be a directed graph and for each directed edge 
+  ///  \f$  e\in A  \f$ , let  \f$  \bar e  \f$  denote the edge obtained by
+  /// reversing its orientation. We are given moreover two bool valued 
+  /// maps on the edge-set, 
+  ///  \f$  forward\_filter  \f$ , and  \f$  backward\_filter  \f$ . 
+  /// SubBidirGraphAdaptor implements the graph structure with node-set 
+  ///  \f$  V  \f$  and edge-set 
+  ///  \f$  \{e : e\in A \mbox{ and } forward\_filter(e) \mbox{ is true}\}+\{\bar e : e\in A \mbox{ and } backward\_filter(e) \mbox{ is true}\}  \f$ . 
+  /// The purpose of writing + instead of union is because parallel 
+  /// edges can arise. (Similarly, antiparallel edges also can arise).
+  /// In other words, a subgraph of the bidirected graph obtained, which 
+  /// is given by orienting the edges of the original graph in both directions.
+  /// As the oppositely directed edges are logically different, 
+  /// the maps are able to attach different values for them. 
+  ///
+  /// An example for such a construction is \c RevGraphAdaptor where the 
+  /// forward_filter is everywhere false and the backward_filter is 
+  /// everywhere true. We note that for sake of efficiency, 
+  /// \c RevGraphAdaptor is implemented in a different way. 
+  /// But BidirGraphAdaptor is obtained from 
+  /// SubBidirGraphAdaptor by considering everywhere true 
+  /// valued maps both for forward_filter and backward_filter. 
+  ///
+  /// The most important application of SubBidirGraphAdaptor 
+  /// is ResGraphAdaptor, which stands for the residual graph in directed 
+  /// flow and circulation problems. 
+  /// As adaptors usually, the SubBidirGraphAdaptor implements the 
+  /// above mentioned graph structure without its physical storage, 
+  /// that is the whole stuff is stored in constant memory. 
   template<typename _Graph, 
 	   typename ForwardFilterMap, typename BackwardFilterMap>
   class SubBidirGraphAdaptor : 
@@ -1102,17 +1101,17 @@
 
 
 
-  //x\brief An adaptor for composing bidirected graph from a directed one. 
-  //x\ingroup graph_adaptors
-  //x
-  //x\warning Graph adaptors are in even more experimental state
-  //xthan the other
-  //xparts of the lib. Use them at you own risk.
-  //x
-  //x An adaptor for composing bidirected graph from a directed one. 
-  //x A bidirected graph is composed over the directed one without physical 
-  //x storage. As the oppositely directed edges are logically different ones 
-  //x the maps are able to attach different values for them.
+  ///\brief An adaptor for composing bidirected graph from a directed one. 
+  ///\ingroup graph_adaptors
+  ///
+  ///\warning Graph adaptors are in even more experimental state
+  ///than the other
+  ///parts of the lib. Use them at you own risk.
+  ///
+  /// An adaptor for composing bidirected graph from a directed one. 
+  /// A bidirected graph is composed over the directed one without physical 
+  /// storage. As the oppositely directed edges are logically different ones 
+  /// the maps are able to attach different values for them.
   template<typename Graph>
   class BidirGraphAdaptor : 
     public SubBidirGraphAdaptor<
@@ -1180,41 +1179,41 @@
   };
 
