doc/groups.dox
author Alpar Juttner <alpar@cs.elte.hu>
Sun, 11 Jan 2009 15:09:53 +0000
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     1 /* -*- mode: C++; indent-tabs-mode: nil; -*-
     2  *
     3  * This file is a part of LEMON, a generic C++ optimization library.
     4  *
     5  * Copyright (C) 2003-2009
     6  * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
     7  * (Egervary Research Group on Combinatorial Optimization, EGRES).
     8  *
     9  * Permission to use, modify and distribute this software is granted
    10  * provided that this copyright notice appears in all copies. For
    11  * precise terms see the accompanying LICENSE file.
    12  *
    13  * This software is provided "AS IS" with no warranty of any kind,
    14  * express or implied, and with no claim as to its suitability for any
    15  * purpose.
    16  *
    17  */
    18 
    19 namespace lemon {
    20 
    21 /**
    22 @defgroup datas Data Structures
    23 This group describes the several data structures implemented in LEMON.
    24 */
    25 
    26 /**
    27 @defgroup graphs Graph Structures
    28 @ingroup datas
    29 \brief Graph structures implemented in LEMON.
    30 
    31 The implementation of combinatorial algorithms heavily relies on
    32 efficient graph implementations. LEMON offers data structures which are
    33 planned to be easily used in an experimental phase of implementation studies,
    34 and thereafter the program code can be made efficient by small modifications.
    35 
    36 The most efficient implementation of diverse applications require the
    37 usage of different physical graph implementations. These differences
    38 appear in the size of graph we require to handle, memory or time usage
    39 limitations or in the set of operations through which the graph can be
    40 accessed.  LEMON provides several physical graph structures to meet
    41 the diverging requirements of the possible users.  In order to save on
    42 running time or on memory usage, some structures may fail to provide
    43 some graph features like arc/edge or node deletion.
    44 
    45 Alteration of standard containers need a very limited number of
    46 operations, these together satisfy the everyday requirements.
    47 In the case of graph structures, different operations are needed which do
    48 not alter the physical graph, but gives another view. If some nodes or
    49 arcs have to be hidden or the reverse oriented graph have to be used, then
    50 this is the case. It also may happen that in a flow implementation
    51 the residual graph can be accessed by another algorithm, or a node-set
    52 is to be shrunk for another algorithm.
    53 LEMON also provides a variety of graphs for these requirements called
    54 \ref graph_adaptors "graph adaptors". Adaptors cannot be used alone but only
    55 in conjunction with other graph representations.
    56 
    57 You are free to use the graph structure that fit your requirements
    58 the best, most graph algorithms and auxiliary data structures can be used
    59 with any graph structure.
    60 
    61 <b>See also:</b> \ref graph_concepts "Graph Structure Concepts".
    62 */
    63 
    64 /**
    65 @defgroup graph_adaptors Adaptor Classes for Graphs
    66 @ingroup graphs
    67 \brief Adaptor classes for digraphs and graphs
    68 
    69 This group contains several useful adaptor classes for digraphs and graphs.
    70 
    71 The main parts of LEMON are the different graph structures, generic
    72 graph algorithms, graph concepts, which couple them, and graph
    73 adaptors. While the previous notions are more or less clear, the
    74 latter one needs further explanation. Graph adaptors are graph classes
    75 which serve for considering graph structures in different ways.
    76 
    77 A short example makes this much clearer.  Suppose that we have an
    78 instance \c g of a directed graph type, say ListDigraph and an algorithm
    79 \code
    80 template <typename Digraph>
    81 int algorithm(const Digraph&);
    82 \endcode
    83 is needed to run on the reverse oriented graph.  It may be expensive
    84 (in time or in memory usage) to copy \c g with the reversed
    85 arcs.  In this case, an adaptor class is used, which (according
    86 to LEMON \ref concepts::Digraph "digraph concepts") works as a digraph.
