Location: LEMON/LEMON-main/lemon/preflow.h

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kpeter (Peter Kovacs)
Implement the scaling Price Refinement heuristic in CostScaling (#417) instead of Early Termination. These two heuristics are similar, but the newer one is faster and not only makes it possible to skip some epsilon phases, but it can improve the performance of the other phases, as well.
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/* -*- mode: C++; indent-tabs-mode: nil; -*-
*
* This file is a part of LEMON, a generic C++ optimization library.
*
* Copyright (C) 2003-2010
* Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
* (Egervary Research Group on Combinatorial Optimization, EGRES).
*
* Permission to use, modify and distribute this software is granted
* provided that this copyright notice appears in all copies. For
* precise terms see the accompanying LICENSE file.
*
* This software is provided "AS IS" with no warranty of any kind,
* express or implied, and with no claim as to its suitability for any
* purpose.
*
*/
#ifndef LEMON_PREFLOW_H
#define LEMON_PREFLOW_H
#include <lemon/tolerance.h>
#include <lemon/elevator.h>
/// \file
/// \ingroup max_flow
/// \brief Implementation of the preflow algorithm.
namespace lemon {
/// \brief Default traits class of Preflow class.
///
/// Default traits class of Preflow class.
/// \tparam GR Digraph type.
/// \tparam CAP Capacity map type.
template <typename GR, typename CAP>
struct PreflowDefaultTraits {
/// \brief The type of the digraph the algorithm runs on.
typedef GR Digraph;
/// \brief The type of the map that stores the arc capacities.
///
/// The type of the map that stores the arc capacities.
/// It must meet the \ref concepts::ReadMap "ReadMap" concept.
typedef CAP CapacityMap;
/// \brief The type of the flow values.
typedef typename CapacityMap::Value Value;
/// \brief The type of the map that stores the flow values.
///
/// The type of the map that stores the flow values.
/// It must meet the \ref concepts::ReadWriteMap "ReadWriteMap" concept.
#ifdef DOXYGEN
typedef GR::ArcMap<Value> FlowMap;
#else
typedef typename Digraph::template ArcMap<Value> FlowMap;
#endif
/// \brief Instantiates a FlowMap.
///
/// This function instantiates a \ref FlowMap.
/// \param digraph The digraph for which we would like to define
/// the flow map.
static FlowMap* createFlowMap(const Digraph& digraph) {
return new FlowMap(digraph);
}
/// \brief The elevator type used by Preflow algorithm.
///
/// The elevator type used by Preflow algorithm.
///
/// \sa Elevator, LinkedElevator
#ifdef DOXYGEN
typedef lemon::Elevator<GR, GR::Node> Elevator;
#else
typedef lemon::Elevator<Digraph, typename Digraph::Node> Elevator;
#endif
/// \brief Instantiates an Elevator.
///
/// This function instantiates an \ref Elevator.
/// \param digraph The digraph for which we would like to define
/// the elevator.
/// \param max_level The maximum level of the elevator.
static Elevator* createElevator(const Digraph& digraph, int max_level) {
return new Elevator(digraph, max_level);
}
/// \brief The tolerance used by the algorithm
///
/// The tolerance used by the algorithm to handle inexact computation.
typedef lemon::Tolerance<Value> Tolerance;
};
/// \ingroup max_flow
///
/// \brief %Preflow algorithm class.
///
/// This class provides an implementation of Goldberg-Tarjan's \e preflow
/// \e push-relabel algorithm producing a \ref max_flow
/// "flow of maximum value" in a digraph \ref clrs01algorithms,
/// \ref amo93networkflows, \ref goldberg88newapproach.
/// The preflow algorithms are the fastest known maximum
/// flow algorithms. The current implementation uses a mixture of the
/// \e "highest label" and the \e "bound decrease" heuristics.
/// The worst case time complexity of the algorithm is \f$O(n^2\sqrt{e})\f$.
