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doc/groups.dox

author | Peter Kovacs <kpeter@inf.elte.hu> |

Fri, 27 Mar 2009 18:49:25 +0100 | |

changeset 605 | f53d641aa967 |

parent 463 | 88ed40ad0d4f |

parent 474 | fbd6e04acf44 |

child 606 | c5fd2d996909 |

child 656 | e6927fe719e6 |

permissions | -rw-r--r-- |

Improve timer and counter tests (#253)

- Do not print the output of counter_test.cc.

- Check the output of counter_test.cc.

- Shorten the running time of time_measure_test.cc.

- Do not print the output of counter_test.cc.

- Check the output of counter_test.cc.

- Shorten the running time of time_measure_test.cc.

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 */

19 namespace lemon {

21 /**

22 @defgroup datas Data Structures

23 This group describes the several data structures implemented in LEMON.

24 */

26 /**

27 @defgroup graphs Graph Structures

28 @ingroup datas

29 \brief Graph structures implemented in LEMON.

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.

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.

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.

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.

61 <b>See also:</b> \ref graph_concepts "Graph Structure Concepts".

62 */

64 /**

65 @defgroup graph_adaptors Adaptor Classes for Graphs

66 @ingroup graphs

67 \brief Adaptor classes for digraphs and graphs

69 This group contains several useful adaptor classes for digraphs and graphs.

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.

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.

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.

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.

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 */

140 /**

141 @defgroup semi_adaptors Semi-Adaptor Classes for Graphs

142 @ingroup graphs

143 \brief Graph types between real graphs and graph adaptors.

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 */

150 /**

151 @defgroup maps Maps

152 @ingroup datas

153 \brief Map structures implemented in LEMON.

155 This group describes the map structures implemented in LEMON.

157 LEMON provides several special purpose maps and map adaptors that e.g. combine

158 new maps from existing ones.

160 <b>See also:</b> \ref map_concepts "Map Concepts".

161 */

163 /**

164 @defgroup graph_maps Graph Maps

165 @ingroup maps

166 \brief Special graph-related maps.

168 This group describes maps that are specifically designed to assign

169 values to the nodes and arcs/edges of graphs.

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 */

175 /**

176 \defgroup map_adaptors Map Adaptors

177 \ingroup maps

178 \brief Tools to create new maps from existing ones

180 This group describes map adaptors that are used to create "implicit"

181 maps from other maps.

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.

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 }

203 Digraph::NodeMap<int> degree_map(graph);

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.

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;

221 typedef Digraph::ArcMap<double> DoubleArcMap;

222 DoubleArcMap length(graph);

223 DoubleArcMap speed(graph);

225 typedef DivMap<DoubleArcMap, DoubleArcMap> TimeMap;

226 TimeMap time(length, speed);

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 */

238 /**

239 @defgroup matrices Matrices

240 @ingroup datas

241 \brief Two dimensional data storages implemented in LEMON.

243 This group describes two dimensional data storages implemented in LEMON.

244 */

246 /**

247 @defgroup paths Path Structures

248 @ingroup datas

249 \brief %Path structures implemented in LEMON.

251 This group describes the path structures implemented in LEMON.

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.

259 \sa lemon::concepts::Path

260 */

262 /**

263 @defgroup auxdat Auxiliary Data Structures

264 @ingroup datas

265 \brief Auxiliary data structures implemented in LEMON.

267 This group describes some data structures implemented in LEMON in

268 order to make it easier to implement combinatorial algorithms.

269 */

271 /**

272 @defgroup algs Algorithms

273 \brief This group describes the several algorithms

274 implemented in LEMON.

276 This group describes the several algorithms

277 implemented in LEMON.

278 */

280 /**

281 @defgroup search Graph Search

282 @ingroup algs

283 \brief Common graph search algorithms.

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 */

289 /**

290 @defgroup shortest_path Shortest Path Algorithms

291 @ingroup algs

292 \brief Algorithms for finding shortest paths.

294 This group describes the algorithms for finding shortest paths in digraphs.

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 */

310 /**

311 @defgroup max_flow Maximum Flow Algorithms

312 @ingroup algs

313 \brief Algorithms for finding maximum flows.

315 This group describes the algorithms for finding maximum flows and

316 feasible circulations.

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.

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]

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.

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 */

342 /**

343 @defgroup min_cost_flow Minimum Cost Flow Algorithms

344 @ingroup algs

346 \brief Algorithms for finding minimum cost flows and circulations.

348 This group describes the algorithms for finding minimum cost flows and

349 circulations.

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.

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]

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 */

379 /**

380 @defgroup min_cut Minimum Cut Algorithms

381 @ingroup algs

383 \brief Algorithms for finding minimum cut in graphs.

385 This group describes the algorithms for finding minimum cut in graphs.

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:

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]

396 LEMON contains several algorithms related to minimum cut problems:

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.

405 If you want to find minimum cut just between two distinict nodes,

406 see the \ref max_flow "maximum flow problem".

407 */

409 /**

410 @defgroup graph_prop Connectivity and Other Graph Properties

411 @ingroup algs

412 \brief Algorithms for discovering the graph properties

414 This group describes the algorithms for discovering the graph properties

415 like connectivity, bipartiteness, euler property, simplicity etc.

