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kpeter (Peter Kovacs)
kpeter@inf.elte.hu
Improvements and fixes for the minimum cut algorithms (#264)
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/* -*- C++ -*-
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 *
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 * This file is a part of LEMON, a generic C++ optimization library
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 *
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 * Copyright (C) 2003-2008
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 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
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 * (Egervary Research Group on Combinatorial Optimization, EGRES).
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 *
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 * Permission to use, modify and distribute this software is granted
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 * provided that this copyright notice appears in all copies. For
11 11
 * precise terms see the accompanying LICENSE file.
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 *
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 * This software is provided "AS IS" with no warranty of any kind,
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 * express or implied, and with no claim as to its suitability for any
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 * purpose.
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 *
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 */
18 18

	
19 19
#ifndef LEMON_GOMORY_HU_TREE_H
20 20
#define LEMON_GOMORY_HU_TREE_H
21 21

	
22 22
#include <limits>
23 23

	
24 24
#include <lemon/core.h>
25 25
#include <lemon/preflow.h>
26 26
#include <lemon/concept_check.h>
27 27
#include <lemon/concepts/maps.h>
28 28

	
29 29
/// \ingroup min_cut
30 30
/// \file 
31 31
/// \brief Gomory-Hu cut tree in graphs.
32 32

	
33 33
namespace lemon {
34 34

	
35 35
  /// \ingroup min_cut
36 36
  ///
37 37
  /// \brief Gomory-Hu cut tree algorithm
38 38
  ///
39 39
  /// The Gomory-Hu tree is a tree on the node set of a given graph, but it
40 40
  /// may contain edges which are not in the original graph. It has the
41 41
  /// property that the minimum capacity edge of the path between two nodes 
42 42
  /// in this tree has the same weight as the minimum cut in the graph
43 43
  /// between these nodes. Moreover the components obtained by removing
44 44
  /// this edge from the tree determine the corresponding minimum cut.
45
  ///
46 45
  /// Therefore once this tree is computed, the minimum cut between any pair
47 46
  /// of nodes can easily be obtained.
48 47
  /// 
49 48
  /// The algorithm calculates \e n-1 distinct minimum cuts (currently with
50
  /// the \ref Preflow algorithm), therefore the algorithm has
51
  /// \f$(O(n^3\sqrt{e})\f$ overall time complexity. It calculates a
52
  /// rooted Gomory-Hu tree, its structure and the weights can be obtained
53
  /// by \c predNode(), \c predValue() and \c rootDist().
54
  /// 
55
  /// The members \c minCutMap() and \c minCutValue() calculate
49
  /// the \ref Preflow algorithm), thus it has \f$O(n^3\sqrt{e})\f$ overall
50
  /// time complexity. It calculates a rooted Gomory-Hu tree.
51
  /// The structure of the tree and the edge weights can be
52
  /// obtained using \c predNode(), \c predValue() and \c rootDist().
53
  /// The functions \c minCutMap() and \c minCutValue() calculate
56 54
  /// the minimum cut and the minimum cut value between any two nodes
57 55
  /// in the graph. You can also list (iterate on) the nodes and the
58 56
  /// edges of the cuts using \c MinCutNodeIt and \c MinCutEdgeIt.
59 57
  ///
60 58
  /// \tparam GR The type of the undirected graph the algorithm runs on.
61
  /// \tparam CAP The type of the edge map describing the edge capacities.
62
  /// It is \ref concepts::Graph::EdgeMap "GR::EdgeMap<int>" by default.
59
  /// \tparam CAP The type of the edge map containing the capacities.
60
  /// The default map type is \ref concepts::Graph::EdgeMap "GR::EdgeMap<int>".
63 61
#ifdef DOXYGEN
64 62
  template <typename GR,
65 63
	    typename CAP>
66 64
#else
67 65
  template <typename GR,
68 66
	    typename CAP = typename GR::template EdgeMap<int> >
69 67
#endif
70 68
  class GomoryHu {
71 69
  public:
72 70

	
73
    /// The graph type
71
    /// The graph type of the algorithm
74 72
    typedef GR Graph;
75
    /// The type of the edge capacity map
73
    /// The capacity map type of the algorithm
76 74
    typedef CAP Capacity;
77 75
    /// The value type of capacities
78 76
    typedef typename Capacity::Value Value;
79 77
    
80 78
  private:
81 79

	
82 80
    TEMPLATE_GRAPH_TYPEDEFS(Graph);
83 81

	
84 82
    const Graph& _graph;
85 83
    const Capacity& _capacity;
86 84

	
87 85
    Node _root;
88 86
    typename Graph::template NodeMap<Node>* _pred;
89 87
    typename Graph::template NodeMap<Value>* _weight;
90 88
    typename Graph::template NodeMap<int>* _order;
91 89

	
92 90
    void createStructures() {
93 91
      if (!_pred) {
94 92
	_pred = new typename Graph::template NodeMap<Node>(_graph);
95 93
      }
96 94
      if (!_weight) {
97 95
	_weight = new typename Graph::template NodeMap<Value>(_graph);
98 96
      }
99 97
      if (!_order) {
100 98
	_order = new typename Graph::template NodeMap<int>(_graph);
101 99
      }
102 100
    }
103 101

	
104 102
    void destroyStructures() {
105 103
      if (_pred) {
106 104
	delete _pred;
107 105
      }
108 106
      if (_weight) {
109 107
	delete _weight;
110 108
      }
111 109
      if (_order) {
112 110
	delete _order;
113 111
      }
114 112
    }
115 113
  
116 114
  public:
117 115

	
118 116
    /// \brief Constructor
119 117
    ///
120
    /// Constructor
118
    /// Constructor.
121 119
    /// \param graph The undirected graph the algorithm runs on.
122 120
    /// \param capacity The edge capacity map.
123 121
    GomoryHu(const Graph& graph, const Capacity& capacity) 
124 122
      : _graph(graph), _capacity(capacity),
125 123
	_pred(0), _weight(0), _order(0) 
126 124
    {
127 125
      checkConcept<concepts::ReadMap<Edge, Value>, Capacity>();
128 126
    }
129 127

	
130 128

	
131 129
    /// \brief Destructor
132 130
    ///
133
    /// Destructor
131
    /// Destructor.
134 132
    ~GomoryHu() {
135 133
      destroyStructures();
136 134
    }
137 135

	
138 136
  private:
139 137
  
140 138
    // Initialize the internal data structures
141 139
    void init() {
142 140
      createStructures();
143 141

	
144 142
      _root = NodeIt(_graph);
145 143
      for (NodeIt n(_graph); n != INVALID; ++n) {
146 144
        (*_pred)[n] = _root;
147 145
        (*_order)[n] = -1;
148 146
      }
149 147
      (*_pred)[_root] = INVALID;
150 148
      (*_weight)[_root] = std::numeric_limits<Value>::max(); 
151 149
    }
152 150

	
153 151

	
154 152
    // Start the algorithm
155 153
    void start() {
156 154
      Preflow<Graph, Capacity> fa(_graph, _capacity, _root, INVALID);
157 155

	
158 156
      for (NodeIt n(_graph); n != INVALID; ++n) {
159 157
	if (n == _root) continue;
160 158

	
161 159
	Node pn = (*_pred)[n];
162 160
	fa.source(n);
163 161
	fa.target(pn);
164 162

	
165 163
	fa.runMinCut();
166 164

	
167 165
	(*_weight)[n] = fa.flowValue();
168 166

	
169 167
	for (NodeIt nn(_graph); nn != INVALID; ++nn) {
170 168
	  if (nn != n && fa.minCut(nn) && (*_pred)[nn] == pn) {
171 169
	    (*_pred)[nn] = n;
172 170
	  }
173 171
	}
174 172
	if ((*_pred)[pn] != INVALID && fa.minCut((*_pred)[pn])) {
175 173
	  (*_pred)[n] = (*_pred)[pn];
176 174
	  (*_pred)[pn] = n;
177 175
	  (*_weight)[n] = (*_weight)[pn];
178 176
	  (*_weight)[pn] = fa.flowValue();
179 177
	}
180 178
      }
181 179

	
182 180
      (*_order)[_root] = 0;
183 181
      int index = 1;
184 182

	
185 183
      for (NodeIt n(_graph); n != INVALID; ++n) {
186 184
	std::vector<Node> st;
187 185
	Node nn = n;
188 186
	while ((*_order)[nn] == -1) {
189 187
	  st.push_back(nn);
190 188
	  nn = (*_pred)[nn];
191 189
	}
192 190
	while (!st.empty()) {
193 191
	  (*_order)[st.back()] = index++;
194 192
	  st.pop_back();
195 193
	}
196 194
      }
197 195
    }
198 196

	
199 197
  public:
200 198

	
201 199
    ///\name Execution Control
202 200
 
203 201
    ///@{
204 202

	
205 203
    /// \brief Run the Gomory-Hu algorithm.
206 204
    ///
207 205
    /// This function runs the Gomory-Hu algorithm.
208 206
    void run() {
209 207
      init();
210 208
      start();
211 209
    }
212 210
    
213 211
    /// @}
214 212

	
215 213
    ///\name Query Functions
216 214
    ///The results of the algorithm can be obtained using these
217 215
    ///functions.\n
218
    ///\ref run() "run()" should be called before using them.\n
216
    ///\ref run() should be called before using them.\n
219 217
    ///See also \ref MinCutNodeIt and \ref MinCutEdgeIt.
220 218

	
221 219
    ///@{
222 220

	
223 221
    /// \brief Return the predecessor node in the Gomory-Hu tree.
224 222
    ///
225
    /// This function returns the predecessor node in the Gomory-Hu tree.
226
    /// If the node is
227
    /// the root of the Gomory-Hu tree, then it returns \c INVALID.
228
    Node predNode(const Node& node) {
223
    /// This function returns the predecessor node of the given node
224
    /// in the Gomory-Hu tree.
225
    /// If \c node is the root of the tree, then it returns \c INVALID.
226
    ///
227
    /// \pre \ref run() must be called before using this function.
228
    Node predNode(const Node& node) const {
229 229
      return (*_pred)[node];
230 230
    }
231 231