///
/// The algorithm consists of two phases. After the first phase
/// the maximum flow value and the minimum cut is obtained. The
/// second phase constructs a feasible maximum flow on each arc.
///
/// \warning This implementation cannot handle infinite or very large
/// capacities (e.g. the maximum value of \c CAP::Value).
///
/// \tparam GR The type of the digraph the algorithm runs on.
/// \tparam CAP The type of the capacity map. The default map
/// type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
/// \tparam TR The traits class that defines various types used by the
/// algorithm. By default, it is \ref PreflowDefaultTraits
/// "PreflowDefaultTraits<GR, CAP>".
/// In most cases, this parameter should not be set directly,
/// consider to use the named template parameters instead.
#ifdef DOXYGEN
template <typename GR, typename CAP, typename TR>
#else
template <typename GR,
typename CAP = typename GR::template ArcMap<int>,
typename TR = PreflowDefaultTraits<GR, CAP> >
#endif
class Preflow {
public:
///The \ref PreflowDefaultTraits "traits class" of the algorithm.
typedef TR Traits;
///The type of the digraph the algorithm runs on.
typedef typename Traits::Digraph Digraph;
///The type of the capacity map.
typedef typename Traits::CapacityMap CapacityMap;
///The type of the flow values.
typedef typename Traits::Value Value;
///The type of the flow map.
typedef typename Traits::FlowMap FlowMap;
///The type of the elevator.
typedef typename Traits::Elevator Elevator;
///The type of the tolerance.
typedef typename Traits::Tolerance Tolerance;
private:
TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
const Digraph& _graph;
const CapacityMap* _capacity;
int _node_num;
Node _source, _target;
FlowMap* _flow;
bool _local_flow;
Elevator* _level;
bool _local_level;
typedef typename Digraph::template NodeMap<Value> ExcessMap;
ExcessMap* _excess;
Tolerance _tolerance;
bool _phase;
void createStructures() {
_node_num = countNodes(_graph);
if (!_flow) {
_flow = Traits::createFlowMap(_graph);
_local_flow = true;
}
if (!_level) {
_level = Traits::createElevator(_graph, _node_num);
_local_level = true;
}
if (!_excess) {
_excess = new ExcessMap(_graph);
}
}
void destroyStructures() {
if (_local_flow) {
delete _flow;
}
if (_local_level) {
delete _level;
}
if (_excess) {
delete _excess;
}
}
public:
typedef Preflow Create;
///\name Named Template Parameters
///@{
template <typename T>
struct SetFlowMapTraits : public Traits {
typedef T FlowMap;
static FlowMap *createFlowMap(const Digraph&) {
LEMON_ASSERT(false, "FlowMap is not initialized");
return 0; // ignore warnings
}
};
/// \brief \ref named-templ-param "Named parameter" for setting
/// FlowMap type
///
/// \ref named-templ-param "Named parameter" for setting FlowMap
/// type.
template <typename T>
struct SetFlowMap
: public Preflow<Digraph, CapacityMap, SetFlowMapTraits<T> > {
typedef Preflow<Digraph, CapacityMap,
SetFlowMapTraits<T> > Create;
};
template <typename T>
struct SetElevatorTraits : public Traits {
typedef T Elevator;
static Elevator *createElevator(const Digraph&, int) {
LEMON_ASSERT(false, "Elevator is not initialized");
return 0; // ignore warnings
}
};
/// \brief \ref named-templ-param "Named parameter" for setting
/// Elevator type
///
/// \ref named-templ-param "Named parameter" for setting Elevator
/// type. If this named parameter is used, then an external
/// elevator object must be passed to the algorithm using the
/// \ref elevator(Elevator&) "elevator()" function before calling
/// \ref run() or \ref init().
