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showpage
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... ...
@@ -152,24 +152,46 @@
152 152
   Disable SoPlex support.
153 153

	
154 154
--with-coin[=PREFIX]
155 155

	
156 156
   Enable support for COIN-OR solvers (CLP and CBC). You should
157 157
   specify the prefix too. (by default, COIN-OR tools install
158 158
   themselves to the source code directory). This command enables the
159 159
   solvers that are actually found.
160 160

	
161 161
--with-coin-includedir=DIR
162 162

	
163 163
   The directory where the COIN-OR header files are located. This is
164 164
   only useful when the COIN-OR headers and libraries are not under
165 165
   the same prefix (which is unlikely).
166 166

	
167 167
--with-coin-libdir=DIR
168 168

	
169 169
   The directory where the COIN-OR libraries are located. This is only
170 170
   useful when the COIN-OR headers and libraries are not under the
171 171
   same prefix (which is unlikely).
172 172

	
173 173
--without-coin
174 174

	
175 175
   Disable COIN-OR support.
176

	
177

	
178
Makefile Variables
179
==================
180

	
181
Some Makefile variables are reserved by the GNU Coding Standards for
182
the use of the "user" - the person building the package. For instance,
183
CXX and CXXFLAGS are such variables, and have the same meaning as
184
explained in the previous section. These variables can be set on the
185
command line when invoking `make' like this:
186
`make [VARIABLE=VALUE]...'
187

	
188
WARNINGCXXFLAGS is a non-standard Makefile variable introduced by us
189
to hold several compiler flags related to warnings. Its default value
190
can be overridden when invoking `make'. For example to disable all
191
warning flags use `make WARNINGCXXFLAGS='.
192

	
193
In order to turn off a single flag from the default set of warning
194
flags, you can use the CXXFLAGS variable, since this is passed after
195
WARNINGCXXFLAGS. For example to turn off `-Wold-style-cast' (which is
196
used by default when g++ is detected) you can use
197
`make CXXFLAGS="-g -O2 -Wno-old-style-cast"'.
Ignore white space 6 line context
... ...
@@ -5,48 +5,49 @@
5 5

	
6 6
CONFIGURE_FILE(
7 7
  ${PROJECT_SOURCE_DIR}/doc/Doxyfile.in
8 8
  ${PROJECT_BINARY_DIR}/doc/Doxyfile
9 9
  @ONLY
10 10
)
11 11

	
12 12
IF(DOXYGEN_EXECUTABLE AND PYTHONINTERP_FOUND AND GHOSTSCRIPT_EXECUTABLE)
13 13
  FILE(MAKE_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/html/)
14 14
  SET(GHOSTSCRIPT_OPTIONS -dNOPAUSE -dBATCH -q -dEPSCrop -dTextAlphaBits=4 -dGraphicsAlphaBits=4 -sDEVICE=pngalpha)
15 15
  ADD_CUSTOM_TARGET(html
16 16
    COMMAND ${CMAKE_COMMAND} -E remove_directory gen-images
17 17
    COMMAND ${CMAKE_COMMAND} -E make_directory gen-images
18 18
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/bipartite_matching.png ${CMAKE_CURRENT_SOURCE_DIR}/images/bipartite_matching.eps
19 19
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/bipartite_partitions.png ${CMAKE_CURRENT_SOURCE_DIR}/images/bipartite_partitions.eps
20 20
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/connected_components.png ${CMAKE_CURRENT_SOURCE_DIR}/images/connected_components.eps
21 21
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/edge_biconnected_components.png ${CMAKE_CURRENT_SOURCE_DIR}/images/edge_biconnected_components.eps
22 22
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/grid_graph.png ${CMAKE_CURRENT_SOURCE_DIR}/images/grid_graph.eps
23 23
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/node_biconnected_components.png ${CMAKE_CURRENT_SOURCE_DIR}/images/node_biconnected_components.eps
24 24
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/nodeshape_0.png ${CMAKE_CURRENT_SOURCE_DIR}/images/nodeshape_0.eps
25 25
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/nodeshape_1.png ${CMAKE_CURRENT_SOURCE_DIR}/images/nodeshape_1.eps
26 26
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/nodeshape_2.png ${CMAKE_CURRENT_SOURCE_DIR}/images/nodeshape_2.eps
27 27
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/nodeshape_3.png ${CMAKE_CURRENT_SOURCE_DIR}/images/nodeshape_3.eps
28 28
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/nodeshape_4.png ${CMAKE_CURRENT_SOURCE_DIR}/images/nodeshape_4.eps
29
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/planar.png ${CMAKE_CURRENT_SOURCE_DIR}/images/planar.eps
29 30
    COMMAND ${GHOSTSCRIPT_EXECUTABLE} ${GHOSTSCRIPT_OPTIONS} -r18 -sOutputFile=gen-images/strongly_connected_components.png ${CMAKE_CURRENT_SOURCE_DIR}/images/strongly_connected_components.eps
30 31
    COMMAND ${CMAKE_COMMAND} -E remove_directory html
31 32
    COMMAND ${PYTHON_EXECUTABLE} ${PROJECT_SOURCE_DIR}/scripts/bib2dox.py ${CMAKE_CURRENT_SOURCE_DIR}/references.bib >references.dox
32 33
    COMMAND ${DOXYGEN_EXECUTABLE} Doxyfile
33 34
    WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}
34 35
  )
35 36

	
36 37
  SET_TARGET_PROPERTIES(html PROPERTIES PROJECT_LABEL BUILD_DOC)
37 38

	
38 39
  IF(UNIX)
39 40
    INSTALL(
40 41
      DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/html/
41 42
      DESTINATION share/doc/lemon/html
42 43
      COMPONENT html_documentation
43 44
    )
44 45
  ELSEIF(WIN32)
45 46
    INSTALL(
46 47
      DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/html/
47 48
      DESTINATION doc
48 49
      COMPONENT html_documentation
49 50
    )
50 51
  ENDIF()
51 52

	
52 53
ENDIF()
Ignore white space 6 line context
... ...
@@ -7,48 +7,49 @@
7 7
	doc/lgf.dox \
8 8
	doc/license.dox \
9 9
	doc/mainpage.dox \
10 10
	doc/migration.dox \
11 11
	doc/min_cost_flow.dox \
12 12
	doc/named-param.dox \
13 13
	doc/namespaces.dox \
14 14
	doc/html \
15 15
	doc/CMakeLists.txt
16 16

	
17 17
DOC_EPS_IMAGES18 = \
18 18
	grid_graph.eps \
19 19
	nodeshape_0.eps \
20 20
	nodeshape_1.eps \
21 21
	nodeshape_2.eps \
22 22
	nodeshape_3.eps \
23 23
	nodeshape_4.eps
24 24

	
25 25
DOC_EPS_IMAGES27 = \
26 26
	bipartite_matching.eps \
27 27
	bipartite_partitions.eps \
28 28
	connected_components.eps \
29 29
	edge_biconnected_components.eps \
30 30
	node_biconnected_components.eps \
31
	planar.eps \
31 32
	strongly_connected_components.eps
32 33

	
33 34
DOC_EPS_IMAGES = \
34 35
	$(DOC_EPS_IMAGES18) \
35 36
	$(DOC_EPS_IMAGES27)
36 37

	
37 38
DOC_PNG_IMAGES = \
38 39
	$(DOC_EPS_IMAGES:%.eps=doc/gen-images/%.png)
39 40

	
40 41
EXTRA_DIST += $(DOC_EPS_IMAGES:%=doc/images/%)
41 42

	
42 43
doc/html:
43 44
	$(MAKE) $(AM_MAKEFLAGS) html
44 45

	
45 46
GS_COMMAND=gs -dNOPAUSE -dBATCH -q -dEPSCrop -dTextAlphaBits=4 -dGraphicsAlphaBits=4
46 47

	
47 48
$(DOC_EPS_IMAGES18:%.eps=doc/gen-images/%.png): doc/gen-images/%.png: doc/images/%.eps
48 49
	-mkdir doc/gen-images
49 50
	if test ${gs_found} = yes; then \
50 51
	  $(GS_COMMAND) -sDEVICE=pngalpha -r18 -sOutputFile=$@ $<; \
51 52
	else \
52 53
	  echo; \
53 54
	  echo "Ghostscript not found."; \
54 55
	  echo; \
Ignore white space 6 line context
... ...
@@ -150,48 +150,53 @@
150 150
  /// This class provides an efficient implementation of the Bellman-Ford 
151 151
  /// algorithm. The maximum time complexity of the algorithm is
152 152
  /// <tt>O(ne)</tt>.
153 153
  ///
154 154
  /// The Bellman-Ford algorithm solves the single-source shortest path
155 155
  /// problem when the arcs can have negative lengths, but the digraph
156 156
  /// should not contain directed cycles with negative total length.
157 157
  /// If all arc costs are non-negative, consider to use the Dijkstra
158 158
  /// algorithm instead, since it is more efficient.
159 159
  ///
160 160
  /// The arc lengths are passed to the algorithm using a
161 161
  /// \ref concepts::ReadMap "ReadMap", so it is easy to change it to any 
162 162
  /// kind of length. The type of the length values is determined by the
163 163
  /// \ref concepts::ReadMap::Value "Value" type of the length map.
164 164
  ///
165 165
  /// There is also a \ref bellmanFord() "function-type interface" for the
166 166
  /// Bellman-Ford algorithm, which is convenient in the simplier cases and
167 167
  /// it can be used easier.
168 168
  ///
169 169
  /// \tparam GR The type of the digraph the algorithm runs on.
170 170
  /// The default type is \ref ListDigraph.
171 171
  /// \tparam LEN A \ref concepts::ReadMap "readable" arc map that specifies
172 172
  /// the lengths of the arcs. The default map type is
173 173
  /// \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
174
  /// \tparam TR The traits class that defines various types used by the
175
  /// algorithm. By default, it is \ref BellmanFordDefaultTraits
176
  /// "BellmanFordDefaultTraits<GR, LEN>".
177
  /// In most cases, this parameter should not be set directly,
178
  /// consider to use the named template parameters instead.
174 179
#ifdef DOXYGEN
175 180
  template <typename GR, typename LEN, typename TR>
176 181
#else
177 182
  template <typename GR=ListDigraph,
178 183
            typename LEN=typename GR::template ArcMap<int>,
179 184
            typename TR=BellmanFordDefaultTraits<GR,LEN> >
180 185
#endif
181 186
  class BellmanFord {
182 187
  public:
183 188

	
184 189
    ///The type of the underlying digraph.
185 190
    typedef typename TR::Digraph Digraph;
186 191
    
187 192
    /// \brief The type of the arc lengths.
188 193
    typedef typename TR::LengthMap::Value Value;
189 194
    /// \brief The type of the map that stores the arc lengths.
190 195
    typedef typename TR::LengthMap LengthMap;
191 196
    /// \brief The type of the map that stores the last
192 197
    /// arcs of the shortest paths.
193 198
    typedef typename TR::PredMap PredMap;
194 199
    /// \brief The type of the map that stores the distances of the nodes.
195 200
    typedef typename TR::DistMap DistMap;
196 201
    /// The type of the paths.
197 202
    typedef PredMapPath<Digraph, PredMap> Path;
... ...
@@ -912,48 +917,51 @@
912 917
    
913 918
    /// This constructor requires two parameters,
914 919
    /// others are initiated to \c 0.
915 920
    /// \param gr The digraph the algorithm runs on.
916 921
    /// \param len The length map.
917 922
    BellmanFordWizardBase(const GR& gr, 
918 923
			  const LEN& len) :
919 924
      _graph(reinterpret_cast<void*>(const_cast<GR*>(&gr))), 
920 925
      _length(reinterpret_cast<void*>(const_cast<LEN*>(&len))), 
921 926
      _pred(0), _dist(0), _path(0), _di(0) {}
922 927

