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fitter.cxx
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#include <stdio.h>
#include <iostream>
#include <iomanip>
#include <vector>
#include <map>
#ifndef __CINT__
#include "RooGlobalFunc.h"
#endif
#include "RooAbsReal.h"
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooAddPdf.h"
#include "RooDataHist.h"
#include "RooProdPdf.h"
#include "RooHistPdf.h"
#include "RooPlot.h"
#include "RooRandom.h"
#include "RooExtendPdf.h"
#include "RooCBShape.h"
#include "RooMCStudy.h"
#include "RooWorkspace.h"
#include "RooFitResult.h"
#include "TROOT.h"
#include "TFile.h"
#include "TTree.h"
#include "TCanvas.h"
#include "TString.h"
#include "TAxis.h"
#include "TF1.h"
#include "TH1.h"
#include "TH2D.h"
#include "TLegend.h"
#include "TMath.h"
#include "../macro/rootlogon.C"
#include "PDFLIB.h"
#include "envelope.h"
using namespace std;
using namespace RooFit;
void makeSigPlot(RooRealVar* Mgg,vector<RooAbsPdf*> Gaussians ,string proc, RooDataSet* MC){
rootlogon();
int color[7] = {kBlue,kRed,kMagenta,kGreen+1,kOrange+7,kAzure+10,kBlack};
RooPlot* sframe = Mgg->frame(Bins(40),Range(115.,135.));
MC->plotOn(sframe,MarkerStyle(20));
TObject *pdfLeg0 = sframe->getObject(int(sframe->numItems())-1);
TLegend leg(0.7,0.7,1.,0.92);
leg.AddEntry(pdfLeg0,Form("%s_126",proc.c_str()),"LP");
int order = 1;
for(vector<RooAbsPdf*>::iterator it = Gaussians.begin();it != Gaussians.end();++it){
(*it)->plotOn(sframe,LineColor(color[order-1]));
TObject *pdfLeg = sframe->getObject(int(sframe->numItems()-1));
leg.AddEntry(pdfLeg,Form("%d order",order),"L");
order++;
}
TCanvas canv("canv","canv",700,600);
TPad pad("pad","",0.,0.,0.98,0.98);
canv.cd();
pad.SetLeftMargin(0.20);
pad.SetRightMargin(0.03);
pad.Draw();
pad.cd();
sframe->SetXTitle("M_{#gamma#gamma} (GeV)");
sframe->GetYaxis()->SetTitleOffset(1.35);
sframe->Draw();
leg.SetFillStyle(0);
leg.SetBorderSize(0);
leg.Draw();
canv.Print(Form("fitresult/%s.pdf",proc.c_str()));
}
double getGoodnessOfFit(RooRealVar* mass, RooAbsPdf* bkgPDF, RooDataSet* data){
RooRealVar norm("norm","norm",data->sumEntries(),0,10e6);
RooExtendPdf* pdf = new RooExtendPdf("ext","ext",*bkgPDF,norm);
RooPlot *plot_chi2 = mass->frame();
data->plotOn(plot_chi2,Binning(320),Name("data"));
pdf->plotOn(plot_chi2,Name("pdf"));
int np = pdf->getParameters(*data)->getSize();
double chi2 = plot_chi2->chiSquare("pdf","data",np);
double prob = TMath::Prob(chi2*(320-np),320-np);
return prob;
delete pdf;
}
map<string,int> plot(RooRealVar* Mgg,map<string,int>candPDF, RooDataSet* BkgDataSet, string* bestpdf, int* bestorder){
rootlogon();
map<string,int> tmp;
map<TString,TObject*> multipdfleg;
int color[7] = {kBlue,kRed,kMagenta,kGreen+1,kOrange+7,kAzure+10,kBlack};
Mgg->setRange("Range1",100.,115.);
Mgg->setRange("Range2",135.,180.);
RooPlot* bframe = Mgg -> frame(Title("Mgg"),Bins(80));
BkgDataSet->plotOn(bframe,MarkerStyle(20),CutRange("Range1,Range2"));
TLegend leg(0.6,0.7,0.9,0.92);
TObject *pdfLeg0 = bframe->getObject(int(bframe->numItems())-1);
leg.AddEntry(pdfLeg0,"Data","LP");
string bestfit = "";
int best_order = 0;
