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X2qVFitter.cc
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X2qVFitter.cc
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using namespace RooFit;
using namespace RooStats ;
static const Int_t NCAT = 8; //for VV and qV analysis together this should be 6--> Now 21!
Double_t MMIN = 1050.;
Double_t MMAX = 6200.;
Double_t CHANNEL = 1; //1==VV 2==qV 3==noPurity
std::string filePOSTfix="";
double signalScaler=35867.*0.01/(100000.); // assume signal cross section of 0.01pb=10fb and 1263.890/pb of luminosity (The factor 10000. is the number of gen events that is set to 10000. for all samples in the interpolation script. Dividing out BR(V-->had)=70% for non-inclusive samples
double scaleFactorHP=0.99; // ICHEP 1.03 tau21 and jet mass scale factors data/MC
double scaleFactorLP=1.03; // ICHEP 0.88 tau21 and jet mass scale factors data/MC
string directory = "/usr/users/dschaefer/CMSSW_7_4_7/src/DijetCombineLimitCode/" ;
TColor *col = new TColor();
// void AddSigData(RooWorkspace*, Float_t);
// void AddBkgData(RooWorkspace*);
// void SigModelFit(RooWorkspace*, Float_t);
// RooFitResult* BkgModelFitBernstein(RooWorkspace*, Bool_t);
// void MakePlots(RooWorkspace*, Float_t, RooFitResult* , TString signalname);
// void MakeSigWS(RooWorkspace* w, const char* filename);
// void MakeBkgWS(RooWorkspace* w, const char* filename);
void SetConstantParams(const RooArgSet* params);
void AddSigData(RooWorkspace* w, Float_t mass, int signalsample, std::vector<string> cat_names);
void AddBkgData(RooWorkspace* w, std::vector<string> cat_names);
void SigModelFit(RooWorkspace* w, Float_t mass, TString signalname, std::vector<string> cat_names);
std::vector<RooFitResult*> BkgModelFitBernstein(std::string altfunc, RooWorkspace* w, Bool_t dobands, std::vector<string> cat_names);
void MakePlots(RooWorkspace* w, Float_t mass, std::vector<RooFitResult*> fitresults, TString signalname, std::vector<string> cat_names);
void MakeSigWS(RooWorkspace* w, const char* fileBaseName, TString signalname, std::vector<string> cat_names);
void MakeBkgWS(std::string altfunc,RooWorkspace* w, const char* fileBaseName, std::vector<string> cat_names);
void MakeDataCard_1Channel(RooWorkspace* w, const char* fileBaseName, const char* fileBkgName, int iChan, TString signalname, int signalsample, std::vector<string> cat_names, double mass);
RooArgSet* defineVariables()
{
// define variables of the input ntuple
RooRealVar* mgg = new RooRealVar("mgg13TeV","M(jet-jet)",MMIN,MMAX,"GeV");
RooRealVar* evWeight = new RooRealVar("evWeight","Reweightings",0,100,"");
RooRealVar* normWeight = new RooRealVar("normWeight","Additionnal Weight",0,10000000,"");
RooCategory* categories = new RooCategory("categories","event category NCAT") ;
categories->defineType("highPureVV",0);
categories->defineType("lowPureVV",1);
categories->defineType("highPureWW",2);
categories->defineType("lowPureWW",3);
categories->defineType("highPureWZ",4);
categories->defineType("lowPureWZ",5);
categories->defineType("highPureZZ",6);
categories->defineType("lowPureZZ",7);
categories->defineType("highPureqV",8);
categories->defineType("lowPureqV",9);
categories->defineType("highPureqW",10);
categories->defineType("lowPureqW",11);
categories->defineType("highPureqZ",12);
categories->defineType("lowPureqZ",13);
categories->defineType("noPureVV",14);
categories->defineType("noPureWW",15);
categories->defineType("noPureWZ",16);
categories->defineType("noPureZZ",17);
categories->defineType("noPureqV",18);
categories->defineType("noPureqW",19);
categories->defineType("noPureqZ",20);
RooArgSet* ntplVars = new RooArgSet(*mgg, *categories, *evWeight, *normWeight);
return ntplVars;
}
void runfits(const Float_t mass=2000, int signalsample = 1, int channel = 1,std::string altfunc="" , Bool_t dobands = false)
{
CHANNEL = channel;
std::cout << "CHANNEL == " << CHANNEL << std::endl;
if(CHANNEL==1)NCAT == 8;
else if(CHANNEL==2){
NCAT == 4;
}
else if(CHANNEL==3)NCAT == 7;
//******************************************************************//
// Running mode corresponds to the following cases
// - full run set:
// - create signal and background data sets
// - make and fit signal and background models
// - write signal and background workspaces in root files
// - write data card
//*******************************************************************//
TString signalname;
if (signalsample==0){
signalname="RS1ZZ";
}