    87 The adaptor uses the original digraph structure and digraph operations when
    88 methods of the reversed oriented graph are called.  This means that the adaptor
    89 have minor memory usage, and do not perform sophisticated algorithmic
    90 actions.  The purpose of it is to give a tool for the cases when a
    91 graph have to be used in a specific alteration.  If this alteration is
    92 obtained by a usual construction like filtering the node or the arc set or
    93 considering a new orientation, then an adaptor is worthwhile to use.
    94 To come back to the reverse oriented graph, in this situation
    95 \code
    96 template<typename Digraph> class ReverseDigraph;
    97 \endcode
    98 template class can be used. The code looks as follows
    99 \code
   100 ListDigraph g;
   101 ReverseDigraph<ListDigraph> rg(g);
   102 int result = algorithm(rg);
   103 \endcode
   104 During running the algorithm, the original digraph \c g is untouched.
   105 This techniques give rise to an elegant code, and based on stable
   106 graph adaptors, complex algorithms can be implemented easily.
   107 
   108 In flow, circulation and matching problems, the residual
   109 graph is of particular importance. Combining an adaptor implementing
   110 this with shortest path algorithms or minimum mean cycle algorithms,
   111 a range of weighted and cardinality optimization algorithms can be
   112 obtained. For other examples, the interested user is referred to the
   113 detailed documentation of particular adaptors.
   114 
   115 The behavior of graph adaptors can be very different. Some of them keep
   116 capabilities of the original graph while in other cases this would be
   117 meaningless. This means that the concepts that they meet depend
   118 on the graph adaptor, and the wrapped graph.
   119 For example, if an arc of a reversed digraph is deleted, this is carried
   120 out by deleting the corresponding arc of the original digraph, thus the
   121 adaptor modifies the original digraph.
   122 However in case of a residual digraph, this operation has no sense.
   123 
   124 Let us stand one more example here to simplify your work.
   125 ReverseDigraph has constructor
   126 \code
   127 ReverseDigraph(Digraph& digraph);
   128 \endcode
   129 This means that in a situation, when a <tt>const %ListDigraph&</tt>
   130 reference to a graph is given, then it have to be instantiated with
   131 <tt>Digraph=const %ListDigraph</tt>.
   132 \code
   133 int algorithm1(const ListDigraph& g) {
   134   ReverseDigraph<const ListDigraph> rg(g);
   135   return algorithm2(rg);
   136 }
   137 \endcode
   138 */
   139 
   140 /**
   141 @defgroup semi_adaptors Semi-Adaptor Classes for Graphs
   142 @ingroup graphs
   143 \brief Graph types between real graphs and graph adaptors.
   144 
   145 This group describes some graph types between real graphs and graph adaptors.
   146 These classes wrap graphs to give new functionality as the adaptors do it.
   147 On the other hand they are not light-weight structures as the adaptors.
   148 */
   149 
   150 /**
   151 @defgroup maps Maps
   152 @ingroup datas
   153 \brief Map structures implemented in LEMON.
   154 
   155 This group describes the map structures implemented in LEMON.
   156 
   157 LEMON provides several special purpose maps and map adaptors that e.g. combine
   158 new maps from existing ones.
   159 
   160 <b>See also:</b> \ref map_concepts "Map Concepts".
   161 */
   162 
   163 /**
   164 @defgroup graph_maps Graph Maps
   165 @ingroup maps
   166 \brief Special graph-related maps.
   167 
   168 This group describes maps that are specifically designed to assign
   169 values to the nodes and arcs/edges of graphs.
   170 
   171 If you are looking for the standard graph maps (\c NodeMap, \c ArcMap,
   172 \c EdgeMap), see the \ref graph_concepts "Graph Structure Concepts".
   173 */
   174 
   175 /**
   176 \defgroup map_adaptors Map Adaptors
   177 \ingroup maps
   178 \brief Tools to create new maps from existing ones
   179 
   180 This group describes map adaptors that are used to create "implicit"
   181 maps from other maps.
   182 
   183 Most of them are \ref concepts::ReadMap "read-only maps".
   184 They can make arithmetic and logical operations between one or two maps
   185 (negation, shifting, addition, multiplication, logical 'and', 'or',
   186 'not' etc.) or e.g. convert a map to another one of different Value type.
