<commit_before>#pragma once
#ifndef OPENGM_GUROBI_HXX
#define OPENGM_GUROBI_HXX

#include <vector>
#include <string>
#include <sstream> 
#include <iostream>

#include "opengm/opengm.hxx"
#include "opengm/inference/visitors/visitor.hxx"
#include "opengm/inference/inference.hxx"
#include "opengm/datastructures/buffer_vector.hxx"




#include "gurobi_c++.h"



namespace opengm {
  



template<class GM>
void findUnariesFi(const GM & gm , std::vector<typename GM::IndexType> & unaryFi){
   typedef typename  GM::IndexType IndexType;

   const IndexType noUnaryFactorFound=gm.numberOfFactors();

   unaryFi.resize(gm.numberOfVariables());
   std::fill(unaryFi.begin(),unaryFi.end(),noUnaryFactorFound);

   for(IndexType fi=0;fi<gm.numberOfFactors();++fi){

      if(gm[fi].numberOfVariables()==1){
         const IndexType vi = gm[fi].variableIndex(0);
         OPENGM_CHECK_OP(unaryFi[vi],==,noUnaryFactorFound, " multiple unary factor found");
         unaryFi[vi]=fi;
      }
   }
}


template<class GM>
typename GM::IndexType findMaxFactorSize(const GM & gm){
   typedef typename  GM::IndexType IndexType;
   IndexType maxSize = 0 ;
   for(IndexType fi=0;fi<gm.numberOfFactors();++fi){
      maxSize = std::max(maxSize ,gm[fi].size());
   }
   return maxSize;
}



template<class GM>
typename GM::LabelType findMaxNumberOfLabels(const GM & gm){
   typedef typename  GM::LabelType LabelType;
   typedef typename  GM::IndexType IndexType;
   LabelType maxL = 0 ;
   for(IndexType vi=0;vi<gm.numberOfVariables();++vi){
      maxL = std::max(maxL ,gm.numberOfLabels(vi));
   }
   return maxL;
}



template<class GM, class ACC,class LP_SOLVER>
class LPGurobi : public Inference<GM, ACC>
{
public:

   typedef ACC AccumulationType;
   typedef GM GraphicalModelType;
   OPENGM_GM_TYPE_TYPEDEFS;

   typedef LP_SOLVER LpSolverType;
   typedef typename LpSolverType::Parameter LpSolverParameter;

   typedef Movemaker<GraphicalModelType> MovemakerType;
   typedef VerboseVisitor<LPGurobi<GM,ACC,LP_SOLVER> > VerboseVisitorType;
   typedef EmptyVisitor<LPGurobi<GM,ACC,LP_SOLVER> > EmptyVisitorType;
   typedef TimingVisitor<LPGurobi<GM,ACC,LP_SOLVER> > TimingVisitorType;
   typedef opengm::ShapeWalker<typename GM::FactorType::ShapeIteratorType> FactorShapeWalkerType;

   typedef double LpValueType;
   typedef int LpIndexType;
   typedef double LpArgType;

   class Parameter {
   public:
      Parameter(
         const LpSolverParameter & lpSolverParamter= LpSolverParameter()
      )
      : lpSolverParamter_(lpSolverParamter){
      }

      LpSolverParameter  lpSolverParamter_;
   };


   LPGurobi(const GraphicalModelType&, const Parameter& = Parameter());
   std::string name() const;
   const GraphicalModelType& graphicalModel() const;
   InferenceTermination infer();
   void reset();
   ValueType bound()const;
   ValueType value()const;
   template<class VisitorType>
   InferenceTermination infer(VisitorType&);
   void setStartingPoint(typename std::vector<LabelType>::const_iterator);
   virtual InferenceTermination arg(std::vector<LabelType>&, const size_t = 1) const ;


   void setupLPObjective();
   void addFirstOrderRelaxationConstraints();