	
923 928
  };
924 929
  
925 930
  /// \brief Auxiliary class for the function-type interface of the
926 931
  /// \ref BellmanFord "Bellman-Ford" algorithm.
927 932
  ///
928 933
  /// This auxiliary class is created to implement the
929 934
  /// \ref bellmanFord() "function-type interface" of the
930 935
  /// \ref BellmanFord "Bellman-Ford" algorithm.
931 936
  /// It does not have own \ref run() method, it uses the
932 937
  /// functions and features of the plain \ref BellmanFord.
933 938
  ///
934 939
  /// This class should only be used through the \ref bellmanFord()
935 940
  /// function, which makes it easier to use the algorithm.
941
  ///
942
  /// \tparam TR The traits class that defines various types used by the
943
  /// algorithm.
936 944
  template<class TR>
937 945
  class BellmanFordWizard : public TR {
938 946
    typedef TR Base;
939 947

	
940 948
    typedef typename TR::Digraph Digraph;
941 949

	
942 950
    typedef typename Digraph::Node Node;
943 951
    typedef typename Digraph::NodeIt NodeIt;
944 952
    typedef typename Digraph::Arc Arc;
945 953
    typedef typename Digraph::OutArcIt ArcIt;
946 954
    
947 955
    typedef typename TR::LengthMap LengthMap;
948 956
    typedef typename LengthMap::Value Value;
949 957
    typedef typename TR::PredMap PredMap;
950 958
    typedef typename TR::DistMap DistMap;
951 959
    typedef typename TR::Path Path;
952 960

	
953 961
  public:
954 962
    /// Constructor.
955 963
    BellmanFordWizard() : TR() {}
956 964

	
957 965
    /// \brief Constructor that requires parameters.
958 966
    ///
959 967
    /// Constructor that requires parameters.
Ignore white space 6 line context
... ...
@@ -100,48 +100,53 @@
100 100
    ///It must conform to the \ref concepts::WriteMap "WriteMap" concept.
101 101
    typedef typename Digraph::template NodeMap<int> DistMap;
102 102
    ///Instantiates a \c DistMap.
103 103

	
104 104
    ///This function instantiates a \ref DistMap.
105 105
    ///\param g is the digraph, to which we would like to define the
106 106
    ///\ref DistMap.
107 107
    static DistMap *createDistMap(const Digraph &g)
108 108
    {
109 109
      return new DistMap(g);
110 110
    }
111 111
  };
112 112

	
113 113
  ///%BFS algorithm class.
114 114

	
115 115
  ///\ingroup search
116 116
  ///This class provides an efficient implementation of the %BFS algorithm.
117 117
  ///
118 118
  ///There is also a \ref bfs() "function-type interface" for the BFS
119 119
  ///algorithm, which is convenient in the simplier cases and it can be
120 120
  ///used easier.
121 121
  ///
122 122
  ///\tparam GR The type of the digraph the algorithm runs on.
123 123
  ///The default type is \ref ListDigraph.
124
  ///\tparam TR The traits class that defines various types used by the
125
  ///algorithm. By default, it is \ref BfsDefaultTraits
126
  ///"BfsDefaultTraits<GR>".
127
  ///In most cases, this parameter should not be set directly,
128
  ///consider to use the named template parameters instead.
124 129
#ifdef DOXYGEN
125 130
  template <typename GR,
126 131
            typename TR>
127 132
#else
128 133
  template <typename GR=ListDigraph,
129 134
            typename TR=BfsDefaultTraits<GR> >
130 135
#endif
131 136
  class Bfs {
132 137
  public:
133 138

	
134 139
    ///The type of the digraph the algorithm runs on.
135 140
    typedef typename TR::Digraph Digraph;
136 141

	
137 142
    ///\brief The type of the map that stores the predecessor arcs of the
138 143
    ///shortest paths.
139 144
    typedef typename TR::PredMap PredMap;
140 145
    ///The type of the map that stores the distances of the nodes.
141 146
    typedef typename TR::DistMap DistMap;
142 147
    ///The type of the map that indicates which nodes are reached.
143 148
    typedef typename TR::ReachedMap ReachedMap;
144 149
    ///The type of the map that indicates which nodes are processed.
145 150
    typedef typename TR::ProcessedMap ProcessedMap;
146 151
    ///The type of the paths.
147 152
    typedef PredMapPath<Digraph, PredMap> Path;
... ...
@@ -936,48 +941,51 @@
936 941
    /// all of the attributes to \c 0.
937 942
    BfsWizardBase() : _g(0), _reached(0), _processed(0), _pred(0),
938 943
                      _dist(0), _path(0), _di(0) {}
939 944

	
940 945
    /// Constructor.
941 946

	
942 947
    /// This constructor requires one parameter,
943 948
    /// others are initiated to \c 0.
944 949
    /// \param g The digraph the algorithm runs on.
945 950
    BfsWizardBase(const GR &g) :
946 951
      _g(reinterpret_cast<void*>(const_cast<GR*>(&g))),
947 952
      _reached(0), _processed(0), _pred(0), _dist(0),  _path(0), _di(0) {}
948 953

	
949 954
  };
950 955

	
951 956
  /// Auxiliary class for the function-type interface of BFS algorithm.
952 957

	
953 958
  /// This auxiliary class is created to implement the
954 959
  /// \ref bfs() "function-type interface" of \ref Bfs algorithm.
955 960
  /// It does not have own \ref run(Node) "run()" method, it uses the
956 961
  /// functions and features of the plain \ref Bfs.
957 962
  ///
958 963
  /// This class should only be used through the \ref bfs() function,
959 964
  /// which makes it easier to use the algorithm.
965
  ///
966
  /// \tparam TR The traits class that defines various types used by the
967
  /// algorithm.
960 968
  template<class TR>
961 969
  class BfsWizard : public TR
962 970
  {
963 971
    typedef TR Base;
964 972

	
965 973
    typedef typename TR::Digraph Digraph;
966 974

	
967 975
    typedef typename Digraph::Node Node;
968 976
    typedef typename Digraph::NodeIt NodeIt;
969 977
    typedef typename Digraph::Arc Arc;
970 978
    typedef typename Digraph::OutArcIt OutArcIt;
971 979

	
972 980
    typedef typename TR::PredMap PredMap;
973 981
    typedef typename TR::DistMap DistMap;
974 982
    typedef typename TR::ReachedMap ReachedMap;
975 983
    typedef typename TR::ProcessedMap ProcessedMap;
976 984
    typedef typename TR::Path Path;
977 985

	
978 986
  public:
979 987

	
980 988
    /// Constructor.
981 989
    BfsWizard() : TR() {}
982 990

	
983 991
    /// Constructor that requires parameters.
... ...
@@ -1274,53 +1282,53 @@
1274 1282
  /// \ingroup search
1275 1283
  ///
1276 1284
  /// \brief BFS algorithm class with visitor interface.
1277 1285
  ///
1278 1286
  /// This class provides an efficient implementation of the BFS algorithm
1279 1287
  /// with visitor interface.
1280 1288
  ///
1281 1289
  /// The BfsVisit class provides an alternative interface to the Bfs
1282 1290
  /// class. It works with callback mechanism, the BfsVisit object calls
1283 1291
  /// the member functions of the \c Visitor class on every BFS event.
1284 1292
  ///
1285 1293
  /// This interface of the BFS algorithm should be used in special cases
1286 1294
  /// when extra actions have to be performed in connection with certain
1287 1295
  /// events of the BFS algorithm. Otherwise consider to use Bfs or bfs()
1288 1296
  /// instead.
1289 1297
  ///
1290 1298
  /// \tparam GR The type of the digraph the algorithm runs on.
1291 1299
  /// The default type is \ref ListDigraph.
1292 1300
  /// The value of GR is not used directly by \ref BfsVisit,
1293 1301
  /// it is only passed to \ref BfsVisitDefaultTraits.
1294 1302
  /// \tparam VS The Visitor type that is used by the algorithm.
1295 1303
  /// \ref BfsVisitor "BfsVisitor<GR>" is an empty visitor, which
1296 1304
  /// does not observe the BFS events. If you want to observe the BFS
1297 1305
  /// events, you should implement your own visitor class.
1298
  /// \tparam TR Traits class to set various data types used by the
1299
  /// algorithm. The default traits class is
1300
  /// \ref BfsVisitDefaultTraits "BfsVisitDefaultTraits<GR>".
1301
  /// See \ref BfsVisitDefaultTraits for the documentation of
1302
  /// a BFS visit traits class.
1306
  /// \tparam TR The traits class that defines various types used by the
1307
  /// algorithm. By default, it is \ref BfsVisitDefaultTraits
1308
  /// "BfsVisitDefaultTraits<GR>".
1309
  /// In most cases, this parameter should not be set directly,
1310
  /// consider to use the named template parameters instead.
1303 1311
#ifdef DOXYGEN
1304 1312
  template <typename GR, typename VS, typename TR>
1305 1313
#else
1306 1314
  template <typename GR = ListDigraph,
1307 1315
            typename VS = BfsVisitor<GR>,
1308 1316
            typename TR = BfsVisitDefaultTraits<GR> >
1309 1317
#endif
1310 1318
  class BfsVisit {
1311 1319
  public:
1312 1320

	
1313 1321
    ///The traits class.
1314 1322
    typedef TR Traits;
1315 1323

	
1316 1324
    ///The type of the digraph the algorithm runs on.
1317 1325
    typedef typename Traits::Digraph Digraph;
1318 1326

	
1319 1327
    ///The visitor type used by the algorithm.
1320 1328
    typedef VS Visitor;
1321 1329

	
1322 1330
    ///The type of the map that indicates which nodes are reached.
1323 1331
    typedef typename Traits::ReachedMap ReachedMap;
1324 1332

	
1325 1333
  private:
1326 1334

	
Ignore white space 6 line context
... ...
@@ -56,51 +56,56 @@
56 56
    /// its priority type must be \c Cost and its cross reference type
57 57
    /// must be \ref RangeMap "RangeMap<int>".
58 58
    typedef BinHeap<Cost, RangeMap<int> > Heap;
59 59
  };
60 60

	
61 61
  /// \addtogroup min_cost_flow_algs
62 62
  /// @{
63 63

	
64 64
  /// \brief Implementation of the Capacity Scaling algorithm for
65 65
  /// finding a \ref min_cost_flow "minimum cost flow".
66 66
  ///
67 67
  /// \ref CapacityScaling implements the capacity scaling version
68 68
  /// of the successive shortest path algorithm for finding a
69 69
  /// \ref min_cost_flow "minimum cost flow" \ref amo93networkflows,
70 70
  /// \ref edmondskarp72theoretical. It is an efficient dual
71 71
  /// solution method.
72 72
  ///
73 73
  /// Most of the parameters of the problem (except for the digraph)
74 74
  /// can be given using separate functions, and the algorithm can be
75 75
  /// executed using the \ref run() function. If some parameters are not
76 76
  /// specified, then default values will be used.
77 77
  ///
78 78
  /// \tparam GR The digraph type the algorithm runs on.
79 79
  /// \tparam V The number type used for flow amounts, capacity bounds
80
  /// and supply values in the algorithm. By default it is \c int.
80
  /// and supply values in the algorithm. By default, it is \c int.
81 81
  /// \tparam C The number type used for costs and potentials in the
82
  /// algorithm. By default it is the same as \c V.
82
  /// algorithm. By default, it is the same as \c V.
83
  /// \tparam TR The traits class that defines various types used by the
84
  /// algorithm. By default, it is \ref CapacityScalingDefaultTraits
85
  /// "CapacityScalingDefaultTraits<GR, V, C>".
86
  /// In most cases, this parameter should not be set directly,
87
  /// consider to use the named template parameters instead.
83 88
  ///
84 89
  /// \warning Both number types must be signed and all input data must
85 90
  /// be integer.
86 91
  /// \warning This algorithm does not support negative costs for such
87 92
  /// arcs that have infinite upper bound.
88 93
#ifdef DOXYGEN
89 94
  template <typename GR, typename V, typename C, typename TR>
90 95
#else
91 96
  template < typename GR, typename V = int, typename C = V,
92 97
             typename TR = CapacityScalingDefaultTraits<GR, V, C> >
93 98
#endif
94 99
  class CapacityScaling
95 100
  {
96 101
  public:
97 102