	
232
    /// \brief Return the distance from the root node in the Gomory-Hu tree.
233
    ///
234
    /// This function returns the distance of \c node from the root node
235
    /// in the Gomory-Hu tree.
236
    int rootDist(const Node& node) {
237
      return (*_order)[node];
238
    }
239

	
240 232
    /// \brief Return the weight of the predecessor edge in the
241 233
    /// Gomory-Hu tree.
242 234
    ///
243
    /// This function returns the weight of the predecessor edge in the
244
    /// Gomory-Hu tree.  If the node is the root, the result is undefined.
245
    Value predValue(const Node& node) {
235
    /// This function returns the weight of the predecessor edge of the 
236
    /// given node in the Gomory-Hu tree.
237
    /// If \c node is the root of the tree, the result is undefined.
238
    ///
239
    /// \pre \ref run() must be called before using this function.
240
    Value predValue(const Node& node) const {
246 241
      return (*_weight)[node];
247 242
    }
248 243

	
244
    /// \brief Return the distance from the root node in the Gomory-Hu tree.
245
    ///
246
    /// This function returns the distance of the given node from the root
247
    /// node in the Gomory-Hu tree.
248
    ///
249
    /// \pre \ref run() must be called before using this function.
250
    int rootDist(const Node& node) const {
251
      return (*_order)[node];
252
    }
253

	
249 254
    /// \brief Return the minimum cut value between two nodes
250 255
    ///
251
    /// This function returns the minimum cut value between two nodes. The
252
    /// algorithm finds the nearest common ancestor in the Gomory-Hu
253
    /// tree and calculates the minimum weight edge on the paths to
254
    /// the ancestor.
256
    /// This function returns the minimum cut value between the nodes
257
    /// \c s and \c t. 
258
    /// It finds the nearest common ancestor of the given nodes in the
259
    /// Gomory-Hu tree and calculates the minimum weight edge on the
260
    /// paths to the ancestor.
261
    ///
262
    /// \pre \ref run() must be called before using this function.
255 263
    Value minCutValue(const Node& s, const Node& t) const {
256 264
      Node sn = s, tn = t;
257 265
      Value value = std::numeric_limits<Value>::max();
258 266
      
259 267
      while (sn != tn) {
260 268
	if ((*_order)[sn] < (*_order)[tn]) {
261 269
	  if ((*_weight)[tn] <= value) value = (*_weight)[tn];
262 270
	  tn = (*_pred)[tn];
263 271
	} else {
264 272
	  if ((*_weight)[sn] <= value) value = (*_weight)[sn];
265 273
	  sn = (*_pred)[sn];
266 274
	}
267 275
      }
268 276
      return value;
269 277
    }
270 278

	
271 279
    /// \brief Return the minimum cut between two nodes
272 280
    ///
273 281
    /// This function returns the minimum cut between the nodes \c s and \c t
274 282
    /// in the \c cutMap parameter by setting the nodes in the component of
275 283
    /// \c s to \c true and the other nodes to \c false.
276 284
    ///
277
    /// For higher level interfaces, see MinCutNodeIt and MinCutEdgeIt.
285
    /// For higher level interfaces see MinCutNodeIt and MinCutEdgeIt.
286
    ///
287
    /// \param s The base node.
288
    /// \param t The node you want to separate from node \c s.
289
    /// \param cutMap The cut will be returned in this map.
290
    /// It must be a \c bool (or convertible) \ref concepts::ReadWriteMap
291
    /// "ReadWriteMap" on the graph nodes.
292
    ///
293
    /// \return The value of the minimum cut between \c s and \c t.
294
    ///
295
    /// \pre \ref run() must be called before using this function.
278 296
    template <typename CutMap>
279
    Value minCutMap(const Node& s, ///< The base node.
297
    Value minCutMap(const Node& s, ///< 
280 298
                    const Node& t,
281
                    ///< The node you want to separate from node \c s.
299
                    ///< 
282 300
                    CutMap& cutMap
283
                    ///< The cut will be returned in this map.
284
                    /// It must be a \c bool (or convertible) 
285
                    /// \ref concepts::ReadWriteMap "ReadWriteMap"
286
                    /// on the graph nodes.
301
                    ///< 
287 302
                    ) const {
288 303
      Node sn = s, tn = t;
289 304
      bool s_root=false;
290 305
      Node rn = INVALID;
291 306
      Value value = std::numeric_limits<Value>::max();
292 307
      
293 308
      while (sn != tn) {
294 309
	if ((*_order)[sn] < (*_order)[tn]) {
295 310
	  if ((*_weight)[tn] <= value) {
296 311
	    rn = tn;
297 312
            s_root = false;
298 313
	    value = (*_weight)[tn];
299 314
	  }
300 315
	  tn = (*_pred)[tn];
301 316
	} else {
302 317
	  if ((*_weight)[sn] <= value) {
303 318
	    rn = sn;
304 319
            s_root = true;
305 320
	    value = (*_weight)[sn];
306 321
	  }
307 322
	  sn = (*_pred)[sn];
308 323
	}
309 324
      }
310 325

	
311 326
      typename Graph::template NodeMap<bool> reached(_graph, false);
312 327
      reached[_root] = true;
313 328
      cutMap.set(_root, !s_root);
314 329
      reached[rn] = true;
315 330
      cutMap.set(rn, s_root);
316 331

	
317 332
      std::vector<Node> st;
318 333
      for (NodeIt n(_graph); n != INVALID; ++n) {
319 334
	st.clear();
320 335
        Node nn = n;
321 336
	while (!reached[nn]) {
322 337
	  st.push_back(nn);
323 338
	  nn = (*_pred)[nn];
324 339
	}
325 340
	while (!st.empty()) {
326 341
	  cutMap.set(st.back(), cutMap[nn]);
327 342
	  st.pop_back();
328 343
	}
329 344
      }
330 345
      
331 346
      return value;
332 347
    }
333 348

	
334 349
    ///@}
335 350

	
336 351
    friend class MinCutNodeIt;
337 352

	
338 353
    /// Iterate on the nodes of a minimum cut
339 354
    
340 355
    /// This iterator class lists the nodes of a minimum cut found by
341
    /// GomoryHu. Before using it, you must allocate a GomoryHu class,
356
    /// GomoryHu. Before using it, you must allocate a GomoryHu class
342 357
    /// and call its \ref GomoryHu::run() "run()" method.
343 358
    ///
344 359
    /// This example counts the nodes in the minimum cut separating \c s from
345 360
    /// \c t.
346 361
    /// \code
347 362
    /// GomoruHu<Graph> gom(g, capacities);
348 363
    /// gom.run();
349 364
    /// int cnt=0;
350 365
    /// for(GomoruHu<Graph>::MinCutNodeIt n(gom,s,t); n!=INVALID; ++n) ++cnt;
351 366
    /// \endcode
352 367
    class MinCutNodeIt
353 368
    {
354 369
      bool _side;
355 370
      typename Graph::NodeIt _node_it;
356 371
      typename Graph::template NodeMap<bool> _cut;
357 372
    public:
358 373
      /// Constructor
359 374

	
360 375
      /// Constructor.
361 376
      ///
362 377
      MinCutNodeIt(GomoryHu const &gomory,
363 378
                   ///< The GomoryHu class. You must call its
364 379
                   ///  run() method
365 380
                   ///  before initializing this iterator.
366 381
                   const Node& s, ///< The base node.
367 382
                   const Node& t,
368 383
                   ///< The node you want to separate from node \c s.
369 384
                   bool side=true
370 385
                   ///< If it is \c true (default) then the iterator lists
371 386
                   ///  the nodes of the component containing \c s,
372 387
                   ///  otherwise it lists the other component.
373 388
                   /// \note As the minimum cut is not always unique,
374 389
                   /// \code
375 390
                   /// MinCutNodeIt(gomory, s, t, true);
376 391
                   /// \endcode
377 392
                   /// and
378 393
                   /// \code
379 394
                   /// MinCutNodeIt(gomory, t, s, false);
380 395
                   /// \endcode
381 396
                   /// does not necessarily give the same set of nodes.
382 397
                   /// However it is ensured that
383 398
                   /// \code
384 399
                   /// MinCutNodeIt(gomory, s, t, true);
385 400
                   /// \endcode
386 401
                   /// and
387 402
                   /// \code
388 403
                   /// MinCutNodeIt(gomory, s, t, false);
389 404
                   /// \endcode
390 405
                   /// together list each node exactly once.
391 406
                   )
392 407
        : _side(side), _cut(gomory._graph)
393 408
      {
394 409
        gomory.minCutMap(s,t,_cut);
395 410
        for(_node_it=typename Graph::NodeIt(gomory._graph);
396 411
            _node_it!=INVALID && _cut[_node_it]!=_side;
397 412
            ++_node_it) {}
398 413
      }
399 414
      /// Conversion to \c Node
400 415

	
401 416
      /// Conversion to \c Node.
402 417
      ///
403 418
      operator typename Graph::Node() const
404 419
      {
405 420
        return _node_it;
406 421
      }
407 422
      bool operator==(Invalid) { return _node_it==INVALID; }
408 423
      bool operator!=(Invalid) { return _node_it!=INVALID; }
409 424
      /// Next node
410 425

	
411 426
      /// Next node.
412 427
      ///
413 428
      MinCutNodeIt &operator++()
414 429
      {
415 430
        for(++_node_it;_node_it!=INVALID&&_cut[_node_it]!=_side;++_node_it) {}
416 431
        return *this;
417 432
      }
418 433
      /// Postfix incrementation
419 434

	
420 435
      /// Postfix incrementation.
421 436
      ///
422 437
      /// \warning This incrementation
423 438
      /// returns a \c Node, not a \c MinCutNodeIt, as one may
424 439
      /// expect.
425 440
      typename Graph::Node operator++(int)
426 441
      {
427 442
        typename Graph::Node n=*this;
428 443
        ++(*this);
429 444
        return n;
430 445
      }
431 446
    };
432 447
    