   UInt64Type addVar(const ValueType obj);
   UInt64Type numberOfLpVariables()const;

   // get the lp variable indices
   UInt64Type lpNodeVi(const IndexType gmVi,const LabelType label)const;
   UInt64Type lpFactorVi(const IndexType gmFi,const UInt64Type labelIndex)const;
   template<class LABELING_ITERATOR>
   UInt64Type lpFactorVi(const IndexType gmFi,  LABELING_ITERATOR labelingBegin, LABELING_ITERATOR labelingEnd)const;





   template<class LPVariableIndexIterator,class CoefficientIterator>
   void addConstraint(LPVariableIndexIterator , LPVariableIndexIterator , CoefficientIterator ,const ValueType , const ValueType   , const std::string & name = std::string() );





private:

      void addVarNodeMarginalizationConstraint(const IndexType vi);



      const GraphicalModelType& gm_;
      Parameter param_;
      

      // new !!
      LpSolverType lpSolver_;

      // gurobi member vars
      std::vector<UInt64Type> nodeVarIndex_;
      std::vector<UInt64Type> factorVarIndex_;
      std::vector<IndexType> unaryFis_;

      std::vector<LabelType> gmArg_;
};




template<class GM, class ACC, class LP_SOLVER>
LPGurobi<GM,ACC,LP_SOLVER>::LPGurobi
(
      const GraphicalModelType& gm,
      const Parameter& parameter
)
:  gm_(gm),
   param_(parameter),
   lpSolver_(), 
   nodeVarIndex_(gm.numberOfVariables()),
   factorVarIndex_(gm.numberOfFactors()),
   unaryFis_(),
   gmArg_(gm.numberOfVariables(),static_cast<LabelType>(0) )
{
   this->setupLPObjective();  
   lpSolver_.updateModel();
   this->addFirstOrderRelaxationConstraints();
   lpSolver_.updateModel();
}


template<class GM, class ACC, class LP_SOLVER>
void<commit_msg>fixed major bug in constructor<commit_after>#pragma once
#ifndef OPENGM_GUROBI_HXX
#define OPENGM_GUROBI_HXX

#include <vector>
#include <string>
#include <sstream> 
#include <iostream>

#include "opengm/opengm.hxx"
#include "opengm/inference/visitors/visitor.hxx"
#include "opengm/inference/inference.hxx"
#include "opengm/datastructures/buffer_vector.hxx"




#include "gurobi_c++.h"



namespace opengm {
  



template<class GM>
void findUnariesFi(const GM & gm , std::vector<typename GM::IndexType> & unaryFi){
   typedef typename  GM::IndexType IndexType;

   const IndexType noUnaryFactorFound=gm.numberOfFactors();

   unaryFi.resize(gm.numberOfVariables());
   std::fill(unaryFi.begin(),unaryFi.end(),noUnaryFactorFound);

   for(IndexType fi=0;fi<gm.numberOfFactors();++fi){

      if(gm[fi].numberOfVariables()==1){
         const IndexType vi = gm[fi].variableIndex(0);
         OPENGM_CHECK_OP(unaryFi[vi],==,noUnaryFactorFound, " multiple unary factor found");
         unaryFi[vi]=fi;
      }
   }
}


template<class GM>
typename GM::IndexType findMaxFactorSize(const GM & gm){
   typedef typename  GM::IndexType IndexType;
   IndexType maxSize = 0 ;
   for(IndexType fi=0;fi<gm.numberOfFactors();++fi){
      maxSize = std::max(maxSize ,gm[fi].size());
   }
   return maxSize;
}



template<class GM>
typename GM::LabelType findMaxNumberOfLabels(const GM & gm){
   typedef typename  GM::LabelType LabelType;
   typedef typename  GM::IndexType IndexType;
   LabelType maxL = 0 ;
   for(IndexType vi=0;vi<gm.numberOfVariables();++vi){
      maxL = std::max(maxL ,gm.numberOfLabels(vi));
   }
   return maxL;
}



