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#ifndef __OPENCV_OPTIM_HPP__
#define __OPENCV_OPTIM_HPP__

#include <iostream>
#include "opencv2/core.hpp"
#include "opencv2/core/mat.hpp"

/*! \namespace cv
 Namespace where all the C++ OpenCV functionality resides
 */
namespace cv{namespace optim
{
//! generic class for optimization algorithms */
class CV_EXPORTS Solver : public Algorithm /* Algorithm is the base OpenCV class */
{
  public:
  class CV_EXPORTS Function
  {
  public:
        virtual ~Function(){}
        virtual double calc(InputArray args) const = 0;
  };
  class CV_EXPORTS Constraints
  {
  public:
        virtual ~Constraints(){}
  };

  //! could be reused for all the generic algorithms like downhill simplex. Return value is the maximum value of a function*/
  virtual double solve(const Function& F,const Constraints& C, OutputArray result) const = 0;

  /*virtual void setTermCriteria(const TermCriteria& criteria) = 0;
  virtual TermCriteria getTermCriteria() = 0;*/

  // more detailed API to be defined later ...
};

class CV_EXPORTS LPSolver : public Solver
{
public:
  class CV_EXPORTS LPFunction:public Solver::Function
  {
      cv::Mat z;
  public:
      //! Note, that this class is supposed to be immutable, so it's ok to make only a shallow copy of z_in.*/
      LPFunction(cv::Mat z_in):z(z_in){}
      ~LPFunction(){};
      const cv::Mat& getz()const{return z;}
      double calc(InputArray args)const;
  };

  //!This class represents constraints for linear problem. There are two matrix stored: m-by-n matrix A and n-by-1 column-vector b.
  //!What this represents is the set of constraints Ax\leq b and x\geq 0. It can be shown that any set of linear constraints can be converted
  //!this form and **we shall create various constructors for this class that will perform these conversions**.
  class CV_EXPORTS LPConstraints:public Solver::Constraints
  {
      cv::Mat A,b;
  public:
      ~LPConstraints(){};
      //! Note, that this class is supposed to be immutable, so it's ok to make only a shallow copy of A_in and b_in.*/
      LPConstraints(cv::Mat A_in, cv::Mat b_in):A(A_in),b(b_in){}
      const cv::Mat& getA()const{return A;}
      const cv::Mat& getb()const{return b;}
  };

  LPSolver(){}
  double solve(const Function& F,const Constraints& C, OutputArray result)const;
};
}}// cv

#endif