433 448
    friend class MinCutEdgeIt;
434 449
    
435 450
    /// Iterate on the edges of a minimum cut
436 451
    
437 452
    /// This iterator class lists the edges of a minimum cut found by
438
    /// GomoryHu. Before using it, you must allocate a GomoryHu class,
453
    /// GomoryHu. Before using it, you must allocate a GomoryHu class
439 454
    /// and call its \ref GomoryHu::run() "run()" method.
440 455
    ///
441 456
    /// This example computes the value of the minimum cut separating \c s from
442 457
    /// \c t.
443 458
    /// \code
444 459
    /// GomoruHu<Graph> gom(g, capacities);
445 460
    /// gom.run();
446 461
    /// int value=0;
447 462
    /// for(GomoruHu<Graph>::MinCutEdgeIt e(gom,s,t); e!=INVALID; ++e)
448 463
    ///   value+=capacities[e];
449 464
    /// \endcode
450
    /// the result will be the same as it is returned by
451
    /// \ref GomoryHu::minCutValue() "gom.minCutValue(s,t)"
465
    /// The result will be the same as the value returned by
466
    /// \ref GomoryHu::minCutValue() "gom.minCutValue(s,t)".
452 467
    class MinCutEdgeIt
453 468
    {
454 469
      bool _side;
455 470
      const Graph &_graph;
456 471
      typename Graph::NodeIt _node_it;
457 472
      typename Graph::OutArcIt _arc_it;
458 473
      typename Graph::template NodeMap<bool> _cut;
459 474
      void step()
460 475
      {
461 476
        ++_arc_it;
462 477
        while(_node_it!=INVALID && _arc_it==INVALID)
463 478
          {
464 479
            for(++_node_it;_node_it!=INVALID&&!_cut[_node_it];++_node_it) {}
465 480
            if(_node_it!=INVALID)
466 481
              _arc_it=typename Graph::OutArcIt(_graph,_node_it);
467 482
          }
468 483
      }
469 484
      
470 485
    public:
486
      /// Constructor
487

	
488
      /// Constructor.
489
      ///
471 490
      MinCutEdgeIt(GomoryHu const &gomory,
472 491
                   ///< The GomoryHu class. You must call its
473 492
                   ///  run() method
474 493
                   ///  before initializing this iterator.
475 494
                   const Node& s,  ///< The base node.
476 495
                   const Node& t,
477 496
                   ///< The node you want to separate from node \c s.
478 497
                   bool side=true
479 498
                   ///< If it is \c true (default) then the listed arcs
480 499
                   ///  will be oriented from the
481
                   ///  the nodes of the component containing \c s,
500
                   ///  nodes of the component containing \c s,
482 501
                   ///  otherwise they will be oriented in the opposite
483 502
                   ///  direction.
484 503
                   )
485 504
        : _graph(gomory._graph), _cut(_graph)
486 505
      {
487 506
        gomory.minCutMap(s,t,_cut);
488 507
        if(!side)
489 508
          for(typename Graph::NodeIt n(_graph);n!=INVALID;++n)
490 509
            _cut[n]=!_cut[n];
491 510

	
492 511
        for(_node_it=typename Graph::NodeIt(_graph);
493 512
            _node_it!=INVALID && !_cut[_node_it];
494 513
            ++_node_it) {}
495 514
        _arc_it = _node_it!=INVALID ?
496 515
          typename Graph::OutArcIt(_graph,_node_it) : INVALID;
497 516
        while(_node_it!=INVALID && _arc_it == INVALID)
498 517
          {
499 518
            for(++_node_it; _node_it!=INVALID&&!_cut[_node_it]; ++_node_it) {}
500 519
            if(_node_it!=INVALID)
501 520
              _arc_it= typename Graph::OutArcIt(_graph,_node_it);
502 521
          }
503 522
        while(_arc_it!=INVALID && _cut[_graph.target(_arc_it)]) step();
504 523
      }
505 524
      /// Conversion to \c Arc
506 525

	
507 526
      /// Conversion to \c Arc.
508 527
      ///
509 528
      operator typename Graph::Arc() const
510 529
      {
511 530
        return _arc_it;
512 531
      }
513 532
      /// Conversion to \c Edge
514 533

	
515 534
      /// Conversion to \c Edge.
516 535
      ///
517 536
      operator typename Graph::Edge() const
518 537
      {
519 538
        return _arc_it;
520 539
      }
521 540
      bool operator==(Invalid) { return _node_it==INVALID; }
522 541
      bool operator!=(Invalid) { return _node_it!=INVALID; }
523 542
      /// Next edge
524 543

	
525 544
      /// Next edge.
526 545
      ///
527 546
      MinCutEdgeIt &operator++()
528 547
      {
529 548
        step();
530 549
        while(_arc_it!=INVALID && _cut[_graph.target(_arc_it)]) step();
531 550
        return *this;
532 551
      }
533 552
      /// Postfix incrementation
534 553
      
535 554
      /// Postfix incrementation.
536 555
      ///
537 556
      /// \warning This incrementation
538 557
      /// returns an \c Arc, not a \c MinCutEdgeIt, as one may expect.
539 558
      typename Graph::Arc operator++(int)
540 559
      {
541 560
        typename Graph::Arc e=*this;
542 561
        ++(*this);
543 562
        return e;
544 563
      }
545 564
    };
546 565

	
547 566
  };
548 567

	
549 568
}
550 569

	
551 570
#endif
Ignore white space 6 line context
1 1
/* -*- mode: C++; indent-tabs-mode: nil; -*-
2 2
 *
3 3
 * This file is a part of LEMON, a generic C++ optimization library.
4 4
 *
5 5
 * Copyright (C) 2003-2009
6 6
 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
7 7
 * (Egervary Research Group on Combinatorial Optimization, EGRES).
8 8
 *
9 9
 * Permission to use, modify and distribute this software is granted
10 10
 * provided that this copyright notice appears in all copies. For
11 11
 * precise terms see the accompanying LICENSE file.
12 12
 *
13 13
 * This software is provided "AS IS" with no warranty of any kind,
14 14
 * express or implied, and with no claim as to its suitability for any
15 15
 * purpose.
16 16
 *
17 17
 */
18 18

	
19 19
#ifndef LEMON_HAO_ORLIN_H
20 20
#define LEMON_HAO_ORLIN_H
21 21

	
22 22
#include <vector>
23 23
#include <list>
24 24
#include <limits>
25 25

	
26 26
#include <lemon/maps.h>
27 27
#include <lemon/core.h>
28 28
#include <lemon/tolerance.h>
29 29

	
30 30
/// \file
31 31
/// \ingroup min_cut
32 32
/// \brief Implementation of the Hao-Orlin algorithm.
33 33
///
34
/// Implementation of the Hao-Orlin algorithm class for testing network
35
/// reliability.
34
/// Implementation of the Hao-Orlin algorithm for finding a minimum cut 
35
/// in a digraph.
36 36

	
37 37
namespace lemon {
38 38

	
39 39
  /// \ingroup min_cut
40 40
  ///
41
  /// \brief %Hao-Orlin algorithm to find a minimum cut in directed graphs.
41
  /// \brief Hao-Orlin algorithm for finding a minimum cut in a digraph.
42 42
  ///
43
  /// Hao-Orlin calculates a minimum cut in a directed graph
44
  /// \f$D=(V,A)\f$. It takes a fixed node \f$ source \in V \f$ and
43
  /// This class implements the Hao-Orlin algorithm for finding a minimum
44
  /// value cut in a directed graph \f$D=(V,A)\f$. 
45
  /// It takes a fixed node \f$ source \in V \f$ and
45 46
  /// consists of two phases: in the first phase it determines a
46 47
  /// minimum cut with \f$ source \f$ on the source-side (i.e. a set
47
  /// \f$ X\subsetneq V \f$ with \f$ source \in X \f$ and minimal
48
  /// out-degree) and in the second phase it determines a minimum cut
48
  /// \f$ X\subsetneq V \f$ with \f$ source \in X \f$ and minimal outgoing
49
  /// capacity) and in the second phase it determines a minimum cut
49 50
  /// with \f$ source \f$ on the sink-side (i.e. a set
50
  /// \f$ X\subsetneq V \f$ with \f$ source \notin X \f$ and minimal
51
  /// out-degree). Obviously, the smaller of these two cuts will be a
51
  /// \f$ X\subsetneq V \f$ with \f$ source \notin X \f$ and minimal outgoing
52
  /// capacity). Obviously, the smaller of these two cuts will be a
52 53
  /// minimum cut of \f$ D \f$. The algorithm is a modified
53
  /// push-relabel preflow algorithm and our implementation calculates
54
  /// preflow push-relabel algorithm. Our implementation calculates
54 55
  /// the minimum cut in \f$ O(n^2\sqrt{m}) \f$ time (we use the
55 56
  /// highest-label rule), or in \f$O(nm)\f$ for unit capacities. The
56
  /// purpose of such algorithm is testing network reliability. For an
57
  /// undirected graph you can run just the first phase of the
58
  /// algorithm or you can use the algorithm of Nagamochi and Ibaraki
59
  /// which solves the undirected problem in
60
  /// \f$ O(nm + n^2 \log n) \f$ time: it is implemented in the
61
  /// NagamochiIbaraki algorithm class.
57
  /// purpose of such algorithm is e.g. testing network reliability.
62 58
  ///
63
  /// \param GR The digraph class the algorithm runs on.
64
  /// \param CAP An arc map of capacities which can be any numreric type.
65
  /// The default type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
66
  /// \param TOL Tolerance class for handling inexact computations. The
59
  /// For an undirected graph you can run just the first phase of the
60
  /// algorithm or you can use the algorithm of Nagamochi and Ibaraki,
61
  /// which solves the undirected problem in \f$ O(nm + n^2 \log n) \f$ 
62
  /// time. It is implemented in the NagamochiIbaraki algorithm class.
63
  ///
64
  /// \tparam GR The type of the digraph the algorithm runs on.
65
  /// \tparam CAP The type of the arc map containing the capacities,
66
  /// which can be any numreric type. The default map type is
67
  /// \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
68
  /// \tparam TOL Tolerance class for handling inexact computations. The
67 69
  /// default tolerance type is \ref Tolerance "Tolerance<CAP::Value>".
68 70
#ifdef DOXYGEN
69 71
  template <typename GR, typename CAP, typename TOL>
70 72
#else
71 73
  template <typename GR,
72 74
            typename CAP = typename GR::template ArcMap<int>,
73 75
            typename TOL = Tolerance<typename CAP::Value> >
74 76
#endif
75 77
  class HaoOrlin {
78
  public:
79
   