if (signalsample==1){
signalname="RS1WW";
}
if (signalsample==2){
signalname="WZ";
}
if (signalsample==3){
signalname="ZprimeWW";
}
if (signalsample==4){
signalname="BulkWW";
}
if (signalsample==5){
signalname="BulkZZ";
}
if (signalsample==6){
signalname="qW";
}
if (signalsample==7){
signalname="qZ";
}
std::cout<< signalname<<std::endl;
TString fileBaseName("CMS_jj_"+signalname+TString::Format("_%.0f_13TeV", mass));
vector<string> cat_names;
cat_names.push_back("CMS_jj_VVHP");
cat_names.push_back("CMS_jj_VVLP");
cat_names.push_back("CMS_jj_WWHP");
cat_names.push_back("CMS_jj_WWLP");
cat_names.push_back("CMS_jj_WZHP");
cat_names.push_back("CMS_jj_WZLP");
cat_names.push_back("CMS_jj_ZZHP");
cat_names.push_back("CMS_jj_ZZLP");
cat_names.push_back("CMS_jj_qVHP");
cat_names.push_back("CMS_jj_qVLP");
cat_names.push_back("CMS_jj_qWHP");
cat_names.push_back("CMS_jj_qWLP");
cat_names.push_back("CMS_jj_qZHP");
cat_names.push_back("CMS_jj_qZLP");
cat_names.push_back("CMS_jj_VVNP");
cat_names.push_back("CMS_jj_WWNP");
cat_names.push_back("CMS_jj_WZNP");
cat_names.push_back("CMS_jj_ZZNP");
cat_names.push_back("CMS_jj_qVNP");
cat_names.push_back("CMS_jj_qWNP");
cat_names.push_back("CMS_jj_qZNP");
TString fileBkgName("CMS_jj_bkg_qV"+altfunc+TString::Format("_13TeV", mass));
TString card_name("qv_models_Bkg_13TeV.rs");
if (altfunc.find("alt")!=std::string::npos)
{
card_name = TString("qv_"+altfunc+"models_Bkg_13TeV.rs");
fileBaseName = TString("CMS_jj_"+altfunc+signalname+TString::Format("_%.0f_13TeV", mass));
}
HLFactory hlf("HLFactory", card_name, false);
RooWorkspace* w = hlf.GetWs();
std::vector<RooFitResult*> fitresults;
w->var("mgg13TeV")->setMin(MMIN);
w->var("mgg13TeV")->setMax(MMAX);
// Add data to the workspace
cout << "SIGNAL SAMPLE = " << signalsample << ".) "<< signalname<< endl;
cout << "CREATE SIGNAL" << endl;
AddSigData(w, mass, signalsample,cat_names);
// Add the signal and background models to the workspace.
// Inside this function you will find a discription our model.
// Fit data with models
cout << "FIT SIGNAL" << endl;
SigModelFit(w, mass, signalname,cat_names);
// Make statistical treatment
// Setup the limit on Higgs production
cout << "CREATE SIGNAL WS" << endl;
MakeSigWS(w, fileBaseName, signalname,cat_names);
// if(mass<1300){
cout << "CREATE BACKGROUND" << endl;
AddBkgData(w,cat_names);
cout << "FIT BACKGROUND" << endl;
fitresults = BkgModelFitBernstein(altfunc,w, dobands,cat_names);
cout << "CREATE BACKGROUND WS" << endl;
MakeBkgWS(altfunc,w, fileBkgName,cat_names);
// }
cout << "CREATE DATACARD" << endl;
if((signalsample==0)||(signalsample==1)||(signalsample==2)||(signalsample==3)||(signalsample==4)||(signalsample==5)){
if(CHANNEL==1){
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 0, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 1, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 2, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 3, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 4, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 5, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 6, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 7, signalname, signalsample, cat_names, mass);
}
else if(CHANNEL==3){
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 14, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 15, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 16, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 17, signalname, signalsample, cat_names, mass);
}
}
if((signalsample==6)||(signalsample==7)){
if(CHANNEL==2){
// MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 8, signalname, signalsample, cat_names, mass);
// MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 9, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 10, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 11, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 12, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 13, signalname, signalsample, cat_names, mass);
}
else if(CHANNEL==3){
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 18, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 19, signalname, signalsample, cat_names, mass);
MakeDataCard_1Channel(w, fileBaseName, fileBkgName, 20, signalname, signalsample, cat_names, mass);
}
}
cout << "MAKE PLOTS" << endl;
// Make plots for data and fit results
MakePlots(w, mass, fitresults, signalname,cat_names);
cout << "DONE WITH SIGNAL " << signalname << " FOR MASS POINT " << mass <<" GEV " << endl;