	
98 103
    /// The type of the digraph
99 104
    typedef typename TR::Digraph Digraph;
100 105
    /// The type of the flow amounts, capacity bounds and supply values
101 106
    typedef typename TR::Value Value;
102 107
    /// The type of the arc costs
103 108
    typedef typename TR::Cost Cost;
104 109

	
105 110
    /// The type of the heap used for internal Dijkstra computations
106 111
    typedef typename TR::Heap Heap;
Ignore white space 6 line context
... ...
@@ -152,48 +152,53 @@
152 152
     constraints have to be satisfied with equality, i.e. all demands
153 153
     have to be satisfied and all supplies have to be used.
154 154
     
155 155
     If you need the opposite inequalities in the supply/demand constraints
156 156
     (i.e. the total demand is less than the total supply and all the demands
157 157
     have to be satisfied while there could be supplies that are not used),
158 158
     then you could easily transform the problem to the above form by reversing
159 159
     the direction of the arcs and taking the negative of the supply values
160 160
     (e.g. using \ref ReverseDigraph and \ref NegMap adaptors).
161 161

	
162 162
     This algorithm either calculates a feasible circulation, or provides
163 163
     a \ref barrier() "barrier", which prooves that a feasible soultion
164 164
     cannot exist.
165 165

	
166 166
     Note that this algorithm also provides a feasible solution for the
167 167
     \ref min_cost_flow "minimum cost flow problem".
168 168

	
169 169
     \tparam GR The type of the digraph the algorithm runs on.
170 170
     \tparam LM The type of the lower bound map. The default
171 171
     map type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
172 172
     \tparam UM The type of the upper bound (capacity) map.
173 173
     The default map type is \c LM.
174 174
     \tparam SM The type of the supply map. The default map type is
175 175
     \ref concepts::Digraph::NodeMap "GR::NodeMap<UM::Value>".
176
     \tparam TR The traits class that defines various types used by the
177
     algorithm. By default, it is \ref CirculationDefaultTraits
178
     "CirculationDefaultTraits<GR, LM, UM, SM>".
179
     In most cases, this parameter should not be set directly,
180
     consider to use the named template parameters instead.
176 181
  */
177 182
#ifdef DOXYGEN
178 183
template< typename GR,
179 184
          typename LM,
180 185
          typename UM,
181 186
          typename SM,
182 187
          typename TR >
183 188
#else
184 189
template< typename GR,
185 190
          typename LM = typename GR::template ArcMap<int>,
186 191
          typename UM = LM,
187 192
          typename SM = typename GR::template NodeMap<typename UM::Value>,
188 193
          typename TR = CirculationDefaultTraits<GR, LM, UM, SM> >
189 194
#endif
190 195
  class Circulation {
191 196
  public:
192 197

	
193 198
    ///The \ref CirculationDefaultTraits "traits class" of the algorithm.
194 199
    typedef TR Traits;
195 200
    ///The type of the digraph the algorithm runs on.
196 201
    typedef typename Traits::Digraph Digraph;
197 202
    ///The type of the flow and supply values.
198 203
    typedef typename Traits::Value Value;
199 204

	
Ignore white space 6 line context
... ...
@@ -83,82 +83,86 @@
83 83
  };
84 84

	
85 85

	
86 86
  /// \addtogroup min_cost_flow_algs
87 87
  /// @{
88 88

	
89 89
  /// \brief Implementation of the Cost Scaling algorithm for
90 90
  /// finding a \ref min_cost_flow "minimum cost flow".
91 91
  ///
92 92
  /// \ref CostScaling implements a cost scaling algorithm that performs
93 93
  /// push/augment and relabel operations for finding a \ref min_cost_flow
94 94
  /// "minimum cost flow" \ref amo93networkflows, \ref goldberg90approximation,
95 95
  /// \ref goldberg97efficient, \ref bunnagel98efficient. 
96 96
  /// It is a highly efficient primal-dual solution method, which
97 97
  /// can be viewed as the generalization of the \ref Preflow
98 98
  /// "preflow push-relabel" algorithm for the maximum flow problem.
99 99
  ///
100 100
  /// Most of the parameters of the problem (except for the digraph)
101 101
  /// can be given using separate functions, and the algorithm can be
102 102
  /// executed using the \ref run() function. If some parameters are not
103 103
  /// specified, then default values will be used.
104 104
  ///
105 105
  /// \tparam GR The digraph type the algorithm runs on.
106 106
  /// \tparam V The number type used for flow amounts, capacity bounds
107
  /// and supply values in the algorithm. By default it is \c int.
107
  /// and supply values in the algorithm. By default, it is \c int.
108 108
  /// \tparam C The number type used for costs and potentials in the
109
  /// algorithm. By default it is the same as \c V.
109
  /// algorithm. By default, it is the same as \c V.
110
  /// \tparam TR The traits class that defines various types used by the
111
  /// algorithm. By default, it is \ref CostScalingDefaultTraits
112
  /// "CostScalingDefaultTraits<GR, V, C>".
113
  /// In most cases, this parameter should not be set directly,
114
  /// consider to use the named template parameters instead.
110 115
  ///
111 116
  /// \warning Both number types must be signed and all input data must
112 117
  /// be integer.
113 118
  /// \warning This algorithm does not support negative costs for such
114 119
  /// arcs that have infinite upper bound.
115 120
  ///
116 121
  /// \note %CostScaling provides three different internal methods,
117 122
  /// from which the most efficient one is used by default.
118 123
  /// For more information, see \ref Method.
119 124
#ifdef DOXYGEN
120 125
  template <typename GR, typename V, typename C, typename TR>
121 126
#else
122 127
  template < typename GR, typename V = int, typename C = V,
123 128
             typename TR = CostScalingDefaultTraits<GR, V, C> >
124 129
#endif
125 130
  class CostScaling
126 131
  {
127 132
  public:
128 133

	
129 134
    /// The type of the digraph
130 135
    typedef typename TR::Digraph Digraph;
131 136
    /// The type of the flow amounts, capacity bounds and supply values
132 137
    typedef typename TR::Value Value;
133 138
    /// The type of the arc costs
134 139
    typedef typename TR::Cost Cost;
135 140

	
136 141
    /// \brief The large cost type
137 142
    ///
138 143
    /// The large cost type used for internal computations.
139
    /// Using the \ref CostScalingDefaultTraits "default traits class",
140
    /// it is \c long \c long if the \c Cost type is integer,
144
    /// By default, it is \c long \c long if the \c Cost type is integer,
141 145
    /// otherwise it is \c double.
142 146
    typedef typename TR::LargeCost LargeCost;
143 147

	
144 148
    /// The \ref CostScalingDefaultTraits "traits class" of the algorithm
145 149
    typedef TR Traits;
146 150

	
147 151
  public:
148 152

	
149 153
    /// \brief Problem type constants for the \c run() function.
150 154
    ///
151 155
    /// Enum type containing the problem type constants that can be
152 156
    /// returned by the \ref run() function of the algorithm.
153 157
    enum ProblemType {
154 158
      /// The problem has no feasible solution (flow).
155 159
      INFEASIBLE,
156 160
      /// The problem has optimal solution (i.e. it is feasible and
157 161
      /// bounded), and the algorithm has found optimal flow and node
158 162
      /// potentials (primal and dual solutions).
159 163
      OPTIMAL,
160 164
      /// The digraph contains an arc of negative cost and infinite
161 165
      /// upper bound. It means that the objective function is unbounded
162 166
      /// on that arc, however, note that it could actually be bounded
163 167
      /// over the feasible flows, but this algroithm cannot handle
164 168
      /// these cases.
Ignore white space 6 line context
... ...
@@ -100,48 +100,53 @@
100 100
    ///It must conform to the \ref concepts::WriteMap "WriteMap" concept.
101 101
    typedef typename Digraph::template NodeMap<int> DistMap;
102 102
    ///Instantiates a \c DistMap.
103 103

	
104 104
    ///This function instantiates a \ref DistMap.
105 105
    ///\param g is the digraph, to which we would like to define the
106 106
    ///\ref DistMap.
107 107
    static DistMap *createDistMap(const Digraph &g)
108 108
    {
109 109
      return new DistMap(g);
110 110
    }
111 111
  };
112 112

	
113 113
  ///%DFS algorithm class.
114 114

	
115 115
  ///\ingroup search
116 116
  ///This class provides an efficient implementation of the %DFS algorithm.
117 117
  ///
118 118
  ///There is also a \ref dfs() "function-type interface" for the DFS
119 119
  ///algorithm, which is convenient in the simplier cases and it can be
120 120
  ///used easier.
121 121
  ///
122 122
  ///\tparam GR The type of the digraph the algorithm runs on.
123 123
  ///The default type is \ref ListDigraph.
124
  ///\tparam TR The traits class that defines various types used by the
125
  ///algorithm. By default, it is \ref DfsDefaultTraits
126
  ///"DfsDefaultTraits<GR>".
127
  ///In most cases, this parameter should not be set directly,
128
  ///consider to use the named template parameters instead.
124 129
#ifdef DOXYGEN
125 130
  template <typename GR,
126 131
            typename TR>
127 132
#else
128 133
  template <typename GR=ListDigraph,
129 134
            typename TR=DfsDefaultTraits<GR> >
130 135
#endif
131 136
  class Dfs {
132 137
  public:
133 138

	
134 139
    ///The type of the digraph the algorithm runs on.
135 140
    typedef typename TR::Digraph Digraph;
136 141

	
137 142
    ///\brief The type of the map that stores the predecessor arcs of the
138 143
    ///DFS paths.
139 144
    typedef typename TR::PredMap PredMap;
140 145
    ///The type of the map that stores the distances of the nodes.
141 146
    typedef typename TR::DistMap DistMap;
142 147
    ///The type of the map that indicates which nodes are reached.
143 148
    typedef typename TR::ReachedMap ReachedMap;
144 149
    ///The type of the map that indicates which nodes are processed.
145 150
    typedef typename TR::ProcessedMap ProcessedMap;
146 151
    ///The type of the paths.
147 152
    typedef PredMapPath<Digraph, PredMap> Path;
... ...
@@ -866,48 +871,51 @@
866 871
    /// all of the attributes to \c 0.
867 872
    DfsWizardBase() : _g(0), _reached(0), _processed(0), _pred(0),
868 873
                      _dist(0), _path(0), _di(0) {}
869 874

	
870 875
    /// Constructor.
871 876

	
872 877
    /// This constructor requires one parameter,
873 878
    /// others are initiated to \c 0.
874 879
    /// \param g The digraph the algorithm runs on.
875 880
    DfsWizardBase(const GR &g) :
876 881
      _g(reinterpret_cast<void*>(const_cast<GR*>(&g))),
877 882
      _reached(0), _processed(0), _pred(0), _dist(0),  _path(0), _di(0) {}
878 883

	
879 884
  };
880 885

	
881 886
  /// Auxiliary class for the function-type interface of DFS algorithm.
882 887

	
883 888
  /// This auxiliary class is created to implement the
884 889
  /// \ref dfs() "function-type interface" of \ref Dfs algorithm.
885 890
  /// It does not have own \ref run(Node) "run()" method, it uses the
886 891
  /// functions and features of the plain \ref Dfs.
887 892
  ///
888 893
  /// This class should only be used through the \ref dfs() function,
889 894
  /// which makes it easier to use the algorithm.
895
  ///
896
  /// \tparam TR The traits class that defines various types used by the
897
  /// algorithm.
890 898
  template<class TR>
891 899
  class DfsWizard : public TR
892 900
  {
893 901
    typedef TR Base;
894 902