int j = 0;
double mincorre = 10e8;
for(map<string,int>::iterator it = candPDF.begin();it!=candPDF.end();++it){
int order = 1;
while(order<=it->second){
RooAbsPdf* bkgCandPDf = BkgPdfbuild(Mgg,it->first,order);
if(!bkgCandPDf){ order++; continue;}
RooFitResult* res = bkgCandPDf->fitTo(*BkgDataSet,Minimizer("Minuit2","minimize"),Save(true),Verbose(false),SumW2Error(true));
double prob = getGoodnessOfFit(Mgg,bkgCandPDf,BkgDataSet);
if(order!=it->second && prob <0.01){ order++;continue; }
double correction = 2*res->minNll()+order;
if(correction<mincorre){
mincorre = correction;
bestfit = it->first;
best_order = order;
}
cout << setw(15) << it->first << order << " ----> 2NLL + lambda(nparams) = " << correction <<endl;
bkgCandPDf -> plotOn(bframe,LineColor(color[j]));
TObject *pdfLeg = bframe->getObject(int(bframe->numItems())-1);
tmp.insert(make_pair(it->first,order));
multipdfleg.insert(make_pair(Form("%s_%d",(it->first).c_str(),order),pdfLeg));
order++;
j++;
}
}
*bestpdf = bestfit;
*bestorder = best_order;
cout << "----> Best fit : " << bestfit << best_order << endl;
for(map<TString,TObject*>::iterator it = multipdfleg.begin();it!=multipdfleg.end();++it){
if(it->first == Form("%s_%d",bestfit.c_str(),best_order) ) leg.AddEntry(it->second,it->first + "(best of fit)","L");
else leg.AddEntry(it->second,it->first,"L");
}
TCanvas canv("canv","",700,600);
canv.cd();
bframe->Draw();
bframe->SetXTitle("M_{#gamma#gamma} (GeV)");
leg.SetFillStyle(0);
leg.SetBorderSize(0);
leg.Draw();
canv.Print("fitresult/bkg.pdf");
return tmp;
}
int main(){
//Option
//-------------------------------------------------------------------------------------
double nBDTbin = 100;
bool _doMCStudy = false;
double LUMI = 30.;
RooMsgService::instance().setGlobalKillBelow(RooFit::ERROR);
RooMsgService::instance().setSilentMode(true);
//Input Information
//-------------------------------------------------------------------------------------
TString inpath = "/wk_cms/youying/Analysis3/fitter/";
TString infile = "DataSet.root";
system("mkdir -p fitresult");
TFile*myfile = TFile::Open( inpath + infile );
RooWorkspace* WS = (RooWorkspace*)myfile->Get("ws");
//Observable(Mgg,BDT)
//---------------------------------------------------------------------------------
RooRealVar* Mgg = (RooRealVar*)WS->var("Mgg");
RooRealVar* BDT = (RooRealVar*)WS->var("BDT");
//DataSet
//---------------------------------------------------------------------------------
RooDataSet* Hgg_vbf_126 = (RooDataSet*)WS->data("Hgg_vbf_126");
RooDataSet* Hgg_ggf_126 = (RooDataSet*)WS->data("Hgg_ggf_126");
RooDataSet* Hgg_vbf_126w = (RooDataSet*)WS->data("Hgg_vbf_126w");
RooDataSet* Hgg_ggf_126w = (RooDataSet*)WS->data("Hgg_ggf_126w");
RooDataSet* bkg = (RooDataSet*)WS->data("bkg_13TeV");
RooDataSet* data = (RooDataSet*)WS->data("data");
//Signal Model Construction
//-------------------------------------------------------------------------------------
int MH =126;
map<string,RooDataSet*> sigdataset;
map<string,RooDataSet*> sigdatasetw;
sigdataset["vbf"] = (RooDataSet*)(Hgg_vbf_126->reduce(RooArgSet(*Mgg)));