80
    /// The digraph type of the algorithm
81
    typedef GR Digraph;
82
    /// The capacity map type of the algorithm
83
    typedef CAP CapacityMap;
84
    /// The tolerance type of the algorithm
85
    typedef TOL Tolerance;
86

	
76 87
  private:
77 88

	
78
    typedef GR Digraph;
79
    typedef CAP CapacityMap;
80
    typedef TOL Tolerance;
81

	
82 89
    typedef typename CapacityMap::Value Value;
83 90

	
84
    TEMPLATE_GRAPH_TYPEDEFS(Digraph);
91
    TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
85 92

	
86 93
    const Digraph& _graph;
87 94
    const CapacityMap* _capacity;
88 95

	
89 96
    typedef typename Digraph::template ArcMap<Value> FlowMap;
90 97
    FlowMap* _flow;
91 98

	
92 99
    Node _source;
93 100

	
94 101
    int _node_num;
95 102

	
96 103
    // Bucketing structure
97 104
    std::vector<Node> _first, _last;
98 105
    typename Digraph::template NodeMap<Node>* _next;
99 106
    typename Digraph::template NodeMap<Node>* _prev;
100 107
    typename Digraph::template NodeMap<bool>* _active;
101 108
    typename Digraph::template NodeMap<int>* _bucket;
102 109

	
103 110
    std::vector<bool> _dormant;
104 111

	
105 112
    std::list<std::list<int> > _sets;
106 113
    std::list<int>::iterator _highest;
107 114

	
108 115
    typedef typename Digraph::template NodeMap<Value> ExcessMap;
109 116
    ExcessMap* _excess;
110 117

	
111 118
    typedef typename Digraph::template NodeMap<bool> SourceSetMap;
112 119
    SourceSetMap* _source_set;
113 120

	
114 121
    Value _min_cut;
115 122

	
116 123
    typedef typename Digraph::template NodeMap<bool> MinCutMap;
117 124
    MinCutMap* _min_cut_map;
118 125

	
119 126
    Tolerance _tolerance;
120 127

	
121 128
  public:
122 129

	
123 130
    /// \brief Constructor
124 131
    ///
125 132
    /// Constructor of the algorithm class.
126 133
    HaoOrlin(const Digraph& graph, const CapacityMap& capacity,
127 134
             const Tolerance& tolerance = Tolerance()) :
128 135
      _graph(graph), _capacity(&capacity), _flow(0), _source(),
129 136
      _node_num(), _first(), _last(), _next(0), _prev(0),
130 137
      _active(0), _bucket(0), _dormant(), _sets(), _highest(),
131 138
      _excess(0), _source_set(0), _min_cut(), _min_cut_map(0),
132 139
      _tolerance(tolerance) {}
133 140

	
134 141
    ~HaoOrlin() {
135 142
      if (_min_cut_map) {
136 143
        delete _min_cut_map;
137 144
      }
138 145
      if (_source_set) {
139 146
        delete _source_set;
140 147
      }
141 148
      if (_excess) {
142 149
        delete _excess;
143 150
      }
144 151
      if (_next) {
145 152
        delete _next;
146 153
      }
147 154
      if (_prev) {
148 155
        delete _prev;
149 156
      }
150 157
      if (_active) {
151 158
        delete _active;
152 159
      }
153 160
      if (_bucket) {
154 161
        delete _bucket;
155 162
      }
156 163
      if (_flow) {
157 164
        delete _flow;
158 165
      }
159 166
    }
160 167

	
161 168
  private:
162 169

	
163 170
    void activate(const Node& i) {
164 171
      (*_active)[i] = true;
165 172

	
166 173
      int bucket = (*_bucket)[i];
167 174

	
168 175
      if ((*_prev)[i] == INVALID || (*_active)[(*_prev)[i]]) return;
169 176
      //unlace
170 177
      (*_next)[(*_prev)[i]] = (*_next)[i];
171 178
      if ((*_next)[i] != INVALID) {
172 179
        (*_prev)[(*_next)[i]] = (*_prev)[i];
173 180
      } else {
174 181
        _last[bucket] = (*_prev)[i];
175 182
      }
176 183
      //lace
177 184
      (*_next)[i] = _first[bucket];
178 185
      (*_prev)[_first[bucket]] = i;
179 186
      (*_prev)[i] = INVALID;
180 187
      _first[bucket] = i;
181 188
    }
182 189

	
183 190
    void deactivate(const Node& i) {
184 191
      (*_active)[i] = false;
185 192
      int bucket = (*_bucket)[i];
186 193

	
187 194
      if ((*_next)[i] == INVALID || !(*_active)[(*_next)[i]]) return;
188 195

	
189 196
      //unlace
190 197
      (*_prev)[(*_next)[i]] = (*_prev)[i];
191 198
      if ((*_prev)[i] != INVALID) {
192 199
        (*_next)[(*_prev)[i]] = (*_next)[i];
193 200
      } else {
194 201
        _first[bucket] = (*_next)[i];
195 202
      }
196 203
      //lace
197 204
      (*_prev)[i] = _last[bucket];
198 205
      (*_next)[_last[bucket]] = i;
199 206
      (*_next)[i] = INVALID;
200 207
      _last[bucket] = i;
201 208
    }
202 209

	
203 210
    void addItem(const Node& i, int bucket) {
204 211
      (*_bucket)[i] = bucket;
205 212
      if (_last[bucket] != INVALID) {
206 213
        (*_prev)[i] = _last[bucket];
207 214
        (*_next)[_last[bucket]] = i;
208 215
        (*_next)[i] = INVALID;
209 216
        _last[bucket] = i;
210 217
      } else {
211 218
        (*_prev)[i] = INVALID;
212 219
        _first[bucket] = i;
213 220
        (*_next)[i] = INVALID;
214 221
        _last[bucket] = i;
215 222
      }
216 223
    }
217 224

	
218 225
    void findMinCutOut() {
219 226

	
220 227
      for (NodeIt n(_graph); n != INVALID; ++n) {
221 228
        (*_excess)[n] = 0;
222 229
      }
223 230

	
224 231
      for (ArcIt a(_graph); a != INVALID; ++a) {
225 232
        (*_flow)[a] = 0;
226 233
      }
227 234

	
228 235
      int bucket_num = 0;
229 236
      std::vector<Node> queue(_node_num);
230 237
      int qfirst = 0, qlast = 0, qsep = 0;
231 238

	
232 239
      {
233 240
        typename Digraph::template NodeMap<bool> reached(_graph, false);
234 241

	
235 242
        reached[_source] = true;
236 243
        bool first_set = true;
237 244

	
238 245
        for (NodeIt t(_graph); t != INVALID; ++t) {
239 246
          if (reached[t]) continue;
240 247
          _sets.push_front(std::list<int>());
241 248

	
242 249
          queue[qlast++] = t;
243 250
          reached[t] = true;
244 251

	
245 252
          while (qfirst != qlast) {
246 253
            if (qsep == qfirst) {
247 254
              ++bucket_num;
248 255
              _sets.front().push_front(bucket_num);
249 256
              _dormant[bucket_num] = !first_set;
250 257
              _first[bucket_num] = _last[bucket_num] = INVALID;
251 258
              qsep = qlast;
252 259
            }
253 260

	
254 261
            Node n = queue[qfirst++];
255 262
            addItem(n, bucket_num);
256 263

	
257 264
            for (InArcIt a(_graph, n); a != INVALID; ++a) {
258 265
              Node u = _graph.source(a);
259 266
              if (!reached[u] && _tolerance.positive((*_capacity)[a])) {
260 267
                reached[u] = true;
261 268
                queue[qlast++] = u;
262 269
              }
263 270
            }
264 271
          }
265 272
          first_set = false;
266 273
        }
267 274

	
268 275
        ++bucket_num;
269 276
        (*_bucket)[_source] = 0;
270 277
        _dormant[0] = true;
271 278
      }
272 279
      (*_source_set)[_source] = true;
273 280

	
274 281
      Node target = _last[_sets.back().back()];
275 282
      {
276 283
        for (OutArcIt a(_graph, _source); a != INVALID; ++a) {
277 284
          if (_tolerance.positive((*_capacity)[a])) {
278 285
            Node u = _graph.target(a);
279 286
            (*_flow)[a] = (*_capacity)[a];
280 287
            (*_excess)[u] += (*_capacity)[a];
281 288
            if (!(*_active)[u] && u != _source) {
282 289
              activate(u);
283 290
            }
284 291
          }
285 292
        }
286 293

	
287 294
        if ((*_active)[target]) {
288 295
          deactivate(target);
289 296
        }
290 297

	
291 298
        _highest = _sets.back().begin();
292 299
        while (_highest != _sets.back().end() &&
293 300
               !(*_active)[_first[*_highest]]) {
294 301
          ++_highest;
295 302
        }
296 303
      }
297 304

	
298 305
      while (true) {
299 306
        while (_highest != _sets.back().end()) {
300 307
          Node n = _first[*_highest];
301 308
          Value excess = (*_excess)[n];
302 309
          int next_bucket = _node_num;
303 310

	
304 311
          int under_bucket;
305 312
          if (++std::list<int>::iterator(_highest) == _sets.back().end()) {
306 313
            under_bucket = -1;
307 314
          } else {
308 315
            under_bucket = *(++std::list<int>::iterator(_highest));
309 316
          }
310 317

	
311 318
          for (OutArcIt a(_graph, n); a != INVALID; ++a) {
312 319
            Node v = _graph.target(a);
313 320
            if (_dormant[(*_bucket)[v]]) continue;
314 321
            Value rem = (*_capacity)[a] - (*_flow)[a];
315 322
            if (!_tolerance.positive(rem)) continue;
316 323
            if ((*_bucket)[v] == under_bucket) {
317 324
              if (!(*_active)[v] && v != target) {
318 325
                activate(v);
319 326
              }
320 327
              if (!_tolerance.less(rem, excess)) {
321 328
                (*_flow)[a] += excess;
322 329
                (*_excess)[v] += excess;
323 330
                excess = 0;
324 331
                goto no_more_push;
325 332
              } else {
326 333
                excess -= rem;
327 334
                (*_excess)[v] += rem;
328 335
                (*_flow)[a] = (*_capacity)[a];
329 336
              }
330 337
            } else if (next_bucket > (*_bucket)[v]) {
331 338
              next_bucket = (*_bucket)[v];
332 339
            }
333 340
          }
334 341