   187 
   188 The typical usage of this classes is passing implicit maps to
   189 algorithms.  If a function type algorithm is called then the function
   190 type map adaptors can be used comfortable. For example let's see the
   191 usage of map adaptors with the \c graphToEps() function.
   192 \code
   193   Color nodeColor(int deg) {
   194     if (deg >= 2) {
   195       return Color(0.5, 0.0, 0.5);
   196     } else if (deg == 1) {
   197       return Color(1.0, 0.5, 1.0);
   198     } else {
   199       return Color(0.0, 0.0, 0.0);
   200     }
   201   }
   202 
   203   Digraph::NodeMap<int> degree_map(graph);
   204 
   205   graphToEps(graph, "graph.eps")
   206     .coords(coords).scaleToA4().undirected()
   207     .nodeColors(composeMap(functorToMap(nodeColor), degree_map))
   208     .run();
   209 \endcode
   210 The \c functorToMap() function makes an \c int to \c Color map from the
   211 \c nodeColor() function. The \c composeMap() compose the \c degree_map
   212 and the previously created map. The composed map is a proper function to
   213 get the color of each node.
   214 
   215 The usage with class type algorithms is little bit harder. In this
   216 case the function type map adaptors can not be used, because the
   217 function map adaptors give back temporary objects.
   218 \code
   219   Digraph graph;
   220 
   221   typedef Digraph::ArcMap<double> DoubleArcMap;
   222   DoubleArcMap length(graph);
   223   DoubleArcMap speed(graph);
   224 
   225   typedef DivMap<DoubleArcMap, DoubleArcMap> TimeMap;
   226   TimeMap time(length, speed);
   227 
   228   Dijkstra<Digraph, TimeMap> dijkstra(graph, time);
   229   dijkstra.run(source, target);
   230 \endcode
   231 We have a length map and a maximum speed map on the arcs of a digraph.
   232 The minimum time to pass the arc can be calculated as the division of
   233 the two maps which can be done implicitly with the \c DivMap template
   234 class. We use the implicit minimum time map as the length map of the
   235 \c Dijkstra algorithm.
   236 */
   237 
   238 /**
   239 @defgroup matrices Matrices
   240 @ingroup datas
   241 \brief Two dimensional data storages implemented in LEMON.
   242 
   243 This group describes two dimensional data storages implemented in LEMON.
   244 */
   245 
   246 /**
   247 @defgroup paths Path Structures
   248 @ingroup datas
   249 \brief %Path structures implemented in LEMON.
   250 
   251 This group describes the path structures implemented in LEMON.
   252 
   253 LEMON provides flexible data structures to work with paths.
   254 All of them have similar interfaces and they can be copied easily with
   255 assignment operators and copy constructors. This makes it easy and
   256 efficient to have e.g. the Dijkstra algorithm to store its result in
   257 any kind of path structure.
   258 
   259 \sa lemon::concepts::Path
   260 */
   261 
   262 /**
   263 @defgroup auxdat Auxiliary Data Structures
   264 @ingroup datas
   265 \brief Auxiliary data structures implemented in LEMON.
   266 
   267 This group describes some data structures implemented in LEMON in
   268 order to make it easier to implement combinatorial algorithms.
   269 */
   270 
   271 /**
   272 @defgroup algs Algorithms
   273 \brief This group describes the several algorithms
   274 implemented in LEMON.
   275 
   276 This group describes the several algorithms
   277 implemented in LEMON.
   278 */
   279 
   280 /**
   281 @defgroup search Graph Search
   282 @ingroup algs
   283 \brief Common graph search algorithms.
   284 
   285 This group describes the common graph search algorithms, namely
   286 \e breadth-first \e search (BFS) and \e depth-first \e search (DFS).
   287 */
   288 
   289 /**
   290 @defgroup shortest_path Shortest Path Algorithms
   291 @ingroup algs
   292 \brief Algorithms for finding shortest paths.
