doc/groups.dox
author Alpar Juttner <alpar@cs.elte.hu>
Wed, 15 May 2019 13:33:55 +0200
branch1.2
changeset 1424 7edc220d6244
parent 961 7af2ae7c1428
parent 959 38213abd2911
permissions -rw-r--r--
Backport relevant parts of bugfixes [ad22262328b3], [61fdd06833a6] and [4add05447ca0] to branch 1.2 (#623)
     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) 2003-2010
     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 contains 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 maps Maps
   142 @ingroup datas
   143 \brief Map structures implemented in LEMON.
   144 
   145 This group contains the map structures implemented in LEMON.
   146 
   147 LEMON provides several special purpose maps and map adaptors that e.g. combine
   148 new maps from existing ones.
   149 
   150 <b>See also:</b> \ref map_concepts "Map Concepts".
   151 */
   152 
   153 /**
   154 @defgroup graph_maps Graph Maps
   155 @ingroup maps
   156 \brief Special graph-related maps.
   157 
   158 This group contains maps that are specifically designed to assign
   159 values to the nodes and arcs/edges of graphs.
   160 
   161 If you are looking for the standard graph maps (\c NodeMap, \c ArcMap,
   162 \c EdgeMap), see the \ref graph_concepts "Graph Structure Concepts".
   163 */
   164 
   165 /**
   166 \defgroup map_adaptors Map Adaptors
   167 \ingroup maps
   168 \brief Tools to create new maps from existing ones
   169 
   170 This group contains map adaptors that are used to create "implicit"
   171 maps from other maps.
   172 
   173 Most of them are \ref concepts::ReadMap "read-only maps".
   174 They can make arithmetic and logical operations between one or two maps
   175 (negation, shifting, addition, multiplication, logical 'and', 'or',
   176 'not' etc.) or e.g. convert a map to another one of different Value type.
   177 
   178 The typical usage of this classes is passing implicit maps to
   179 algorithms.  If a function type algorithm is called then the function
   180 type map adaptors can be used comfortable. For example let's see the
   181 usage of map adaptors with the \c graphToEps() function.
   182 \code
   183   Color nodeColor(int deg) {
   184     if (deg >= 2) {
   185       return Color(0.5, 0.0, 0.5);
   186     } else if (deg == 1) {
   187       return Color(1.0, 0.5, 1.0);
   188     } else {
   189       return Color(0.0, 0.0, 0.0);
   190     }
   191   }
   192 
   193   Digraph::NodeMap<int> degree_map(graph);
   194 
   195   graphToEps(graph, "graph.eps")
   196     .coords(coords).scaleToA4().undirected()
   197     .nodeColors(composeMap(functorToMap(nodeColor), degree_map))
   198     .run();
   199 \endcode
   200 The \c functorToMap() function makes an \c int to \c Color map from the
   201 \c nodeColor() function. The \c composeMap() compose the \c degree_map
   202 and the previously created map. The composed map is a proper function to
   203 get the color of each node.
   204 
   205 The usage with class type algorithms is little bit harder. In this
   206 case the function type map adaptors can not be used, because the
   207 function map adaptors give back temporary objects.
   208 \code
   209   Digraph graph;
   210 
   211   typedef Digraph::ArcMap<double> DoubleArcMap;
   212   DoubleArcMap length(graph);
   213   DoubleArcMap speed(graph);
   214 
   215   typedef DivMap<DoubleArcMap, DoubleArcMap> TimeMap;
   216   TimeMap time(length, speed);
   217 
   218   Dijkstra<Digraph, TimeMap> dijkstra(graph, time);
   219   dijkstra.run(source, target);
   220 \endcode
   221 We have a length map and a maximum speed map on the arcs of a digraph.
   222 The minimum time to pass the arc can be calculated as the division of
   223 the two maps which can be done implicitly with the \c DivMap template
   224 class. We use the implicit minimum time map as the length map of the
   225 \c Dijkstra algorithm.
   226 */
   227 
   228 /**
   229 @defgroup paths Path Structures
   230 @ingroup datas
   231 \brief %Path structures implemented in LEMON.
   232 
   233 This group contains the path structures implemented in LEMON.
   234 
   235 LEMON provides flexible data structures to work with paths.
   236 All of them have similar interfaces and they can be copied easily with
   237 assignment operators and copy constructors. This makes it easy and
   238 efficient to have e.g. the Dijkstra algorithm to store its result in
   239 any kind of path structure.
   240 
   241 \sa \ref concepts::Path "Path concept"
   242 */
   243 
   244 /**
   245 @defgroup heaps Heap Structures
   246 @ingroup datas
   247 \brief %Heap structures implemented in LEMON.