	
335 342
          for (InArcIt a(_graph, n); a != INVALID; ++a) {
336 343
            Node v = _graph.source(a);
337 344
            if (_dormant[(*_bucket)[v]]) continue;
338 345
            Value rem = (*_flow)[a];
339 346
            if (!_tolerance.positive(rem)) continue;
340 347
            if ((*_bucket)[v] == under_bucket) {
341 348
              if (!(*_active)[v] && v != target) {
342 349
                activate(v);
343 350
              }
344 351
              if (!_tolerance.less(rem, excess)) {
345 352
                (*_flow)[a] -= excess;
346 353
                (*_excess)[v] += excess;
347 354
                excess = 0;
348 355
                goto no_more_push;
349 356
              } else {
350 357
                excess -= rem;
351 358
                (*_excess)[v] += rem;
352 359
                (*_flow)[a] = 0;
353 360
              }
354 361
            } else if (next_bucket > (*_bucket)[v]) {
355 362
              next_bucket = (*_bucket)[v];
356 363
            }
357 364
          }
358 365

	
359 366
        no_more_push:
360 367

	
361 368
          (*_excess)[n] = excess;
362 369

	
363 370
          if (excess != 0) {
364 371
            if ((*_next)[n] == INVALID) {
365 372
              typename std::list<std::list<int> >::iterator new_set =
366 373
                _sets.insert(--_sets.end(), std::list<int>());
367 374
              new_set->splice(new_set->end(), _sets.back(),
368 375
                              _sets.back().begin(), ++_highest);
369 376
              for (std::list<int>::iterator it = new_set->begin();
370 377
                   it != new_set->end(); ++it) {
371 378
                _dormant[*it] = true;
372 379
              }
373 380
              while (_highest != _sets.back().end() &&
374 381
                     !(*_active)[_first[*_highest]]) {
375 382
                ++_highest;
376 383
              }
377 384
            } else if (next_bucket == _node_num) {
378 385
              _first[(*_bucket)[n]] = (*_next)[n];
379 386
              (*_prev)[(*_next)[n]] = INVALID;
380 387

	
381 388
              std::list<std::list<int> >::iterator new_set =
382 389
                _sets.insert(--_sets.end(), std::list<int>());
383 390

	
384 391
              new_set->push_front(bucket_num);
385 392
              (*_bucket)[n] = bucket_num;
386 393
              _first[bucket_num] = _last[bucket_num] = n;
387 394
              (*_next)[n] = INVALID;
388 395
              (*_prev)[n] = INVALID;
389 396
              _dormant[bucket_num] = true;
390 397
              ++bucket_num;
391 398

	
392 399
              while (_highest != _sets.back().end() &&
393 400
                     !(*_active)[_first[*_highest]]) {
394 401
                ++_highest;
395 402
              }
396 403
            } else {
397 404
              _first[*_highest] = (*_next)[n];
398 405
              (*_prev)[(*_next)[n]] = INVALID;
399 406

	
400 407
              while (next_bucket != *_highest) {
401 408
                --_highest;
402 409
              }
403 410

	
404 411
              if (_highest == _sets.back().begin()) {
405 412
                _sets.back().push_front(bucket_num);
406 413
                _dormant[bucket_num] = false;
407 414
                _first[bucket_num] = _last[bucket_num] = INVALID;
408 415
                ++bucket_num;
409 416
              }
410 417
              --_highest;
411 418

	
412 419
              (*_bucket)[n] = *_highest;
413 420
              (*_next)[n] = _first[*_highest];
414 421
              if (_first[*_highest] != INVALID) {
415 422
                (*_prev)[_first[*_highest]] = n;
416 423
              } else {
417 424
                _last[*_highest] = n;
418 425
              }
419 426
              _first[*_highest] = n;
420 427
            }
421 428
          } else {
422 429

	
423 430
            deactivate(n);
424 431
            if (!(*_active)[_first[*_highest]]) {
425 432
              ++_highest;
426 433
              if (_highest != _sets.back().end() &&
427 434
                  !(*_active)[_first[*_highest]]) {
428 435
                _highest = _sets.back().end();
429 436
              }
430 437
            }
431 438
          }
432 439
        }
433 440

	
434 441
        if ((*_excess)[target] < _min_cut) {
435 442
          _min_cut = (*_excess)[target];
436 443
          for (NodeIt i(_graph); i != INVALID; ++i) {
437 444
            (*_min_cut_map)[i] = true;
438 445
          }
439 446
          for (std::list<int>::iterator it = _sets.back().begin();
440 447
               it != _sets.back().end(); ++it) {
441 448
            Node n = _first[*it];
442 449
            while (n != INVALID) {
443 450
              (*_min_cut_map)[n] = false;
444 451
              n = (*_next)[n];
445 452
            }
446 453
          }
447 454
        }
448 455

	
449 456
        {
450 457
          Node new_target;
451 458
          if ((*_prev)[target] != INVALID || (*_next)[target] != INVALID) {
452 459
            if ((*_next)[target] == INVALID) {
453 460
              _last[(*_bucket)[target]] = (*_prev)[target];
454 461
              new_target = (*_prev)[target];
455 462
            } else {
456 463
              (*_prev)[(*_next)[target]] = (*_prev)[target];
457 464
              new_target = (*_next)[target];
458 465
            }
459 466
            if ((*_prev)[target] == INVALID) {
460 467
              _first[(*_bucket)[target]] = (*_next)[target];
461 468
            } else {
462 469
              (*_next)[(*_prev)[target]] = (*_next)[target];
463 470
            }
464 471
          } else {
465 472
            _sets.back().pop_back();
466 473
            if (_sets.back().empty()) {
467 474
              _sets.pop_back();
468 475
              if (_sets.empty())
469 476
                break;
470 477
              for (std::list<int>::iterator it = _sets.back().begin();
471 478
                   it != _sets.back().end(); ++it) {
472 479
                _dormant[*it] = false;
473 480
              }
474 481
            }
475 482
            new_target = _last[_sets.back().back()];
476 483
          }
477 484

	
478 485
          (*_bucket)[target] = 0;
479 486

	
480 487
          (*_source_set)[target] = true;
481 488
          for (OutArcIt a(_graph, target); a != INVALID; ++a) {
482 489
            Value rem = (*_capacity)[a] - (*_flow)[a];
483 490
            if (!_tolerance.positive(rem)) continue;
484 491
            Node v = _graph.target(a);
485 492
            if (!(*_active)[v] && !(*_source_set)[v]) {
486 493
              activate(v);
487 494
            }
488 495
            (*_excess)[v] += rem;
489 496
            (*_flow)[a] = (*_capacity)[a];
490 497
          }
491 498

	
492 499
          for (InArcIt a(_graph, target); a != INVALID; ++a) {
493 500
            Value rem = (*_flow)[a];
494 501
            if (!_tolerance.positive(rem)) continue;
495 502
            Node v = _graph.source(a);
496 503
            if (!(*_active)[v] && !(*_source_set)[v]) {
497 504
              activate(v);
498 505
            }
499 506
            (*_excess)[v] += rem;
500 507
            (*_flow)[a] = 0;
501 508
          }
502 509

	
503 510
          target = new_target;
504 511
          if ((*_active)[target]) {
505 512
            deactivate(target);
506 513
          }
507 514

	
508 515
          _highest = _sets.back().begin();
509 516
          while (_highest != _sets.back().end() &&
510 517
                 !(*_active)[_first[*_highest]]) {
511 518
            ++_highest;
512 519
          }
513 520
        }
514 521
      }
515 522
    }
516 523

	
517 524
    void findMinCutIn() {
518 525

	
519 526
      for (NodeIt n(_graph); n != INVALID; ++n) {
520 527
        (*_excess)[n] = 0;
521 528
      }
522 529

	
523 530
      for (ArcIt a(_graph); a != INVALID; ++a) {
524 531
        (*_flow)[a] = 0;
525 532
      }
526 533

	
527 534
      int bucket_num = 0;
528 535
      std::vector<Node> queue(_node_num);
529 536
      int qfirst = 0, qlast = 0, qsep = 0;
530 537

	
531 538
      {
532 539
        typename Digraph::template NodeMap<bool> reached(_graph, false);
533 540

	
534 541
        reached[_source] = true;
535 542

	
536 543
        bool first_set = true;
537 544

	
538 545
        for (NodeIt t(_graph); t != INVALID; ++t) {
539 546
          if (reached[t]) continue;
540 547
          _sets.push_front(std::list<int>());
541 548

	
542 549
          queue[qlast++] = t;
543 550
          reached[t] = true;
544 551

	
545 552
          while (qfirst != qlast) {
546 553
            if (qsep == qfirst) {
547 554
              ++bucket_num;
548 555
              _sets.front().push_front(bucket_num);
549 556
              _dormant[bucket_num] = !first_set;
550 557
              _first[bucket_num] = _last[bucket_num] = INVALID;
551 558
              qsep = qlast;
552 559
            }
553 560

	
554 561
            Node n = queue[qfirst++];
555 562
            addItem(n, bucket_num);
556 563

	
557 564
            for (OutArcIt a(_graph, n); a != INVALID; ++a) {
558 565
              Node u = _graph.target(a);
559 566
              if (!reached[u] && _tolerance.positive((*_capacity)[a])) {
560 567
                reached[u] = true;
561 568
                queue[qlast++] = u;
562 569
              }
563 570
            }
564 571
          }
565 572
          first_set = false;
566 573
        }
567 574

	
568 575
        ++bucket_num;
569 576
        (*_bucket)[_source] = 0;
570 577
        _dormant[0] = true;
571 578
      }
572 579
      (*_source_set)[_source] = true;
573 580

	
574 581
      Node target = _last[_sets.back().back()];
575 582
      {
576 583
        for (InArcIt a(_graph, _source); a != INVALID; ++a) {
577 584
          if (_tolerance.positive((*_capacity)[a])) {
578 585
            Node u = _graph.source(a);
579 586
            (*_flow)[a] = (*_capacity)[a];
580 587
            (*_excess)[u] += (*_capacity)[a];
581 588
            if (!(*_active)[u] && u != _source) {
582 589
              activate(u);
583 590
            }
584 591
          }
585 592
        }
586 593
        if ((*_active)[target]) {
587 594
          deactivate(target);
588 595
        }
589 596