   293 
   294 This group describes the algorithms for finding shortest paths in digraphs.
   295 
   296  - \ref Dijkstra algorithm for finding shortest paths from a source node
   297    when all arc lengths are non-negative.
   298  - \ref BellmanFord "Bellman-Ford" algorithm for finding shortest paths
   299    from a source node when arc lenghts can be either positive or negative,
   300    but the digraph should not contain directed cycles with negative total
   301    length.
   302  - \ref FloydWarshall "Floyd-Warshall" and \ref Johnson "Johnson" algorithms
   303    for solving the \e all-pairs \e shortest \e paths \e problem when arc
   304    lenghts can be either positive or negative, but the digraph should
   305    not contain directed cycles with negative total length.
   306  - \ref Suurballe A successive shortest path algorithm for finding
   307    arc-disjoint paths between two nodes having minimum total length.
   308 */
   309 
   310 /**
   311 @defgroup max_flow Maximum Flow Algorithms
   312 @ingroup algs
   313 \brief Algorithms for finding maximum flows.
   314 
   315 This group describes the algorithms for finding maximum flows and
   316 feasible circulations.
   317 
   318 The \e maximum \e flow \e problem is to find a flow of maximum value between
   319 a single source and a single target. Formally, there is a \f$G=(V,A)\f$
   320 digraph, a \f$cap:A\rightarrow\mathbf{R}^+_0\f$ capacity function and
   321 \f$s, t \in V\f$ source and target nodes.
   322 A maximum flow is an \f$f:A\rightarrow\mathbf{R}^+_0\f$ solution of the
   323 following optimization problem.
   324 
   325 \f[ \max\sum_{a\in\delta_{out}(s)}f(a) - \sum_{a\in\delta_{in}(s)}f(a) \f]
   326 \f[ \sum_{a\in\delta_{out}(v)} f(a) = \sum_{a\in\delta_{in}(v)} f(a)
   327     \qquad \forall v\in V\setminus\{s,t\} \f]
   328 \f[ 0 \leq f(a) \leq cap(a) \qquad \forall a\in A \f]
   329 
   330 LEMON contains several algorithms for solving maximum flow problems:
   331 - \ref EdmondsKarp Edmonds-Karp algorithm.
   332 - \ref Preflow Goldberg-Tarjan's preflow push-relabel algorithm.
   333 - \ref DinitzSleatorTarjan Dinitz's blocking flow algorithm with dynamic trees.
   334 - \ref GoldbergTarjan Preflow push-relabel algorithm with dynamic trees.
   335 
   336 In most cases the \ref Preflow "Preflow" algorithm provides the
   337 fastest method for computing a maximum flow. All implementations
   338 provides functions to also query the minimum cut, which is the dual
   339 problem of the maximum flow.
   340 */
   341 
   342 /**
   343 @defgroup min_cost_flow Minimum Cost Flow Algorithms
   344 @ingroup algs
   345 
   346 \brief Algorithms for finding minimum cost flows and circulations.
   347 
   348 This group describes the algorithms for finding minimum cost flows and
   349 circulations.
   350 
   351 The \e minimum \e cost \e flow \e problem is to find a feasible flow of
   352 minimum total cost from a set of supply nodes to a set of demand nodes
   353 in a network with capacity constraints and arc costs.
   354 Formally, let \f$G=(V,A)\f$ be a digraph,
   355 \f$lower, upper: A\rightarrow\mathbf{Z}^+_0\f$ denote the lower and
   356 upper bounds for the flow values on the arcs,
   357 \f$cost: A\rightarrow\mathbf{Z}^+_0\f$ denotes the cost per unit flow
   358 on the arcs, and
   359 \f$supply: V\rightarrow\mathbf{Z}\f$ denotes the supply/demand values
   360 of the nodes.
   361 A minimum cost flow is an \f$f:A\rightarrow\mathbf{R}^+_0\f$ solution of
   362 the following optimization problem.