cout << "" << endl;
cout << "" << endl;
cout << "" << endl;
cout << "" << endl;
cout << "" << endl;
return;
}
void AddSigData(RooWorkspace* w, Float_t mass, int signalsample, std::vector<string> cat_names) {
// Int_t ncat = NCAT;
std::cout << "CHANNEL == " << CHANNEL << std::endl;
Int_t ncat_min = 0;
Int_t ncat = NCAT;
if(CHANNEL==1){
ncat_min = 0;
ncat = 8;
}
else if(CHANNEL==2){
ncat_min = 10;
ncat == 4;
}
else if(CHANNEL==3){
ncat_min = 14;
ncat = 7;
}
TString inDir = directory+"MiniTrees/Signal_qV_13TeV/";
Float_t MASS(mass);
// Float_t sqrts(21);
Float_t sqrts(21);
cout << " min = "<< ncat_min<<" ncat = "<<ncat << " max = " << ncat_min+ncat<<endl;
//****************************//
// Signal Data Set
//****************************//
// Variables
RooArgSet* ntplVars = defineVariables();
RooRealVar weightVar("weightVar","",1,0,1000);
//signal300_tree_radcut.root
int iMass = abs(mass);
// TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_QstarQWOUT%d_miniTree.root", iMass)));
// if (signalsample==1) {
// sigFile1.Close();
// TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_RS1WWOUT%d_miniTree.root", iMass)));
// }
// if (signalsample==2) {
// sigFile1.Close();
// TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_WZOUT%d_miniTree.root", iMass)));
// }
// if (signalsample==3) {
// sigFile1.Close();
// TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_ZprimeWWOUT%d_miniTree.root", iMass)));
// }
// if (signalsample==4) {
// sigFile1.Close();
// TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_BulkWWOUT%d_miniTree.root", iMass)));
// }
// if (signalsample==5) {
// sigFile1.Close();
// TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_BulkZZOUT%d_miniTree.root", iMass)));
// }
// if (signalsample==6) {
// sigFile1.Close();
// TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_QstarQWOUT%d_miniTree.root", iMass)));
// }
// if (signalsample==7) {
// sigFile1.Close();
// TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_QstarQZOUT%d_miniTree.root", iMass)));
// }
TString sigfilename = TString(Form("dijetVV_13TeV_RS1ZZOUT%d_miniTree.root", iMass));
//TFile sigFile1; //(inDir+TString(Form("dijetVV_13TeV_RS1ZZOUT%d_miniTree.root", iMass)));
if (signalsample==1) {
//sigFile1.Close();
//TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_RS1WWOUT%d_miniTree.root", iMass)));
sigfilename = TString(Form("dijetVV_13TeV_RS1WWOUT%d_miniTree.root", iMass));
}
if (signalsample==2) {
//sigFile1.Close();
//TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_WZOUT%d_miniTree.root", iMass)));
sigfilename = TString(Form("dijetVV_13TeV_WZOUT%d_miniTree.root", iMass));
}
if (signalsample==3) {
// sigFile1.Close();
// TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_ZprimeWWOUT%d_miniTree.root", iMass)));
sigfilename = TString(Form("dijetVV_13TeV_ZprimeWWOUT%d_miniTree.root", iMass));
}
if (signalsample==4) {
//sigFile1.Close();
//TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_BulkWWOUT%d_miniTree.root", iMass)));
sigfilename = TString(Form("dijetVV_13TeV_BulkWWOUT%d_miniTree.root", iMass));
}
if (signalsample==5) {
//sigFile1.Close();
//TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_BulkZZOUT%d_miniTree.root", iMass)));
sigfilename = TString(Form("dijetVV_13TeV_BulkZZOUT%d_miniTree.root", iMass));
}
if (signalsample==6) {
// sigFile1.Close();
// TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_QstarQWOUT%d_miniTree.root", iMass)));
sigfilename = TString(Form("dijetVV_13TeV_QstarQWOUT%d_miniTree.root", iMass));
}
if (signalsample==7) {
// sigFile1.Close();
// TFile sigFile1(inDir+TString(Form("dijetVV_13TeV_QstarQZOUT%d_miniTree.root", iMass)));
sigfilename = TString(Form("dijetVV_13TeV_QstarQZOUT%d_miniTree.root", iMass));
}
TFile sigFile1(inDir+sigfilename);
std::cout<< "Opening signal file: " << sigFile1.GetName() << std::endl;
TTree* sigTree1 = (TTree*) sigFile1.Get("TCVARS");
sigTree1->Print();
std::cout<< "Opening signal tree: " << sigTree1->GetName() << std::endl;
// add weight var into the list of ntuple variables
std::cout<< "Adding weight variable into the list of ntuple variables " << std::endl;
weightVar.setVal(1.);
ntplVars->add(RooArgList(weightVar));
// common preselection cut
TString mainCut("1");
//****************************//
// Signal Data Set
//****************************//
// Create non scaled signal dataset composed with different productions