sigdataset["ggf"] = (RooDataSet*)(Hgg_ggf_126->reduce(RooArgSet(*Mgg)));
//To get expexted yields
sigdatasetw["vbf"] = (RooDataSet*)(Hgg_vbf_126w->reduce(RooArgSet(*Mgg)));
sigdatasetw["ggf"] = (RooDataSet*)(Hgg_ggf_126w->reduce(RooArgSet(*Mgg)));
//F-Test
//--------------------------------------------------------------------------------------
cout << "[INFO]: Start to construct the signal model by using f-test" << endl;
cout << "-----------------------------------------------------------------------"<<endl;
map<string, RooAbsPdf*> SignalPDF;
for(map<string,RooDataSet*>::iterator it=sigdataset.begin();it!=sigdataset.end();++it){
int pre_order = 0;
int best_order = 0;
double thisNll = 0;
double preNll = 0;
double chi2 = 0;
double prob = 0;
int status = 0;
vector<RooAbsPdf*> Gaussians;
cout << "[INFO]: Start to handle " << it->first << " ....." << endl;
for(int order=1;order<7;order++){
RooAbsPdf* SigMggPdf = buildMultiGaussians(Mgg,order,MH,false,it->first,it->second);
RooFitResult* fitres = SigMggPdf->fitTo(*(it->second),Minimizer("Minuit2","minimize"),Save(true),Verbose(false),SumW2Error(true),Range(115.,135.));
thisNll = fitres->minNll();
chi2 = 2.*(preNll - thisNll);
if(order > 1 && chi2 < 0 ) chi2 = 0;
int delta_dof = (2*order+(order-1))-(2*pre_order+(pre_order-1));
prob = TMath::Prob(chi2,delta_dof);
status = fitres->status();
printf("............ This order = %d, Pre Order = %d ,p-value = %1.2e, status = %d \n",order,pre_order,prob,status);
if(prob>0.05) break;
Gaussians.push_back(SigMggPdf);
pre_order = order;
preNll = thisNll;
}
best_order = pre_order;
cout << "----> Best Order is " << best_order << "(number of gaussians)." << endl;
//best_order = 1;
makeSigPlot(Mgg,Gaussians,it->first,it->second);
RooAbsPdf* bestSigPDF = buildMultiGaussians(Mgg,best_order,MH,true/*Do fit*/,it->first,it->second);
cout << "-----------------------------------------------------------------------"<<endl;
SignalPDF.insert(make_pair(it->first,bestSigPDF));
}
map<string, RooExtendPdf*> extSignalPDF;
for(map<string,RooAbsPdf*>::iterator it = SignalPDF.begin();it!=SignalPDF.end();++it){
RooRealVar* norm = new RooRealVar("norm","",sigdatasetw[it->first]->sumEntries(),-1000.,1000.);
norm->setConstant(true);
RooExtendPdf* extsigpdf = new RooExtendPdf(Form("%s_Extend",(it->first).c_str()),"",*(it->second),*norm);
extSignalPDF.insert(make_pair(it->first,extsigpdf));
}
cout << "[INFO]: Signal construction has Finished." << endl;
cout << "*******************************************************************************************" << endl << endl;
//Background Shapes Construction
//-----------------------------------------------------------------------------------------------------------------------------------
vector<string>PDFfamily;
PDFfamily.push_back("Bernstein");
PDFfamily.push_back("Laurent");
PDFfamily.push_back("PowerLaw");
//PDFfamily.push_back("PowerLaw2");
PDFfamily.push_back("Exponential");
//PDFfamily.push_back("Exponential2");
//Use the dataSet of real data
RooDataSet* BkgDataSet = (RooDataSet*)data->reduce(RooArgSet(*Mgg));
//F-Test
//---------------------------------------------------------------------------------------------------------------------------