/// \sa SetStandardElevator
template <typename T>
struct SetElevator
: public Preflow<Digraph, CapacityMap, SetElevatorTraits<T> > {
typedef Preflow<Digraph, CapacityMap,
SetElevatorTraits<T> > Create;
};
template <typename T>
struct SetStandardElevatorTraits : public Traits {
typedef T Elevator;
static Elevator *createElevator(const Digraph& digraph, int max_level) {
return new Elevator(digraph, max_level);
}
};
/// \brief \ref named-templ-param "Named parameter" for setting
/// Elevator type with automatic allocation
///
/// \ref named-templ-param "Named parameter" for setting Elevator
/// type with automatic allocation.
/// The Elevator should have standard constructor interface to be
/// able to automatically created by the algorithm (i.e. the
/// digraph and the maximum level should be passed to it).
/// However, an external elevator object could also be passed to the
/// algorithm with the \ref elevator(Elevator&) "elevator()" function
/// before calling \ref run() or \ref init().
/// \sa SetElevator
template <typename T>
struct SetStandardElevator
: public Preflow<Digraph, CapacityMap,
SetStandardElevatorTraits<T> > {
typedef Preflow<Digraph, CapacityMap,
SetStandardElevatorTraits<T> > Create;
};
/// @}
protected:
Preflow() {}
public:
/// \brief The constructor of the class.
///
/// The constructor of the class.
/// \param digraph The digraph the algorithm runs on.
/// \param capacity The capacity of the arcs.
/// \param source The source node.
/// \param target The target node.
Preflow(const Digraph& digraph, const CapacityMap& capacity,
Node source, Node target)
: _graph(digraph), _capacity(&capacity),
_node_num(0), _source(source), _target(target),
_flow(0), _local_flow(false),
_level(0), _local_level(false),
_excess(0), _tolerance(), _phase() {}
/// \brief Destructor.
///
/// Destructor.
~Preflow() {
destroyStructures();
}
/// \brief Sets the capacity map.
///
/// Sets the capacity map.
/// \return <tt>(*this)</tt>
Preflow& capacityMap(const CapacityMap& map) {
_capacity = &map;
return *this;
}
/// \brief Sets the flow map.
///
/// Sets the flow map.
/// If you don't use this function before calling \ref run() or
/// \ref init(), an instance will be allocated automatically.
/// The destructor deallocates this automatically allocated map,
/// of course.
/// \return <tt>(*this)</tt>
Preflow& flowMap(FlowMap& map) {
if (_local_flow) {
delete _flow;
_local_flow = false;
}
_flow = &map;
return *this;
}
/// \brief Sets the source node.
///
/// Sets the source node.
/// \return <tt>(*this)</tt>
Preflow& source(const Node& node) {
_source = node;
return *this;
}
/// \brief Sets the target node.
///
/// Sets the target node.
/// \return <tt>(*this)</tt>
Preflow& target(const Node& node) {
_target = node;
return *this;
}
/// \brief Sets the elevator used by algorithm.
///
/// Sets the elevator used by algorithm.
/// If you don't use this function before calling \ref run() or
/// \ref init(), an instance will be allocated automatically.
/// The destructor deallocates this automatically allocated elevator,
/// of course.
/// \return <tt>(*this)</tt>
Preflow& elevator(Elevator& elevator) {
if (_local_level) {
delete _level;
_local_level = false;
}
_level = &elevator;
return *this;
}
/// \brief Returns a const reference to the elevator.
///
/// Returns a const reference to the elevator.
///
/// \pre Either \ref run() or \ref init() must be called before
/// using this function.
const Elevator& elevator() const {
return *_level;
}
/// \brief Sets the tolerance used by the algorithm.
///
/// Sets the tolerance object used by the algorithm.
/// \return <tt>(*this)</tt>
Preflow& tolerance(const Tolerance& tolerance) {
_tolerance = tolerance;
return *this;
}
/// \brief Returns a const reference to the tolerance.
///
/// Returns a const reference to the tolerance object used by
/// the algorithm.
const Tolerance& tolerance() const {
return _tolerance;
}
/// \name Execution Control
/// The simplest way to execute the preflow algorithm is to use
/// \ref run() or \ref runMinCut().\n
/// If you need better control on the initial solution or the execution,
/// you have to call one of the \ref init() functions first, then
/// \ref startFirstPhase() and if you need it \ref startSecondPhase().