   363 
   364 \f[ \min\sum_{a\in A} f(a) cost(a) \f]
   365 \f[ \sum_{a\in\delta_{out}(v)} f(a) - \sum_{a\in\delta_{in}(v)} f(a) =
   366     supply(v) \qquad \forall v\in V \f]
   367 \f[ lower(a) \leq f(a) \leq upper(a) \qquad \forall a\in A \f]
   368 
   369 LEMON contains several algorithms for solving minimum cost flow problems:
   370  - \ref CycleCanceling Cycle-canceling algorithms.
   371  - \ref CapacityScaling Successive shortest path algorithm with optional
   372    capacity scaling.
   373  - \ref CostScaling Push-relabel and augment-relabel algorithms based on
   374    cost scaling.
   375  - \ref NetworkSimplex Primal network simplex algorithm with various
   376    pivot strategies.
   377 */
   378 
   379 /**
   380 @defgroup min_cut Minimum Cut Algorithms
   381 @ingroup algs
   382 
   383 \brief Algorithms for finding minimum cut in graphs.
   384 
   385 This group describes the algorithms for finding minimum cut in graphs.
   386 
   387 The \e minimum \e cut \e problem is to find a non-empty and non-complete
   388 \f$X\f$ subset of the nodes with minimum overall capacity on
   389 outgoing arcs. Formally, there is a \f$G=(V,A)\f$ digraph, a
   390 \f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function. The minimum
   391 cut is the \f$X\f$ solution of the next optimization problem:
   392 
   393 \f[ \min_{X \subset V, X\not\in \{\emptyset, V\}}
   394     \sum_{uv\in A, u\in X, v\not\in X}cap(uv) \f]
   395 
   396 LEMON contains several algorithms related to minimum cut problems:
   397 
   398 - \ref HaoOrlin "Hao-Orlin algorithm" for calculating minimum cut
   399   in directed graphs.
   400 - \ref NagamochiIbaraki "Nagamochi-Ibaraki algorithm" for
   401   calculating minimum cut in undirected graphs.
   402 - \ref GomoryHuTree "Gomory-Hu tree computation" for calculating
   403   all-pairs minimum cut in undirected graphs.
   404 
   405 If you want to find minimum cut just between two distinict nodes,
   406 see the \ref max_flow "maximum flow problem".
   407 */
   408 
   409 /**
   410 @defgroup graph_prop Connectivity and Other Graph Properties
   411 @ingroup algs
   412 \brief Algorithms for discovering the graph properties
   413 
   414 This group describes the algorithms for discovering the graph properties
   415 like connectivity, bipartiteness, euler property, simplicity etc.
   416 
   417 \image html edge_biconnected_components.png
   418 \image latex edge_biconnected_components.eps "bi-edge-connected components" width=\textwidth
   419 */
   420 
   421 /**
   422 @defgroup planar Planarity Embedding and Drawing
   423 @ingroup algs
   424 \brief Algorithms for planarity checking, embedding and drawing
   425 
   426 This group describes the algorithms for planarity checking,
   427 embedding and drawing.
   428 
   429 \image html planar.png
   430 \image latex planar.eps "Plane graph" width=\textwidth
   431 */
   432 
   433 /**
   434 @defgroup matching Matching Algorithms
   435 @ingroup algs
   436 \brief Algorithms for finding matchings in graphs and bipartite graphs.
   437 
   438 This group contains algorithm objects and functions to calculate
   439 matchings in graphs and bipartite graphs. The general matching problem is
   440 finding a subset of the arcs which does not shares common endpoints.
   441 
   442 There are several different algorithms for calculate matchings in
   443 graphs.  The matching problems in bipartite graphs are generally
   444 easier than in general graphs. The goal of the matching optimization
   445 can be finding maximum cardinality, maximum weight or minimum cost
   446 matching. The search can be constrained to find perfect or
   447 maximum cardinality matching.
   448 
   449 The matching algorithms implemented in LEMON:
   450 - \ref MaxBipartiteMatching Hopcroft-Karp augmenting path algorithm
   451   for calculating maximum cardinality matching in bipartite graphs.