	
895 903
    typedef typename TR::Digraph Digraph;
896 904

	
897 905
    typedef typename Digraph::Node Node;
898 906
    typedef typename Digraph::NodeIt NodeIt;
899 907
    typedef typename Digraph::Arc Arc;
900 908
    typedef typename Digraph::OutArcIt OutArcIt;
901 909

	
902 910
    typedef typename TR::PredMap PredMap;
903 911
    typedef typename TR::DistMap DistMap;
904 912
    typedef typename TR::ReachedMap ReachedMap;
905 913
    typedef typename TR::ProcessedMap ProcessedMap;
906 914
    typedef typename TR::Path Path;
907 915

	
908 916
  public:
909 917

	
910 918
    /// Constructor.
911 919
    DfsWizard() : TR() {}
912 920

	
913 921
    /// Constructor that requires parameters.
... ...
@@ -1216,53 +1224,53 @@
1216 1224
  /// \ingroup search
1217 1225
  ///
1218 1226
  /// \brief DFS algorithm class with visitor interface.
1219 1227
  ///
1220 1228
  /// This class provides an efficient implementation of the DFS algorithm
1221 1229
  /// with visitor interface.
1222 1230
  ///
1223 1231
  /// The DfsVisit class provides an alternative interface to the Dfs
1224 1232
  /// class. It works with callback mechanism, the DfsVisit object calls
1225 1233
  /// the member functions of the \c Visitor class on every DFS event.
1226 1234
  ///
1227 1235
  /// This interface of the DFS algorithm should be used in special cases
1228 1236
  /// when extra actions have to be performed in connection with certain
1229 1237
  /// events of the DFS algorithm. Otherwise consider to use Dfs or dfs()
1230 1238
  /// instead.
1231 1239
  ///
1232 1240
  /// \tparam GR The type of the digraph the algorithm runs on.
1233 1241
  /// The default type is \ref ListDigraph.
1234 1242
  /// The value of GR is not used directly by \ref DfsVisit,
1235 1243
  /// it is only passed to \ref DfsVisitDefaultTraits.
1236 1244
  /// \tparam VS The Visitor type that is used by the algorithm.
1237 1245
  /// \ref DfsVisitor "DfsVisitor<GR>" is an empty visitor, which
1238 1246
  /// does not observe the DFS events. If you want to observe the DFS
1239 1247
  /// events, you should implement your own visitor class.
1240
  /// \tparam TR Traits class to set various data types used by the
1241
  /// algorithm. The default traits class is
1242
  /// \ref DfsVisitDefaultTraits "DfsVisitDefaultTraits<GR>".
1243
  /// See \ref DfsVisitDefaultTraits for the documentation of
1244
  /// a DFS visit traits class.
1248
  /// \tparam TR The traits class that defines various types used by the
1249
  /// algorithm. By default, it is \ref DfsVisitDefaultTraits
1250
  /// "DfsVisitDefaultTraits<GR>".
1251
  /// In most cases, this parameter should not be set directly,
1252
  /// consider to use the named template parameters instead.
1245 1253
#ifdef DOXYGEN
1246 1254
  template <typename GR, typename VS, typename TR>
1247 1255
#else
1248 1256
  template <typename GR = ListDigraph,
1249 1257
            typename VS = DfsVisitor<GR>,
1250 1258
            typename TR = DfsVisitDefaultTraits<GR> >
1251 1259
#endif
1252 1260
  class DfsVisit {
1253 1261
  public:
1254 1262

	
1255 1263
    ///The traits class.
1256 1264
    typedef TR Traits;
1257 1265

	
1258 1266
    ///The type of the digraph the algorithm runs on.
1259 1267
    typedef typename Traits::Digraph Digraph;
1260 1268

	
1261 1269
    ///The visitor type used by the algorithm.
1262 1270
    typedef VS Visitor;
1263 1271

	
1264 1272
    ///The type of the map that indicates which nodes are reached.
1265 1273
    typedef typename Traits::ReachedMap ReachedMap;
1266 1274

	
1267 1275
  private:
1268 1276

	
Ignore white space 6 line context
... ...
@@ -171,48 +171,53 @@
171 171
  ///
172 172
  ///The %Dijkstra algorithm solves the single-source shortest path problem
173 173
  ///when all arc lengths are non-negative. If there are negative lengths,
174 174
  ///the BellmanFord algorithm should be used instead.
175 175
  ///
176 176
  ///The arc lengths are passed to the algorithm using a
177 177
  ///\ref concepts::ReadMap "ReadMap",
178 178
  ///so it is easy to change it to any kind of length.
179 179
  ///The type of the length is determined by the
180 180
  ///\ref concepts::ReadMap::Value "Value" of the length map.
181 181
  ///It is also possible to change the underlying priority heap.
182 182
  ///
183 183
  ///There is also a \ref dijkstra() "function-type interface" for the
184 184
  ///%Dijkstra algorithm, which is convenient in the simplier cases and
185 185
  ///it can be used easier.
186 186
  ///
187 187
  ///\tparam GR The type of the digraph the algorithm runs on.
188 188
  ///The default type is \ref ListDigraph.
189 189
  ///\tparam LEN A \ref concepts::ReadMap "readable" arc map that specifies
190 190
  ///the lengths of the arcs.
191 191
  ///It is read once for each arc, so the map may involve in
192 192
  ///relatively time consuming process to compute the arc lengths if
193 193
  ///it is necessary. The default map type is \ref
194 194
  ///concepts::Digraph::ArcMap "GR::ArcMap<int>".
195
  ///\tparam TR The traits class that defines various types used by the
196
  ///algorithm. By default, it is \ref DijkstraDefaultTraits
197
  ///"DijkstraDefaultTraits<GR, LEN>".
198
  ///In most cases, this parameter should not be set directly,
199
  ///consider to use the named template parameters instead.
195 200
#ifdef DOXYGEN
196 201
  template <typename GR, typename LEN, typename TR>
197 202
#else
198 203
  template <typename GR=ListDigraph,
199 204
            typename LEN=typename GR::template ArcMap<int>,
200 205
            typename TR=DijkstraDefaultTraits<GR,LEN> >
201 206
#endif
202 207
  class Dijkstra {
203 208
  public:
204 209

	
205 210
    ///The type of the digraph the algorithm runs on.
206 211
    typedef typename TR::Digraph Digraph;
207 212

	
208 213
    ///The type of the arc lengths.
209 214
    typedef typename TR::Value Value;
210 215
    ///The type of the map that stores the arc lengths.
211 216
    typedef typename TR::LengthMap LengthMap;
212 217
    ///\brief The type of the map that stores the predecessor arcs of the
213 218
    ///shortest paths.
214 219
    typedef typename TR::PredMap PredMap;
215 220
    ///The type of the map that stores the distances of the nodes.
216 221
    typedef typename TR::DistMap DistMap;
217 222
    ///The type of the map that indicates which nodes are processed.
218 223
    typedef typename TR::ProcessedMap ProcessedMap;
... ...
@@ -1071,48 +1076,51 @@
1071 1076
                           _dist(0), _path(0), _di(0) {}
1072 1077

	
1073 1078
    /// Constructor.
1074 1079

	
1075 1080
    /// This constructor requires two parameters,
1076 1081
    /// others are initiated to \c 0.
1077 1082
    /// \param g The digraph the algorithm runs on.
1078 1083
    /// \param l The length map.
1079 1084
    DijkstraWizardBase(const GR &g,const LEN &l) :
1080 1085
      _g(reinterpret_cast<void*>(const_cast<GR*>(&g))),
1081 1086
      _length(reinterpret_cast<void*>(const_cast<LEN*>(&l))),
1082 1087
      _processed(0), _pred(0), _dist(0), _path(0), _di(0) {}
1083 1088

	
1084 1089
  };
1085 1090

	
1086 1091
  /// Auxiliary class for the function-type interface of Dijkstra algorithm.
1087 1092

	
1088 1093
  /// This auxiliary class is created to implement the
1089 1094
  /// \ref dijkstra() "function-type interface" of \ref Dijkstra algorithm.
1090 1095
  /// It does not have own \ref run(Node) "run()" method, it uses the
1091 1096
  /// functions and features of the plain \ref Dijkstra.
1092 1097
  ///
1093 1098
  /// This class should only be used through the \ref dijkstra() function,
1094 1099
  /// which makes it easier to use the algorithm.
1100
  ///
1101
  /// \tparam TR The traits class that defines various types used by the
1102
  /// algorithm.
1095 1103
  template<class TR>
1096 1104
  class DijkstraWizard : public TR
1097 1105
  {
1098 1106
    typedef TR Base;
1099 1107

	
1100 1108
    typedef typename TR::Digraph Digraph;
1101 1109

	
1102 1110
    typedef typename Digraph::Node Node;
1103 1111
    typedef typename Digraph::NodeIt NodeIt;
1104 1112
    typedef typename Digraph::Arc Arc;
1105 1113
    typedef typename Digraph::OutArcIt OutArcIt;
1106 1114

	
1107 1115
    typedef typename TR::LengthMap LengthMap;
1108 1116
    typedef typename LengthMap::Value Value;
1109 1117
    typedef typename TR::PredMap PredMap;
1110 1118
    typedef typename TR::DistMap DistMap;
1111 1119
    typedef typename TR::ProcessedMap ProcessedMap;
1112 1120
    typedef typename TR::Path Path;
1113 1121
    typedef typename TR::Heap Heap;
1114 1122

	
1115 1123
  public:
1116 1124

	
1117 1125
    /// Constructor.
1118 1126
    DijkstraWizard() : TR() {}
Ignore white space 6 line context
... ...
@@ -85,71 +85,75 @@
85 85
#else
86 86
    typedef long LargeValue;
87 87
#endif
88 88
    typedef lemon::Tolerance<LargeValue> Tolerance;
89 89
    typedef lemon::Path<Digraph> Path;
90 90
  };
91 91

	
92 92

	
93 93
  /// \addtogroup min_mean_cycle
94 94
  /// @{
95 95

	
96 96
  /// \brief Implementation of the Hartmann-Orlin algorithm for finding
97 97
  /// a minimum mean cycle.
98 98
  ///
99 99
  /// This class implements the Hartmann-Orlin algorithm for finding
100 100
  /// a directed cycle of minimum mean length (cost) in a digraph
101 101
  /// \ref amo93networkflows, \ref dasdan98minmeancycle.
102 102
  /// It is an improved version of \ref Karp "Karp"'s original algorithm,
103 103
  /// it applies an efficient early termination scheme.
104 104
  /// It runs in time O(ne) and uses space O(n<sup>2</sup>+e).
105 105
  ///
106 106
  /// \tparam GR The type of the digraph the algorithm runs on.
107 107
  /// \tparam LEN The type of the length map. The default
108 108
  /// map type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
109
  /// \tparam TR The traits class that defines various types used by the
110
  /// algorithm. By default, it is \ref HartmannOrlinDefaultTraits
111
  /// "HartmannOrlinDefaultTraits<GR, LEN>".
112
  /// In most cases, this parameter should not be set directly,
113
  /// consider to use the named template parameters instead.
109 114
#ifdef DOXYGEN
110 115
  template <typename GR, typename LEN, typename TR>
111 116
#else
112 117
  template < typename GR,
113 118
             typename LEN = typename GR::template ArcMap<int>,
114 119
             typename TR = HartmannOrlinDefaultTraits<GR, LEN> >
115 120
#endif
116 121
  class HartmannOrlin
117 122
  {
118 123
  public:
119 124

	
120 125
    /// The type of the digraph
121 126
    typedef typename TR::Digraph Digraph;
122 127
    /// The type of the length map
123 128
    typedef typename TR::LengthMap LengthMap;
124 129
    /// The type of the arc lengths
125 130
    typedef typename TR::Value Value;
126 131