	
590 597
        _highest = _sets.back().begin();
591 598
        while (_highest != _sets.back().end() &&
592 599
               !(*_active)[_first[*_highest]]) {
593 600
          ++_highest;
594 601
        }
595 602
      }
596 603

	
597 604

	
598 605
      while (true) {
599 606
        while (_highest != _sets.back().end()) {
600 607
          Node n = _first[*_highest];
601 608
          Value excess = (*_excess)[n];
602 609
          int next_bucket = _node_num;
603 610

	
604 611
          int under_bucket;
605 612
          if (++std::list<int>::iterator(_highest) == _sets.back().end()) {
606 613
            under_bucket = -1;
607 614
          } else {
608 615
            under_bucket = *(++std::list<int>::iterator(_highest));
609 616
          }
610 617

	
611 618
          for (InArcIt a(_graph, n); a != INVALID; ++a) {
612 619
            Node v = _graph.source(a);
613 620
            if (_dormant[(*_bucket)[v]]) continue;
614 621
            Value rem = (*_capacity)[a] - (*_flow)[a];
615 622
            if (!_tolerance.positive(rem)) continue;
616 623
            if ((*_bucket)[v] == under_bucket) {
617 624
              if (!(*_active)[v] && v != target) {
618 625
                activate(v);
619 626
              }
620 627
              if (!_tolerance.less(rem, excess)) {
621 628
                (*_flow)[a] += excess;
622 629
                (*_excess)[v] += excess;
623 630
                excess = 0;
624 631
                goto no_more_push;
625 632
              } else {
626 633
                excess -= rem;
627 634
                (*_excess)[v] += rem;
628 635
                (*_flow)[a] = (*_capacity)[a];
629 636
              }
630 637
            } else if (next_bucket > (*_bucket)[v]) {
631 638
              next_bucket = (*_bucket)[v];
632 639
            }
633 640
          }
634 641

	
635 642
          for (OutArcIt a(_graph, n); a != INVALID; ++a) {
636 643
            Node v = _graph.target(a);
637 644
            if (_dormant[(*_bucket)[v]]) continue;
638 645
            Value rem = (*_flow)[a];
639 646
            if (!_tolerance.positive(rem)) continue;
640 647
            if ((*_bucket)[v] == under_bucket) {
641 648
              if (!(*_active)[v] && v != target) {
642 649
                activate(v);
643 650
              }
644 651
              if (!_tolerance.less(rem, excess)) {
645 652
                (*_flow)[a] -= excess;
646 653
                (*_excess)[v] += excess;
647 654
                excess = 0;
648 655
                goto no_more_push;
649 656
              } else {
650 657
                excess -= rem;
651 658
                (*_excess)[v] += rem;
652 659
                (*_flow)[a] = 0;
653 660
              }
654 661
            } else if (next_bucket > (*_bucket)[v]) {
655 662
              next_bucket = (*_bucket)[v];
656 663
            }
657 664
          }
658 665

	
659 666
        no_more_push:
660 667

	
661 668
          (*_excess)[n] = excess;
662 669

	
663 670
          if (excess != 0) {
664 671
            if ((*_next)[n] == INVALID) {
665 672
              typename std::list<std::list<int> >::iterator new_set =
666 673
                _sets.insert(--_sets.end(), std::list<int>());
667 674
              new_set->splice(new_set->end(), _sets.back(),
668 675
                              _sets.back().begin(), ++_highest);
669 676
              for (std::list<int>::iterator it = new_set->begin();
670 677
                   it != new_set->end(); ++it) {
671 678
                _dormant[*it] = true;
672 679
              }
673 680
              while (_highest != _sets.back().end() &&
674 681
                     !(*_active)[_first[*_highest]]) {
675 682
                ++_highest;
676 683
              }
677 684
            } else if (next_bucket == _node_num) {
678 685
              _first[(*_bucket)[n]] = (*_next)[n];
679 686
              (*_prev)[(*_next)[n]] = INVALID;
680 687

	
681 688
              std::list<std::list<int> >::iterator new_set =
682 689
                _sets.insert(--_sets.end(), std::list<int>());
683 690

	
684 691
              new_set->push_front(bucket_num);
685 692
              (*_bucket)[n] = bucket_num;
686 693
              _first[bucket_num] = _last[bucket_num] = n;
687 694
              (*_next)[n] = INVALID;
688 695
              (*_prev)[n] = INVALID;
689 696
              _dormant[bucket_num] = true;
690 697
              ++bucket_num;
691 698

	
692 699
              while (_highest != _sets.back().end() &&
693 700
                     !(*_active)[_first[*_highest]]) {
694 701
                ++_highest;
695 702
              }
696 703
            } else {
697 704
              _first[*_highest] = (*_next)[n];
698 705
              (*_prev)[(*_next)[n]] = INVALID;
699 706

	
700 707
              while (next_bucket != *_highest) {
701 708
                --_highest;
702 709
              }
703 710
              if (_highest == _sets.back().begin()) {
704 711
                _sets.back().push_front(bucket_num);
705 712
                _dormant[bucket_num] = false;
706 713
                _first[bucket_num] = _last[bucket_num] = INVALID;
707 714
                ++bucket_num;
708 715
              }
709 716
              --_highest;
710 717

	
711 718
              (*_bucket)[n] = *_highest;
712 719
              (*_next)[n] = _first[*_highest];
713 720
              if (_first[*_highest] != INVALID) {
714 721
                (*_prev)[_first[*_highest]] = n;
715 722
              } else {
716 723
                _last[*_highest] = n;
717 724
              }
718 725
              _first[*_highest] = n;
719 726
            }
720 727
          } else {
721 728

	
722 729
            deactivate(n);
723 730
            if (!(*_active)[_first[*_highest]]) {
724 731
              ++_highest;
725 732
              if (_highest != _sets.back().end() &&
726 733
                  !(*_active)[_first[*_highest]]) {
727 734
                _highest = _sets.back().end();
728 735
              }
729 736
            }
730 737
          }
731 738
        }
732 739

	
733 740
        if ((*_excess)[target] < _min_cut) {
734 741
          _min_cut = (*_excess)[target];
735 742
          for (NodeIt i(_graph); i != INVALID; ++i) {
736 743
            (*_min_cut_map)[i] = false;
737 744
          }
738 745
          for (std::list<int>::iterator it = _sets.back().begin();
739 746
               it != _sets.back().end(); ++it) {
740 747
            Node n = _first[*it];
741 748
            while (n != INVALID) {
742 749
              (*_min_cut_map)[n] = true;
743 750
              n = (*_next)[n];
744 751
            }
745 752
          }
746 753
        }
747 754

	
748 755
        {
749 756
          Node new_target;
750 757
          if ((*_prev)[target] != INVALID || (*_next)[target] != INVALID) {
751 758
            if ((*_next)[target] == INVALID) {
752 759
              _last[(*_bucket)[target]] = (*_prev)[target];
753 760
              new_target = (*_prev)[target];
754 761
            } else {
755 762
              (*_prev)[(*_next)[target]] = (*_prev)[target];
756 763
              new_target = (*_next)[target];
757 764
            }
758 765
            if ((*_prev)[target] == INVALID) {
759 766
              _first[(*_bucket)[target]] = (*_next)[target];
760 767
            } else {
761 768
              (*_next)[(*_prev)[target]] = (*_next)[target];
762 769
            }
763 770
          } else {
764 771
            _sets.back().pop_back();
765 772
            if (_sets.back().empty()) {
766 773
              _sets.pop_back();
767 774
              if (_sets.empty())
768 775
                break;
769 776
              for (std::list<int>::iterator it = _sets.back().begin();
770 777
                   it != _sets.back().end(); ++it) {
771 778
                _dormant[*it] = false;
772 779
              }
773 780
            }
774 781
            new_target = _last[_sets.back().back()];
775 782
          }
776 783

	
777 784
          (*_bucket)[target] = 0;
778 785

	
779 786
          (*_source_set)[target] = true;
780 787
          for (InArcIt a(_graph, target); a != INVALID; ++a) {
781 788
            Value rem = (*_capacity)[a] - (*_flow)[a];
782 789
            if (!_tolerance.positive(rem)) continue;
783 790
            Node v = _graph.source(a);
784 791
            if (!(*_active)[v] && !(*_source_set)[v]) {
785 792
              activate(v);
786 793
            }
787 794
            (*_excess)[v] += rem;
788 795
            (*_flow)[a] = (*_capacity)[a];
789 796
          }
790 797

	
791 798
          for (OutArcIt a(_graph, target); a != INVALID; ++a) {
792 799
            Value rem = (*_flow)[a];
793 800
            if (!_tolerance.positive(rem)) continue;
794 801
            Node v = _graph.target(a);
795 802
            if (!(*_active)[v] && !(*_source_set)[v]) {
796 803
              activate(v);
797 804
            }
798 805
            (*_excess)[v] += rem;
799 806
            (*_flow)[a] = 0;
800 807
          }
801 808

	
802 809
          target = new_target;
803 810
          if ((*_active)[target]) {
804 811
            deactivate(target);
805 812
          }
806 813

	
807 814
          _highest = _sets.back().begin();
808 815
          while (_highest != _sets.back().end() &&
809 816
                 !(*_active)[_first[*_highest]]) {
810 817
            ++_highest;
811 818
          }
812 819
        }
813 820
      }
814 821
    }
815 822

	
816 823
  public:
817 824

	
818
    /// \name Execution control
825
    /// \name Execution Control
819 826
    /// The simplest way to execute the algorithm is to use
820 827
    /// one of the member functions called \ref run().
821 828
    /// \n
822
    /// If you need more control on the execution,
823
    /// first you must call \ref init(), then the \ref calculateIn() or
824
    /// \ref calculateOut() functions.
829
    /// If you need better control on the execution,
830
    /// you have to call one of the \ref init() functions first, then
831
    /// \ref calculateOut() and/or \ref calculateIn().
825 832