// according to their cross sections
RooDataSet sigScaled("sigScaled","dataset",sigTree1,*ntplVars,mainCut,"evWeight");
// RooRealVar *scaleWeightVar1 = (RooRealVar*) (*ntplVars)["evWeight"] ;
// RooRealVar *scaleWeightVar2 = (RooRealVar*) (*ntplVars)["normWeight"] ;
// RooFormulaVar *scaleWeightVar3 = new RooFormulaVar( "scaleWeight3", "", "@0*@1",
// RooArgList(*scaleWeightVar1, *scaleWeightVar2));
sigScaled.Print("v");
RooDataSet* sigToFit[21];
// for (int c = 0; c < ncat; ++c) {
std::cout<< "Looping over N categories: " << ncat_min+ncat << std::endl;
for (int c = ncat_min; c < ncat_min+ncat; ++c) {
std::cout<< "Category: " << c << std::endl;
std::cout<< "Name: " << TString::Format("Sig_%s",cat_names.at(c).c_str()) << std::endl;
sigToFit[c] = (RooDataSet*) sigScaled.reduce(*w->var("mgg13TeV"),mainCut+TString::Format(" && categories==%d",c));
w->import(*sigToFit[c],Rename(TString::Format("Sig_%s",cat_names.at(c).c_str())));
}
std::cout<< "Create full signal data set without categorization: "<< std::endl;
// Create full signal data set without categorization
RooDataSet* sigToFitAll = (RooDataSet*) sigScaled.reduce(*w->var("mgg13TeV"),mainCut);
w->import(*sigToFitAll,Rename("Sig"));
// Create weighted signal dataset composed with different
// production processes according to their cross sections
// no common preselection cut applied yet
//RooRealVar *weightVar1 = (RooRealVar*) (*ntplVars)["evWeight"] ;
//RooRealVar *weightVar2 = (RooRealVar*) (*ntplVars)["normWeight"] ;
RooRealVar *weightVar1 = dynamic_cast<RooRealVar*>( &(*ntplVars)["evWeight"] );
RooRealVar *weightVar2 = dynamic_cast<RooRealVar*>(&(*ntplVars)["normWeight"]);
RooFormulaVar *weightVar3 = new RooFormulaVar( "weight3", "", "@0*@1", RooArgList(*weightVar1, *weightVar2));
weightVar.setVal(1.);
ntplVars->setRealValue("normWeight", 1.);
RooDataSet sigWeightedTmp1("sigData","dataset",sigTree1,*ntplVars,mainCut,"weightVar");
RooRealVar *weightX = (RooRealVar*) sigWeightedTmp1.addColumn(*weightVar3) ;
RooDataSet sigWeighted("sigData","dataset",
RooArgList((*ntplVars)["mgg13TeV"],
(*ntplVars)["categories"],*weightX),
Import(sigWeightedTmp1),WeightVar(*weightX));
cout << "---- nX: " << sigWeighted.sumEntries() << endl;
// for (int c = 0; c < ncat; ++c) {
for (int c = ncat_min; c < ncat_min+ncat; ++c) {
Float_t nExpEvt = sigWeighted.reduce(*w->var("mgg13TeV"),TString::Format("categories==%d",c))->sumEntries();
cout << TString::Format("nEvt exp. %s : ",cat_names.at(c).c_str()) << nExpEvt << endl;
}
sigWeighted.Print("v");
// apply a common preselection cut;
// split into 4 categories;
RooDataSet* signal[21];
// for (int c = 0; c < ncat; ++c) {
for (int c = ncat_min; c < ncat_min+ncat; ++c) {
signal[c] = (RooDataSet*) sigWeighted.reduce(*w->var("mgg13TeV"),mainCut+TString::Format(" && categories==%d",c));
w->import(*signal[c],Rename(TString::Format("SigWeight_%s",cat_names.at(c).c_str())));
}
// Create full weighted signal data set without categorization
RooDataSet* signalAll = (RooDataSet*) sigWeighted.reduce(*w->var("mgg13TeV"),mainCut);
w->import(*signalAll, Rename("SigWeight"));
}
void AddBkgData(RooWorkspace* w, std::vector<string> cat_names) {
// Int_t ncat = NCAT;
Int_t ncat_min = NCAT;
Int_t ncat = NCAT;
if(CHANNEL==1){
ncat_min = 0;
ncat = 8;
}
else if(CHANNEL==2){
ncat_min = 10;
ncat = 4;
}
else if(CHANNEL==3){
ncat_min = 14;
ncat = 7;
}
TString inDir = directory+"MiniTrees/Data_qV_13TeV/";
// common preselection cut
TString mainCut("1");
Float_t minMassFit(MMIN),maxMassFit(MMAX);
//****************************//
// CMS Data Set
//****************************//
// retrieve the data tree;
// no common preselection cut applied yet;
TFile dataFile(inDir+"dijetqV_13TeV_miniTree.root");
TTree* dataTree = (TTree*) dataFile.Get("TCVARS");
// Variables
RooArgSet* ntplVars = defineVariables();
RooDataSet Data("Data","dataset",dataTree,*ntplVars,"","normWeight");
// apply a common preselection cut;
// split into NCAT categories;
RooDataSet* dataToFit[21];
// for (int c = 0; c < ncat; ++c) {
for (int c = ncat_min; c < ncat_min+ncat; ++c) {
// Real data
dataToFit[c] = (RooDataSet*) Data.reduce(*w->var("mgg13TeV"),mainCut+TString::Format(" && categories==%d",c));
std::cout << " make data workspace " << std::endl;
std::cout << " category : " << c << std::endl;
std::cout << " nevents : " << dataToFit[c]->sumEntries() << std::endl;
w->import(*dataToFit[c],Rename(TString::Format("Data_%s",cat_names.at(c).c_str())));
}
