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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 |
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* 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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*/ |
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|
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#ifndef LEMON_HAO_ORLIN_H |
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#define LEMON_HAO_ORLIN_H |
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|
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#include <vector> |
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#include <list> |
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#include <limits> |
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|
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#include <lemon/maps.h> |
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#include <lemon/core.h> |
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#include <lemon/tolerance.h> |
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|
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/// \file |
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/// \ingroup min_cut |
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/// \brief Implementation of the Hao-Orlin algorithm. |
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/// |
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/// Implementation of the Hao-Orlin algorithm for finding a minimum cut |
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/// in a digraph. |
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|
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namespace lemon {
|
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|
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/// \ingroup min_cut |
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/// |
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/// \brief Hao-Orlin algorithm for finding a minimum cut in a digraph. |
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/// |
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/// This class implements the Hao-Orlin algorithm for finding a minimum |
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/// value cut in a directed graph \f$D=(V,A)\f$. |
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/// It takes a fixed node \f$ source \in V \f$ and |
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/// consists of two phases: in the first phase it determines a |
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/// minimum cut with \f$ source \f$ on the source-side (i.e. a set |
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/// \f$ X\subsetneq V \f$ with \f$ source \in X \f$ and minimal outgoing |
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/// capacity) and in the second phase it determines a minimum cut |
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/// with \f$ source \f$ on the sink-side (i.e. a set |
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/// \f$ X\subsetneq V \f$ with \f$ source \notin X \f$ and minimal outgoing |
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/// capacity). Obviously, the smaller of these two cuts will be a |
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/// minimum cut of \f$ D \f$. The algorithm is a modified |
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/// preflow push-relabel algorithm. Our implementation calculates |
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/// the minimum cut in \f$ O(n^2\sqrt{m}) \f$ time (we use the
|
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/// highest-label rule), or in \f$O(nm)\f$ for unit capacities. The |
|
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/// purpose of such algorithm is e.g. testing network reliability. |
|
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/// highest-label rule), or in \f$O(nm)\f$ for unit capacities. A notable |
|
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/// use of this algorithm is testing network reliability. |
|
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/// |
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/// For an undirected graph you can run just the first phase of the |
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/// algorithm or you can use the algorithm of Nagamochi and Ibaraki, |
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/// which solves the undirected problem in \f$ O(nm + n^2 \log n) \f$ |
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/// time. It is implemented in the NagamochiIbaraki algorithm class. |
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/// |
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/// \tparam GR The type of the digraph the algorithm runs on. |
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/// \tparam CAP The type of the arc map containing the capacities, |
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/// which can be any numreric type. The default map type is |
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/// \ref concepts::Digraph::ArcMap "GR::ArcMap<int>". |
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/// \tparam TOL Tolerance class for handling inexact computations. The |
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/// default tolerance type is \ref Tolerance "Tolerance<CAP::Value>". |
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#ifdef DOXYGEN |
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template <typename GR, typename CAP, typename TOL> |
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#else |
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template <typename GR, |
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typename CAP = typename GR::template ArcMap<int>, |
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typename TOL = Tolerance<typename CAP::Value> > |
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#endif |
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class HaoOrlin {
|
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public: |
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|
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/// The digraph type of the algorithm |
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typedef GR Digraph; |
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/// The capacity map type of the algorithm |
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typedef CAP CapacityMap; |
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/// The tolerance type of the algorithm |
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typedef TOL Tolerance; |
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|
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private: |
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|
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typedef typename CapacityMap::Value Value; |
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|
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TEMPLATE_DIGRAPH_TYPEDEFS(Digraph); |
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|
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const Digraph& _graph; |
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const CapacityMap* _capacity; |
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|
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typedef typename Digraph::template ArcMap<Value> FlowMap; |
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FlowMap* _flow; |
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|
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Node _source; |
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|
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int _node_num; |
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|
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// Bucketing structure |
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std::vector<Node> _first, _last; |
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typename Digraph::template NodeMap<Node>* _next; |
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/// the maps and some bucket structures for the algorithm. |
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/// The given node is used as the source node for the push-relabel |
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/// algorithm. |
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void init(const Node& source) {
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_source = source; |
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|
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_node_num = countNodes(_graph); |
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|
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_first.resize(_node_num); |
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_last.resize(_node_num); |
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|
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_dormant.resize(_node_num); |
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|
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if (!_flow) {
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_flow = new FlowMap(_graph); |
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} |
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if (!_next) {
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_next = new typename Digraph::template NodeMap<Node>(_graph); |
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} |
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if (!_prev) {
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_prev = new typename Digraph::template NodeMap<Node>(_graph); |
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} |
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if (!_active) {
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_active = new typename Digraph::template NodeMap<bool>(_graph); |
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} |
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if (!_bucket) {
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_bucket = new typename Digraph::template NodeMap<int>(_graph); |
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} |
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if (!_excess) {
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_excess = new ExcessMap(_graph); |
