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RooContainer.h
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RooContainer.h
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#ifndef ROOCONTAINER
#define ROOCONTAINER
// ROOT includes
#include "TROOT.h"
#include "TCanvas.h"
#include "TPaveText.h"
#include "TLatex.h"
#include "TH1F.h"
#include "TF1.h"
#include "TAxis.h"
#include "TString.h"
#include "TMath.h"
#include "TMatrixDSym.h"
#include "TMatrixD.h"
#include "TVectorD.h"
// RooFit includes
#include "RooDataHist.h"
#include "RooDataSet.h"
#include "RooRealVar.h"
#include "RooConstVar.h"
#include "RooFormulaVar.h"
#include "RooPlot.h"
#include "RooGenericPdf.h"
#include "RooExponential.h"
#include "RooGaussian.h"
#include "RooBreitWigner.h"
#include "RooVoigtian.h"
#include "RooCBShape.h"
#include "RooChebychev.h"
#include "RooBernstein.h"
#include "RooExtendPdf.h"
#include "RooFFTConvPdf.h"
#include "RooAddPdf.h"
#include "RooFitResult.h"
#include "RooArgSet.h"
#include "RooArgList.h"
#include "RooAddPdf.h"
#include "RooGlobalFunc.h"
#include "RooCmdArg.h"
// RooStats includes
#include "RooWorkspace.h"
// standard includes
#include <cmath>
#include <ctime>
#include <iostream>
#include <fstream>
#include <map>
#include <set>
#include <vector>
//#include <algorithm>
class RooContainer {
public:
RooContainer(int ncat=1, int nsigmas=1);
~RooContainer();
void SetNCategories(int);
void Verbose(bool noisy=true);
void BlindData(bool blind=true);
void AddGlobalSystematic(std::string,double,double);
void AddNormalisationSystematics(std::string,std::vector<std::pair<double,double> >, int);
void SaveSystematicsData(bool save=true);
void MakeSystematicPdfs(bool save=true);
void SaveRooDataHists(bool save=true);
void MakeSystematicStudy(std::vector<std::string>,std::vector<int>);
void AddObservable(std::string,double,double);
void AddConstant(std::string,double);
void AddRealVar(std::string,double,double xmin=-10,double xmax=10);
void AddFormulaVar(std::string,std::string,std::string);
void AddGenericPdf(std::string,std::string,std::string,
std::vector<std::string> &,
int form,double norm_guess=10
,double norm_min=0., double norm_max=1.e6);
void AddSpecificCategoryPdf(int *,std::string,std::string,std::string,
std::vector<std::string> &,
int form,double norm_guess=10
,double norm_min=0., double norm_max=1.e6);
void ComposePdf(std::string, std::string
,std::vector<std::string> &,bool use_extended=true);
void ComposeSpecificCategoryPdf(int *,std::string, std::string
,std::vector<std::string> &,bool use_extended=true);
// void ConvolutePdf(std::string,std::string,std::string,std::string
// ,double norm_guess=100);
void MergeHistograms(std::string,std::string, bool systematics=false);
void SumBinnedDatasets(std::string,std::string,std::string,std::vector<double>, std::vector<double>, bool scale=true);
void SumBinnedDatasets(std::string,std::string,std::string,double,double, bool scale=true);
void SumMultiBinnedDatasets(std::string,std::vector<std::string>,std::vector<double>,bool scale=true);
void SumMultiBinnedDatasets(std::string,std::vector<std::string>,double,bool scale=true);
void CreateDataSet(std::string,std::string,int nbins,double x1=-990,double x2=-990);
void MakeSystematics(std::string,std::string,int);
void FitToData(std::string,std::string
,double x1,double x2,double x3,double x4);
void FitToData(std::string,std::string,double x1,double x2);
void FitToData(std::string,std::string);
void FitToSystematicSet(std::string,std::string,std::string
,double x1,double x2,double x3,double x4);
void FitToSystematicSet(std::string,std::string,std::string,double x1,double x2);
void FitToSystematicSet(std::string,std::string,std::string);
void InputDataPoint(std::string,int,double,double w=1.);
void InputBinnedDataPoint(std::string,int,double,double w=1.);
void InputSystematicSet(std::string s_name, std::string sys_name, std::vector<int> cats
,std::vector<double> x, std::vector<double> weights=std::vector<double>(0));
void InputSystematicPoint(std::string s_name, std::string sys_name, int cat, int ishift,double x, double w=1);
void RebinBinnedDataset(std::string,std::string,std::vector <std::vector<double> >, bool);
void RebinBinnedDataset(std::string,std::string,std::vector<double> , bool);
std::vector<std::vector<double> >OptimizedBinning(std::string,int,bool,bool,int direction=1);
std::vector<std::vector<double> >RebinConstantEdges(std::string,int);
std::vector<std::vector<double> >SoverBOptimizedBinning(std::string,std::string,int,double);
std::vector<std::vector<double> > SignificanceOptimizedBinning(std::string signalname,std::string bkgname,int nTargetBins);
void WriteDataCard(std::string,std::string,std::string,std::string);
void WriteSpecificCategoryDataCards(std::string,std::string,std::string,std::string);
void GenerateBinnedPdf(std::string,std::string,std::string,int,int,int,double x1=-999,double x2=-999);
void CombineBinnedDatasets(std::string,std::string, double fraction=-1);
std::vector<double> GetFitNormalisations(std::string,std::string,double,double,bool external_fit=false);