	
127 132
    /// \brief The large value type
128 133
    ///
129 134
    /// The large value type used for internal computations.
130
    /// Using the \ref HartmannOrlinDefaultTraits "default traits class",
131
    /// it is \c long \c long if the \c Value type is integer,
135
    /// By default, it is \c long \c long if the \c Value type is integer,
132 136
    /// otherwise it is \c double.
133 137
    typedef typename TR::LargeValue LargeValue;
134 138

	
135 139
    /// The tolerance type
136 140
    typedef typename TR::Tolerance Tolerance;
137 141

	
138 142
    /// \brief The path type of the found cycles
139 143
    ///
140 144
    /// The path type of the found cycles.
141 145
    /// Using the \ref HartmannOrlinDefaultTraits "default traits class",
142 146
    /// it is \ref lemon::Path "Path<Digraph>".
143 147
    typedef typename TR::Path Path;
144 148

	
145 149
    /// The \ref HartmannOrlinDefaultTraits "traits class" of the algorithm
146 150
    typedef TR Traits;
147 151

	
148 152
  private:
149 153

	
150 154
    TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
151 155

	
152 156
    // Data sturcture for path data
153 157
    struct PathData
154 158
    {
155 159
      LargeValue dist;
Ignore white space 6 line context
... ...
@@ -85,71 +85,75 @@
85 85
#else
86 86
    typedef long LargeValue;
87 87
#endif
88 88
    typedef lemon::Tolerance<LargeValue> Tolerance;
89 89
    typedef lemon::Path<Digraph> Path;
90 90
  };
91 91

	
92 92

	
93 93
  /// \addtogroup min_mean_cycle
94 94
  /// @{
95 95

	
96 96
  /// \brief Implementation of Howard's algorithm for finding a minimum
97 97
  /// mean cycle.
98 98
  ///
99 99
  /// This class implements Howard's policy iteration algorithm for finding
100 100
  /// a directed cycle of minimum mean length (cost) in a digraph
101 101
  /// \ref amo93networkflows, \ref dasdan98minmeancycle.
102 102
  /// This class provides the most efficient algorithm for the
103 103
  /// minimum mean cycle problem, though the best known theoretical
104 104
  /// bound on its running time is exponential.
105 105
  ///
106 106
  /// \tparam GR The type of the digraph the algorithm runs on.
107 107
  /// \tparam LEN The type of the length map. The default
108 108
  /// map type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
109
  /// \tparam TR The traits class that defines various types used by the
110
  /// algorithm. By default, it is \ref HowardDefaultTraits
111
  /// "HowardDefaultTraits<GR, LEN>".
112
  /// In most cases, this parameter should not be set directly,
113
  /// consider to use the named template parameters instead.
109 114
#ifdef DOXYGEN
110 115
  template <typename GR, typename LEN, typename TR>
111 116
#else
112 117
  template < typename GR,
113 118
             typename LEN = typename GR::template ArcMap<int>,
114 119
             typename TR = HowardDefaultTraits<GR, LEN> >
115 120
#endif
116 121
  class Howard
117 122
  {
118 123
  public:
119 124
  
120 125
    /// The type of the digraph
121 126
    typedef typename TR::Digraph Digraph;
122 127
    /// The type of the length map
123 128
    typedef typename TR::LengthMap LengthMap;
124 129
    /// The type of the arc lengths
125 130
    typedef typename TR::Value Value;
126 131

	
127 132
    /// \brief The large value type
128 133
    ///
129 134
    /// The large value type used for internal computations.
130
    /// Using the \ref HowardDefaultTraits "default traits class",
131
    /// it is \c long \c long if the \c Value type is integer,
135
    /// By default, it is \c long \c long if the \c Value type is integer,
132 136
    /// otherwise it is \c double.
133 137
    typedef typename TR::LargeValue LargeValue;
134 138

	
135 139
    /// The tolerance type
136 140
    typedef typename TR::Tolerance Tolerance;
137 141

	
138 142
    /// \brief The path type of the found cycles
139 143
    ///
140 144
    /// The path type of the found cycles.
141 145
    /// Using the \ref HowardDefaultTraits "default traits class",
142 146
    /// it is \ref lemon::Path "Path<Digraph>".
143 147
    typedef typename TR::Path Path;
144 148

	
145 149
    /// The \ref HowardDefaultTraits "traits class" of the algorithm
146 150
    typedef TR Traits;
147 151

	
148 152
  private:
149 153

	
150 154
    TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
151 155
  
152 156
    // The digraph the algorithm runs on
153 157
    const Digraph &_gr;
154 158
    // The length of the arcs
155 159
    const LengthMap &_length;
Ignore white space 6 line context
... ...
@@ -83,71 +83,75 @@
83 83
#ifdef LEMON_HAVE_LONG_LONG
84 84
    typedef long long LargeValue;
85 85
#else
86 86
    typedef long LargeValue;
87 87
#endif
88 88
    typedef lemon::Tolerance<LargeValue> Tolerance;
89 89
    typedef lemon::Path<Digraph> Path;
90 90
  };
91 91

	
92 92

	
93 93
  /// \addtogroup min_mean_cycle
94 94
  /// @{
95 95

	
96 96
  /// \brief Implementation of Karp's algorithm for finding a minimum
97 97
  /// mean cycle.
98 98
  ///
99 99
  /// This class implements Karp's algorithm for finding a directed
100 100
  /// cycle of minimum mean length (cost) in a digraph
101 101
  /// \ref amo93networkflows, \ref dasdan98minmeancycle.
102 102
  /// It runs in time O(ne) and uses space O(n<sup>2</sup>+e).
103 103
  ///
104 104
  /// \tparam GR The type of the digraph the algorithm runs on.
105 105
  /// \tparam LEN The type of the length map. The default
106 106
  /// map type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
107
  /// \tparam TR The traits class that defines various types used by the
108
  /// algorithm. By default, it is \ref KarpDefaultTraits
109
  /// "KarpDefaultTraits<GR, LEN>".
110
  /// In most cases, this parameter should not be set directly,
111
  /// consider to use the named template parameters instead.
107 112
#ifdef DOXYGEN
108 113
  template <typename GR, typename LEN, typename TR>
109 114
#else
110 115
  template < typename GR,
111 116
             typename LEN = typename GR::template ArcMap<int>,
112 117
             typename TR = KarpDefaultTraits<GR, LEN> >
113 118
#endif
114 119
  class Karp
115 120
  {
116 121
  public:
117 122

	
118 123
    /// The type of the digraph
119 124
    typedef typename TR::Digraph Digraph;
120 125
    /// The type of the length map
121 126
    typedef typename TR::LengthMap LengthMap;
122 127
    /// The type of the arc lengths
123 128
    typedef typename TR::Value Value;
124 129

	
125 130
    /// \brief The large value type
126 131
    ///
127 132
    /// The large value type used for internal computations.
128
    /// Using the \ref KarpDefaultTraits "default traits class",
129
    /// it is \c long \c long if the \c Value type is integer,
133
    /// By default, it is \c long \c long if the \c Value type is integer,
130 134
    /// otherwise it is \c double.
131 135
    typedef typename TR::LargeValue LargeValue;
132 136

	
133 137
    /// The tolerance type
134 138
    typedef typename TR::Tolerance Tolerance;
135 139

	
136 140
    /// \brief The path type of the found cycles
137 141
    ///
138 142
    /// The path type of the found cycles.
139 143
    /// Using the \ref KarpDefaultTraits "default traits class",
140 144
    /// it is \ref lemon::Path "Path<Digraph>".
141 145
    typedef typename TR::Path Path;
142 146

	
143 147
    /// The \ref KarpDefaultTraits "traits class" of the algorithm
144 148
    typedef TR Traits;
145 149

	
146 150
  private:
147 151

	
148 152
    TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
149 153

	
150 154
    // Data sturcture for path data
151 155
    struct PathData
152 156
    {
153 157
      LargeValue dist;
Ignore white space 48 line context
... ...
@@ -91,59 +91,60 @@
91 91

	
92 92
  };
93 93

	
94 94
  /// \ingroup spantree
95 95
  ///
96 96
  /// \brief Minimum Cost Arborescence algorithm class.
97 97
  ///
98 98
  /// This class provides an efficient implementation of the
99 99
  /// Minimum Cost Arborescence algorithm. The arborescence is a tree
100 100
  /// which is directed from a given source node of the digraph. One or
101 101
  /// more sources should be given to the algorithm and it will calculate
102 102
  /// the minimum cost subgraph that is the union of arborescences with the
103 103
  /// given sources and spans all the nodes which are reachable from the
104 104
  /// sources. The time complexity of the algorithm is O(n<sup>2</sup>+e).
105 105
  ///
106 106
  /// The algorithm also provides an optimal dual solution, therefore
107 107
  /// the optimality of the solution can be checked.
108 108
  ///
109 109
  /// \param GR The digraph type the algorithm runs on.
110 110
  /// \param CM A read-only arc map storing the costs of the
111 111
  /// arcs. It is read once for each arc, so the map may involve in
112 112
  /// relatively time consuming process to compute the arc costs if
113 113
  /// it is necessary. The default map type is \ref
114 114
  /// concepts::Digraph::ArcMap "Digraph::ArcMap<int>".
115
  /// \param TR Traits class to set various data types used
116
  /// by the algorithm. The default traits class is
117
  /// \ref MinCostArborescenceDefaultTraits
115
  /// \tparam TR The traits class that defines various types used by the
116
  /// algorithm. By default, it is \ref MinCostArborescenceDefaultTraits
118 117
  /// "MinCostArborescenceDefaultTraits<GR, CM>".
118
  /// In most cases, this parameter should not be set directly,
119
  /// consider to use the named template parameters instead.
119 120
#ifndef DOXYGEN
120 121
  template <typename GR,
121 122
            typename CM = typename GR::template ArcMap<int>,
122 123
            typename TR =
123 124
              MinCostArborescenceDefaultTraits<GR, CM> >
124 125
#else
125
  template <typename GR, typename CM, typedef TR>
126
  template <typename GR, typename CM, typename TR>
126 127
#endif
127 128
  class MinCostArborescence {
128 129
  public:
129 130

	
130 131
    /// \brief The \ref MinCostArborescenceDefaultTraits "traits class" 
131 132
    /// of the algorithm. 
132 133
    typedef TR Traits;
133 134
    /// The type of the underlying digraph.
134 135
    typedef typename Traits::Digraph Digraph;
135 136
    /// The type of the map that stores the arc costs.
136 137
    typedef typename Traits::CostMap CostMap;
137 138
    ///The type of the costs of the arcs.
138 139
    typedef typename Traits::Value Value;
139 140
    ///The type of the predecessor map.
140 141
    typedef typename Traits::PredMap PredMap;
141 142
    ///The type of the map that stores which arcs are in the arborescence.
142 143
    typedef typename Traits::ArborescenceMap ArborescenceMap;
143 144

	
144 145
    typedef MinCostArborescence Create;
145 146

	
146 147
  private:
147 148

	
148 149
    TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
149 150

	
Ignore white space 6 line context
... ...
@@ -497,72 +497,73 @@
497 497

	
498 498
        if (child != INVALID) {
499 499
          if (low_map[child] < rorder) return true;
500 500
        }
501 501

	
502 502
        if (ancestor_map[node] < rorder) return true;
503 503

	
504 504
        return false;
505 505
      }
506 506

	
507 507
      bool pertinent(const Node& node, const EmbedArc& embed_arc,
508 508
                     const MergeRoots& merge_roots) {
509 509
        return !merge_roots[node].empty() || embed_arc[node];
510 510
      }
511 511