   248 
   249 This group contains the heap structures implemented in LEMON.
   250 
   251 LEMON provides several heap classes. They are efficient implementations
   252 of the abstract data type \e priority \e queue. They store items with
   253 specified values called \e priorities in such a way that finding and
   254 removing the item with minimum priority are efficient.
   255 The basic operations are adding and erasing items, changing the priority
   256 of an item, etc.
   257 
   258 Heaps are crucial in several algorithms, such as Dijkstra and Prim.
   259 The heap implementations have the same interface, thus any of them can be
   260 used easily in such algorithms.
   261 
   262 \sa \ref concepts::Heap "Heap concept"
   263 */
   264 
   265 /**
   266 @defgroup auxdat Auxiliary Data Structures
   267 @ingroup datas
   268 \brief Auxiliary data structures implemented in LEMON.
   269 
   270 This group contains some data structures implemented in LEMON in
   271 order to make it easier to implement combinatorial algorithms.
   272 */
   273 
   274 /**
   275 @defgroup geomdat Geometric Data Structures
   276 @ingroup auxdat
   277 \brief Geometric data structures implemented in LEMON.
   278 
   279 This group contains geometric data structures implemented in LEMON.
   280 
   281  - \ref lemon::dim2::Point "dim2::Point" implements a two dimensional
   282    vector with the usual operations.
   283  - \ref lemon::dim2::Box "dim2::Box" can be used to determine the
   284    rectangular bounding box of a set of \ref lemon::dim2::Point
   285    "dim2::Point"'s.
   286 */
   287 
   288 /**
   289 @defgroup algs Algorithms
   290 \brief This group contains the several algorithms
   291 implemented in LEMON.
   292 
   293 This group contains the several algorithms
   294 implemented in LEMON.
   295 */
   296 
   297 /**
   298 @defgroup search Graph Search
   299 @ingroup algs
   300 \brief Common graph search algorithms.
   301 
   302 This group contains the common graph search algorithms, namely
   303 \e breadth-first \e search (BFS) and \e depth-first \e search (DFS)
   304 \ref clrs01algorithms.
   305 */
   306 
   307 /**
   308 @defgroup shortest_path Shortest Path Algorithms
   309 @ingroup algs
   310 \brief Algorithms for finding shortest paths.
   311 
   312 This group contains the algorithms for finding shortest paths in digraphs
   313 \ref clrs01algorithms.
   314 
   315  - \ref Dijkstra algorithm for finding shortest paths from a source node
   316    when all arc lengths are non-negative.
   317  - \ref BellmanFord "Bellman-Ford" algorithm for finding shortest paths
   318    from a source node when arc lenghts can be either positive or negative,
   319    but the digraph should not contain directed cycles with negative total
   320    length.
   321  - \ref Suurballe A successive shortest path algorithm for finding
   322    arc-disjoint paths between two nodes having minimum total length.
   323 */
   324 
   325 /**
   326 @defgroup spantree Minimum Spanning Tree Algorithms
   327 @ingroup algs
   328 \brief Algorithms for finding minimum cost spanning trees and arborescences.
   329 
   330 This group contains the algorithms for finding minimum cost spanning
   331 trees and arborescences \ref clrs01algorithms.
   332 */
   333 
   334 /**
   335 @defgroup max_flow Maximum Flow Algorithms
   336 @ingroup algs
   337 \brief Algorithms for finding maximum flows.
   338 
   339 This group contains the algorithms for finding maximum flows and
   340 feasible circulations \ref clrs01algorithms, \ref amo93networkflows.
   341 
   342 The \e maximum \e flow \e problem is to find a flow of maximum value between
   343 a single source and a single target. Formally, there is a \f$G=(V,A)\f$
   344 digraph, a \f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function and
   345 \f$s, t \in V\f$ source and target nodes.
   346 A maximum flow is an \f$f: A\rightarrow\mathbf{R}^+_0\f$ solution of the
   347 following optimization problem.
   348 
   349 \f[ \max\sum_{sv\in A} f(sv) - \sum_{vs\in A} f(vs) \f]
   350 \f[ \sum_{uv\in A} f(uv) = \sum_{vu\in A} f(vu)
   351     \quad \forall u\in V\setminus\{s,t\} \f]
   352 \f[ 0 \leq f(uv) \leq cap(uv) \quad \forall uv\in A \f]
   353 
   354 \ref Preflow is an efficient implementation of Goldberg-Tarjan's
   355 preflow push-relabel algorithm \ref goldberg88newapproach for finding
   356 maximum flows. It also provides functions to query the minimum cut,
   357 which is the dual problem of maximum flow.