// Create full data set without categorization
RooDataSet* data = (RooDataSet*) Data.reduce(*w->var("mgg13TeV"),mainCut);
w->import(*data, Rename("Data"));
data->Print("v");
}
void SigModelFit(RooWorkspace* w, Float_t mass, TString signalname, std::vector<string> cat_names) {
// Int_t ncat = NCAT;
Int_t ncat_min = NCAT;
Int_t ncat = NCAT;
if(CHANNEL==1){
ncat_min = 0;
ncat = 8;
}
else if(CHANNEL==2){
ncat_min = 10;
ncat = 4;
}
else if(CHANNEL==3){
ncat_min = 14;
ncat = 7;
}
Float_t MASS(mass);
//******************************************//
// Fit signal with model pdfs
//******************************************//
// retrieve pdfs and datasets from workspace to fit with pdf models
RooDataSet* sigToFit[21];
RooAbsPdf* jjSig[21];
Float_t minMassFit(MMIN),maxMassFit(MMAX);
// Fit Signal
// for (int c = 0; c < ncat; ++c) {
for (int c = ncat_min; c < ncat_min+ncat; ++c) {
sigToFit[c] = (RooDataSet*) w->data(TString::Format("SigWeight_%s",cat_names.at(c).c_str()));
// cerr << ("jj_"+signalname+TString::Format("_sig_m0_%s",cat_names.at(c).c_str())) << endl;
// ((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_m0_%s",cat_names.at(c).c_str())))->setVal(MASS);
// ((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_m0_%s",cat_names.at(c).c_str())))->setRange(0.8*MASS,1.2*MASS);
// // ((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_gm0_%s",cat_names.at(c).c_str())))->setVal(MASS);
// // ((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_gm0_%s",cat_names.at(c).c_str())))->setRange(0.8*MASS,1.2*MASS);
// ((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_sigma_%s",cat_names.at(c).c_str())))->setVal(MASS*0.05);
// ((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_gsigma_%s",cat_names.at(c).c_str())))->setVal(MASS*0.15);
RooRealVar* m0 = new RooRealVar( "jj_"+signalname+TString::Format("_sig_m0_%s" ,cat_names.at(c).c_str()), "jj_"+signalname+TString::Format("_sig_m0_%s" ,cat_names.at(c).c_str()), MASS, 0.8*MASS, 1.2*MASS);
RooRealVar* gm0 = new RooRealVar( "jj_"+signalname+TString::Format("_sig_gm0_%s" ,cat_names.at(c).c_str()), "jj_"+signalname+TString::Format("_sig_gm0_%s" ,cat_names.at(c).c_str()), MASS, 0.8*MASS, 1.2*MASS);
RooRealVar* sigma = new RooRealVar( "jj_"+signalname+TString::Format("_sig_sigma_%s" ,cat_names.at(c).c_str()), "jj_"+signalname+TString::Format("_sig_sigma_%s" ,cat_names.at(c).c_str()), MASS*0.05 ,20., 700.);
RooRealVar* scalesigma = new RooRealVar( "jj_"+signalname+TString::Format("_scalesigma_%s",cat_names.at(c).c_str()), "jj_"+signalname+TString::Format("_scalesigma_%s",cat_names.at(c).c_str()), 2., 1.2, 10.);
RooRealVar* alpha = new RooRealVar( "jj_"+signalname+TString::Format("_sig_alpha_%s" ,cat_names.at(c).c_str()), "jj_"+signalname+TString::Format("_sig_alpha_%s" ,cat_names.at(c).c_str()), 1.85288, 0.5, 20);
RooRealVar* sig_n = new RooRealVar( "jj_"+signalname+TString::Format("_sig_n_%s" ,cat_names.at(c).c_str()), "jj_"+signalname+TString::Format("_sig_n_%s" ,cat_names.at(c).c_str()), 129.697, 0., 300);
RooRealVar* frac = new RooRealVar( "jj_"+signalname+TString::Format("_sig_frac_%s" ,cat_names.at(c).c_str()), "jj_"+signalname+TString::Format("_sig_frac_%s" ,cat_names.at(c).c_str()), 0.0, 0.0, 0.25);
RooFormulaVar* gsigma = new RooFormulaVar( "jj_"+signalname+TString::Format("_sig_gsigma_%s",cat_names.at(c).c_str()),"jj_"+signalname+TString::Format("_sig_gsigma_%s",cat_names.at(c).c_str()),"@0*@1", RooArgList( *sigma, *scalesigma ));
RooGaussian* gaus = new RooGaussian( "jj_GaussSig"+signalname+TString::Format("_%s",cat_names.at(c).c_str()), "jj_GaussSig"+signalname+TString::Format("_%s",cat_names.at(c).c_str()), *w->var("mgg13TeV") ,*m0,*gsigma);
RooCBShape* cb = new RooCBShape ( "jj_CBSig" +signalname+TString::Format("_%s",cat_names.at(c).c_str()), "jj_CBSig" +signalname+TString::Format("_%s",cat_names.at(c).c_str()), *w->var("mgg13TeV") ,*m0 , *sigma, *alpha, *sig_n);
RooAddPdf* sigmodel = new RooAddPdf ( signalname+"_jj"+TString::Format("_%s",cat_names.at(c).c_str()) , signalname+"_jj"+TString::Format("_%s",cat_names.at(c).c_str()) , RooArgList( *gaus, *cb ), RooArgList(*frac),1);
jjSig[c] = (RooAbsPdf*) sigmodel;
// int stopProgram = 1;
// for (int i = 0; i < 1; ++i) {
// RooFitResult* fr = jjSig[c] -> fitTo(*sigToFit[c],Range(mass*0.8,mass*1.2),SumW2Error(kTRUE),Save(kTRUE));
jjSig[c] -> fitTo(*sigToFit[c],Range(mass*0.8,mass*1.2),SumW2Error(kTRUE),PrintEvalErrors(-1),Save(kTRUE));
