lemon-0.x: comparison lemon/capacity

equal deleted inserted replaced

-:a49b1b3dcd37
+:56918ba44652
 /// \tparam SupplyMap The type of the supply map.
 ///
 /// \warning
 /// - Edge capacities and costs should be \e non-negative \e integers.
 /// - Supply values should be \e signed \e integers.
-/// - \c LowerMap::Value must be convertible to \c CapacityMap::Value.
+/// - The value types of the maps should be convertible to each other.
-/// - \c CapacityMap::Value and \c SupplyMap::Value must be
+/// - \c CostMap::Value must be signed type.
-///   convertible to each other.
-/// - All value types must be convertible to \c CostMap::Value, which
-///   must be signed type.
 ///
 /// \author Peter Kovacs
 template < typename Graph,
 typename LowerMap = typename Graph::template EdgeMap<int>,
 // The processed (i.e. permanently labeled) nodes
 std::vector<Node> _proc_nodes;
 public:
-/// The constructor of the class.
+/// Constructor.
 ResidualDijkstra( const Graph &graph,
 const FlowMap &flow,
 const CapacityEdgeMap &res_cap,
 const CostMap &cost,
 const SupplyMap &excess,
 // The modified supply map
 SupplyNodeMap _supply;
 bool _valid_supply;
 // Edge map of the current flow
-FlowMap _flow;
+FlowMap *_flow;
+bool _local_flow;
 // Node map of the current potentials
-PotentialMap _potential;
+PotentialMap *_potential;
+bool _local_potential;
 // The residual capacity map
 CapacityEdgeMap _res_cap;
 // The excess map
 SupplyNodeMap _excess;
 // The pred edge map
 PredMap _pred;
 // Implementation of the Dijkstra algorithm for finding augmenting
 // shortest paths in the residual network
-ResidualDijkstra _dijkstra;
+ResidualDijkstra *_dijkstra;
-public :
+public:
-/// \brief General constructor of the class (with lower bounds).
+/// \brief General constructor (with lower bounds).
 ///
-/// General constructor of the class (with lower bounds).
+/// General constructor (with lower bounds).
 ///
 /// \param graph The directed graph the algorithm runs on.
 /// \param lower The lower bounds of the edges.
 /// \param capacity The capacities (upper bounds) of the edges.
 /// \param cost The cost (length) values of the edges.
 const LowerMap &lower,
 const CapacityMap &capacity,
 const CostMap &cost,
 const SupplyMap &supply ) :
 _graph(graph), _lower(&lower), _capacity(graph), _cost(cost),
-_supply(graph), _flow(graph, 0), _potential(graph, 0),
+_supply(graph), _flow(0), _local_flow(false),
-_res_cap(graph), _excess(graph), _pred(graph),
+_potential(0), _local_potential(false),
-_dijkstra(_graph, _flow, _res_cap, _cost, _excess, _potential, _pred)
+_res_cap(graph), _excess(graph), _pred(graph)
 {
 // Removing non-zero lower bounds
 _capacity = subMap(capacity, lower);
 _res_cap = _capacity;
 Supply sum = 0;
 sum += s;
 }
 _valid_supply = sum == 0;
 }
-/// \brief General constructor of the class (without lower bounds).
+/// \brief General constructor (without lower bounds).
 ///
-/// General constructor of the class (without lower bounds).
+/// General constructor (without lower bounds).
 ///
 /// \param graph The directed graph the algorithm runs on.
 /// \param capacity The capacities (upper bounds) of the edges.
 /// \param cost The cost (length) values of the edges.
 /// \param supply The supply values of the nodes (signed).
 CapacityScaling( const Graph &graph,
 const CapacityMap &capacity,
 const CostMap &cost,
 const SupplyMap &supply ) :
 _graph(graph), _lower(NULL), _capacity(capacity), _cost(cost),
-_supply(supply), _flow(graph, 0), _potential(graph, 0),
+_supply(supply), _flow(0), _local_flow(false),
-_res_cap(capacity), _excess(graph), _pred(graph),
+_potential(0), _local_potential(false),
-_dijkstra(_graph, _flow, _res_cap, _cost, _excess, _potential, _pred)
+_res_cap(capacity), _excess(graph), _pred(graph)
 {
 // Checking the sum of supply values
 Supply sum = 0;
 for (NodeIt n(_graph); n != INVALID; ++n) sum += _supply[n];
 _valid_supply = sum == 0;
 }
-/// \brief Simple constructor of the class (with lower bounds).
+/// \brief Simple constructor (with lower bounds).
 ///
-/// Simple constructor of the class (with lower bounds).
+/// Simple constructor (with lower bounds).
 ///
 /// \param graph The directed graph the algorithm runs on.
 /// \param lower The lower bounds of the edges.
 /// \param capacity The capacities (upper bounds) of the edges.