   358 
   359 \ref Circulation is a preflow push-relabel algorithm implemented directly
   360 for finding feasible circulations, which is a somewhat different problem,
   361 but it is strongly related to maximum flow.
   362 For more information, see \ref Circulation.
   363 */
   364 
   365 /**
   366 @defgroup min_cost_flow_algs Minimum Cost Flow Algorithms
   367 @ingroup algs
   368 
   369 \brief Algorithms for finding minimum cost flows and circulations.
   370 
   371 This group contains the algorithms for finding minimum cost flows and
   372 circulations \ref amo93networkflows. For more information about this
   373 problem and its dual solution, see \ref min_cost_flow
   374 "Minimum Cost Flow Problem".
   375 
   376 LEMON contains several algorithms for this problem.
   377  - \ref NetworkSimplex Primal Network Simplex algorithm with various
   378    pivot strategies \ref dantzig63linearprog, \ref kellyoneill91netsimplex.
   379  - \ref CostScaling Cost Scaling algorithm based on push/augment and
   380    relabel operations \ref goldberg90approximation, \ref goldberg97efficient,
   381    \ref bunnagel98efficient.
   382  - \ref CapacityScaling Capacity Scaling algorithm based on the successive
   383    shortest path method \ref edmondskarp72theoretical.
   384  - \ref CycleCanceling Cycle-Canceling algorithms, two of which are
   385    strongly polynomial \ref klein67primal, \ref goldberg89cyclecanceling.
   386 
   387 In general NetworkSimplex is the most efficient implementation,
   388 but in special cases other algorithms could be faster.
   389 For example, if the total supply and/or capacities are rather small,
   390 CapacityScaling is usually the fastest algorithm (without effective scaling).
   391 */
   392 
   393 /**
   394 @defgroup min_cut Minimum Cut Algorithms
   395 @ingroup algs
   396 
   397 \brief Algorithms for finding minimum cut in graphs.
   398 
   399 This group contains the algorithms for finding minimum cut in graphs.
   400 
   401 The \e minimum \e cut \e problem is to find a non-empty and non-complete
   402 \f$X\f$ subset of the nodes with minimum overall capacity on
   403 outgoing arcs. Formally, there is a \f$G=(V,A)\f$ digraph, a
   404 \f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function. The minimum
   405 cut is the \f$X\f$ solution of the next optimization problem:
   406 
   407 \f[ \min_{X \subset V, X\not\in \{\emptyset, V\}}
   408     \sum_{uv\in A: u\in X, v\not\in X}cap(uv) \f]
   409 
   410 LEMON contains several algorithms related to minimum cut problems:
   411 
   412 - \ref HaoOrlin "Hao-Orlin algorithm" for calculating minimum cut
   413   in directed graphs.
   414 - \ref GomoryHu "Gomory-Hu tree computation" for calculating
   415   all-pairs minimum cut in undirected graphs.
   416 
   417 If you want to find minimum cut just between two distinict nodes,
   418 see the \ref max_flow "maximum flow problem".
   419 */
   420 
   421 /**
   422 @defgroup min_mean_cycle Minimum Mean Cycle Algorithms
   423 @ingroup algs
   424 \brief Algorithms for finding minimum mean cycles.
   425 
   426 This group contains the algorithms for finding minimum mean cycles
   427 \ref clrs01algorithms, \ref amo93networkflows.
   428 
   429 The \e minimum \e mean \e cycle \e problem is to find a directed cycle
   430 of minimum mean length (cost) in a digraph.
   431 The mean length of a cycle is the average length of its arcs, i.e. the
   432 ratio between the total length of the cycle and the number of arcs on it.
   433 
   434 This problem has an important connection to \e conservative \e length
   435 \e functions, too. A length function on the arcs of a digraph is called
   436 conservative if and only if there is no directed cycle of negative total
   437 length. For an arbitrary length function, the negative of the minimum
   438 cycle mean is the smallest \f$\epsilon\f$ value so that increasing the
   439 arc lengths uniformly by \f$\epsilon\f$ results in a conservative length
   440 function.
   441 
   442 LEMON contains three algorithms for solving the minimum mean cycle problem:
   443 - \ref KarpMmc Karp's original algorithm \ref amo93networkflows,
   444   \ref dasdan98minmeancycle.
   445 - \ref HartmannOrlinMmc Hartmann-Orlin's algorithm, which is an improved
   446   version of Karp's algorithm \ref dasdan98minmeancycle.
