0
4
0
64
45
89
69
130
18
... | ... |
@@ -41,26 +41,24 @@ |
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 |
... | ... |
@@ -69,11 +67,11 @@ |
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 |
|
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 |
|
... | ... |
@@ -116,9 +114,9 @@ |
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), |
... | ... |
@@ -129,9 +127,9 @@ |
129 | 127 |
|
130 | 128 |
|
131 | 129 |
/// \brief Destructor |
132 | 130 |
/// |
133 |
/// Destructor |
|
131 |
/// Destructor. |
|
134 | 132 |
~GomoryHu() { |
135 | 133 |
destroyStructures(); |
136 | 134 |
} |
137 | 135 |
|
... | ... |
@@ -214,45 +212,55 @@ |
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() |
|
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 |
|
|
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 |
|
... | ... |
@@ -273,18 +281,25 @@ |
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 |
|
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, ///< |
|
297 |
Value minCutMap(const Node& s, ///< |
|
280 | 298 |
const Node& t, |
281 |
///< |
|
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; |
... | ... |
@@ -337,9 +352,9 @@ |
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. |
... | ... |
@@ -434,9 +449,9 @@ |
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. |
... | ... |
@@ -446,10 +461,10 @@ |
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; |
... | ... |
@@ -467,8 +482,12 @@ |
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. |
... | ... |
@@ -477,9 +496,9 @@ |
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 |
/// |
|
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) |
... | ... |
@@ -30,41 +30,43 @@ |
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 |
|
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$. The algorithm is a modified |
53 |
/// push-relabel |
|
54 |
/// preflow push-relabel algorithm. Our implementation calculates |
|
54 | 55 |
/// the minimum cut in \f$ 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 |
... | ... |
@@ -72,17 +74,22 @@ |
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 |
|
|
91 |
TEMPLATE_DIGRAPH_TYPEDEFS(Digraph); |
|
85 | 92 |
|
86 | 93 |
const Digraph& _graph; |
87 | 94 |
const CapacityMap* _capacity; |
88 | 95 |
|
... | ... |
@@ -814,33 +821,34 @@ |
814 | 821 |
} |
815 | 822 |
|
816 | 823 |
public: |
817 | 824 |
|
818 |
/// \name Execution |
|
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 |
/// |
|
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 |
|
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 |
/// |
|
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 |
|
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); |
... | ... |
@@ -878,45 +886,49 @@ |
878 | 886 |
_min_cut = std::numeric_limits<Value>::max(); |
879 | 887 |
} |
880 | 888 |
|
881 | 889 |
|
882 |
/// \brief |
|
890 |
/// \brief Calculate a minimum cut with \f$ source \f$ on the |
|
883 | 891 |
/// source-side. |
884 | 892 |
/// |
885 |
/// |
|
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 |
|
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 \ |
|
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 |
|
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 |
|
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 |
/// |
|
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(); |
... | ... |
@@ -925,42 +937,50 @@ |
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 |
|
947 |
/// \brief Return the value of the minimum cut. |
|
937 | 948 |
/// |
938 |
/// |
|
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 |
|
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$). \pre nodeMap should be a |
|
950 |
/// bool-valued node-map. |
|
951 |
template <typename NodeMap> |
|
952 |
|
|
960 |
/// This function sets \c cutMap to the characteristic vector of a |
|
961 |
/// minimum value cut: it will give a non-empty set \f$ 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 |
|
|
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 |
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 |
|
... | ... |
@@ -31,8 +33,38 @@ |
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 |
|
... | ... |
@@ -69,10 +101,10 @@ |
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]; |
... | ... |
@@ -83,9 +115,8 @@ |
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; |
... | ... |
@@ -18,11 +18,14 @@ |
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; |
... | ... |
@@ -36,28 +39,137 @@ |
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 |
|
|
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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