	
512 512
    };
513 513

	
514 514
  }
515 515

	
516 516
  /// \ingroup planar
517 517
  ///
518 518
  /// \brief Planarity checking of an undirected simple graph
519 519
  ///
520 520
  /// This function implements the Boyer-Myrvold algorithm for
521
  /// planarity checking of an undirected graph. It is a simplified
521
  /// planarity checking of an undirected simple graph. It is a simplified
522 522
  /// version of the PlanarEmbedding algorithm class because neither
523
  /// the embedding nor the kuratowski subdivisons are not computed.
523
  /// the embedding nor the Kuratowski subdivisons are computed.
524 524
  template <typename GR>
525 525
  bool checkPlanarity(const GR& graph) {
526 526
    _planarity_bits::PlanarityChecking<GR> pc(graph);
527 527
    return pc.run();
528 528
  }
529 529

	
530 530
  /// \ingroup planar
531 531
  ///
532 532
  /// \brief Planar embedding of an undirected simple graph
533 533
  ///
534 534
  /// This class implements the Boyer-Myrvold algorithm for planar
535
  /// embedding of an undirected graph. The planar embedding is an
535
  /// embedding of an undirected simple graph. The planar embedding is an
536 536
  /// ordering of the outgoing edges of the nodes, which is a possible
537 537
  /// configuration to draw the graph in the plane. If there is not
538
  /// such ordering then the graph contains a \f$ K_5 \f$ (full graph
539
  /// with 5 nodes) or a \f$ K_{3,3} \f$ (complete bipartite graph on
540
  /// 3 ANode and 3 BNode) subdivision.
538
  /// such ordering then the graph contains a K<sub>5</sub> (full graph
539
  /// with 5 nodes) or a K<sub>3,3</sub> (complete bipartite graph on
540
  /// 3 Red and 3 Blue nodes) subdivision.
541 541
  ///
542 542
  /// The current implementation calculates either an embedding or a
543
  /// Kuratowski subdivision. The running time of the algorithm is 
544
  /// \f$ O(n) \f$.
543
  /// Kuratowski subdivision. The running time of the algorithm is O(n).
544
  ///
545
  /// \see PlanarDrawing, checkPlanarity()
545 546
  template <typename Graph>
546 547
  class PlanarEmbedding {
547 548
  private:
548 549

	
549 550
    TEMPLATE_GRAPH_TYPEDEFS(Graph);
550 551

	
551 552
    const Graph& _graph;
552 553
    typename Graph::template ArcMap<Arc> _embedding;
553 554

	
554 555
    typename Graph::template EdgeMap<bool> _kuratowski;
555 556

	
556 557
  private:
557 558

	
558 559
    typedef typename Graph::template NodeMap<Arc> PredMap;
559 560

	
560 561
    typedef typename Graph::template EdgeMap<bool> TreeMap;
561 562

	
562 563
    typedef typename Graph::template NodeMap<int> OrderMap;
563 564
    typedef std::vector<Node> OrderList;
564 565

	
565 566
    typedef typename Graph::template NodeMap<int> LowMap;
566 567
    typedef typename Graph::template NodeMap<int> AncestorMap;
567 568

	
568 569
    typedef _planarity_bits::NodeDataNode<Graph> NodeDataNode;
... ...
@@ -570,64 +571,68 @@
570 571

	
571 572
    typedef _planarity_bits::ChildListNode<Graph> ChildListNode;
572 573
    typedef typename Graph::template NodeMap<ChildListNode> ChildLists;
573 574

	
574 575
    typedef typename Graph::template NodeMap<std::list<int> > MergeRoots;
575 576

	
576 577
    typedef typename Graph::template NodeMap<Arc> EmbedArc;
577 578

	
578 579
    typedef _planarity_bits::ArcListNode<Graph> ArcListNode;
579 580
    typedef typename Graph::template ArcMap<ArcListNode> ArcLists;
580 581

	
581 582
    typedef typename Graph::template NodeMap<bool> FlipMap;
582 583

	
583 584
    typedef typename Graph::template NodeMap<int> TypeMap;
584 585

	
585 586
    enum IsolatorNodeType {
586 587
      HIGHX = 6, LOWX = 7,
587 588
      HIGHY = 8, LOWY = 9,
588 589
      ROOT = 10, PERTINENT = 11,
589 590
      INTERNAL = 12
590 591
    };
591 592

	
592 593
  public:
593 594

	
594
    /// \brief The map for store of embedding
595
    /// \brief The map type for storing the embedding
596
    ///
597
    /// The map type for storing the embedding.
598
    /// \see embeddingMap()
595 599
    typedef typename Graph::template ArcMap<Arc> EmbeddingMap;
596 600

	
597 601
    /// \brief Constructor
598 602
    ///
599
    /// \note The graph should be simple, i.e. parallel and loop arc
600
    /// free.
603
    /// Constructor.
604
    /// \pre The graph must be simple, i.e. it should not
605
    /// contain parallel or loop arcs.
601 606
    PlanarEmbedding(const Graph& graph)
602 607
      : _graph(graph), _embedding(_graph), _kuratowski(graph, false) {}
603 608

	
604
    /// \brief Runs the algorithm.
609
    /// \brief Run the algorithm.
605 610
    ///
606
    /// Runs the algorithm.
607
    /// \param kuratowski If the parameter is false, then the
611
    /// This function runs the algorithm.
612
    /// \param kuratowski If this parameter is set to \c false, then the
608 613
    /// algorithm does not compute a Kuratowski subdivision.
609
    ///\return %True when the graph is planar.
614
    /// \return \c true if the graph is planar.
610 615
    bool run(bool kuratowski = true) {
611 616
      typedef _planarity_bits::PlanarityVisitor<Graph> Visitor;
612 617

	
613 618
      PredMap pred_map(_graph, INVALID);
614 619
      TreeMap tree_map(_graph, false);
615 620

	
616 621
      OrderMap order_map(_graph, -1);
617 622
      OrderList order_list;
618 623

	
619 624
      AncestorMap ancestor_map(_graph, -1);
620 625
      LowMap low_map(_graph, -1);
621 626

	
622 627
      Visitor visitor(_graph, pred_map, tree_map,
623 628
                      order_map, order_list, ancestor_map, low_map);
624 629
      DfsVisit<Graph, Visitor> visit(_graph, visitor);
625 630
      visit.run();
626 631

	
627 632
      ChildLists child_lists(_graph);
628 633
      createChildLists(tree_map, order_map, low_map, child_lists);
629 634

	
630 635
      NodeData node_data(2 * order_list.size());
631 636

	
632 637
      EmbedArc embed_arc(_graph, INVALID);
633 638

	
... ...
@@ -678,72 +683,74 @@
678 683
            if (embed_arc[target] != INVALID) {
679 684
              if (kuratowski) {
680 685
                isolateKuratowski(e, node_data, arc_lists, flip_map,
681 686
                                  order_map, order_list, pred_map, child_lists,
682 687
                                  ancestor_map, low_map,
683 688
                                  embed_arc, merge_roots);
684 689
              }
685 690
              return false;
686 691
            }
687 692
          }
688 693
        }
689 694
      }
690 695

	
691 696
      for (int i = 0; i < int(order_list.size()); ++i) {
692 697

	
693 698
        mergeRemainingFaces(order_list[i], node_data, order_list, order_map,
694 699
                            child_lists, arc_lists);
695 700
        storeEmbedding(order_list[i], node_data, order_map, pred_map,
696 701
                       arc_lists, flip_map);
697 702
      }
698 703

	
699 704
      return true;
700 705
    }
701 706

	
702
    /// \brief Gives back the successor of an arc
707
    /// \brief Give back the successor of an arc
703 708
    ///
704
    /// Gives back the successor of an arc. This function makes
709
    /// This function gives back the successor of an arc. It makes
705 710
    /// possible to query the cyclic order of the outgoing arcs from
706 711
    /// a node.
707 712
    Arc next(const Arc& arc) const {
708 713
      return _embedding[arc];
709 714
    }
710 715

	
711
    /// \brief Gives back the calculated embedding map
716
    /// \brief Give back the calculated embedding map
712 717
    ///
713
    /// The returned map contains the successor of each arc in the
714
    /// graph.
718
    /// This function gives back the calculated embedding map, which
719
    /// contains the successor of each arc in the cyclic order of the
720
    /// outgoing arcs of its source node.
715 721
    const EmbeddingMap& embeddingMap() const {
716 722
      return _embedding;
717 723
    }
718 724

	
719
    /// \brief Gives back true if the undirected arc is in the
720
    /// kuratowski subdivision
725
    /// \brief Give back \c true if the given edge is in the Kuratowski
726
    /// subdivision
721 727
    ///
722
    /// Gives back true if the undirected arc is in the kuratowski
723
    /// subdivision
724
    /// \note The \c run() had to be called with true value.
725
    bool kuratowski(const Edge& edge) {
728
    /// This function gives back \c true if the given edge is in the found
729
    /// Kuratowski subdivision.
730
    /// \pre The \c run() function must be called with \c true parameter
731
    /// before using this function.
732
    bool kuratowski(const Edge& edge) const {
726 733
      return _kuratowski[edge];
727 734
    }
728 735

	
729 736
  private:
730 737

	
731 738
    void createChildLists(const TreeMap& tree_map, const OrderMap& order_map,
732 739
                          const LowMap& low_map, ChildLists& child_lists) {
733 740

	
734 741
      for (NodeIt n(_graph); n != INVALID; ++n) {
735 742
        Node source = n;
736 743

	
737 744
        std::vector<Node> targets;
738 745
        for (OutArcIt e(_graph, n); e != INVALID; ++e) {
739 746
          Node target = _graph.target(e);
740 747

	
741 748
          if (order_map[source] < order_map[target] && tree_map[e]) {
742 749
            targets.push_back(target);
743 750
          }
744 751
        }
745 752

	
746 753
        if (targets.size() == 0) {
747 754
          child_lists[source].first = INVALID;
748 755
        } else if (targets.size() == 1) {
749 756
          child_lists[source].first = targets[0];
... ...
@@ -2038,71 +2045,74 @@
2038 2045
              graph.direct(graph.addEdge(t, graph.source(e)), true);
2039 2046

	
2040 2047
            embedding[n] = pn;
2041 2048
            embedding[graph.oppositeArc(n)] = e;
2042 2049
            embedding[graph.oppositeArc(p)] = graph.oppositeArc(n);
2043 2050

	
2044 2051
            pn = n;
2045 2052

	
2046 2053
            p = e;
2047 2054
            e = embedding[graph.oppositeArc(e)];
2048 2055

	
2049 2056
          }
2050 2057
          embedding[graph.oppositeArc(e)] = pn;
2051 2058
        }
2052 2059
      }
2053 2060
    }
2054 2061

	
2055 2062
  }
2056 2063

	
2057 2064
  /// \ingroup planar
2058 2065
  ///
2059 2066
  /// \brief Schnyder's planar drawing algorithm
2060 2067
  ///
2061 2068
  /// The planar drawing algorithm calculates positions for the nodes
2062
  /// in the plane which coordinates satisfy that if the arcs are
2063
  /// represented with straight lines then they will not intersect
2069
  /// in the plane. These coordinates satisfy that if the edges are
2070
  /// represented with straight lines, then they will not intersect
2064 2071
  /// each other.
2065 2072
  ///
2066
  /// Scnyder's algorithm embeds the graph on \c (n-2,n-2) size grid,
2067
  /// i.e. each node will be located in the \c [0,n-2]x[0,n-2] square.
2073
  /// Scnyder's algorithm embeds the graph on an \c (n-2)x(n-2) size grid,
2074
  /// i.e. each node will be located in the \c [0..n-2]x[0..n-2] square.
2068 2075
  /// The time complexity of the algorithm is O(n).
2076
  ///
2077
  /// \see PlanarEmbedding
2069 2078
  template <typename Graph>
2070 2079
  class PlanarDrawing {
2071 2080
  public:
2072 2081