 /// \param cost The cost (length) values of the edges.
 const CapacityMap &capacity,
 const CostMap &cost,
 Node s, Node t,
 Supply flow_value ) :
 _graph(graph), _lower(&lower), _capacity(graph), _cost(cost),
-_supply(graph), _flow(graph, 0), _potential(graph, 0),
+_supply(graph), _flow(0), _local_flow(false),
-_res_cap(graph), _excess(graph), _pred(graph),
+_potential(0), _local_potential(false),
-_dijkstra(_graph, _flow, _res_cap, _cost, _excess, _potential, _pred)
+_res_cap(graph), _excess(graph), _pred(graph)
 {
 // Removing non-zero lower bounds
 _capacity = subMap(capacity, lower);
 _res_cap = _capacity;
 for (NodeIt n(_graph); n != INVALID; ++n) {
 _supply[n] = sum;
 }
 _valid_supply = true;
 }
-/// \brief Simple constructor of the class (without lower bounds).
+/// \brief Simple constructor (without lower bounds).
 ///
-/// Simple constructor of the class (without lower bounds).
+/// Simple constructor (without lower bounds).
 ///
 /// \param graph The directed graph the algorithm runs on.
 /// \param capacity The capacities (upper bounds) of the edges.
 /// \param cost The cost (length) values of the edges.
 /// \param s The source node.
 const CapacityMap &capacity,
 const CostMap &cost,
 Node s, Node t,
 Supply flow_value ) :
 _graph(graph), _lower(NULL), _capacity(capacity), _cost(cost),
-_supply(graph, 0), _flow(graph, 0), _potential(graph, 0),
+_supply(graph, 0), _flow(0), _local_flow(false),
-_res_cap(capacity), _excess(graph), _pred(graph),
+_potential(0), _local_potential(false),
-_dijkstra(_graph, _flow, _res_cap, _cost, _excess, _potential, _pred)
+_res_cap(capacity), _excess(graph), _pred(graph)
 {
 _supply[s] =  flow_value;
 _supply[t] = -flow_value;
 _valid_supply = true;
 }
+/// Destructor.
+~CapacityScaling() {
+if (_local_flow) delete _flow;
+if (_local_potential) delete _potential;
+delete _dijkstra;
+}
+/// \brief Sets the flow map.
+///
+/// Sets the flow map.
+///
+/// \return \c (*this)
+CapacityScaling& flowMap(FlowMap &map) {
+if (_local_flow) {
+delete _flow;
+_local_flow = false;
+}
+_flow = &map;
+return *this;
+}
+/// \brief Sets the potential map.
+///
+/// Sets the potential map.
+///
+/// \return \c (*this)
+CapacityScaling& potentialMap(PotentialMap &map) {
+if (_local_potential) {
+delete _potential;
+_local_potential = false;
+}
+_potential = &map;
+return *this;
+}
+/// \name Execution control
+/// The only way to execute the algorithm is to call the run()
+/// function.
+/// @{
 /// \brief Runs the algorithm.
 ///
 /// Runs the algorithm.
 ///
 /// \param scaling Enable or disable capacity scaling.
 /// \return \c true if a feasible flow can be found.
 bool run(bool scaling = true) {
 return init(scaling) && start();
 }
+/// @}
+/// \name Query Functions
+/// The result of the algorithm can be obtained using these
+/// functions.
+/// \n run() must be called before using them.
+/// @{
 /// \brief Returns a const reference to the edge map storing the
 /// found flow.
 ///
 /// Returns a const reference to the edge map storing the found flow.
 ///
 /// \pre \ref run() must be called before using this function.
 const FlowMap& flowMap() const {
-return _flow;
+return *_flow;
 }
 /// \brief Returns a const reference to the node map storing the
 /// found potentials (the dual solution).
 ///
 /// Returns a const reference to the node map storing the found
 /// potentials (the dual solution).
 ///
 /// \pre \ref run() must be called before using this function.
 const PotentialMap& potentialMap() const {
-return _potential;
+return *_potential;
+}
+/// \brief Returns the flow on the edge.
+///
+/// Returns the flow on the edge.
+///
+/// \pre \ref run() must be called before using this function.
+Capacity flow(const Edge& edge) const {
+return (*_flow)[edge];
+}
+/// \brief Returns the potential of the node.
+///
+/// Returns the potential of the node.
+///
+/// \pre \ref run() must be called before using this function.
+Cost potential(const Node& node) const {
+return (*_potential)[node];
 }
 /// \brief Returns the total cost of the found flow.
 ///
 /// Returns the total cost of the found flow. The complexity of the
 ///
 /// \pre \ref run() must be called before using this function.