417 \image html edge_biconnected_components.png

418 \image latex edge_biconnected_components.eps "bi-edge-connected components" width=\textwidth

419 */

421 /**

422 @defgroup planar Planarity Embedding and Drawing

423 @ingroup algs

424 \brief Algorithms for planarity checking, embedding and drawing

426 This group describes the algorithms for planarity checking,

427 embedding and drawing.

429 \image html planar.png

430 \image latex planar.eps "Plane graph" width=\textwidth

431 */

433 /**

434 @defgroup matching Matching Algorithms

435 @ingroup algs

436 \brief Algorithms for finding matchings in graphs and bipartite graphs.

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.

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.

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.

468 \image html bipartite_matching.png

469 \image latex bipartite_matching.eps "Bipartite Matching" width=\textwidth

470 */

472 /**

473 @defgroup spantree Minimum Spanning Tree Algorithms

474 @ingroup algs

475 \brief Algorithms for finding a minimum cost spanning tree in a graph.

477 This group describes the algorithms for finding a minimum cost spanning

478 tree in a graph.

479 */

481 /**

482 @defgroup auxalg Auxiliary Algorithms

483 @ingroup algs

484 \brief Auxiliary algorithms implemented in LEMON.

486 This group describes some algorithms implemented in LEMON

487 in order to make it easier to implement complex algorithms.

488 */

490 /**

491 @defgroup approx Approximation Algorithms

492 @ingroup algs

493 \brief Approximation algorithms.

495 This group describes the approximation and heuristic algorithms

496 implemented in LEMON.

497 */

499 /**

500 @defgroup gen_opt_group General Optimization Tools

501 \brief This group describes some general optimization frameworks

502 implemented in LEMON.

504 This group describes some general optimization frameworks

505 implemented in LEMON.

506 */

508 /**

509 @defgroup lp_group Lp and Mip Solvers

510 @ingroup gen_opt_group

511 \brief Lp and Mip solver interfaces for LEMON.

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 */

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.

523 This group adds some helper tools to general optimization framework

524 implemented in LEMON.

525 */

527 /**

528 @defgroup metah Metaheuristics

529 @ingroup gen_opt_group

530 \brief Metaheuristics for LEMON library.

532 This group describes some metaheuristic optimization tools.

533 */

535 /**

536 @defgroup utils Tools and Utilities

537 \brief Tools and utilities for programming in LEMON

539 Tools and utilities for programming in LEMON.

540 */

542 /**

543 @defgroup gutils Basic Graph Utilities

544 @ingroup utils

545 \brief Simple basic graph utilities.

547 This group describes some simple basic graph utilities.

548 */

550 /**

551 @defgroup misc Miscellaneous Tools

552 @ingroup utils

553 \brief Tools for development, debugging and testing.

555 This group describes several useful tools for development,

556 debugging and testing.

557 */

559 /**

560 @defgroup timecount Time Measuring and Counting

561 @ingroup misc

562 \brief Simple tools for measuring the performance of algorithms.

564 This group describes simple tools for measuring the performance

565 of algorithms.

566 */

568 /**

569 @defgroup exceptions Exceptions

570 @ingroup utils

571 \brief Exceptions defined in LEMON.

573 This group describes the exceptions defined in LEMON.

574 */

576 /**

577 @defgroup io_group Input-Output

578 \brief Graph Input-Output methods

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 */

586 /**

587 @defgroup lemon_io LEMON Graph Format

588 @ingroup io_group

589 \brief Reading and writing LEMON Graph Format.

591 This group describes methods for reading and writing

592 \ref lgf-format "LEMON Graph Format".

593 */

595 /**

596 @defgroup eps_io Postscript Exporting

597 @ingroup io_group

598 \brief General \c EPS drawer and graph exporter

600 This group describes general \c EPS drawing methods and special

601 graph exporting tools.

602 */

604 /**

605 @defgroup dimacs_group DIMACS format

606 @ingroup io_group

607 \brief Read and write files in DIMACS format

609 Tools to read a digraph from or write it to a file in DIMACS format data.

610 */

612 /**

613 @defgroup nauty_group NAUTY Format

614 @ingroup io_group

615 \brief Read \e Nauty format

617 Tool to read graphs from \e Nauty format data.

618 */

620 /**

621 @defgroup concept Concepts

622 \brief Skeleton classes and concept checking classes

624 This group describes the data/algorithm skeletons and concept checking

625 classes implemented in LEMON.

627 The purpose of the classes in this group is fourfold.

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.

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.

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.

646 - Finally, They can serve as a skeleton of a new implementation of a concept.

647 */

649 /**

650 @defgroup graph_concepts Graph Structure Concepts

651 @ingroup concept

652 \brief Skeleton and concept checking classes for graph structures

654 This group describes the skeletons and concept checking classes of LEMON's

655 graph structures and helper classes used to implement these.

656 */

658 /**

659 @defgroup map_concepts Map Concepts

660 @ingroup concept

661 \brief Skeleton and concept checking classes for maps

663 This group describes the skeletons and concept checking classes of maps.

664 */

666 /**

667 \anchor demoprograms

669 @defgroup demos Demo Programs

671 Some demo programs are listed here. Their full source codes can be found in

672 the \c demo subdirectory of the source tree.

674 It order to compile them, use <tt>--enable-demo</tt> configure option when

675 build the library.

676 */

678 /**

679 @defgroup tools Standalone Utility Applications

681 Some utility applications are listed here.

683 The standard compilation procedure (<tt>./configure;make</tt>) will compile

684 them, as well.

685 */

687 }