	
2073 2082
    TEMPLATE_GRAPH_TYPEDEFS(Graph);
2074 2083

	
2075
    /// \brief The point type for store coordinates
2084
    /// \brief The point type for storing coordinates
2076 2085
    typedef dim2::Point<int> Point;
2077
    /// \brief The map type for store coordinates
2086
    /// \brief The map type for storing the coordinates of the nodes
2078 2087
    typedef typename Graph::template NodeMap<Point> PointMap;
2079 2088

	
2080 2089

	
2081 2090
    /// \brief Constructor
2082 2091
    ///
2083 2092
    /// Constructor
2084
    /// \pre The graph should be simple, i.e. loop and parallel arc free.
2093
    /// \pre The graph must be simple, i.e. it should not
2094
    /// contain parallel or loop arcs.
2085 2095
    PlanarDrawing(const Graph& graph)
2086 2096
      : _graph(graph), _point_map(graph) {}
2087 2097

	
2088 2098
  private:
2089 2099

	
2090 2100
    template <typename AuxGraph, typename AuxEmbeddingMap>
2091 2101
    void drawing(const AuxGraph& graph,
2092 2102
                 const AuxEmbeddingMap& next,
2093 2103
                 PointMap& point_map) {
2094 2104
      TEMPLATE_GRAPH_TYPEDEFS(AuxGraph);
2095 2105

	
2096 2106
      typename AuxGraph::template ArcMap<Arc> prev(graph);
2097 2107

	
2098 2108
      for (NodeIt n(graph); n != INVALID; ++n) {
2099 2109
        Arc e = OutArcIt(graph, n);
2100 2110

	
2101 2111
        Arc p = e, l = e;
2102 2112

	
2103 2113
        e = next[e];
2104 2114
        while (e != l) {
2105 2115
          prev[e] = p;
2106 2116
          p = e;
2107 2117
          e = next[e];
2108 2118
        }
... ...
@@ -2345,241 +2355,246 @@
2345 2355
      cpath[anode] = cpath[bnode] = 1;
2346 2356
      typename AuxGraph::template NodeMap<int> cpath_atree(graph, 0);
2347 2357
      cpath_atree[anode] = atree[anode];
2348 2358
      typename AuxGraph::template NodeMap<int> cpath_btree(graph, 0);
2349 2359
      cpath_btree[bnode] = btree[bnode];
2350 2360
      for (int i = 1; i < int(corder.size()); ++i) {
2351 2361
        Node n = corder[i];
2352 2362
        cpath[n] = cpath[cpred[n]] + 1;
2353 2363
        cpath_atree[n] = atree[n] + cpath_atree[cpred[n]];
2354 2364
        cpath_btree[n] = btree[n] + cpath_btree[cpred[n]];
2355 2365
      }
2356 2366

	
2357 2367
      typename AuxGraph::template NodeMap<int> third(graph);
2358 2368
      for (NodeIt n(graph); n != INVALID; ++n) {
2359 2369
        point_map[n].x =
2360 2370
          bpath_atree[n] + cpath_atree[n] - atree[n] - cpath[n] + 1;
2361 2371
        point_map[n].y =
2362 2372
          cpath_btree[n] + apath_btree[n] - btree[n] - apath[n] + 1;
2363 2373
      }
2364 2374

	
2365 2375
    }
2366 2376

	
2367 2377
  public:
2368 2378

	
2369
    /// \brief Calculates the node positions
2379
    /// \brief Calculate the node positions
2370 2380
    ///
2371
    /// This function calculates the node positions.
2372
    /// \return %True if the graph is planar.
2381
    /// This function calculates the node positions on the plane.
2382
    /// \return \c true if the graph is planar.
2373 2383
    bool run() {
2374 2384
      PlanarEmbedding<Graph> pe(_graph);
2375 2385
      if (!pe.run()) return false;
2376 2386

	
2377 2387
      run(pe);
2378 2388
      return true;
2379 2389
    }
2380 2390

	
2381
    /// \brief Calculates the node positions according to a
2391
    /// \brief Calculate the node positions according to a
2382 2392
    /// combinatorical embedding
2383 2393
    ///
2384
    /// This function calculates the node locations. The \c embedding
2385
    /// parameter should contain a valid combinatorical embedding, i.e.
2386
    /// a valid cyclic order of the arcs.
2394
    /// This function calculates the node positions on the plane.
2395
    /// The given \c embedding map should contain a valid combinatorical
2396
    /// embedding, i.e. a valid cyclic order of the arcs.
2397
    /// It can be computed using PlanarEmbedding.
2387 2398
    template <typename EmbeddingMap>
2388 2399
    void run(const EmbeddingMap& embedding) {
2389 2400
      typedef SmartEdgeSet<Graph> AuxGraph;
2390 2401

	
2391 2402
      if (3 * countNodes(_graph) - 6 == countEdges(_graph)) {
2392 2403
        drawing(_graph, embedding, _point_map);
2393 2404
        return;
2394 2405
      }
2395 2406

	
2396 2407
      AuxGraph aux_graph(_graph);
2397 2408
      typename AuxGraph::template ArcMap<typename AuxGraph::Arc>
2398 2409
        aux_embedding(aux_graph);
2399 2410

	
2400 2411
      {
2401 2412

	
2402 2413
        typename Graph::template EdgeMap<typename AuxGraph::Edge>
2403 2414
          ref(_graph);
2404 2415

	
2405 2416
        for (EdgeIt e(_graph); e != INVALID; ++e) {
2406 2417
          ref[e] = aux_graph.addEdge(_graph.u(e), _graph.v(e));
2407 2418
        }
2408 2419

	
2409 2420
        for (EdgeIt e(_graph); e != INVALID; ++e) {
2410 2421
          Arc ee = embedding[_graph.direct(e, true)];
2411 2422
          aux_embedding[aux_graph.direct(ref[e], true)] =
2412 2423
            aux_graph.direct(ref[ee], _graph.direction(ee));
2413 2424
          ee = embedding[_graph.direct(e, false)];
2414 2425
          aux_embedding[aux_graph.direct(ref[e], false)] =
2415 2426
            aux_graph.direct(ref[ee], _graph.direction(ee));
2416 2427
        }
2417 2428
      }
2418 2429
      _planarity_bits::makeConnected(aux_graph, aux_embedding);
2419 2430
      _planarity_bits::makeBiNodeConnected(aux_graph, aux_embedding);
2420 2431
      _planarity_bits::makeMaxPlanar(aux_graph, aux_embedding);
2421 2432
      drawing(aux_graph, aux_embedding, _point_map);
2422 2433
    }
2423 2434

	
2424 2435
    /// \brief The coordinate of the given node
2425 2436
    ///
2426
    /// The coordinate of the given node.
2437
    /// This function returns the coordinate of the given node.
2427 2438
    Point operator[](const Node& node) const {
2428 2439
      return _point_map[node];
2429 2440
    }
2430 2441

	
2431
    /// \brief Returns the grid embedding in a \e NodeMap.
2442
    /// \brief Return the grid embedding in a node map
2432 2443
    ///
2433
    /// Returns the grid embedding in a \e NodeMap of \c dim2::Point<int> .
2444
    /// This function returns the grid embedding in a node map of
2445
    /// \c dim2::Point<int> coordinates.
2434 2446
    const PointMap& coords() const {
2435 2447
      return _point_map;
2436 2448
    }
2437 2449

	
2438 2450
  private:
2439 2451

	
2440 2452
    const Graph& _graph;
2441 2453
    PointMap _point_map;
2442 2454

	
2443 2455
  };
2444 2456

	
2445 2457
  namespace _planarity_bits {
2446 2458

	
2447 2459
    template <typename ColorMap>
2448 2460
    class KempeFilter {
2449 2461
    public:
2450 2462
      typedef typename ColorMap::Key Key;
2451 2463
      typedef bool Value;
2452 2464

	
2453 2465
      KempeFilter(const ColorMap& color_map,
2454 2466
                  const typename ColorMap::Value& first,
2455 2467
                  const typename ColorMap::Value& second)
2456 2468
        : _color_map(color_map), _first(first), _second(second) {}
2457 2469

	
2458 2470
      Value operator[](const Key& key) const {
2459 2471
        return _color_map[key] == _first || _color_map[key] == _second;
2460 2472
      }
2461 2473

	
2462 2474
    private:
2463 2475
      const ColorMap& _color_map;
2464 2476
      typename ColorMap::Value _first, _second;
2465 2477
    };
2466 2478
  }
2467 2479

	
2468 2480
  /// \ingroup planar
2469 2481
  ///
2470 2482
  /// \brief Coloring planar graphs
2471 2483
  ///
2472 2484
  /// The graph coloring problem is the coloring of the graph nodes
2473
  /// that there are not adjacent nodes with the same color. The
2474
  /// planar graphs can be always colored with four colors, it is
2475
  /// proved by Appel and Haken and their proofs provide a quadratic
2485
  /// so that there are no adjacent nodes with the same color. The
2486
  /// planar graphs can always be colored with four colors, which is
2487
  /// proved by Appel and Haken. Their proofs provide a quadratic
2476 2488
  /// time algorithm for four coloring, but it could not be used to
2477
  /// implement efficient algorithm. The five and six coloring can be
2478
  /// made in linear time, but in this class the five coloring has
2489
  /// implement an efficient algorithm. The five and six coloring can be
2490
  /// made in linear time, but in this class, the five coloring has
2479 2491
  /// quadratic worst case time complexity. The two coloring (if
2480 2492
  /// possible) is solvable with a graph search algorithm and it is
2481 2493
  /// implemented in \ref bipartitePartitions() function in LEMON. To
2482
  /// decide whether the planar graph is three colorable is
2483
  /// NP-complete.
2494
  /// decide whether a planar graph is three colorable is NP-complete.
2484 2495
  ///
2485 2496
  /// This class contains member functions for calculate colorings
2486 2497
  /// with five and six colors. The six coloring algorithm is a simple
2487 2498
  /// greedy coloring on the backward minimum outgoing order of nodes.
2488
  /// This order can be computed as in each phase the node with least
2489
  /// outgoing arcs to unprocessed nodes is chosen. This order
2499
  /// This order can be computed by selecting the node with least
2500
  /// outgoing arcs to unprocessed nodes in each phase. This order
2490 2501
  /// guarantees that when a node is chosen for coloring it has at
2491 2502
  /// most five already colored adjacents. The five coloring algorithm
2492 2503
  /// use the same method, but if the greedy approach fails to color
2493 2504
  /// with five colors, i.e. the node has five already different
2494 2505
  /// colored neighbours, it swaps the colors in one of the connected
2495 2506
  /// two colored sets with the Kempe recoloring method.
2496 2507
  template <typename Graph>
2497 2508
  class PlanarColoring {
2498 2509
  public:
2499 2510

	
2500 2511
    TEMPLATE_GRAPH_TYPEDEFS(Graph);
2501 2512

	
2502
    /// \brief The map type for store color indexes
2513
    /// \brief The map type for storing color indices
2503 2514
    typedef typename Graph::template NodeMap<int> IndexMap;
2504
    /// \brief The map type for store colors
2515
    /// \brief The map type for storing colors
2516
    ///
2517
    /// The map type for storing colors.
2518
    /// \see Palette, Color
2505 2519
    typedef ComposeMap<Palette, IndexMap> ColorMap;
2506 2520

	
2507 2521
    /// \brief Constructor
2508 2522
    ///
2509
    /// Constructor
2510
    /// \pre The graph should be simple, i.e. loop and parallel arc free.
2523
    /// Constructor.
2524
    /// \pre The graph must be simple, i.e. it should not
2525
    /// contain parallel or loop arcs.
2511 2526
    PlanarColoring(const Graph& graph)
2512 2527
      : _graph(graph), _color_map(graph), _palette(0) {
2513 2528
      _palette.add(Color(1,0,0));
2514 2529
      _palette.add(Color(0,1,0));
2515 2530
      _palette.add(Color(0,0,1));
2516 2531
      _palette.add(Color(1,1,0));
2517 2532
      _palette.add(Color(1,0,1));
2518 2533
      _palette.add(Color(0,1,1));
2519 2534
    }
2520 2535

