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alpar (Alpar Juttner)
alpar@cs.elte.hu
Doc improvements in HaoOrlin (#398)
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/* -*- mode: C++; indent-tabs-mode: nil; -*-
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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) 2003-2010
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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
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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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#ifndef LEMON_HAO_ORLIN_H
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#define LEMON_HAO_ORLIN_H
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#include <vector>
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#include <list>
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#include <limits>
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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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/// \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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namespace lemon {
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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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    /// 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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  private:
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    typedef typename CapacityMap::Value Value;
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    TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
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    const Digraph& _graph;
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    const CapacityMap* _capacity;
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    typedef typename Digraph::template ArcMap<Value> FlowMap;
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    FlowMap* _flow;
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    Node _source;
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    int _node_num;
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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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    typename Digraph::template NodeMap<Node>* _prev;
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    typename Digraph::template NodeMap<bool>* _active;
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    typename Digraph::template NodeMap<int>* _bucket;
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    std::vector<bool> _dormant;
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    std::list<std::list<int> > _sets;
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    std::list<int>::iterator _highest;
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    typedef typename Digraph::template NodeMap<Value> ExcessMap;
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    ExcessMap* _excess;
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    typedef typename Digraph::template NodeMap<bool> SourceSetMap;
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    SourceSetMap* _source_set;
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    Value _min_cut;
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    typedef typename Digraph::template NodeMap<bool> MinCutMap;
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    MinCutMap* _min_cut_map;
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    Tolerance _tolerance;
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  public:
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    /// \brief Constructor
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    ///
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    /// Constructor of the algorithm class.
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    HaoOrlin(const Digraph& graph, const CapacityMap& capacity,
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             const Tolerance& tolerance = Tolerance()) :
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      _graph(graph), _capacity(&capacity), _flow(0), _source(),
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      _node_num(), _first(), _last(), _next(0), _prev(0),
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      _active(0), _bucket(0), _dormant(), _sets(), _highest(),
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      _excess(0), _source_set(0), _min_cut(), _min_cut_map(0),
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      _tolerance(tolerance) {}
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    ~HaoOrlin() {
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      if (_min_cut_map) {
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        delete _min_cut_map;
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      }
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      if (_source_set) {
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        delete _source_set;
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      }
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      if (_excess) {
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        delete _excess;
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      }
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      if (_next) {
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        delete _next;
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      }
... ...
@@ -819,187 +819,197 @@
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            if (!_tolerance.positive(rem)) continue;
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            Node v = _graph.target(a);
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            if (!(*_active)[v] && !(*_source_set)[v]) {
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              activate(v);
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            }
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            (*_excess)[v] += rem;
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            (*_flow)[a] = 0;
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          }
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          target = new_target;
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          if ((*_active)[target]) {
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            deactivate(target);
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          }
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          _highest = _sets.back().begin();
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          while (_highest != _sets.back().end() &&
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                 !(*_active)[_first[*_highest]]) {
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            ++_highest;
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          }
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        }
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      }
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    }
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  public:
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    /// \name Execution Control
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    /// The simplest way to execute the algorithm is to use
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    /// one of the member functions called \ref run().
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    /// \n
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    /// If you need better control on the execution,
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    /// you have to call one of the \ref init() functions first, then
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    /// \ref calculateOut() and/or \ref calculateIn().
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    /// @{
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    /// \brief Initialize the internal data structures.
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    ///
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    /// This function initializes the internal data structures. It creates
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    /// the maps and some bucket structures for the algorithm.
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    /// The first node is used as the source node for the push-relabel
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    /// algorithm.
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    void init() {
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      init(NodeIt(_graph));
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    }
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    /// \brief Initialize the internal data structures.
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    ///
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    /// This function initializes the internal data structures. It creates
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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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      _node_num = countNodes(_graph);
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      _first.resize(_node_num);
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      _last.resize(_node_num);
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      _dormant.resize(_node_num);
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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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      _min_cut = std::numeric_limits<Value>::max();
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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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    /// \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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    /// \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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    /// \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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    /// \ref calculateOut() and \ref calculateIn().
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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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    /// \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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    /// \brief Return the value of the minimum cut.
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    ///
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    /// This function returns the value of the minimum cut.
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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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    /// \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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    /// with minimal outgoing capacity (i.e. \c cutMap will be \c true exactly
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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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  }; //class HaoOrlin
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} //namespace lemon
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#endif //LEMON_HAO_ORLIN_H
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