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} |
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if (!_source_set) {
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_source_set = new SourceSetMap(_graph); |
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} |
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if (!_min_cut_map) {
|
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_min_cut_map = new MinCutMap(_graph); |
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} |
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|
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_min_cut = std::numeric_limits<Value>::max(); |
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} |
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|
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|
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/// \brief Calculate a minimum cut with \f$ source \f$ on the |
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/// source-side. |
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/// |
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/// This function calculates a minimum cut with \f$ source \f$ on the |
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/// source-side (i.e. a set \f$ X\subsetneq V \f$ with |
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/// \f$ source \in X \f$ and minimal outgoing capacity). |
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/// It updates the stored cut if (and only if) the newly found one |
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/// is better. |
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/// |
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/// \pre \ref init() must be called before using this function. |
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void calculateOut() {
|
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findMinCutOut(); |
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} |
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|
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/// \brief Calculate a minimum cut with \f$ source \f$ on the |
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/// sink-side. |
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/// |
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/// This function calculates a minimum cut with \f$ source \f$ on the |
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/// sink-side (i.e. a set \f$ X\subsetneq V \f$ with |
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/// \f$ source \notin X \f$ and minimal outgoing capacity). |
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/// It updates the stored cut if (and only if) the newly found one |
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/// is better. |
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/// |
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/// \pre \ref init() must be called before using this function. |
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void calculateIn() {
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findMinCutIn(); |
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} |
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|
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|
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/// \brief Run the algorithm. |
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/// |
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/// This function runs the algorithm. It finds nodes \c source and |
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/// \c target arbitrarily and then calls \ref init(), \ref calculateOut() |
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/// This function runs the algorithm. It chooses source node, |
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/// then calls \ref init(), \ref calculateOut() |
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/// and \ref calculateIn(). |
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void run() {
|
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init(); |
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calculateOut(); |
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calculateIn(); |
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} |
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|
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/// \brief Run the algorithm. |
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/// |
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/// This function runs the algorithm. It uses the given \c source node, |
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/// finds a proper \c target node and then calls the \ref init(), |
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/// |
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/// This function runs the algorithm. It calls \ref init(), |
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/// \ref calculateOut() and \ref calculateIn() with the given |
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/// source node. |
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void run(const Node& s) {
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init(s); |
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calculateOut(); |
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calculateIn(); |
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} |
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|
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/// @} |
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|
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/// \name Query Functions |
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/// The result of the %HaoOrlin algorithm |
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/// can be obtained using these functions.\n |
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/// \ref run(), \ref calculateOut() or \ref calculateIn() |
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/// should be called before using them. |
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|
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/// @{
|
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|
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/// \brief Return the value of the minimum cut. |
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/// |
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/// This function returns the value of the |
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/// This function returns the value of the best cut found by the |
|
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/// previously called \ref run(), \ref calculateOut() or \ref |
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/// calculateIn(). |
|
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/// |
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/// \pre \ref run(), \ref calculateOut() or \ref calculateIn() |
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/// must be called before using this function. |
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Value minCutValue() const {
|
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return _min_cut; |
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} |
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|
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|
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/// \brief Return a minimum cut. |
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/// |
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/// This function sets \c cutMap to the characteristic vector of a |
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/// minimum value cut: it will give a non-empty set \f$ X\subsetneq V \f$ |
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/// |
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/// This function gives the best cut found by the |
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/// previously called \ref run(), \ref calculateOut() or \ref |
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/// calculateIn(). |
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/// |
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/// It sets \c cutMap to the characteristic vector of the found |
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/// minimum value cut - a non-empty set \f$ X\subsetneq V \f$ |
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/// of minimum outgoing capacity (i.e. \c cutMap will be \c true exactly |
|
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/// for the nodes of \f$ X \f$). |
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/// |
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/// \param cutMap A \ref concepts::WriteMap "writable" node map with |
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/// \c bool (or convertible) value type. |
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/// |
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/// \return The value of the minimum cut. |
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/// |
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/// \pre \ref run(), \ref calculateOut() or \ref calculateIn() |
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/// must be called before using this function. |
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template <typename CutMap> |
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Value minCutMap(CutMap& cutMap) const {
|
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for (NodeIt it(_graph); it != INVALID; ++it) {
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cutMap.set(it, (*_min_cut_map)[it]); |
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} |
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return _min_cut; |
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} |
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|
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/// @} |
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|
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}; //class HaoOrlin |
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|
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} //namespace lemon |
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|
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#endif //LEMON_HAO_ORLIN_H |
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