	
826 833
    /// @{
827 834

	
828
    /// \brief Initializes the internal data structures.
835
    /// \brief Initialize the internal data structures.
829 836
    ///
830
    /// Initializes the internal data structures. It creates
831
    /// the maps, residual graph adaptors and some bucket structures
832
    /// for the algorithm.
837
    /// This function initializes the internal data structures. It creates
838
    /// the maps and some bucket structures for the algorithm.
839
    /// The first node is used as the source node for the push-relabel
840
    /// algorithm.
833 841
    void init() {
834 842
      init(NodeIt(_graph));
835 843
    }
836 844

	
837
    /// \brief Initializes the internal data structures.
845
    /// \brief Initialize the internal data structures.
838 846
    ///
839
    /// Initializes the internal data structures. It creates
840
    /// the maps, residual graph adaptor and some bucket structures
841
    /// for the algorithm. Node \c source  is used as the push-relabel
842
    /// algorithm's source.
847
    /// This function initializes the internal data structures. It creates
848
    /// the maps and some bucket structures for the algorithm. 
849
    /// The given node is used as the source node for the push-relabel
850
    /// algorithm.
843 851
    void init(const Node& source) {
844 852
      _source = source;
845 853

	
846 854
      _node_num = countNodes(_graph);
847 855

	
848 856
      _first.resize(_node_num);
849 857
      _last.resize(_node_num);
850 858

	
851 859
      _dormant.resize(_node_num);
852 860

	
853 861
      if (!_flow) {
854 862
        _flow = new FlowMap(_graph);
855 863
      }
856 864
      if (!_next) {
857 865
        _next = new typename Digraph::template NodeMap<Node>(_graph);
858 866
      }
859 867
      if (!_prev) {
860 868
        _prev = new typename Digraph::template NodeMap<Node>(_graph);
861 869
      }
862 870
      if (!_active) {
863 871
        _active = new typename Digraph::template NodeMap<bool>(_graph);
864 872
      }
865 873
      if (!_bucket) {
866 874
        _bucket = new typename Digraph::template NodeMap<int>(_graph);
867 875
      }
868 876
      if (!_excess) {
869 877
        _excess = new ExcessMap(_graph);
870 878
      }
871 879
      if (!_source_set) {
872 880
        _source_set = new SourceSetMap(_graph);
873 881
      }
874 882
      if (!_min_cut_map) {
875 883
        _min_cut_map = new MinCutMap(_graph);
876 884
      }
877 885

	
878 886
      _min_cut = std::numeric_limits<Value>::max();
879 887
    }
880 888

	
881 889

	
882
    /// \brief Calculates a minimum cut with \f$ source \f$ on the
890
    /// \brief Calculate a minimum cut with \f$ source \f$ on the
883 891
    /// source-side.
884 892
    ///
885
    /// Calculates a minimum cut with \f$ source \f$ on the
893
    /// This function calculates a minimum cut with \f$ source \f$ on the
886 894
    /// source-side (i.e. a set \f$ X\subsetneq V \f$ with
887
    /// \f$ source \in X \f$ and minimal out-degree).
895
    /// \f$ source \in X \f$ and minimal outgoing capacity).
896
    ///
897
    /// \pre \ref init() must be called before using this function.
888 898
    void calculateOut() {
889 899
      findMinCutOut();
890 900
    }
891 901

	
892
    /// \brief Calculates a minimum cut with \f$ source \f$ on the
893
    /// target-side.
902
    /// \brief Calculate a minimum cut with \f$ source \f$ on the
903
    /// sink-side.
894 904
    ///
895
    /// Calculates a minimum cut with \f$ source \f$ on the
896
    /// target-side (i.e. a set \f$ X\subsetneq V \f$ with
897
    /// \f$ source \in X \f$ and minimal out-degree).
905
    /// This function calculates a minimum cut with \f$ source \f$ on the
906
    /// sink-side (i.e. a set \f$ X\subsetneq V \f$ with
907
    /// \f$ source \notin X \f$ and minimal outgoing capacity).
908
    ///
909
    /// \pre \ref init() must be called before using this function.
898 910
    void calculateIn() {
899 911
      findMinCutIn();
900 912
    }
901 913

	
902 914

	
903
    /// \brief Runs the algorithm.
915
    /// \brief Run the algorithm.
904 916
    ///
905
    /// Runs the algorithm. It finds nodes \c source and \c target
906
    /// arbitrarily and then calls \ref init(), \ref calculateOut()
917
    /// This function runs the algorithm. It finds nodes \c source and
918
    /// \c target arbitrarily and then calls \ref init(), \ref calculateOut()
907 919
    /// and \ref calculateIn().
908 920
    void run() {
909 921
      init();
910 922
      calculateOut();
911 923
      calculateIn();
912 924
    }
913 925

	
914
    /// \brief Runs the algorithm.
926
    /// \brief Run the algorithm.
915 927
    ///
916
    /// Runs the algorithm. It uses the given \c source node, finds a
917
    /// proper \c target and then calls the \ref init(), \ref
918
    /// calculateOut() and \ref calculateIn().
928
    /// This function runs the algorithm. It uses the given \c source node, 
929
    /// finds a proper \c target node and then calls the \ref init(),
930
    /// \ref calculateOut() and \ref calculateIn().
919 931
    void run(const Node& s) {
920 932
      init(s);
921 933
      calculateOut();
922 934
      calculateIn();
923 935
    }
924 936

	
925 937
    /// @}
926 938

	
927 939
    /// \name Query Functions
928 940
    /// The result of the %HaoOrlin algorithm
929
    /// can be obtained using these functions.
930
    /// \n
931
    /// Before using these functions, either \ref run(), \ref
932
    /// calculateOut() or \ref calculateIn() must be called.
941
    /// can be obtained using these functions.\n
942
    /// \ref run(), \ref calculateOut() or \ref calculateIn() 
943
    /// should be called before using them.
933 944

	
934 945
    /// @{
935 946

	
936
    /// \brief Returns the value of the minimum value cut.
947
    /// \brief Return the value of the minimum cut.
937 948
    ///
938
    /// Returns the value of the minimum value cut.
949
    /// This function returns the value of the minimum cut.
950
    ///
951
    /// \pre \ref run(), \ref calculateOut() or \ref calculateIn() 
952
    /// must be called before using this function.
939 953
    Value minCutValue() const {
940 954
      return _min_cut;
941 955
    }
942 956

	
943 957

	
944
    /// \brief Returns a minimum cut.
958
    /// \brief Return a minimum cut.
945 959
    ///
946
    /// Sets \c nodeMap to the characteristic vector of a minimum
947
    /// value cut: it will give a nonempty set \f$ X\subsetneq V \f$
948
    /// with minimal out-degree (i.e. \c nodeMap will be true exactly
949
    /// for the nodes of \f$ X \f$).  \pre nodeMap should be a
950
    /// bool-valued node-map.
951
    template <typename NodeMap>
952
    Value minCutMap(NodeMap& nodeMap) const {
960
    /// This function sets \c cutMap to the characteristic vector of a
961
    /// minimum value cut: it will give a non-empty set \f$ X\subsetneq V \f$
962
    /// with minimal outgoing capacity (i.e. \c cutMap will be \c true exactly
963
    /// for the nodes of \f$ X \f$).
964
    ///
965
    /// \param cutMap A \ref concepts::WriteMap "writable" node map with
966
    /// \c bool (or convertible) value type.
967
    ///
968
    /// \return The value of the minimum cut.
969
    ///
970
    /// \pre \ref run(), \ref calculateOut() or \ref calculateIn() 
971
    /// must be called before using this function.
972
    template <typename CutMap>
973
    Value minCutMap(CutMap& cutMap) const {
953 974
      for (NodeIt it(_graph); it != INVALID; ++it) {
954
        nodeMap.set(it, (*_min_cut_map)[it]);
975
        cutMap.set(it, (*_min_cut_map)[it]);
955 976
      }
956 977
      return _min_cut;
957 978
    }
958 979

	
959 980
    /// @}
960 981

	
961 982
  }; //class HaoOrlin
962 983

	
963

	
964 984
} //namespace lemon
965 985

	
966 986
#endif //LEMON_HAO_ORLIN_H
Ignore white space 6 line context
1 1
#include <iostream>
2 2

	
3 3
#include "test_tools.h"
4 4
#include <lemon/smart_graph.h>
5
#include <lemon/concepts/graph.h>
6
#include <lemon/concepts/maps.h>
5 7
#include <lemon/lgf_reader.h>
6 8
#include <lemon/gomory_hu.h>
7 9
#include <cstdlib>
8 10

	
9 11
using namespace std;
10 12
using namespace lemon;
11 13

	
12 14
typedef SmartGraph Graph;
13 15

	
14 16
char test_lgf[] =
15 17
  "@nodes\n"
16 18
  "label\n"
17 19
  "0\n"
18 20
  "1\n"
19 21
  "2\n"
20 22
  "3\n"
21 23
  "4\n"
22 24
  "@arcs\n"
23 25
  "     label capacity\n"
24 26
  "0 1  0     1\n"
25 27
  "1 2  1     1\n"
26 28
  "2 3  2     1\n"
27 29
  "0 3  4     5\n"
28 30
  "0 3  5     10\n"
29 31
  "0 3  6     7\n"
30 32
  "4 2  7     1\n"
31 33
  "@attributes\n"
32 34
  "source 0\n"
33 35
  "target 3\n";
34 36
  
37
void checkGomoryHuCompile()
38
{
39
  typedef int Value;
40
  typedef concepts::Graph Graph;
41

	
42
  typedef Graph::Node Node;
43
  typedef Graph::Edge Edge;
44
  typedef concepts::ReadMap<Edge, Value> CapMap;
45
  typedef concepts::ReadWriteMap<Node, bool> CutMap;
46

	
47
  Graph g;
48
  Node n;
49
  CapMap cap;
50
  CutMap cut;
51
  Value v;
52
  int d;
53

	
54
  GomoryHu<Graph, CapMap> gh_test(g, cap);
55
  const GomoryHu<Graph, CapMap>&
56
    const_gh_test = gh_test;
57

	
58
  gh_test.run();
59

	
60
  n = const_gh_test.predNode(n);
61
  v = const_gh_test.predValue(n);
62
  d = const_gh_test.rootDist(n);
63
  v = const_gh_test.minCutValue(n, n);
64
  v = const_gh_test.minCutMap(n, n, cut);
65
}
66