// jjSig[c] -> fitTo(*sigToFit[c],SumW2Error(kTRUE),PrintEvalErrors(-1),Save(kTRUE));
// int fitStatus = int(fr->status());
// int covQuality = int(fr->covQual());
// cout<< "Fit status = " << fr->status() <<endl;
// cout<< "Cov quality = " << fr->covQual() <<endl;
// if(fitStatus == 0 && covQuality == 0):
// cout<< "Fit" << i << " passed! "<<endl;
// stopProgram = 0;
// break ;
// }
// if(stopProgram==1){
// cout<< "Fit failed!!! "<<endl;
// }
cout<<"FIT PASSED! Start importing and fixing parameters" <<endl;
w->import(*sigmodel );
w->import(*gaus );
w->import(*cb );
w->import(*m0 );
w->import(*gm0 );
w->import(*sigma );
w->import(*scalesigma);
w->import(*gsigma );
w->import(*alpha );
w->import(*sig_n );
w->import(*frac );
// // IMPORTANT: fix all pdf parameters to constant
// w->defineSet(TString::Format("SigPdfParam_%s",cat_names.at(c).c_str()), RooArgSet(
// *w->var("jj_"+signalname+TString::Format("_sig_m0_%s" ,cat_names.at(c).c_str())),
// *w->var("jj_"+signalname+TString::Format("_sig_gm0_%s" ,cat_names.at(c).c_str())),
// *w->var("jj_"+signalname+TString::Format("_sig_sigma_%s" ,cat_names.at(c).c_str())),
// *w->var("jj_"+signalname+TString::Format("_scalesigma_%s",cat_names.at(c).c_str())),
// *w->var("jj_"+signalname+TString::Format("_sig_alpha_%s" ,cat_names.at(c).c_str())),
// *w->var("jj_"+signalname+TString::Format("_sig_n_%s" ,cat_names.at(c).c_str())),
// *w->var("jj_"+signalname+TString::Format("_sig_gsigma_%s",cat_names.at(c).c_str())),
// *w->var("jj_"+signalname+TString::Format("_sig_frac_%s" ,cat_names.at(c).c_str()))
// ));
// SetConstantParams(w->set(TString::Format("SigPdfParam_%s",cat_names.at(c).c_str())));
((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_m0_%s" ,cat_names.at(c).c_str())))->setConstant(true);
((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_gm0_%s" ,cat_names.at(c).c_str())))->setConstant(true);
((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_sigma_%s" ,cat_names.at(c).c_str())))->setConstant(true);
((RooRealVar*) w->var("jj_"+signalname+TString::Format("_scalesigma_%s",cat_names.at(c).c_str())))->setConstant(true);
((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_alpha_%s" ,cat_names.at(c).c_str())))->setConstant(true);
((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_n_%s" ,cat_names.at(c).c_str())))->setConstant(true);
// ((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_gsigma_%s",cat_names.at(c).c_str())))->setConstant(true);
((RooRealVar*) w->var("jj_"+signalname+TString::Format("_sig_frac_%s" ,cat_names.at(c).c_str())))->setConstant(true);
}
}
std::vector<RooFitResult*> BkgModelFitBernstein(std::string altfunc, RooWorkspace* w, Bool_t dobands, std::vector<string> cat_names) {
// Int_t ncat = NCAT;
Int_t ncat_min = NCAT;
Int_t ncat = NCAT;
if(CHANNEL==1){
ncat_min = 0;
ncat = 8;
}
else if(CHANNEL==2){
ncat_min = 10;
ncat = 4;
}
else if(CHANNEL==3){
ncat_min = 14;
ncat = 7;
}
//******************************************//
// Fit background with model pdfs
//******************************************//
// retrieve pdfs and datasets from workspace to fit with pdf models
RooDataSet* data[21];
RooBernstein* bkg_fit[21];
std::vector<RooFitResult*> fitresult;
for( int i =0;i<21;i++)
{
fitresult.push_back(0);
}
RooPlot* plotbkg_fit[21];
// dobands and dosignal
RooDataSet* signal[21];
RooAbsPdf* jjSig[21];
Float_t minMassFit(MMIN),maxMassFit(MMAX);
// Fit data with background pdf for data limit
RooRealVar* mgg = w->var("mgg13TeV");
mgg->setUnit("GeV");
// TLatex *text = new TLatex();
// text->SetNDC();
// text->SetTextSize(0.04);
// for (int c = 0; c < ncat; ++c) {
for (int c = ncat_min; c < ncat_min+ncat; ++c) {
data[c] = (RooDataSet*) w->data(TString::Format("Data_%s",cat_names.at(c).c_str()));
// if(c==3 || c==4 || c==6){
// cout << "---------------- For channel: " << cat_names.at(c)<< endl;
// ((RooRealVar*) w->var(TString::Format("bkg_fit_slope1_%s",cat_names.at(c).c_str())))->setConstant(true);
// cout << "---------------- Parameter 1 set to const" << endl;
// }
//
// if(c!=10 ){
// ((RooRealVar*) w->var(TString::Format("bkg_fit_slope3_%s",cat_names.at(c).c_str())))->setConstant(true);
// cout << "---------------- Parameter 3 set to const" << endl;
// }
RooFormulaVar *p1mod = new RooFormulaVar(TString::Format("p1mod_%s",cat_names.at(c).c_str()),"","@0",*w->var(TString::Format("bkg_fit_slope1_%s",cat_names.at(c).c_str())));