   447 - \ref HowardMmc Howard's policy iteration algorithm
   448   \ref dasdan98minmeancycle.
   449 
   450 In practice, the \ref HowardMmc "Howard" algorithm proved to be by far the
   451 most efficient one, though the best known theoretical bound on its running
   452 time is exponential.
   453 Both \ref KarpMmc "Karp" and \ref HartmannOrlinMmc "Hartmann-Orlin" algorithms
   454 run in time O(ne) and use space O(n<sup>2</sup>+e), but the latter one is
   455 typically faster due to the applied early termination scheme.
   456 */
   457 
   458 /**
   459 @defgroup matching Matching Algorithms
   460 @ingroup algs
   461 \brief Algorithms for finding matchings in graphs and bipartite graphs.
   462 
   463 This group contains the algorithms for calculating
   464 matchings in graphs and bipartite graphs. The general matching problem is
   465 finding a subset of the edges for which each node has at most one incident
   466 edge.
   467 
   468 There are several different algorithms for calculate matchings in
   469 graphs.  The matching problems in bipartite graphs are generally
   470 easier than in general graphs. The goal of the matching optimization
   471 can be finding maximum cardinality, maximum weight or minimum cost
   472 matching. The search can be constrained to find perfect or
   473 maximum cardinality matching.
   474 
   475 The matching algorithms implemented in LEMON:
   476 - \ref MaxMatching Edmond's blossom shrinking algorithm for calculating
   477   maximum cardinality matching in general graphs.
   478 - \ref MaxWeightedMatching Edmond's blossom shrinking algorithm for calculating
   479   maximum weighted matching in general graphs.
   480 - \ref MaxWeightedPerfectMatching
   481   Edmond's blossom shrinking algorithm for calculating maximum weighted
   482   perfect matching in general graphs.
   483 - \ref MaxFractionalMatching Push-relabel algorithm for calculating
   484   maximum cardinality fractional matching in general graphs.
   485 - \ref MaxWeightedFractionalMatching Augmenting path algorithm for calculating
   486   maximum weighted fractional matching in general graphs.
   487 - \ref MaxWeightedPerfectFractionalMatching
   488   Augmenting path algorithm for calculating maximum weighted
   489   perfect fractional matching in general graphs.
   490 
   491 \image html matching.png
   492 \image latex matching.eps "Min Cost Perfect Matching" width=\textwidth
   493 */
   494 
   495 /**
   496 @defgroup graph_properties Connectivity and Other Graph Properties
   497 @ingroup algs
   498 \brief Algorithms for discovering the graph properties
   499 
   500 This group contains the algorithms for discovering the graph properties
   501 like connectivity, bipartiteness, euler property, simplicity etc.
   502 
   503 \image html connected_components.png
   504 \image latex connected_components.eps "Connected components" width=\textwidth
   505 */
   506 
   507 /**
   508 @defgroup planar Planarity Embedding and Drawing
   509 @ingroup algs
   510 \brief Algorithms for planarity checking, embedding and drawing
   511 
   512 This group contains the algorithms for planarity checking,
   513 embedding and drawing.
   514 
   515 \image html planar.png
   516 \image latex planar.eps "Plane graph" width=\textwidth
   517 */
   518 
   519 /**
   520 @defgroup auxalg Auxiliary Algorithms
   521 @ingroup algs
   522 \brief Auxiliary algorithms implemented in LEMON.
   523 
   524 This group contains some algorithms implemented in LEMON
   525 in order to make it easier to implement complex algorithms.
   526 */
   527 
   528 /**
   529 @defgroup gen_opt_group General Optimization Tools
   530 \brief This group contains some general optimization frameworks
   531 implemented in LEMON.
   532 
   533 This group contains some general optimization frameworks
   534 implemented in LEMON.
   535 */
   536 
   537 /**
   538 @defgroup lp_group LP and MIP Solvers
   539 @ingroup gen_opt_group
   540 \brief LP and MIP solver interfaces for LEMON.
   541 
   542 This group contains LP and MIP solver interfaces for LEMON.
   543 Various LP solvers could be used in the same manner with this
   544 high-level interface.
   545 
   546 The currently supported solvers are \ref glpk, \ref clp, \ref cbc,
   547 \ref cplex, \ref soplex.
   548 */
   549 
   550 /**
   551 @defgroup utils Tools and Utilities
   552 \brief Tools and utilities for programming in LEMON
   553 
   554 Tools and utilities for programming in LEMON.
   555 */
   556 
   557 /**
   558 @defgroup gutils Basic Graph Utilities
   559 @ingroup utils
   560 \brief Simple basic graph utilities.