cout << "[INFO]: Start to construct the background shape by using f-test" << endl;
cout << "-----------------------------------------------------------------------"<<endl;
map<string,int>candPDF;
for(vector<string>::iterator it = PDFfamily.begin();it!=PDFfamily.end();++it){
int order = 1;
int pre_order = 0;
int cache_order = 0;
int highest_order = 0;
double thisNll = 0.;
double preNll = 10e8;
double chi2 = 0.;
double prob = 0.;
int status = 0;
cout <<"[INFO]:"<< *it << " function family... " << endl;
while(order<7 && prob < 0.05 ){
RooAbsPdf* bkgCandPDf = BkgPdfbuild(Mgg,*it,order);
if(!bkgCandPDf){
order++;
}else{
RooFitResult* fitres = bkgCandPDf->fitTo(*BkgDataSet,Minimizer("Minuit2","minimize"),Save(true),Verbose(false),SumW2Error(true));
thisNll = fitres->minNll();
chi2 = 2.*(preNll - thisNll);
if(order > 1 && chi2 < 0 ) chi2 = 0;
int delta_dof = order - pre_order;
prob = TMath::Prob(chi2,delta_dof);
status = fitres ->status();
printf("............ This order = %d, Pre Order = %d ,p-value = %1.2e, status = %d \n",order,pre_order,prob,status);
cache_order = pre_order;
pre_order = order;
preNll = thisNll;
order++;
}
}
highest_order = cache_order;
candPDF.insert(pair<string,int>(*it,highest_order));
cout << "----> The highest order is " << highest_order << endl;
cout << "-----------------------------------------------------------------------" << endl;
}
cout << "[INFO]: f-test has finished." << endl;
cout << "[INFO]: Decide which pdf is the best." << endl;
cout << "-----------------------------------------------------------------------" << endl;
string bestPDF = "";
int best_order = 0;
map<string,int> multipdf = plot(Mgg,candPDF,BkgDataSet,&bestPDF,&best_order);
RooAbsPdf* MggBkgShape = BkgPdfbuild(Mgg,bestPDF,best_order,true/*Do fit*/,BkgDataSet);
cout << "-----------------------------------------------------------------------" << endl;
cout << "[INFO]: Do envelope plot" << endl;
cout << "-----------------------------------------------------------------------" << endl;
envelope(Mgg,multipdf,BkgDataSet,bestPDF,best_order,extSignalPDF,true/*blind*/,true/*addSignal*/,false/*combine*/);
cout << "-----------------------------------------------------------------------" << endl;
cout << "[INFO]: Background shape construction has finiched" << endl;
cout << "*******************************************************************************************" << endl << endl;
//BDT Shapes Test
//-------------------------------------------------------------------------------------------------------------------------------------------------------
RooDataSet* vbfBDT = (RooDataSet*)Hgg_vbf_126->reduce(RooArgSet(*BDT));
RooDataSet* ggfBDT = (RooDataSet*)Hgg_ggf_126->reduce(RooArgSet(*BDT));
RooDataSet* bkgBDT = (RooDataSet*)bkg->reduce(RooArgSet(*BDT));
RooDataSet* dataBDT = (RooDataSet*)data->reduce(RooArgSet(*BDT));
RooAbsPdf* vbfBDTPDF;
RooAbsPdf* ggfBDTPDF;
RooAbsPdf* bkgBDTPDF;
bool isBinnedBDT = false;
if(isBinnedBDT){
BDT->setBins(nBDTbin);
RooDataHist*DHvbfBDT = vbfBDT->binnedClone();
RooDataHist*DHggfBDT = ggfBDT->binnedClone();