 Cost totalCost() const {
 Cost c = 0;
 for (EdgeIt e(_graph); e != INVALID; ++e)
-c += _flow[e] * _cost[e];
+c += (*_flow)[e] * _cost[e];
 return c;
 }
+/// @}
 private:
 /// Initializes the algorithm.
 bool init(bool scaling) {
 if (!_valid_supply) return false;
+// Initializing maps
+if (!_flow) {
+_flow = new FlowMap(_graph);
+_local_flow = true;
+}
+if (!_potential) {
+_potential = new PotentialMap(_graph);
+_local_potential = true;
+}
+for (EdgeIt e(_graph); e != INVALID; ++e) (*_flow)[e] = 0;
+for (NodeIt n(_graph); n != INVALID; ++n) (*_potential)[n] = 0;
 _excess = _supply;
-// Initilaizing delta value
+_dijkstra = new ResidualDijkstra( _graph, *_flow, _res_cap, _cost,
+_excess, *_potential, _pred );
+// Initializing delta value
 if (scaling) {
 // With scaling
 Supply max_sup = 0, max_dem = 0;
 for (NodeIt n(_graph); n != INVALID; ++n) {
 if ( _supply[n] > max_sup) max_sup =  _supply[n];
 ++_phase_num;
 } else {
 // Without scaling
 _delta = 1;
 }
 return true;
 }
 bool start() {
 if (_delta > 1)
 int factor = 4;
 while (true) {
 // Saturating all edges not satisfying the optimality condition
 for (EdgeIt e(_graph); e != INVALID; ++e) {
 Node u = _graph.source(e), v = _graph.target(e);
-Cost c = _cost[e] + _potential[u] - _potential[v];
+Cost c = _cost[e] + (*_potential)[u] - (*_potential)[v];
 if (c < 0 && _res_cap[e] >= _delta) {
 _excess[u] -= _res_cap[e];
 _excess[v] += _res_cap[e];
-_flow[e] = _capacity[e];
+(*_flow)[e] = _capacity[e];
 _res_cap[e] = 0;
 }
-else if (c > 0 && _flow[e] >= _delta) {
+else if (c > 0 && (*_flow)[e] >= _delta) {
-_excess[u] += _flow[e];
+_excess[u] += (*_flow)[e];
-_excess[v] -= _flow[e];
+_excess[v] -= (*_flow)[e];
-_flow[e] = 0;
+(*_flow)[e] = 0;
 _res_cap[e] = _capacity[e];
 }
 }
 // Finding excess nodes and deficit nodes
 if (!delta_deficit) break;
 }
 // Running Dijkstra
 s = _excess_nodes[next_node];
-if ((t = _dijkstra.run(s, _delta)) == INVALID) {
+if ((t = _dijkstra->run(s, _delta)) == INVALID) {
 if (_delta > 1) {
 ++next_node;
 continue;
 }
 return false;
 Capacity rc;
 if (u == _graph.target(e)) {
 rc = _res_cap[e];
 u = _graph.source(e);
 } else {
-rc = _flow[e];
+rc = (*_flow)[e];
 u = _graph.target(e);
 }
 if (rc < d) d = rc;
 }
 }
 u = t;
 while ((e = _pred[u]) != INVALID) {
 if (u == _graph.target(e)) {
-_flow[e] += d;
+(*_flow)[e] += d;
 _res_cap[e] -= d;
 u = _graph.source(e);
 } else {
-_flow[e] -= d;
+(*_flow)[e] -= d;
 _res_cap[e] += d;
 u = _graph.target(e);
 }
 }
 _excess[s] -= d;
 }
 // Handling non-zero lower bounds
 if (_lower) {
 for (EdgeIt e(_graph); e != INVALID; ++e)
-_flow[e] += (*_lower)[e];
+(*_flow)[e] += (*_lower)[e];
 }
 return true;
 }
 /// Executes the successive shortest path algorithm.
 while ( _excess[_excess_nodes[next_node]] > 0 ||
 ++next_node < int(_excess_nodes.size()) )
 {
 // Running Dijkstra
 s = _excess_nodes[next_node];
-if ((t = _dijkstra.run(s, 1)) == INVALID)
+if ((t = _dijkstra->run(s, 1)) == INVALID)
 return false;
 // Augmenting along a shortest path from s to t
 Capacity d = _excess[s] < -_excess[t] ? _excess[s] : -_excess[t];
 Node u = t;
 Capacity rc;
 if (u == _graph.target(e)) {
 rc = _res_cap[e];
 u = _graph.source(e);
 } else {
-rc = _flow[e];
+rc = (*_flow)[e];
 u = _graph.target(e);
 }
 if (rc < d) d = rc;
 }
 u = t;
 while ((e = _pred[u]) != INVALID) {
 if (u == _graph.target(e)) {
-_flow[e] += d;
+(*_flow)[e] += d;
 _res_cap[e] -= d;
 u = _graph.source(e);
 } else {
-_flow[e] -= d;
+(*_flow)[e] -= d;
 _res_cap[e] += d;
 u = _graph.target(e);
 }
 }
 _excess[s] -= d;
 }
 // Handling non-zero lower bounds
 if (_lower) {
 for (EdgeIt e(_graph); e != INVALID; ++e)
-_flow[e] += (*_lower)[e];
+(*_flow)[e] += (*_lower)[e];
 }
 return true;
 }
 }; //class CapacityScaling

changeset 2585	20d42311e344
parent 2574	7058c9690e7d
child 2588	4d3bc1d04c1d