template<class GM, class ACC,class LP_SOLVER>
class LPGurobi : public Inference<GM, ACC>
{
public:

   typedef ACC AccumulationType;
   typedef GM GraphicalModelType;
   OPENGM_GM_TYPE_TYPEDEFS;

   typedef LP_SOLVER LpSolverType;
   typedef typename LpSolverType::Parameter LpSolverParameter;

   typedef Movemaker<GraphicalModelType> MovemakerType;
   typedef VerboseVisitor<LPGurobi<GM,ACC,LP_SOLVER> > VerboseVisitorType;
   typedef EmptyVisitor<LPGurobi<GM,ACC,LP_SOLVER> > EmptyVisitorType;
   typedef TimingVisitor<LPGurobi<GM,ACC,LP_SOLVER> > TimingVisitorType;
   typedef opengm::ShapeWalker<typename GM::FactorType::ShapeIteratorType> FactorShapeWalkerType;

   typedef double LpValueType;
   typedef int LpIndexType;
   typedef double LpArgType;

   class Parameter {
   public:
      Parameter(
         const LpSolverParameter & lpSolverParamter= LpSolverParameter()
      )
      : lpSolverParamter_(lpSolverParamter){
      }

      LpSolverParameter  lpSolverParamter_;
   };


   LPGurobi(const GraphicalModelType&, const Parameter& = Parameter());
   std::string name() const;
   const GraphicalModelType& graphicalModel() const;
   InferenceTermination infer();
   void reset();
   ValueType bound()const;
   ValueType value()const;
   template<class VisitorType>
   InferenceTermination infer(VisitorType&);
   void setStartingPoint(typename std::vector<LabelType>::const_iterator);
   virtual InferenceTermination arg(std::vector<LabelType>&, const size_t = 1) const ;


   void setupLPObjective();
   void addFirstOrderRelaxationConstraints();


   UInt64Type addVar(const ValueType obj);
   UInt64Type numberOfLpVariables()const;

   // get the lp variable indices
   UInt64Type lpNodeVi(const IndexType gmVi,const LabelType label)const;
   UInt64Type lpFactorVi(const IndexType gmFi,const UInt64Type labelIndex)const;
   template<class LABELING_ITERATOR>
   UInt64Type lpFactorVi(const IndexType gmFi,  LABELING_ITERATOR labelingBegin, LABELING_ITERATOR labelingEnd)const;





   template<class LPVariableIndexIterator,class CoefficientIterator>
   void addConstraint(LPVariableIndexIterator , LPVariableIndexIterator , CoefficientIterator ,const ValueType , const ValueType   , const std::string & name = std::string() );





private:

      void addVarNodeMarginalizationConstraint(const IndexType vi);



      const GraphicalModelType& gm_;
      Parameter param_;
      

      // new !!
      LpSolverType lpSolver_;

      // gurobi member vars
      std::vector<UInt64Type> nodeVarIndex_;
      std::vector<UInt64Type> factorVarIndex_;
      std::vector<IndexType> unaryFis_;

      std::vector<LabelType> gmArg_;
};




template<class GM, class ACC, class LP_SOLVER>
LPGurobi<GM,ACC,LP_SOLVER>::LPGurobi
(
      const GraphicalModelType& gm,
      const Parameter& parameter
)
:  gm_(gm),
   param_(parameter),
   lpSolver_(parameter.lpSolverParamter_), 
   nodeVarIndex_(gm.numberOfVariables()),
   factorVarIndex_(gm.numberOfFactors()),
   unaryFis_(),
   gmArg_(gm.numberOfVariables(),static_cast<LabelType>(0) )
{
   this->setupLPObjective();  
   lpSolver_.updateModel();
   this->addFirstOrderRelaxationConstraints();
   lpSolver_.updateModel();
}


template<class GM, class ACC, class LP_SOLVER>
void
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