dust3d/thirdparty/QuadriFlow/3rd/lemon-1.3.1/lemon/preflow.h

986 lines
30 KiB
C++
Executable File

/* -*- mode: C++; indent-tabs-mode: nil; -*-
*
* This file is a part of LEMON, a generic C++ optimization library.
*
* Copyright (C) 2003-2013
* 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 \cite clrs01algorithms,
/// \cite amo93networkflows, \cite 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$O(n^2\sqrt{m})\f$.
///
/// 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 lemon::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