// -*- c++ -*-

#ifndef HUGO_MINCOSTFLOWS_H

#define HUGO_MINCOSTFLOWS_H

///\ingroup galgs

///\file

///\brief An algorithm for finding a flow of value \c k (for small values of \c k) having minimal total cost 

#include <hugo/dijkstra.h>

#include <hugo/graph_wrapper.h>

#include <hugo/maps.h>

#include <vector>

#include <hugo/for_each_macros.h>

namespace hugo {

/// \addtogroup galgs

/// @{

  ///\brief Implementation of an algorithm for finding a flow of value \c k 

  ///(for small values of \c k) having minimal total cost between 2 nodes 

  /// 

  ///

  /// The class \ref hugo::MinCostFlows "MinCostFlows" implements

  /// an algorithm for finding a flow of value \c k 

  ///(for small values of \c k) having minimal total cost  

  /// from a given source node to a given target node in an

  /// edge-weighted directed graph having nonnegative integer capacities.

  /// The range of the length (weight) function is nonnegative reals but 

  /// the range of capacity function is the set of nonnegative integers. 

  /// It is not a polinomial time algorithm for counting the minimum cost

  /// maximal flow, since it counts the minimum cost flow for every value 0..M

  /// where \c M is the value of the maximal flow.

  ///

  ///\author Attila Bernath

  template <typename Graph, typename LengthMap, typename CapacityMap>

  class MinCostFlows {

    typedef typename LengthMap::ValueType Length;

    //Warning: this should be integer type

    typedef typename CapacityMap::ValueType Capacity;

    typedef typename Graph::Node Node;

    typedef typename Graph::NodeIt NodeIt;

    typedef typename Graph::Edge Edge;

    typedef typename Graph::OutEdgeIt OutEdgeIt;

    typedef typename Graph::template EdgeMap<int> EdgeIntMap;

    //    typedef ConstMap<Edge,int> ConstMap;

    typedef ResGraphWrapper<const Graph,int,CapacityMap,EdgeIntMap> ResGraphType;

    typedef typename ResGraphType::Edge ResGraphEdge;

    class ModLengthMap {   

      //typedef typename ResGraphType::template NodeMap<Length> NodeMap;

      typedef typename Graph::template NodeMap<Length> NodeMap;

      const ResGraphType& G;

      //      const EdgeIntMap& rev;

      const LengthMap &ol;

      const NodeMap &pot;

    public :

      typedef typename LengthMap::KeyType KeyType;

      typedef typename LengthMap::ValueType ValueType;

      ValueType operator[](typename ResGraphType::Edge e) const {     

	if (G.forward(e))

	  return  ol[e]-(pot[G.head(e)]-pot[G.tail(e)]);   

	else

	  return -ol[e]-(pot[G.head(e)]-pot[G.tail(e)]);   

      }     

      ModLengthMap(const ResGraphType& _G,

		   const LengthMap &o,  const NodeMap &p) : 

	G(_G), /*rev(_rev),*/ ol(o), pot(p){}; 

    };//ModLengthMap

  protected:

    //Input

    const Graph& G;

    const LengthMap& length;

    const CapacityMap& capacity;

    //auxiliary variables

    //To store the flow

    EdgeIntMap flow; 

    //To store the potentila (dual variables)

    typedef typename Graph::template NodeMap<Length> PotentialMap;

    PotentialMap potential;

    Length total_length;

  public :

    MinCostFlows(Graph& _G, LengthMap& _length, CapacityMap& _cap) : G(_G), 

      length(_length), capacity(_cap), flow(_G), potential(_G){ }

    ///Runs the algorithm.

    ///Runs the algorithm.

    ///Returns k if there are at least k edge-disjoint paths from s to t.

    ///Otherwise it returns the number of found edge-disjoint paths from s to t.

    ///\todo May be it does make sense to be able to start with a nonzero 

    /// feasible primal-dual solution pair as well.

    int run(Node s, Node t, int k) {

      //Resetting variables from previous runs

      total_length = 0;

      FOR_EACH_LOC(typename Graph::EdgeIt, e, G){

	flow.set(e,0);

      }

      //Initialize the potential to zero

      FOR_EACH_LOC(typename Graph::NodeIt, n, G){

	potential.set(n,0);

      }

      //We need a residual graph

      ResGraphType res_graph(G, capacity, flow);

      ModLengthMap mod_length(res_graph, length, potential);

      Dijkstra<ResGraphType, ModLengthMap> dijkstra(res_graph, mod_length);

      int i;

      for (i=0; i<k; ++i){

	dijkstra.run(s);

	if (!dijkstra.reached(t)){

	  //There are no k paths from s to t

	  break;

	};

	//We have to change the potential

	FOR_EACH_LOC(typename ResGraphType::NodeIt, n, res_graph){

	  potential[n] += dijkstra.distMap()[n];

	}

	//Augmenting on the sortest path

	Node n=t;

	ResGraphEdge e;

	while (n!=s){

	  e = dijkstra.pred(n);

	  n = dijkstra.predNode(n);

	  res_graph.augment(e,1);

	  //Let's update the total length

	  if (res_graph.forward(e))

	    total_length += length[e];

	  else 

	    total_length -= length[e];	    

	}

      }

      return i;

    }

    ///This function gives back the total length of the found paths.

    ///Assumes that \c run() has been run and nothing changed since then.

    Length totalLength(){

      return total_length;

    }

    ///Returns a const reference to the EdgeMap \c flow. \pre \ref run() must

    ///be called before using this function.

    const EdgeIntMap &getFlow() const { return flow;}

  ///Returns a const reference to the NodeMap \c potential (the dual solution).

    /// \pre \ref run() must be called before using this function.

    const PotentialMap &getPotential() const { return potential;}

    ///This function checks, whether the given solution is optimal

    ///Running after a \c run() should return with true

    ///In this "state of the art" this only check optimality, doesn't bother with feasibility

    ///

    ///\todo Is this OK here?

    bool checkComplementarySlackness(){

      Length mod_pot;

      Length fl_e;

      FOR_EACH_LOC(typename Graph::EdgeIt, e, G){

	//C^{\Pi}_{i,j}

	mod_pot = length[e]-potential[G.head(e)]+potential[G.tail(e)];

	fl_e = flow[e];

	//	std::cout << fl_e << std::endl;

	if (0<fl_e && fl_e<capacity[e]){

	  if (mod_pot != 0)

	    return false;

	}

	else{

	  if (mod_pot > 0 && fl_e != 0)

	    return false;

	  if (mod_pot < 0 && fl_e != capacity[e])

	    return false;

	}

      }

      return true;

    }

  }; //class MinCostFlows

  ///@}

} //namespace hugo

#endif //HUGO_MINCOSTFLOWS_H