RooDataHist*DHbkgBDT = bkgBDT->binnedClone();
RooHistPdf* HvbfBDTPDF = new RooHistPdf("HvbfBDTPDF","",RooArgSet(*BDT),*DHvbfBDT);
RooHistPdf* HggfBDTPDF = new RooHistPdf("HvbfBDTPDF","",RooArgSet(*BDT),*DHggfBDT);
RooHistPdf* HbkgBDTPDF = new RooHistPdf("HvbfBDTPDF","",RooArgSet(*BDT),*DHbkgBDT);
vbfBDTPDF = (RooAbsPdf*)HvbfBDTPDF->Clone();
ggfBDTPDF = (RooAbsPdf*)HggfBDTPDF->Clone();
bkgBDTPDF = (RooAbsPdf*)HbkgBDTPDF->Clone();
}
//VBF Unbinned Shape
//------------------------------------------------------------------------------------------------------
RooRealVar* BDTmean = new RooRealVar("BDTmean","BDTmean",1.,0,10);
RooRealVar* sigma = new RooRealVar("sigma","sigma" ,0.2,0,10);
RooRealVar* alpha = new RooRealVar("alpha","alpha" ,1.,0,10);
RooRealVar* n = new RooRealVar("n","n" ,1.3,0,10);
vbfBDTPDF = new RooCBShape("vbfBDTPDF","vbfBDTPDF",*BDT,*BDTmean,*sigma,*alpha,*n);
vbfBDTPDF->fitTo(*vbfBDT,Minimizer("Minuit2","minimize"),SumW2Error(true));
BDTmean -> setConstant(true);
sigma -> setConstant(true);
alpha -> setConstant(true);
n -> setConstant(true);
RooPlot* VBFBDTframe = BDT->frame(Bins(nBDTbin));
vbfBDT->plotOn(VBFBDTframe,DataError(RooAbsData::SumW2));
vbfBDTPDF->plotOn(VBFBDTframe);
TCanvas canv1("c1","c1",650,600);
canv1.cd();VBFBDTframe->Draw();canv1.Print("fitresult/VBFBDT.pdf");
//GGF Unbinned Shape
//------------------------------------------------------------------------------------------------------
RooRealVar* gBDTmean = new RooRealVar("gBDTmean","gBDTmean",1,0,10);
RooRealVar* gsigma = new RooRealVar("gsigma" ,"gsigma" ,0.2,0,10);
RooRealVar* galpha = new RooRealVar("galpha" ,"galpha" ,1,0,10);
RooRealVar* gn = new RooRealVar("gn" ,"gn" ,1.3,0,10);
ggfBDTPDF = new RooCBShape("ggfBDTPDF","ggfBDTPDF",*BDT,*gBDTmean,*gsigma,*galpha,*gn);
ggfBDTPDF->fitTo(*ggfBDT,Minimizer("Minuit2","minimize2"),SumW2Error(true));
gBDTmean->setConstant(true);
gsigma ->setConstant(true);
galpha ->setConstant(true);
gn ->setConstant(true);
RooPlot* GGFBDTframe = BDT->frame(Bins(nBDTbin));
ggfBDT->plotOn(GGFBDTframe,DataError(RooAbsData::SumW2));
ggfBDTPDF->plotOn(GGFBDTframe);
TCanvas canv2("c2","c2",650,600);
canv2.cd();GGFBDTframe->Draw();canv2.Print("fitresult/GGFBDT.pdf");
//Background Unbinned Shape
//------------------------------------------------------------------------------------------------------
bkgBDTPDF = BkgPdfbuild(BDT,"Bernstein",3,true,dataBDT);
RooPlot* bkgBDTframe = BDT->frame(Title("BDT"),Bins(nBDTbin));
dataBDT->plotOn(bkgBDTframe,DataError(RooAbsData::SumW2));
bkgBDTPDF->plotOn(bkgBDTframe);
TCanvas canv3("canv3","canv3",650,600);
canv3.cd();bkgBDTframe->Draw();canv3.Print("fitresult/ContBDT.pdf");
//Conbine Shapes(1D * 1D shapes)
//---------------------------------------------------------------------------------------------------------------------------------------
//Calculate Scale Factor
RooDataSet* sMCDataSet = (RooDataSet*)bkg->reduce(RooArgSet(*Mgg),"!(Mgg>120&&Mgg<130)");
RooDataSet* sBkgDataSet = (RooDataSet*)data->reduce(RooArgSet(*Mgg),"!(Mgg>120&&Mgg<130)");
double scale = sBkgDataSet->sumEntries()/sMCDataSet->sumEntries();