RooFormulaVar *p2mod = new RooFormulaVar(TString::Format("p2mod_%s",cat_names.at(c).c_str()),"","@0",*w->var(TString::Format("bkg_fit_slope2_%s",cat_names.at(c).c_str())));
RooFormulaVar *p3mod = new RooFormulaVar(TString::Format("p3mod_%s",cat_names.at(c).c_str()),"","@0",*w->var(TString::Format("bkg_fit_slope3_%s",cat_names.at(c).c_str())));
RooFormulaVar *p4mod = new RooFormulaVar(TString::Format("p4mod_%s",cat_names.at(c).c_str()),"","@0",*w->var("bkg_fit_slope4_CMS_jj_qWHP"));
RooFormulaVar *sqrtS = new RooFormulaVar(TString::Format("sqrtS_%s",cat_names.at(c).c_str()),"","@0",*w->var("sqrtS"));
RooFormulaVar *x = new RooFormulaVar(TString::Format("x_%s",cat_names.at(c).c_str()),"","@0/@1",RooArgList(*mgg, *sqrtS));
RooAbsPdf* bkg_fitTmp = new RooGenericPdf(TString::Format("bkg_fit_%s",cat_names.at(c).c_str()), "pow(1-@0, @1)/pow(@0, @2)", RooArgList(*x, *p1mod, *p2mod)); // 3 parameter fit
// for qV only three paramter fit!
// if(c==3 || c==4 || c==6){
// cout << "Using 2 parameter fit for channels WWLP, WZHP and ZZHP!!" << endl;
// bkg_fitTmp = new RooGenericPdf(TString::Format("bkg_fit_%s",cat_names.at(c).c_str()), "1./pow(@0, @1)", RooArgList(*x, *p1mod));
// }
// else if(c==10){
// cout << "Using 5 parameter fit for channels qWHP!!" << endl;
// bkg_fitTmp = new RooGenericPdf(TString::Format("bkg_fit_%s",cat_names.at(c).c_str()), "pow(1-@0, @1)/pow(@0, @2+@3*log(@0)+@4*pow(log(@0),2))", RooArgList(*x, *p1mod, *p2mod, *p3mod, *p4mod));
// }
// else{
cout << "Using 3 parameter fit for this category!!!!!" << endl;
bkg_fitTmp = new RooGenericPdf(TString::Format("bkg_fit_%s",cat_names.at(c).c_str()), "pow(1-@0, @1)/pow(@0, @2)", RooArgList(*x, *p1mod, *p2mod)); // 3 parameter fit
// }
if (altfunc.find("alt")!=std::string::npos)
{
x = new RooFormulaVar(TString::Format("x_%s",cat_names.at(c).c_str()),"","@0",RooArgList(*mgg, *sqrtS));
p4mod = new RooFormulaVar(TString::Format("p4mod_%s",cat_names.at(c).c_str()),"","@0",*w->var(TString::Format("bkg_fit_slope4_%s",cat_names.at(c).c_str())));
bkg_fitTmp = new RooGenericPdf(TString::Format("bkg_fit_%s",cat_names.at(c).c_str()), "( @1*pow(1-@0/13000. + @4*pow(@0/13000.,2),@2) ) / ( pow(@0/13000.,@3) )", RooArgList(*x, *p1mod, *p2mod, *p3mod,*p4mod));
}
RooAbsReal* bkg_fitTmp2 = new RooRealVar(TString::Format("bkg_fit_%s_norm",cat_names.at(c).c_str()),"",data[c]->sumEntries(),1.0,1000000000);
w->import(*bkg_fitTmp);
w->import(*bkg_fitTmp2);
//************************************************//
// Plot jj background fit results per categories
//************************************************//
// Plot Background Categories
//****************************//
TCanvas* ctmp = new TCanvas("ctmp","jj Background Categories",0,0,500,500);
Int_t nBinsMass(80);
plotbkg_fit[c] = mgg->frame(nBinsMass);
data[c]->plotOn(plotbkg_fit[c],LineColor(kWhite),MarkerColor(kWhite));
bkg_fitTmp->plotOn(plotbkg_fit[c],LineColor(kBlue),Range("fitrange"),NormRange("fitrange"),PrintEvalErrors(-1));
data[c]->plotOn(plotbkg_fit[c]);
plotbkg_fit[c]->Draw();
//********************************************************************************//
if (dobands) {
RooAbsPdf *cpdf; cpdf = bkg_fitTmp;
TGraphAsymmErrors *onesigma = new TGraphAsymmErrors();
TGraphAsymmErrors *twosigma = new TGraphAsymmErrors();
RooRealVar *nlim = new RooRealVar(TString::Format("nlim%d",c),"",0.0,0.0,10.0);
nlim->removeRange();
RooCurve *nomcurve = dynamic_cast<RooCurve*>(plotbkg_fit[c]->getObject(1));
for (int i=1; i<(plotbkg_fit[c]->GetXaxis()->GetNbins()+1); ++i) {
double lowedge = plotbkg_fit[c]->GetXaxis()->GetBinLowEdge(i);
double upedge = plotbkg_fit[c]->GetXaxis()->GetBinUpEdge(i);
double center = plotbkg_fit[c]->GetXaxis()->GetBinCenter(i);
double nombkg = nomcurve->interpolate(center);
nlim->setVal(nombkg);
mgg->setRange("errRange",lowedge,upedge);
RooAbsPdf *epdf = 0;
epdf = new RooExtendPdf("epdf","",*cpdf,*nlim,"errRange");
RooAbsReal *nll = epdf->createNLL(*(data[c]),Extended());
RooMinimizer minim(*nll);
minim.setStrategy(0);
double clone = 1.0 - 2.0*RooStats::SignificanceToPValue(1.0);
double cltwo = 1.0 - 2.0*RooStats::SignificanceToPValue(2.0);
minim.migrad();
minim.minos(*nlim);
// printf("errlo = %5f, errhi = %5f\n",nlim->getErrorLo(),nlim->getErrorHi());
onesigma->SetPoint(i-1,center,nombkg);
onesigma->SetPointError(i-1,0.,0.,-nlim->getErrorLo(),nlim->getErrorHi());
minim.setErrorLevel(0.5*pow(ROOT::Math::normal_quantile(1-0.5*(1-cltwo),1.0), 2)); // the 0.5 is because qmu is -2*NLL
// eventually if cl = 0.95 this is the usual 1.92!