   561 
   562 This group contains some simple basic graph utilities.
   563 */
   564 
   565 /**
   566 @defgroup misc Miscellaneous Tools
   567 @ingroup utils
   568 \brief Tools for development, debugging and testing.
   569 
   570 This group contains several useful tools for development,
   571 debugging and testing.
   572 */
   573 
   574 /**
   575 @defgroup timecount Time Measuring and Counting
   576 @ingroup misc
   577 \brief Simple tools for measuring the performance of algorithms.
   578 
   579 This group contains simple tools for measuring the performance
   580 of algorithms.
   581 */
   582 
   583 /**
   584 @defgroup exceptions Exceptions
   585 @ingroup utils
   586 \brief Exceptions defined in LEMON.
   587 
   588 This group contains the exceptions defined in LEMON.
   589 */
   590 
   591 /**
   592 @defgroup io_group Input-Output
   593 \brief Graph Input-Output methods
   594 
   595 This group contains the tools for importing and exporting graphs
   596 and graph related data. Now it supports the \ref lgf-format
   597 "LEMON Graph Format", the \c DIMACS format and the encapsulated
   598 postscript (EPS) format.
   599 */
   600 
   601 /**
   602 @defgroup lemon_io LEMON Graph Format
   603 @ingroup io_group
   604 \brief Reading and writing LEMON Graph Format.
   605 
   606 This group contains methods for reading and writing
   607 \ref lgf-format "LEMON Graph Format".
   608 */
   609 
   610 /**
   611 @defgroup eps_io Postscript Exporting
   612 @ingroup io_group
   613 \brief General \c EPS drawer and graph exporter
   614 
   615 This group contains general \c EPS drawing methods and special
   616 graph exporting tools.
   617 */
   618 
   619 /**
   620 @defgroup dimacs_group DIMACS Format
   621 @ingroup io_group
   622 \brief Read and write files in DIMACS format
   623 
   624 Tools to read a digraph from or write it to a file in DIMACS format data.
   625 */
   626 
   627 /**
   628 @defgroup nauty_group NAUTY Format
   629 @ingroup io_group
   630 \brief Read \e Nauty format
   631 
   632 Tool to read graphs from \e Nauty format data.
   633 */
   634 
   635 /**
   636 @defgroup concept Concepts
   637 \brief Skeleton classes and concept checking classes
   638 
   639 This group contains the data/algorithm skeletons and concept checking
   640 classes implemented in LEMON.
   641 
   642 The purpose of the classes in this group is fourfold.
   643 
   644 - These classes contain the documentations of the %concepts. In order
   645   to avoid document multiplications, an implementation of a concept
   646   simply refers to the corresponding concept class.
   647 
   648 - These classes declare every functions, <tt>typedef</tt>s etc. an
   649   implementation of the %concepts should provide, however completely
   650   without implementations and real data structures behind the
   651   interface. On the other hand they should provide nothing else. All
   652   the algorithms working on a data structure meeting a certain concept
   653   should compile with these classes. (Though it will not run properly,
   654   of course.) In this way it is easily to check if an algorithm
   655   doesn't use any extra feature of a certain implementation.
   656 
   657 - The concept descriptor classes also provide a <em>checker class</em>
   658   that makes it possible to check whether a certain implementation of a
   659   concept indeed provides all the required features.
   660 
   661 - Finally, They can serve as a skeleton of a new implementation of a concept.
   662 */
   663 
   664 /**
   665 @defgroup graph_concepts Graph Structure Concepts
   666 @ingroup concept
   667 \brief Skeleton and concept checking classes for graph structures
   668 
   669 This group contains the skeletons and concept checking classes of
   670 graph structures.
   671 */
   672 
   673 /**
   674 @defgroup map_concepts Map Concepts
   675 @ingroup concept
   676 \brief Skeleton and concept checking classes for maps
   677 
   678 This group contains the skeletons and concept checking classes of maps.
   679 */
   680 
   681 /**
   682 @defgroup tools Standalone Utility Applications
   683 
   684 Some utility applications are listed here.
   685 
   686 The standard compilation procedure (<tt>./configure;make</tt>) will compile
   687 them, as well.
   688 */
   689 
   690 /**
   691 \anchor demoprograms
   692 
   693 @defgroup demos Demo Programs
   694 
   695 Some demo programs are listed here. Their full source codes can be found in
   696 the \c demo subdirectory of the source tree.
   697 
   698 In order to compile them, use the <tt>make demo</tt> or the
   699 <tt>make check</tt> commands.
   700 */
   701 
   702 }