///@{
/// \brief Initializes the internal data structures.
///
/// Initializes the internal data structures and sets the initial
/// flow to zero on each arc.
void init() {
createStructures();
_phase = true;
for (NodeIt n(_graph); n != INVALID; ++n) {
(*_excess)[n] = 0;
}
for (ArcIt e(_graph); e != INVALID; ++e) {
_flow->set(e, 0);
}
typename Digraph::template NodeMap<bool> reached(_graph, false);
_level->initStart();
_level->initAddItem(_target);
std::vector<Node> queue;
reached[_source] = true;
queue.push_back(_target);
reached[_target] = true;
while (!queue.empty()) {
_level->initNewLevel();
std::vector<Node> nqueue;
for (int i = 0; i < int(queue.size()); ++i) {
Node n = queue[i];
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Node u = _graph.source(e);
if (!reached[u] && _tolerance.positive((*_capacity)[e])) {
reached[u] = true;
_level->initAddItem(u);
nqueue.push_back(u);
}
}
}
queue.swap(nqueue);
}
_level->initFinish();
for (OutArcIt e(_graph, _source); e != INVALID; ++e) {
if (_tolerance.positive((*_capacity)[e])) {
Node u = _graph.target(e);
if ((*_level)[u] == _level->maxLevel()) continue;
_flow->set(e, (*_capacity)[e]);
(*_excess)[u] += (*_capacity)[e];
if (u != _target && !_level->active(u)) {
_level->activate(u);
}
}
}
}
/// \brief Initializes the internal data structures using the
/// given flow map.
///
/// Initializes the internal data structures and sets the initial
/// flow to the given \c flowMap. The \c flowMap should contain a
/// flow or at least a preflow, i.e. at each node excluding the
/// source node the incoming flow should greater or equal to the
/// outgoing flow.
/// \return \c false if the given \c flowMap is not a preflow.
template <typename FlowMap>
bool init(const FlowMap& flowMap) {
createStructures();
for (ArcIt e(_graph); e != INVALID; ++e) {
_flow->set(e, flowMap[e]);
}
for (NodeIt n(_graph); n != INVALID; ++n) {
Value excess = 0;
for (InArcIt e(_graph, n); e != INVALID; ++e) {
excess += (*_flow)[e];
}
for (OutArcIt e(_graph, n); e != INVALID; ++e) {
excess -= (*_flow)[e];
}
if (excess < 0 && n != _source) return false;
(*_excess)[n] = excess;
}
typename Digraph::template NodeMap<bool> reached(_graph, false);
_level->initStart();
_level->initAddItem(_target);
std::vector<Node> queue;
reached[_source] = true;
queue.push_back(_target);
reached[_target] = true;
while (!queue.empty()) {
_level->initNewLevel();
std::vector<Node> nqueue;
for (int i = 0; i < int(queue.size()); ++i) {
Node n = queue[i];
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Node u = _graph.source(e);
if (!reached[u] &&
_tolerance.positive((*_capacity)[e] - (*_flow)[e])) {
reached[u] = true;
_level->initAddItem(u);
nqueue.push_back(u);
}
}
for (OutArcIt e(_graph, n); e != INVALID; ++e) {
Node v = _graph.target(e);
if (!reached[v] && _tolerance.positive((*_flow)[e])) {
reached[v] = true;
_level->initAddItem(v);
nqueue.push_back(v);
}
}
}
queue.swap(nqueue);
}
_level->initFinish();
for (OutArcIt e(_graph, _source); e != INVALID; ++e) {
Value rem = (*_capacity)[e] - (*_flow)[e];
if (_tolerance.positive(rem)) {
Node u = _graph.target(e);
if ((*_level)[u] == _level->maxLevel()) continue;
_flow->set(e, (*_capacity)[e]);
(*_excess)[u] += rem;
}
}
for (InArcIt e(_graph, _source); e != INVALID; ++e) {
Value rem = (*_flow)[e];
if (_tolerance.positive(rem)) {
Node v = _graph.source(e);
if ((*_level)[v] == _level->maxLevel()) continue;
_flow->set(e, 0);
(*_excess)[v] += rem;
}
}
for (NodeIt n(_graph); n != INVALID; ++n)
if(n!=_source && n!=_target && _tolerance.positive((*_excess)[n]))
_level->activate(n);
return true;
}
/// \brief Starts the first phase of the preflow algorithm.