std::vector< std::pair<double,double> > GetFitNormalisationsAndErrors(std::string,std::string,double,double,bool external_fit=false); // external Fit bool depricated
void Save();
void AppendDataSet(std::string, RooDataSet*);
void AppendTH1F(std::string, TH1F*);
std::vector<std::string> GetDataSetNames();
std::vector<std::string> GetTH1FNames();
int ncat;
int nsigmas;
float sigmaRange;
bool make_systematics;
bool fit_systematics;
bool save_systematics_data;
bool verbosity_;
bool save_roodatahists;
private:
void addRealVar(std::string,double,double);
void addRealVar(std::string,double,double,double);
void addFormulaVar(std::string,std::string,std::string);
void addGenericPdf(std::string,std::string,std::string,
std::vector<std::string> &,
int form,
double,double, double);
void composePdf(std::string , std::string
,std::vector<std::string> &,bool);
// void convolutePdf(std::string,std::string,std::string,RooRealVar &,double norm_guess=100);
void mergeHistograms(std::string, TH1F*, TH1F*);
void sumBinnedDatasets(std::string,std::string,std::string,double,double,bool);
void sumMultiBinnedDatasets(std::string,std::vector<std::string>,double,bool scale=true);
void createDataSet(std::string,std::string,int,double x1,double x2);
void makeSystematics(std::string,std::string,int);
void fitToData(std::string,std::string,std::string
,double,double,double,double);
void fitToSystematicSet(std::string,std::string,std::string
,double,double,double,double);
void generateBinnedPdf(int,std::string,std::string,std::string,std::string,RooRealVar*,RooDataSet&,int,int,int,double,double);
void combineBinnedDatasets(std::string,std::string,double);
void writeRooDataHist(std::string, TH1F *);
void writeRooPlot(RooPlot *,double);
void writeSpecificCategoryDataCard(int,std::string,std::string,std::string,std::string);
void removeDuplicateElements(std::vector<RooAbsPdf*> &);
void histogramSmoothing(TH1F*, int);
void histogramSmoothingFit(TH1F*);
void setAllParametersConstant();
void rebinBinnedDataset(std::string,std::string,TH1F *,std::vector<double>);
std::vector<double> optimizedBinning(TH1F *,int,bool,bool);
std::vector<double> rebinConstantEdges(TH1F *,int);
std::vector<double> optimizedReverseBinning(TH1F *,int,bool,bool);
std::vector<double> soverBOptimizedBinning(TH1F *,TH1F*,int,double);
std::vector<double> significanceOptimizedBinning(TH1F *hs,TH1F *hb,int nTargetBins);
double calculateSig(double s1, double s2, double b1, double b2);
double calculateSigMulti(std::vector<double> &s1, std::vector<double> &b1);
double calculateSigMulti(double *s1, double *b1, int nchannel);
bool compareLHWide(double s1, double sdiff,double s2,double b1,double bdiff, double b2,double n, std::vector<double> &chanS, std::vector<double> &chanB);
double getNormalisationFromFit(std::string,std::string,RooAbsPdf *,RooRealVar*,double,double,bool,bool);
std::pair<double,double> getNormalisationAndErrorFromFit(std::string,std::string,RooAbsPdf *,RooRealVar*,double,double,bool,bool);
void getArgSetParameters(RooArgSet*,std::vector<double> &);
void setArgSetParameters(RooArgSet*,std::vector<double> &);
void maxSigScan(double *maximumSignificance,int *frozen_counters,int *chosen_counters,TH1F *hs, TH1F *hb, int N,int *counters, int movingCounterIndex);
std::map<std::string,int> systematics_;
std::map<std::string,std::pair<double,double> > global_systematics_;
std::map<std::string,std::vector <std::pair<double,double> > > normalisation_systematics_;
std::map<std::string,int>::iterator it_sys;
std::string getweightName(std::string);
std::string getnormName(std::string);
std::string getcatName(std::string,int);
std::string getsysName(std::string,std::string);
std::string getsysindexName(std::string,std::string
,int,int);
std::vector<RooAbsPdf*> pdf_saves_;
std::map<std::string, RooRealVar> m_real_var_;
std::map<std::string, RooFormulaVar> m_form_var_;
std::map<std::string, RooAbsPdf*> m_gen_;
std::map<std::string, RooExtendPdf> m_exp_;
std::map<std::string, RooAddPdf> m_pdf_;
std::map<std::string, std::vector<RooRealVar*> > m_comp_pdf_norm_;
std::map<std::string, TH1F> m_th1f_;
std::map<std::string, double> m_var_min_;
std::map<std::string, double> m_var_max_;
std::map<std::string,RooDataSet> data_;
std::map<std::string,std::string> data_obs_names_;
std::map<std::string,RooRealVar*> m_data_var_ptr_;
std::map<std::string,RooRealVar*> m_weight_var_ptr_;
std::map<std::string,std::vector<RooDataSet*> > data_up_;
std::map<std::string,std::vector<RooDataSet*> > data_dn_;
std::map<std::string,std::vector<TH1F*> > m_th1f_up_;
std::map<std::string,std::vector<TH1F*> > m_th1f_dn_;
std::map<std::string,int> bins_;
std::map<std::string,double> inits_;
std::map<RooPlot*,double> fit_res_;
std::vector<TCanvas*> fit_canvases_;
std::map<std::string,RooFitResult*> fit_results_;
std::map<std::string,RooAbsReal* > latestFitRangeIntegral_;
std::map<std::string,RooAbsReal* > DUMP_;
double *signalVector1;
double *backgroundVector1;
int g_step;
int sweepmode;
bool blind_data;
RooWorkspace ws;
};
#endif