////////////////////////////////////////////////////////////////////
/// \class RAT::DropoutFitter
///
/// \brief Given a histogram of CAEN baselines performs a fit to extract
///        values related to the amount of dropout
///
/// \author Eric Marzec <marzece@hep.upenn.edu>
///
/// \details Meant to be used with the DropoutEvaluator class.
///          This performs a fit using simulated annealing to extract
///          the frequency of dropout. Must be supplied with a histogram
///          of CAEN values from the DropoutEvaluator.
///
////////////////////////////////////////////////////////////////////

#ifndef __RAT_DropoutFitter__
#define __RAT_DropoutFitter__

#include <RAT/OptimisedComponent.hh>
#include <vector>
#include <map>

using std::vector;
using std::map;
namespace RAT
{

    class DropoutFitter: public OptimisedComponent {
        public:
            DropoutFitter();
            virtual ~DropoutFitter();
            vector<double> GetParams() const;
            void SetParams(const vector<double> & params);
            void SetParam(const int& iparam, const double& value);
            vector<double> GetPositiveErrors() const;
            vector<double> GetNegativeErrors() const;
            void SetError(const int& iparam, const double& value);
            void SetFOM(const std::string& fomName, const double fom);
            void SetTemperature(const int & temp);
            void SetIterations(const int & iterations);
            void PerformFit();
            double Chi2(const vector<double>& y, const vector<double>& yp);
            double LogLikelihood(const vector<double>& y, const vector<double>& yp);
            double operator() (const vector<double> & params);
            vector<double> DropoutModel(const vector<double> &x,
                                        const double&rate,
                                        const double& pos,
                                        const double& separation,
                                        const double& sigma);
            map<std::string, double> fFoms;
            vector<double> xax; // x-axis to be used in fit
            vector<double> yvals; // Y values to be fitted to
            vector<double> fParams; // Fit parameters
            vector<double> fErrors; // Fit errors
            double fNormalization; // Normalization factor for yvalues
        protected:
            Optimisers::Optimiser *fOptimiser;
            unsigned int fTemperature; // Temperature to be given to simulated annealing algorithm
            unsigned int fIterations; // Number of iterations (per temperature) for simulated annealing
            unsigned int fSampleCount; // Counter to make sure optimizer is doing its job
            double Prior(const double& rate, const double& pos, const double& sep, const double& sigma);
            double ClipProbability(const double &mu, const double& sigma);
    };
}
#endif