	
2521
    /// \brief Returns the \e NodeMap of color indexes
2536
    /// \brief Return the node map of color indices
2522 2537
    ///
2523
    /// Returns the \e NodeMap of color indexes. The values are in the
2524
    /// range \c [0..4] or \c [0..5] according to the coloring method.
2538
    /// This function returns the node map of color indices. The values are
2539
    /// in the range \c [0..4] or \c [0..5] according to the coloring method.
2525 2540
    IndexMap colorIndexMap() const {
2526 2541
      return _color_map;
2527 2542
    }
2528 2543

	
2529
    /// \brief Returns the \e NodeMap of colors
2544
    /// \brief Return the node map of colors
2530 2545
    ///
2531
    /// Returns the \e NodeMap of colors. The values are five or six
2532
    /// distinct \ref lemon::Color "colors".
2546
    /// This function returns the node map of colors. The values are among
2547
    /// five or six distinct \ref lemon::Color "colors".
2533 2548
    ColorMap colorMap() const {
2534 2549
      return composeMap(_palette, _color_map);
2535 2550
    }
2536 2551

	
2537
    /// \brief Returns the color index of the node
2552
    /// \brief Return the color index of the node
2538 2553
    ///
2539
    /// Returns the color index of the node. The values are in the
2540
    /// range \c [0..4] or \c [0..5] according to the coloring method.
2554
    /// This function returns the color index of the given node. The value is
2555
    /// in the range \c [0..4] or \c [0..5] according to the coloring method.
2541 2556
    int colorIndex(const Node& node) const {
2542 2557
      return _color_map[node];
2543 2558
    }
2544 2559

	
2545
    /// \brief Returns the color of the node
2560
    /// \brief Return the color of the node
2546 2561
    ///
2547
    /// Returns the color of the node. The values are five or six
2548
    /// distinct \ref lemon::Color "colors".
2562
    /// This function returns the color of the given node. The value is among
2563
    /// five or six distinct \ref lemon::Color "colors".
2549 2564
    Color color(const Node& node) const {
2550 2565
      return _palette[_color_map[node]];
2551 2566
    }
2552 2567

	
2553 2568

	
2554
    /// \brief Calculates a coloring with at most six colors
2569
    /// \brief Calculate a coloring with at most six colors
2555 2570
    ///
2556 2571
    /// This function calculates a coloring with at most six colors. The time
2557 2572
    /// complexity of this variant is linear in the size of the graph.
2558
    /// \return %True when the algorithm could color the graph with six color.
2559
    /// If the algorithm fails, then the graph could not be planar.
2560
    /// \note This function can return true if the graph is not
2561
    /// planar but it can be colored with 6 colors.
2573
    /// \return \c true if the algorithm could color the graph with six colors.
2574
    /// If the algorithm fails, then the graph is not planar.
2575
    /// \note This function can return \c true if the graph is not
2576
    /// planar, but it can be colored with at most six colors.
2562 2577
    bool runSixColoring() {
2563 2578

	
2564 2579
      typename Graph::template NodeMap<int> heap_index(_graph, -1);
2565 2580
      BucketHeap<typename Graph::template NodeMap<int> > heap(heap_index);
2566 2581

	
2567 2582
      for (NodeIt n(_graph); n != INVALID; ++n) {
2568 2583
        _color_map[n] = -2;
2569 2584
        heap.push(n, countOutArcs(_graph, n));
2570 2585
      }
2571 2586

	
2572 2587
      std::vector<Node> order;
2573 2588

	
2574 2589
      while (!heap.empty()) {
2575 2590
        Node n = heap.top();
2576 2591
        heap.pop();
2577 2592
        _color_map[n] = -1;
2578 2593
        order.push_back(n);
2579 2594
        for (OutArcIt e(_graph, n); e != INVALID; ++e) {
2580 2595
          Node t = _graph.runningNode(e);
2581 2596
          if (_color_map[t] == -2) {
2582 2597
            heap.decrease(t, heap[t] - 1);
2583 2598
          }
2584 2599
        }
2585 2600
      }
... ...
@@ -2639,99 +2654,102 @@
2639 2654
    void kempeRecoloring(const Node& node, const EmbeddingMap& embedding) {
2640 2655
      std::vector<Node> nodes;
2641 2656
      nodes.reserve(4);
2642 2657

	
2643 2658
      for (Arc e = OutArcIt(_graph, node); e != INVALID; e = embedding[e]) {
2644 2659
        Node t = _graph.target(e);
2645 2660
        if (_color_map[t] != -1) {
2646 2661
          nodes.push_back(t);
2647 2662
          if (nodes.size() == 4) break;
2648 2663
        }
2649 2664
      }
2650 2665

	
2651 2666
      int color = _color_map[nodes[0]];
2652 2667
      if (recolor(nodes[0], nodes[2])) {
2653 2668
        _color_map[node] = color;
2654 2669
      } else {
2655 2670
        color = _color_map[nodes[1]];
2656 2671
        recolor(nodes[1], nodes[3]);
2657 2672
        _color_map[node] = color;
2658 2673
      }
2659 2674
    }
2660 2675

	
2661 2676
  public:
2662 2677

	
2663
    /// \brief Calculates a coloring with at most five colors
2678
    /// \brief Calculate a coloring with at most five colors
2664 2679
    ///
2665 2680
    /// This function calculates a coloring with at most five
2666 2681
    /// colors. The worst case time complexity of this variant is
2667 2682
    /// quadratic in the size of the graph.
2683
    /// \param embedding This map should contain a valid combinatorical
2684
    /// embedding, i.e. a valid cyclic order of the arcs.
2685
    /// It can be computed using PlanarEmbedding.
2668 2686
    template <typename EmbeddingMap>
2669 2687
    void runFiveColoring(const EmbeddingMap& embedding) {
2670 2688

	
2671 2689
      typename Graph::template NodeMap<int> heap_index(_graph, -1);
2672 2690
      BucketHeap<typename Graph::template NodeMap<int> > heap(heap_index);
2673 2691

	
2674 2692
      for (NodeIt n(_graph); n != INVALID; ++n) {
2675 2693
        _color_map[n] = -2;
2676 2694
        heap.push(n, countOutArcs(_graph, n));
2677 2695
      }
2678 2696

	
2679 2697
      std::vector<Node> order;
2680 2698

	
2681 2699
      while (!heap.empty()) {
2682 2700
        Node n = heap.top();
2683 2701
        heap.pop();
2684 2702
        _color_map[n] = -1;
2685 2703
        order.push_back(n);
2686 2704
        for (OutArcIt e(_graph, n); e != INVALID; ++e) {
2687 2705
          Node t = _graph.runningNode(e);
2688 2706
          if (_color_map[t] == -2) {
2689 2707
            heap.decrease(t, heap[t] - 1);
2690 2708
          }
2691 2709
        }
2692 2710
      }
2693 2711

	
2694 2712
      for (int i = order.size() - 1; i >= 0; --i) {
2695 2713
        std::vector<bool> forbidden(5, false);
2696 2714
        for (OutArcIt e(_graph, order[i]); e != INVALID; ++e) {
2697 2715
          Node t = _graph.runningNode(e);
2698 2716
          if (_color_map[t] != -1) {
2699 2717
            forbidden[_color_map[t]] = true;
2700 2718
          }
2701 2719
        }
2702 2720
        for (int k = 0; k < 5; ++k) {
2703 2721
          if (!forbidden[k]) {
2704 2722
            _color_map[order[i]] = k;
2705 2723
            break;
2706 2724
          }
2707 2725
        }
2708 2726
        if (_color_map[order[i]] == -1) {
2709 2727
          kempeRecoloring(order[i], embedding);
2710 2728
        }
2711 2729
      }
2712 2730
    }
2713 2731

	
2714
    /// \brief Calculates a coloring with at most five colors
2732
    /// \brief Calculate a coloring with at most five colors
2715 2733
    ///
2716 2734
    /// This function calculates a coloring with at most five
2717 2735
    /// colors. The worst case time complexity of this variant is
2718 2736
    /// quadratic in the size of the graph.
2719
    /// \return %True when the graph is planar.
2737
    /// \return \c true if the graph is planar.
2720 2738
    bool runFiveColoring() {
2721 2739
      PlanarEmbedding<Graph> pe(_graph);
2722 2740
      if (!pe.run()) return false;
2723 2741

	
2724 2742
      runFiveColoring(pe.embeddingMap());
2725 2743
      return true;
2726 2744
    }
2727 2745

	
2728 2746
  private:
2729 2747

	
2730 2748
    const Graph& _graph;
2731 2749
    IndexMap _color_map;
2732 2750
    Palette _palette;
2733 2751
  };
2734 2752

	
2735 2753
}
2736 2754

	
2737 2755
#endif
Ignore white space 6 line context
... ...
@@ -98,48 +98,53 @@
98 98

	
99 99
  /// \ingroup max_flow
100 100
  ///
101 101
  /// \brief %Preflow algorithm class.
102 102
  ///
103 103
  /// This class provides an implementation of Goldberg-Tarjan's \e preflow
104 104
  /// \e push-relabel algorithm producing a \ref max_flow
105 105
  /// "flow of maximum value" in a digraph \ref clrs01algorithms,
106 106
  /// \ref amo93networkflows, \ref goldberg88newapproach.
107 107
  /// The preflow algorithms are the fastest known maximum
108 108
  /// flow algorithms. The current implementation uses a mixture of the
109 109
  /// \e "highest label" and the \e "bound decrease" heuristics.
110 110
  /// The worst case time complexity of the algorithm is \f$O(n^2\sqrt{e})\f$.
111 111
  ///
112 112
  /// The algorithm consists of two phases. After the first phase
113 113
  /// the maximum flow value and the minimum cut is obtained. The
114 114
  /// second phase constructs a feasible maximum flow on each arc.
115 115
  ///
116 116
  /// \warning This implementation cannot handle infinite or very large
117 117
  /// capacities (e.g. the maximum value of \c CAP::Value).
118 118
  ///
119 119
  /// \tparam GR The type of the digraph the algorithm runs on.
120 120
  /// \tparam CAP The type of the capacity map. The default map
121 121
  /// type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
122
  /// \tparam TR The traits class that defines various types used by the
123
  /// algorithm. By default, it is \ref PreflowDefaultTraits
124
  /// "PreflowDefaultTraits<GR, CAP>".
125
  /// In most cases, this parameter should not be set directly,
126
  /// consider to use the named template parameters instead.
122 127
#ifdef DOXYGEN
123 128
  template <typename GR, typename CAP, typename TR>
124 129
#else
125 130
  template <typename GR,
126 131
            typename CAP = typename GR::template ArcMap<int>,
127 132
            typename TR = PreflowDefaultTraits<GR, CAP> >
128 133
#endif
129 134
  class Preflow {
130 135
  public:
131 136

	
132 137
    ///The \ref PreflowDefaultTraits "traits class" of the algorithm.
133 138
    typedef TR Traits;
134 139
    ///The type of the digraph the algorithm runs on.
135 140
    typedef typename Traits::Digraph Digraph;
136 141
    ///The type of the capacity map.
137 142
    typedef typename Traits::CapacityMap CapacityMap;
138 143
    ///The type of the flow values.
139 144
    typedef typename Traits::Value Value;
140 145

	
141 146
    ///The type of the flow map.
142 147
    typedef typename Traits::FlowMap FlowMap;
143 148
    ///The type of the elevator.
144 149
    typedef typename Traits::Elevator Elevator;
145 150
    ///The type of the tolerance.
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