//VBF 1D*1D
double SM_VBF = sigdatasetw["vbf"]->sumEntries() /12.887*LUMI;
RooRealVar* N_vbf = new RooRealVar("N_vbf","N_vbf", SM_VBF, -1000, 1000);
RooProdPdf*h2dVBFPDF = new RooProdPdf("h2dVBFPDF","Mgg*BDT",*(SignalPDF["vbf"]),*vbfBDTPDF);
//GGF 1D*1D
double SM_GGF = sigdatasetw["ggf"]->sumEntries() /12.887*LUMI;
RooRealVar* N_ggf = new RooRealVar("N_ggf","N_ggf", SM_GGF, -1000, 1000);
RooProdPdf* h2dGGFPDF = new RooProdPdf("h2dGGFPDF","Mgg*BDT",*(SignalPDF["ggf"]),*ggfBDTPDF);
//Bkg 1D*1D
RooDataSet* MCDataSet = (RooDataSet*)bkg->reduce(RooArgSet(*Mgg));
double SM_Bkg = MCDataSet->sumEntries() /12.887*LUMI*scale;
RooRealVar* N_Bkg = new RooRealVar("N_gj","N_gj", SM_Bkg, 0, 20000);
RooProdPdf* h2dBkgPDF = new RooProdPdf("h2dBkgPDF","Mgg*BDT",*MggBkgShape,*bkgBDTPDF);
//Store the shapes into the same workspace file
RooWorkspace outws("outws");
outws.import(*h2dVBFPDF);
outws.import(*h2dGGFPDF);
outws.import(*h2dBkgPDF);
outws.import(*data);
outws.writeToFile("FinalResult.root",true);
outws.Print();
//Make Plots about the Results of 1D*1D Fitting
//----------------------------------------------------------------------------------------------------------------------------------------
rootlogon();
//Ext PDF
//------------------------------------------------------------------------------------------------------------
RooExtendPdf* exth2dVBFPDF = new RooExtendPdf("exh2dVBFPDF","",*h2dVBFPDF,*N_vbf);
RooExtendPdf* exth2dGGFPDF = new RooExtendPdf("exh2dGGFPDF","",*h2dGGFPDF,*N_ggf);
RooExtendPdf* exth2dBkgPDF = new RooExtendPdf("exh2dBkgPDF","",*h2dBkgPDF,*N_Bkg);
//Totally Conbime
//------------------------------------------------------------------------------------------------------------
RooAddPdf* model = new RooAddPdf("model","model",RooArgList(*exth2dVBFPDF,*exth2dGGFPDF,*exth2dBkgPDF));
//Total 1D*1D PDF Plot
//-------------------------------------------------------------------------------------------
TCanvas canv4("canv4","",600,600);
canv4.cd();
TH1* h2model = model->createHistogram("Mgg,BDT",80,100);
h2model->SetLineColor(kBlue);
h2model->Draw("surf");
//h2model->Draw("histo");
canv4.SetPhi(220);
canv4.Print("fitresult/Fit2d.pdf");
//Decouple to Mgg and BDT
//-------------------------------------------------------------------------------------------
int gen_num = SM_VBF + SM_GGF + SM_Bkg;
RooDataSet* fakedata = model->generate(RooArgSet(*Mgg,*BDT),gen_num);
TCanvas canv5("canv5","",1300,600);
canv5.Divide(2,1);
//Mgg
//-------------------------------------
canv5.cd(1);
RooPlot* Mggframe = Mgg->frame(Bins(80),Range(100,180));
fakedata->plotOn(Mggframe);
TObject* dataleg = (TObject*)Mggframe->getObject(Mggframe->numItems()-1);
model->plotOn(Mggframe) ;
TObject* totalleg = (TObject*)Mggframe->getObject(Mggframe->numItems()-1);
model->plotOn(Mggframe,Components(*exth2dVBFPDF),LineColor(kGreen),LineStyle(kDashed));
TObject* vbfleg = (TObject*)Mggframe->getObject(Mggframe->numItems()-1);
model->plotOn(Mggframe,Components(*exth2dGGFPDF),LineColor(kRed),LineStyle(kDashed));
TObject* ggfleg = (TObject*)Mggframe->getObject(Mggframe->numItems()-1);