   
-  //x\brief An adaptor for composing the residual
-  //xgraph for directed flow and circulation problems.
-  //x\ingroup graph_adaptors
-  //x
-  //xAn adaptor for composing the residual graph for
-  //xdirected flow and circulation problems. 
-  //xLet \f$G=(V, A)\f$ be a directed graph and let \f$F\f$ be a 
-  //xnumber type. Let moreover 
-  //x\f$f,c:A\to F\f$, be functions on the edge-set. 
-  //xIn the appications of ResGraphAdaptor, \f$f\f$ usually stands for a flow 
-  //xand \f$c\f$ for a capacity function.   
-  //xSuppose that a graph instange \c g of type 
-  //x\c ListGraph implements \f$G\f$ .
-  //x\code
-  //x  ListGraph g;
-  //x\endcode
-  //xThen RevGraphAdaptor implements the graph structure with node-set 
-  //x\f$V\f$ and edge-set \f$A_{forward}\cup A_{backward}\f$, where 
-  //x\f$A_{forward}=\{uv : uv\in A, f(uv)<c(uv)\}\f$ and 
-  //x\f$A_{backward}=\{vu : uv\in A, f(uv)>0\}\f$, 
-  //xi.e. the so called residual graph. 
-  //xWhen we take the union \f$A_{forward}\cup A_{backward}\f$, 
-  //xmultilicities are counted, i.e. if an edge is in both 
-  //x\f$A_{forward}\f$ and \f$A_{backward}\f$, then in the adaptor it 
-  //xappears twice. 
-  //xThe following code shows how 
-  //xsuch an instance can be constructed.
-  //x\code
-  //xtypedef ListGraph Graph;
-  //xGraph::EdgeMap<int> f(g);
-  //xGraph::EdgeMap<int> c(g);
-  //xResGraphAdaptor<Graph, int, Graph::EdgeMap<int>, Graph::EdgeMap<int> > gw(g);
-  //x\endcode
-  //x\author Marton Makai
-  //x
+  ///\brief An adaptor for composing the residual
+  ///graph for directed flow and circulation problems.
+  ///\ingroup graph_adaptors
+  ///
+  ///An adaptor for composing the residual graph for
+  ///directed flow and circulation problems. 
+  ///Let  \f$ G=(V, A) \f$  be a directed graph and let  \f$ F \f$  be a 
+  ///number type. Let moreover 
+  /// \f$ f,c:A\to F \f$ , be functions on the edge-set. 
+  ///In the appications of ResGraphAdaptor,  \f$ f \f$  usually stands for a flow 
+  ///and  \f$ c \f$  for a capacity function.   
+  ///Suppose that a graph instange \c g of type 
+  ///\c ListGraph implements  \f$ G \f$  .
+  ///\code
+  ///  ListGraph g;
+  ///\endcode
+  ///Then RevGraphAdaptor implements the graph structure with node-set 
+  /// \f$ V \f$  and edge-set  \f$ A_{forward}\cup A_{backward} \f$ , where 
+  /// \f$ A_{forward}=\{uv : uv\in A, f(uv)<c(uv)\} \f$  and 
+  /// \f$ A_{backward}=\{vu : uv\in A, f(uv)>0\} \f$ , 
+  ///i.e. the so called residual graph. 
+  ///When we take the union  \f$ A_{forward}\cup A_{backward} \f$ , 
+  ///multilicities are counted, i.e. if an edge is in both 
+  /// \f$ A_{forward} \f$  and  \f$ A_{backward} \f$ , then in the adaptor it 
+  ///appears twice. 
+  ///The following code shows how 
+  ///such an instance can be constructed.
+  ///\code
+  ///typedef ListGraph Graph;
+  ///Graph::EdgeMap<int> f(g);
+  ///Graph::EdgeMap<int> c(g);
+  ///ResGraphAdaptor<Graph, int, Graph::EdgeMap<int>, Graph::EdgeMap<int> > gw(g);
+  ///\endcode
+  ///\author Marton Makai
+  ///
   template<typename Graph, typename Number, 
 	   typename CapacityMap, typename FlowMap>
   class ResGraphAdaptor : 
@@ -1264,10 +1263,10 @@
 	flow->set(e, (*flow)[e]-a);
     }
 
-    //x \brief Residual capacity map.
-    //x
-    //x In generic residual graphs the residual capacity can be obtained 
-    //x as a map. 
+    /// \brief Residual capacity map.
+    ///
+    /// In generic residual graphs the residual capacity can be obtained 
+    /// as a map. 
     class ResCap {
     protected:
       const ResGraphAdaptor<Graph, Number, CapacityMap, FlowMap>* res_graph;
@@ -1321,23 +1320,23 @@
   };
 
 
-  //x\brief For blocking flows.
-  //x\ingroup graph_adaptors
-  //x
-  //x\warning Graph adaptors are in even more
-  //xexperimental state than the other
-  //xparts of the lib. Use them at you own risk.
-  //x
-  //xThis graph adaptor is used for on-the-fly 
-  //xDinits blocking flow computations.
-  //xFor each node, an out-edge is stored which is used when the 
-  //x\code
-  //xOutEdgeIt& first(OutEdgeIt&, const Node&)
-  //x\endcode
-  //xis called. 
-  //x
-  //x\author Marton Makai
-  //x
+  ///\brief For blocking flows.
+  ///\ingroup graph_adaptors
+  ///
+  ///\warning Graph adaptors are in even more
+  ///experimental state than the other
+  ///parts of the lib. Use them at you own risk.
+  ///
+  ///This graph adaptor is used for on-the-fly 
+  ///Dinits blocking flow computations.
+  ///For each node, an out-edge is stored which is used when the 
+  ///\code
+  ///OutEdgeIt& first(OutEdgeIt&, const Node&)
+  ///\endcode
+  ///is called. 
+  ///
+  ///\author Marton Makai
+  ///
   template <typename _Graph, typename FirstOutEdgesMap>
   class ErasingFirstGraphAdaptor : 
     public IterableGraphExtender<
@@ -1394,7 +1393,7 @@
       }
     };
 
-    //x \todo May we want VARIANT/union type
+    /// \todo May we want VARIANT/union type
     class Edge : public Parent::Edge {
       friend class SplitGraphAdaptorBase;
       template <typename T> friend class EdgeMap;