Angular analysis of B+->K*+(K+pi0)mumu
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/**
* @file parameterscan.hh * @author Christoph Langenbruch, Renata Kopecna * @date 2009-03-18 * */
#ifndef PARAMETERSCAN_H
#define PARAMETERSCAN_H
#include <string>
#include <vector>
#include <multifit.hh>
//TODO: move to /Run/!
namespace fcnc { class options; class generator; class parameters; class pdf;
///class to perform repeated fits while changing a parameter value, e.g. background fraction
class parameterscan: public multifit { private: ///common parameters in different parameter sets
std::vector< std::string > common_params; public: ///constructor
parameterscan(options* o); /**
* perform a parameter scan * @param param_name the name of the parameter which will be varied in the scan * @param min the start value for the varied parameter * @param max the stop value for the varied parameter * @param nsteps the number of steps in which to vary the parameter * @param nevents the number of events used per fit of the toy data * @param reruns the number of repeats for a single value of the parameter * @param prob pointer to the pdf to use in the likelihood fit * @param params pointer to parameterset to use in the likelihood fit * @param gen pointer to the toy data generator to use * @param only_float_in_generation only varies the parameter in the generation, * but fixes it in the fit. This way one can do systematic studies. **/ void scan(std::string param_name, double min, double max, unsigned int nsteps, unsigned int nevents, unsigned int reruns, pdf* prob, parameters* params, generator* gen, bool only_float_in_generation=false); /**
* perform a parameter scan * @param param_name the name of the parameter which will be varied in the scan * @param min the start value for the varied parameter * @param max the stop value for the varied parameter * @param nsteps the number of steps in which to vary the parameter * @param nevents the number of events used per fit of the toy data * @param reruns the number of repeats for a single value of the parameter * @param prob pointer to the pdf to use in the likelihood fit * @param params pointer to parameterset to use in the likelihood fit * @param gen pointer to the toy data generator to use * @param only_float_in_generation only varies the parameter in the generation, * but fixes it in the fit. This way one can do systematic studies. **/ void scan(std::string param_name, double min, double max, unsigned int nsteps, std::vector<unsigned int> nevents, unsigned int reruns, std::vector<pdf*> pdfs, std::vector<parameters*> params, std::vector<generator*> gens, bool only_float_in_generation=false); ///set common parameters
void set_common_parameters(std::vector<std::string> common_pars) { common_params = common_pars; }; };
}
#endif
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