model->plotOn(Mggframe,Components(*exth2dBkgPDF),LineColor(kBlack),LineStyle(kDashed));
TObject* bkgleg = (TObject*)Mggframe->getObject(Mggframe->numItems()-1);
Mggframe->SetXTitle("M_{#gamma#gamma} (GeV)");
Mggframe->Draw();
TLegend* leg1 = new TLegend(0.65, 0.75, 0.88, 0.93);
leg1->AddEntry(dataleg,Form("pseudo data %.1f fb^{-1}",LUMI),"LP");
leg1->AddEntry(totalleg,"MggPDF","L");
leg1->AddEntry(vbfleg,"VBF","L");
leg1->AddEntry(ggfleg,"GGF","L");
leg1->AddEntry(bkgleg,"Continuum","L");
leg1->SetFillStyle(0);
leg1->SetBorderSize(0);
leg1->Draw();
//BDT
//-----------------------------------------------------------------------------------------------------------------
canv5.cd(2);
RooPlot* BDTframe = BDT->frame(Bins(100)) ;
fakedata->plotOn(BDTframe);
TObject* datalegb = (TObject*)BDTframe->getObject(BDTframe->numItems()-1);
model->plotOn(BDTframe) ;
TObject* totallegb = (TObject*)BDTframe->getObject(BDTframe->numItems()-1);
model->plotOn(BDTframe,Components(*exth2dVBFPDF),LineColor(kGreen),LineStyle(kDashed),RooFit::Normalization(10));
TObject* vbflegb = (TObject*)BDTframe->getObject(BDTframe->numItems()-1);
model->plotOn(BDTframe,Components(*exth2dGGFPDF),LineColor(kRed),LineStyle(kDashed),RooFit::Normalization(10));
TObject* ggflegb = (TObject*)BDTframe->getObject(BDTframe->numItems()-1);
model->plotOn(BDTframe,Components(*exth2dBkgPDF),LineColor(kBlack),LineStyle(kDashed));
TObject* bkglegb = (TObject*)BDTframe->getObject(BDTframe->numItems()-1);
BDTframe->SetXTitle("dijet BDT");
BDTframe->Draw();
TLegend* leg2 = new TLegend(0.65, 0.75, 0.88, 0.93);
leg2->AddEntry(datalegb,Form("pseudo data %.1f fb^{-1}",LUMI),"LP");
leg2->AddEntry(totallegb,"BDTPDF","L");
leg2->AddEntry(vbflegb,"VBF x10","L");
leg2->AddEntry(ggflegb,"GGF x10","L");
leg2->AddEntry(bkglegb,"Continuum","L");
leg2->SetFillStyle(0);
leg2->SetBorderSize(0);
leg2->Draw();
canv5.Print("fitresult/MggvsBDT.pdf");
//MC Study
//--------------------------------------------------------------------------------------------------------------------------------------------
if(_doMCStudy){
RooMCStudy* mcstudy = new RooMCStudy(*model,RooArgSet(*Mgg,*BDT),Binned(false),Silence(),Extended(),FitOptions(Save(kTRUE),SumW2Error(true),Verbose(kFALSE),PrintEvalErrors(0)));
//RooMCStudy* mcstudy = new RooMCStudy(*model,RooArgSet(*Mgg,*BDT),Binned(false),Silence(),Extended(),FitOptions(Save(kTRUE),Verbose(kFALSE),PrintEvalErrors(0)));
mcstudy->generateAndFit(1000);
//RooPlot* MCframe1 = mcstudy->plotParam(*N_vbf,Bins(100)) ;
//RooPlot* MCframe2 = mcstudy->plotError(*N_vbf,Bins(100)) ;
RooPlot* MCframe3 = mcstudy->plotPull(*N_vbf,Bins(50) ,FitGauss(kTRUE)) ;
//RooPlot* MCframe4 = mcstudy->plotParam(*N_ggf,Bins(100)) ;
//RooPlot* MCframe5 = mcstudy->plotError(*N_ggf,Bins(100)) ;
RooPlot* MCframe6 = mcstudy->plotPull(*N_ggf,Bins(50) ,FitGauss(kTRUE)) ;
TCanvas canv6("canv6","",1300,600);
canv6.Divide(2,1);
//canv6->cd();MCframe1->Draw();
//canv6->cd();MCframe2->Draw();
canv6.cd(1);MCframe3->Draw();
//canv6->cd();MCframe4->Draw();
//canv6->cd();MCframe5->Draw();
canv6.cd(2);MCframe6->Draw();
canv6.Print("fitresult/pull.pdf");
}
return 0;
}