   452 - \ref PrBipartiteMatching Push-relabel algorithm
   453   for calculating maximum cardinality matching in bipartite graphs.
   454 - \ref MaxWeightedBipartiteMatching
   455   Successive shortest path algorithm for calculating maximum weighted
   456   matching and maximum weighted bipartite matching in bipartite graphs.
   457 - \ref MinCostMaxBipartiteMatching
   458   Successive shortest path algorithm for calculating minimum cost maximum
   459   matching in bipartite graphs.
   460 - \ref MaxMatching Edmond's blossom shrinking algorithm for calculating
   461   maximum cardinality matching in general graphs.
   462 - \ref MaxWeightedMatching Edmond's blossom shrinking algorithm for calculating
   463   maximum weighted matching in general graphs.
   464 - \ref MaxWeightedPerfectMatching
   465   Edmond's blossom shrinking algorithm for calculating maximum weighted
   466   perfect matching in general graphs.
   467 
   468 \image html bipartite_matching.png
   469 \image latex bipartite_matching.eps "Bipartite Matching" width=\textwidth
   470 */
   471 
   472 /**
   473 @defgroup spantree Minimum Spanning Tree Algorithms
   474 @ingroup algs
   475 \brief Algorithms for finding a minimum cost spanning tree in a graph.
   476 
   477 This group describes the algorithms for finding a minimum cost spanning
   478 tree in a graph.
   479 */
   480 
   481 /**
   482 @defgroup auxalg Auxiliary Algorithms
   483 @ingroup algs
   484 \brief Auxiliary algorithms implemented in LEMON.
   485 
   486 This group describes some algorithms implemented in LEMON
   487 in order to make it easier to implement complex algorithms.
   488 */
   489 
   490 /**
   491 @defgroup approx Approximation Algorithms
   492 @ingroup algs
   493 \brief Approximation algorithms.
   494 
   495 This group describes the approximation and heuristic algorithms
   496 implemented in LEMON.
   497 */
   498 
   499 /**
   500 @defgroup gen_opt_group General Optimization Tools
   501 \brief This group describes some general optimization frameworks
   502 implemented in LEMON.
   503 
   504 This group describes some general optimization frameworks
   505 implemented in LEMON.
   506 */
   507 
   508 /**
   509 @defgroup lp_group Lp and Mip Solvers
   510 @ingroup gen_opt_group
   511 \brief Lp and Mip solver interfaces for LEMON.
   512 
   513 This group describes Lp and Mip solver interfaces for LEMON. The
   514 various LP solvers could be used in the same manner with this
   515 interface.
   516 */
   517 
   518 /**
   519 @defgroup lp_utils Tools for Lp and Mip Solvers
   520 @ingroup lp_group
   521 \brief Helper tools to the Lp and Mip solvers.
   522 
   523 This group adds some helper tools to general optimization framework
   524 implemented in LEMON.
   525 */
   526 
   527 /**
   528 @defgroup metah Metaheuristics
   529 @ingroup gen_opt_group
   530 \brief Metaheuristics for LEMON library.
   531 
   532 This group describes some metaheuristic optimization tools.
   533 */
   534 
   535 /**
   536 @defgroup utils Tools and Utilities
   537 \brief Tools and utilities for programming in LEMON
   538 
   539 Tools and utilities for programming in LEMON.
   540 */
   541 
   542 /**
   543 @defgroup gutils Basic Graph Utilities
   544 @ingroup utils
   545 \brief Simple basic graph utilities.
   546 
   547 This group describes some simple basic graph utilities.
   548 */
   549 
   550 /**
   551 @defgroup misc Miscellaneous Tools
   552 @ingroup utils
   553 \brief Tools for development, debugging and testing.
   554 
   555 This group describes several useful tools for development,
   556 debugging and testing.
   557 */
   558 
   559 /**
   560 @defgroup timecount Time Measuring and Counting
   561 @ingroup misc
   562 \brief Simple tools for measuring the performance of algorithms.
   563 
   564 This group describes simple tools for measuring the performance
   565 of algorithms.