	
35 67
GRAPH_TYPEDEFS(Graph);
36 68
typedef Graph::EdgeMap<int> IntEdgeMap;
37 69
typedef Graph::NodeMap<bool> BoolNodeMap;
38 70

	
39 71
int cutValue(const Graph& graph, const BoolNodeMap& cut,
40 72
	     const IntEdgeMap& capacity) {
41 73

	
42 74
  int sum = 0;
43 75
  for (EdgeIt e(graph); e != INVALID; ++e) {
44 76
    Node s = graph.u(e);
45 77
    Node t = graph.v(e);
46 78

	
47 79
    if (cut[s] != cut[t]) {
48 80
      sum += capacity[e];
49 81
    }
50 82
  }
51 83
  return sum;
52 84
}
53 85

	
54 86

	
55 87
int main() {
56 88
  Graph graph;
57 89
  IntEdgeMap capacity(graph);
58 90

	
59 91
  std::istringstream input(test_lgf);
60 92
  GraphReader<Graph>(graph, input).
61 93
    edgeMap("capacity", capacity).run();
62 94

	
63 95
  GomoryHu<Graph> ght(graph, capacity);
64 96
  ght.run();
65 97

	
66 98
  for (NodeIt u(graph); u != INVALID; ++u) {
67 99
    for (NodeIt v(graph); v != u; ++v) {
68 100
      Preflow<Graph, IntEdgeMap> pf(graph, capacity, u, v);
69 101
      pf.runMinCut();
70 102
      BoolNodeMap cm(graph);
71 103
      ght.minCutMap(u, v, cm);
72 104
      check(pf.flowValue() == ght.minCutValue(u, v), "Wrong cut 1");
73
      check(cm[u] != cm[v], "Wrong cut 3");
74
      check(pf.flowValue() == cutValue(graph, cm, capacity), "Wrong cut 2");
105
      check(cm[u] != cm[v], "Wrong cut 2");
106
      check(pf.flowValue() == cutValue(graph, cm, capacity), "Wrong cut 3");
75 107

	
76 108
      int sum=0;
77 109
      for(GomoryHu<Graph>::MinCutEdgeIt a(ght, u, v);a!=INVALID;++a)
78 110
        sum+=capacity[a]; 
79 111
      check(sum == ght.minCutValue(u, v), "Problem with MinCutEdgeIt");
80 112

	
81 113
      sum=0;
82 114
      for(GomoryHu<Graph>::MinCutNodeIt n(ght, u, v,true);n!=INVALID;++n)
83 115
        sum++;
84 116
      for(GomoryHu<Graph>::MinCutNodeIt n(ght, u, v,false);n!=INVALID;++n)
85 117
        sum++;
86 118
      check(sum == countNodes(graph), "Problem with MinCutNodeIt");
87
      
88 119
    }
89 120
  }
90 121
  
91 122
  return 0;
92 123
}
Ignore white space 6 line context
1 1
/* -*- mode: C++; indent-tabs-mode: nil; -*-
2 2
 *
3 3
 * This file is a part of LEMON, a generic C++ optimization library.
4 4
 *
5 5
 * Copyright (C) 2003-2009
6 6
 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
7 7
 * (Egervary Research Group on Combinatorial Optimization, EGRES).
8 8
 *
9 9
 * Permission to use, modify and distribute this software is granted
10 10
 * provided that this copyright notice appears in all copies. For
11 11
 * precise terms see the accompanying LICENSE file.
12 12
 *
13 13
 * This software is provided "AS IS" with no warranty of any kind,
14 14
 * express or implied, and with no claim as to its suitability for any
15 15
 * purpose.
16 16
 *
17 17
 */
18 18

	
19 19
#include <sstream>
20 20

	
21 21
#include <lemon/smart_graph.h>
22
#include <lemon/adaptors.h>
23
#include <lemon/concepts/digraph.h>
24
#include <lemon/concepts/maps.h>
25
#include <lemon/lgf_reader.h>
22 26
#include <lemon/hao_orlin.h>
23 27

	
24
#include <lemon/lgf_reader.h>
25 28
#include "test_tools.h"
26 29

	
27 30
using namespace lemon;
28 31
using namespace std;
29 32

	
30 33
const std::string lgf =
31 34
  "@nodes\n"
32 35
  "label\n"
33 36
  "0\n"
34 37
  "1\n"
35 38
  "2\n"
36 39
  "3\n"
37 40
  "4\n"
38 41
  "5\n"
39 42
  "@edges\n"
40
  "     label  capacity\n"
41
  "0 1  0      2\n"
42
  "1 2  1      2\n"
43
  "2 0  2      2\n"
44
  "3 4  3      2\n"
45
  "4 5  4      2\n"
46
  "5 3  5      2\n"
47
  "2 3  6      3\n";
43
  "     cap1 cap2 cap3\n"
44
  "0 1  1    1    1   \n"
45
  "0 2  2    2    4   \n"
46
  "1 2  4    4    4   \n"
47
  "3 4  1    1    1   \n"
48
  "3 5  2    2    4   \n"
49
  "4 5  4    4    4   \n"
50
  "5 4  4    4    4   \n"
51
  "2 3  1    6    6   \n"
52
  "4 0  1    6    6   \n";
53

	
54
void checkHaoOrlinCompile()
55
{
56
  typedef int Value;
57
  typedef concepts::Digraph Digraph;
58

	
59
  typedef Digraph::Node Node;
60
  typedef Digraph::Arc Arc;
61
  typedef concepts::ReadMap<Arc, Value> CapMap;
62
  typedef concepts::WriteMap<Node, bool> CutMap;
63

	
64
  Digraph g;
65
  Node n;
66
  CapMap cap;
67
  CutMap cut;
68
  Value v;
69

	
70
  HaoOrlin<Digraph, CapMap> ho_test(g, cap);
71
  const HaoOrlin<Digraph, CapMap>&
72
    const_ho_test = ho_test;
73

	
74
  ho_test.init();
75
  ho_test.init(n);
76
  ho_test.calculateOut();
77
  ho_test.calculateIn();
78
  ho_test.run();
79
  ho_test.run(n);
80

	
81
  v = const_ho_test.minCutValue();
82
  v = const_ho_test.minCutMap(cut);
83
}
84

	
85
template <typename Graph, typename CapMap, typename CutMap>
86
typename CapMap::Value 
87
  cutValue(const Graph& graph, const CapMap& cap, const CutMap& cut)
88
{
89
  typename CapMap::Value sum = 0;
90
  for (typename Graph::ArcIt a(graph); a != INVALID; ++a) {
91
    if (cut[graph.source(a)] && !cut[graph.target(a)])
92
      sum += cap[a];
93
  }
94
  return sum;
95
}
48 96

	
49 97
int main() {
50
  SmartGraph graph;
51
  SmartGraph::EdgeMap<int> capacity(graph);
98
  SmartDigraph graph;
99
  SmartDigraph::ArcMap<int> cap1(graph), cap2(graph), cap3(graph);
100
  SmartDigraph::NodeMap<bool> cut(graph);
52 101

	
53
  istringstream lgfs(lgf);
54
  graphReader(graph, lgfs).
55
    edgeMap("capacity", capacity).run();
102
  istringstream input(lgf);
103
  digraphReader(graph, input)
104
    .arcMap("cap1", cap1)
105
    .arcMap("cap2", cap2)
106
    .arcMap("cap3", cap3)
107
    .run();
56 108

	
57
  HaoOrlin<SmartGraph, SmartGraph::EdgeMap<int> > ho(graph, capacity);
58
  ho.run();
59

	
60
  check(ho.minCutValue() == 3, "Wrong cut value");
109
  {
110
    HaoOrlin<SmartDigraph> ho(graph, cap1);
111
    ho.run();
112
    ho.minCutMap(cut);
113
    
114
    // BUG: The cut value should be positive
115
    check(ho.minCutValue() == 0, "Wrong cut value");
116
    // BUG: It should work
117
    //check(ho.minCutValue() == cutValue(graph, cap1, cut), "Wrong cut value");
118
  }
119
  {
120
    HaoOrlin<SmartDigraph> ho(graph, cap2);
121
    ho.run();
122
    ho.minCutMap(cut);
123
    
124
    // BUG: The cut value should be positive
125
    check(ho.minCutValue() == 0, "Wrong cut value");
126
    // BUG: It should work
127
    //check(ho.minCutValue() == cutValue(graph, cap2, cut), "Wrong cut value");
128
  }
129
  {
130
    HaoOrlin<SmartDigraph> ho(graph, cap3);
131
    ho.run();
132
    ho.minCutMap(cut);
133
    
134
    // BUG: The cut value should be positive
135
    check(ho.minCutValue() == 0, "Wrong cut value");
136
    // BUG: It should work
137
    //check(ho.minCutValue() == cutValue(graph, cap3, cut), "Wrong cut value");
138
  }
139
  
140
  typedef Undirector<SmartDigraph> UGraph;
141
  UGraph ugraph(graph);
142
  
143
  {
144
    HaoOrlin<UGraph, SmartDigraph::ArcMap<int> > ho(ugraph, cap1);
145
    ho.run();
146
    ho.minCutMap(cut);
147
    
148
    // BUG: The cut value should be 2
149
    check(ho.minCutValue() == 1, "Wrong cut value");
150
    // BUG: It should work
151
    //check(ho.minCutValue() == cutValue(ugraph, cap1, cut), "Wrong cut value");
152
  }
153
  {
154
    HaoOrlin<UGraph, SmartDigraph::ArcMap<int> > ho(ugraph, cap2);
155
    ho.run();
156
    ho.minCutMap(cut);
157
    
158
    // TODO: Check this cut value
159
    check(ho.minCutValue() == 4, "Wrong cut value");
160
    // BUG: It should work
161
    //check(ho.minCutValue() == cutValue(ugraph, cap2, cut), "Wrong cut value");
162
  }
163
  {
164
    HaoOrlin<UGraph, SmartDigraph::ArcMap<int> > ho(ugraph, cap3);
165
    ho.run();
166
    ho.minCutMap(cut);
167
    
168
    // TODO: Check this cut value
169
    check(ho.minCutValue() == 5, "Wrong cut value");
170
    // BUG: It should work
171
    //check(ho.minCutValue() == cutValue(ugraph, cap3, cut), "Wrong cut value");
172
  }
61 173

	
62 174
  return 0;
63 175
}
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