///
/// The preflow algorithm consists of two phases, this method runs
/// the first phase. After the first phase the maximum flow value
/// and a minimum value cut can already be computed, although a
/// maximum flow is not yet obtained. So after calling this method
/// \ref flowValue() returns the value of a maximum flow and \ref
/// minCut() returns a minimum cut.
/// \pre One of the \ref init() functions must be called before
/// using this function.
void startFirstPhase() {
_phase = true;
while (true) {
int num = _node_num;
Node n = INVALID;
int level = -1;
while (num > 0) {
n = _level->highestActive();
if (n == INVALID) goto first_phase_done;
level = _level->highestActiveLevel();
--num;
Value excess = (*_excess)[n];
int new_level = _level->maxLevel();
for (OutArcIt e(_graph, n); e != INVALID; ++e) {
Value rem = (*_capacity)[e] - (*_flow)[e];
if (!_tolerance.positive(rem)) continue;
Node v = _graph.target(e);
if ((*_level)[v] < level) {
if (!_level->active(v) && v != _target) {
_level->activate(v);
}
if (!_tolerance.less(rem, excess)) {
_flow->set(e, (*_flow)[e] + excess);
(*_excess)[v] += excess;
excess = 0;
goto no_more_push_1;
} else {
excess -= rem;
(*_excess)[v] += rem;
_flow->set(e, (*_capacity)[e]);
}
} else if (new_level > (*_level)[v]) {
new_level = (*_level)[v];
}
}
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Value rem = (*_flow)[e];
if (!_tolerance.positive(rem)) continue;
Node v = _graph.source(e);
if ((*_level)[v] < level) {
if (!_level->active(v) && v != _target) {
_level->activate(v);
}
if (!_tolerance.less(rem, excess)) {
_flow->set(e, (*_flow)[e] - excess);
(*_excess)[v] += excess;
excess = 0;
goto no_more_push_1;
} else {
excess -= rem;
(*_excess)[v] += rem;
_flow->set(e, 0);
}
} else if (new_level > (*_level)[v]) {
new_level = (*_level)[v];
}
}
no_more_push_1:
(*_excess)[n] = excess;
if (excess != 0) {
if (new_level + 1 < _level->maxLevel()) {
_level->liftHighestActive(new_level + 1);
} else {
_level->liftHighestActiveToTop();
}
if (_level->emptyLevel(level)) {
_level->liftToTop(level);
}
} else {
_level->deactivate(n);
}
}
num = _node_num * 20;
while (num > 0) {
while (level >= 0 && _level->activeFree(level)) {
--level;
}
if (level == -1) {
n = _level->highestActive();
level = _level->highestActiveLevel();
if (n == INVALID) goto first_phase_done;
} else {
n = _level->activeOn(level);
}
--num;
Value excess = (*_excess)[n];
int new_level = _level->maxLevel();
for (OutArcIt e(_graph, n); e != INVALID; ++e) {
Value rem = (*_capacity)[e] - (*_flow)[e];
if (!_tolerance.positive(rem)) continue;
Node v = _graph.target(e);
if ((*_level)[v] < level) {
if (!_level->active(v) && v != _target) {
_level->activate(v);
}
if (!_tolerance.less(rem, excess)) {
_flow->set(e, (*_flow)[e] + excess);
(*_excess)[v] += excess;
excess = 0;
goto no_more_push_2;
} else {
excess -= rem;
(*_excess)[v] += rem;
_flow->set(e, (*_capacity)[e]);
}
} else if (new_level > (*_level)[v]) {
new_level = (*_level)[v];
}
}
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Value rem = (*_flow)[e];
if (!_tolerance.positive(rem)) continue;
Node v = _graph.source(e);
if ((*_level)[v] < level) {
if (!_level->active(v) && v != _target) {
_level->activate(v);
}
if (!_tolerance.less(rem, excess)) {
_flow->set(e, (*_flow)[e] - excess);
(*_excess)[v] += excess;
excess = 0;
goto no_more_push_2;
} else {
excess -= rem;
(*_excess)[v] += rem;
_flow->set(e, 0);
}
} else if (new_level > (*_level)[v]) {
new_level = (*_level)[v];
}
}
no_more_push_2:
(*_excess)[n] = excess;
if (excess != 0) {
if (new_level + 1 < _level->maxLevel()) {
_level->liftActiveOn(level, new_level + 1);
} else {
_level->liftActiveToTop(level);
}
if (_level->emptyLevel(level)) {
_level->liftToTop(level);
}
} else {
_level->deactivate(n);
}
}
}
first_phase_done:;
}
/// \brief Starts the second phase of the preflow algorithm.