   566 */
   567 
   568 /**
   569 @defgroup exceptions Exceptions
   570 @ingroup utils
   571 \brief Exceptions defined in LEMON.
   572 
   573 This group describes the exceptions defined in LEMON.
   574 */
   575 
   576 /**
   577 @defgroup io_group Input-Output
   578 \brief Graph Input-Output methods
   579 
   580 This group describes the tools for importing and exporting graphs
   581 and graph related data. Now it supports the \ref lgf-format
   582 "LEMON Graph Format", the \c DIMACS format and the encapsulated
   583 postscript (EPS) format.
   584 */
   585 
   586 /**
   587 @defgroup lemon_io LEMON Graph Format
   588 @ingroup io_group
   589 \brief Reading and writing LEMON Graph Format.
   590 
   591 This group describes methods for reading and writing
   592 \ref lgf-format "LEMON Graph Format".
   593 */
   594 
   595 /**
   596 @defgroup eps_io Postscript Exporting
   597 @ingroup io_group
   598 \brief General \c EPS drawer and graph exporter
   599 
   600 This group describes general \c EPS drawing methods and special
   601 graph exporting tools.
   602 */
   603 
   604 /**
   605 @defgroup dimacs_group DIMACS format
   606 @ingroup io_group
   607 \brief Read and write files in DIMACS format
   608 
   609 Tools to read a digraph from or write it to a file in DIMACS format data.
   610 */
   611 
   612 /**
   613 @defgroup nauty_group NAUTY Format
   614 @ingroup io_group
   615 \brief Read \e Nauty format
   616 
   617 Tool to read graphs from \e Nauty format data.
   618 */
   619 
   620 /**
   621 @defgroup concept Concepts
   622 \brief Skeleton classes and concept checking classes
   623 
   624 This group describes the data/algorithm skeletons and concept checking
   625 classes implemented in LEMON.
   626 
   627 The purpose of the classes in this group is fourfold.
   628 
   629 - These classes contain the documentations of the %concepts. In order
   630   to avoid document multiplications, an implementation of a concept
   631   simply refers to the corresponding concept class.
   632 
   633 - These classes declare every functions, <tt>typedef</tt>s etc. an
   634   implementation of the %concepts should provide, however completely
   635   without implementations and real data structures behind the
   636   interface. On the other hand they should provide nothing else. All
   637   the algorithms working on a data structure meeting a certain concept
   638   should compile with these classes. (Though it will not run properly,
   639   of course.) In this way it is easily to check if an algorithm
   640   doesn't use any extra feature of a certain implementation.
   641 
   642 - The concept descriptor classes also provide a <em>checker class</em>
   643   that makes it possible to check whether a certain implementation of a
   644   concept indeed provides all the required features.
   645 
   646 - Finally, They can serve as a skeleton of a new implementation of a concept.
   647 */
   648 
   649 /**
   650 @defgroup graph_concepts Graph Structure Concepts
   651 @ingroup concept
   652 \brief Skeleton and concept checking classes for graph structures
   653 
   654 This group describes the skeletons and concept checking classes of LEMON's
   655 graph structures and helper classes used to implement these.
   656 */
   657 
   658 /**
   659 @defgroup map_concepts Map Concepts
   660 @ingroup concept
   661 \brief Skeleton and concept checking classes for maps
   662 
   663 This group describes the skeletons and concept checking classes of maps.
   664 */
   665 
   666 /**
   667 \anchor demoprograms
   668 
   669 @defgroup demos Demo Programs
   670 
   671 Some demo programs are listed here. Their full source codes can be found in
   672 the \c demo subdirectory of the source tree.
   673 
   674 It order to compile them, use <tt>--enable-demo</tt> configure option when
   675 build the library.
   676 */
   677 
   678 /**
   679 @defgroup tools Standalone Utility Applications
   680 
   681 Some utility applications are listed here.
   682 
   683 The standard compilation procedure (<tt>./configure;make</tt>) will compile
   684 them, as well.
   685 */
   686 
   687 }