///
/// The preflow algorithm consists of two phases, this method runs
/// the second phase. After calling one of the \ref init() functions
/// and \ref startFirstPhase() and then \ref startSecondPhase(),
/// \ref flowMap() returns a maximum flow, \ref flowValue() returns the
/// value of a maximum flow, \ref minCut() returns a minimum cut
/// \pre One of the \ref init() functions and \ref startFirstPhase()
/// must be called before using this function.
void startSecondPhase() {
_phase = false;
typename Digraph::template NodeMap<bool> reached(_graph);
for (NodeIt n(_graph); n != INVALID; ++n) {
reached[n] = (*_level)[n] < _level->maxLevel();
}
_level->initStart();
_level->initAddItem(_source);
std::vector<Node> queue;
queue.push_back(_source);
reached[_source] = true;
while (!queue.empty()) {
_level->initNewLevel();
std::vector<Node> nqueue;
for (int i = 0; i < int(queue.size()); ++i) {
Node n = queue[i];
for (OutArcIt e(_graph, n); e != INVALID; ++e) {
Node v = _graph.target(e);
if (!reached[v] && _tolerance.positive((*_flow)[e])) {
reached[v] = true;
_level->initAddItem(v);
nqueue.push_back(v);
}
}
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Node u = _graph.source(e);
if (!reached[u] &&
_tolerance.positive((*_capacity)[e] - (*_flow)[e])) {
reached[u] = true;
_level->initAddItem(u);
nqueue.push_back(u);
}
}
}
queue.swap(nqueue);
}
_level->initFinish();
for (NodeIt n(_graph); n != INVALID; ++n) {
if (!reached[n]) {
_level->dirtyTopButOne(n);
} else if ((*_excess)[n] > 0 && _target != n) {
_level->activate(n);
}
}
Node n;
while ((n = _level->highestActive()) != INVALID) {
Value excess = (*_excess)[n];
int level = _level->highestActiveLevel();
int new_level = _level->maxLevel();
for (OutArcIt e(_graph, n); e != INVALID; ++e) {
Value rem = (*_capacity)[e] - (*_flow)[e];
if (!_tolerance.positive(rem)) continue;
Node v = _graph.target(e);
if ((*_level)[v] < level) {
if (!_level->active(v) && v != _source) {
_level->activate(v);
}
if (!_tolerance.less(rem, excess)) {
_flow->set(e, (*_flow)[e] + excess);
(*_excess)[v] += excess;
excess = 0;
goto no_more_push;
} else {
excess -= rem;
(*_excess)[v] += rem;
_flow->set(e, (*_capacity)[e]);
}
} else if (new_level > (*_level)[v]) {
new_level = (*_level)[v];
}
}
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Value rem = (*_flow)[e];
if (!_tolerance.positive(rem)) continue;
Node v = _graph.source(e);
if ((*_level)[v] < level) {
if (!_level->active(v) && v != _source) {
_level->activate(v);
}
if (!_tolerance.less(rem, excess)) {
_flow->set(e, (*_flow)[e] - excess);
(*_excess)[v] += excess;
excess = 0;
goto no_more_push;
} else {
excess -= rem;
(*_excess)[v] += rem;
_flow->set(e, 0);
}
} else if (new_level > (*_level)[v]) {
new_level = (*_level)[v];
}
}
no_more_push:
(*_excess)[n] = excess;
if (excess != 0) {
if (new_level + 1 < _level->maxLevel()) {
_level->liftHighestActive(new_level + 1);
} else {
// Calculation error
_level->liftHighestActiveToTop();
}
if (_level->emptyLevel(level)) {
// Calculation error
_level->liftToTop(level);
}
} else {
_level->deactivate(n);
}
}
}
/// \brief Runs the preflow algorithm.
///
/// Runs the preflow algorithm.
/// \note pf.run() is just a shortcut of the following code.
/// \code
/// pf.init();
/// pf.startFirstPhase();
/// pf.startSecondPhase();
/// \endcode
void run() {
init();
startFirstPhase();
startSecondPhase();
}
/// \brief Runs the preflow algorithm to compute the minimum cut.
///
/// Runs the preflow algorithm to compute the minimum cut.
/// \note pf.runMinCut() is just a shortcut of the following code.
/// \code
/// pf.init();
/// pf.startFirstPhase();
/// \endcode
void runMinCut() {
init();
startFirstPhase();
}
/// @}
/// \name Query Functions
/// The results of the preflow algorithm can be obtained using these
/// functions.\n
/// Either one of the \ref run() "run*()" functions or one of the
/// \ref startFirstPhase() "start*()" functions should be called
/// before using them.
///@{
/// \brief Returns the value of the maximum flow.
///
/// Returns the value of the maximum flow by returning the excess
/// of the target node. This value equals to the value of
/// the maximum flow already after the first phase of the algorithm.
///
/// \pre Either \ref run() or \ref init() must be called before
/// using this function.
Value flowValue() const {
return (*_excess)[_target];
}
/// \brief Returns the flow value on the given arc.
///
/// Returns the flow value on the given arc. This method can
/// be called after the second phase of the algorithm.
///
/// \pre Either \ref run() or \ref init() must be called before
/// using this function.
Value flow(const Arc& arc) const {
return (*_flow)[arc];
}
/// \brief Returns a const reference to the flow map.
///
/// Returns a const reference to the arc map storing the found flow.
/// This method can be called after the second phase of the algorithm.
///
/// \pre Either \ref run() or \ref init() must be called before
/// using this function.
const FlowMap& flowMap() const {
return *_flow;
}
/// \brief Returns \c true when the node is on the source side of the
/// minimum cut.
///
/// Returns true when the node is on the source side of the found
/// minimum cut. This method can be called both after running \ref
/// startFirstPhase() and \ref startSecondPhase().
///
/// \pre Either \ref run() or \ref init() must be called before
/// using this function.
bool minCut(const Node& node) const {
return ((*_level)[node] == _level->maxLevel()) == _phase;
}
/// \brief Gives back a minimum value cut.
///
/// Sets \c cutMap to the characteristic vector of a minimum value
/// cut. \c cutMap should be a \ref concepts::WriteMap "writable"
/// node map with \c bool (or convertible) value type.
///
/// This method can be called both after running \ref startFirstPhase()
/// and \ref startSecondPhase(). The result after the second phase
/// could be slightly different if inexact computation is used.
///
/// \note This function calls \ref minCut() for each node, so it runs in
/// O(n) time.
///
/// \pre Either \ref run() or \ref init() must be called before
/// using this function.
template <typename CutMap>
void minCutMap(CutMap& cutMap) const {
for (NodeIt n(_graph); n != INVALID; ++n) {
cutMap.set(n, minCut(n));
}
}
/// @}
};
}
#endif