minim.migrad();
minim.minos(*nlim);
twosigma->SetPoint(i-1,center,nombkg);
twosigma->SetPointError(i-1,0.,0.,-nlim->getErrorLo(),nlim->getErrorHi());
delete nll;
delete epdf;
}
mgg->setRange("errRange",minMassFit,maxMassFit);
twosigma->SetLineColor(kGreen);
twosigma->SetFillColor(kGreen);
twosigma->SetMarkerColor(kGreen);
twosigma->Draw("L3 SAME");
onesigma->SetLineColor(kYellow);
onesigma->SetFillColor(kYellow);
onesigma->SetMarkerColor(kYellow);
onesigma->Draw("L3 SAME");
plotbkg_fit[c]->Draw("SAME");
}
}
return fitresult;
}
void SetConstantParams(const RooArgSet* params) {
TIterator* iter(params->createIterator());
for (TObject *a = iter->Next(); a != 0; a = iter->Next()) {
RooRealVar *rrv = dynamic_cast<RooRealVar *>(a);
if (rrv) { rrv->setConstant(true); std::cout << " " << rrv->GetName(); }
}
}
void MakePlots(RooWorkspace* w, Float_t mass, std::vector<RooFitResult*> fitresults, TString signalname, std::vector<string> cat_names) {
cout << "Start plotting" << endl;
// Int_t ncat = NCAT;
Int_t ncat_min = NCAT;
Int_t ncat = NCAT;
if(CHANNEL==1){
ncat_min = 0;
ncat = 8;
}
else if(CHANNEL==2){
ncat_min = 10;
ncat = 4;
}
else if(CHANNEL==3){
ncat_min = 14;
ncat = 7;
}
// retrieve data sets from the workspace
RooDataSet* dataAll = (RooDataSet*) w->data("Data");
RooDataSet* signalAll = (RooDataSet*) w->data("Sig");
RooDataSet* data[21];
RooDataSet* signal[21];
RooAbsPdf* jjGaussSig[21];
RooAbsPdf* jjCBSig[21];
RooAbsPdf* jjSig[21];
RooAbsPdf* bkg_fit[21];
// RooAbsPdf* bkg_fit2[21];
// for (int c = 0; c < ncat; ++c) {
for (int c = ncat_min; c < ncat_min+ncat; ++c) {
data[c] = (RooDataSet*) w->data(TString::Format("Data_%s",cat_names.at(c).c_str()));
// signal[c] = (RooDataSet*) w->data(TString::Format("Sig_%s",cat_names.at(c).c_str()));
signal[c] = (RooDataSet*) w->data(TString::Format("SigWeight_%s",cat_names.at(c).c_str()));
jjGaussSig[c] = (RooAbsPdf*) w->pdf(TString::Format("jj_GaussSig_%s",cat_names.at(c).c_str()));
jjCBSig[c] = (RooAbsPdf*) w->pdf(TString::Format("jj_CBSig_%s",cat_names.at(c).c_str()));
jjSig[c] = (RooAbsPdf*) w->pdf(signalname+"_jj"+TString::Format("_%s",cat_names.at(c).c_str()));
bkg_fit[c] = (RooAbsPdf*) w->pdf(TString::Format("bkg_fit_%s",cat_names.at(c).c_str()));
// bkg_fit2[c] = (RooAbsPdf*) w->pdf(TString::Format("bkg_fit2_%s",cat_names.at(c).c_str()));
}
// retrieve mass observable from the workspace
RooRealVar* mgg = w->var("mgg13TeV");
mgg->setUnit("GeV");
// retrieve pdfs after the fits
// Signal Model
// RooAbsPdf* jjGaussSigAll = w->pdf("jjGaussSig"+signalname);
// RooAbsPdf* jjCBSigAll = w->pdf("jjCBSig"+signalname);
// RooAbsPdf* jjSigAll = w->pdf(signalname+"_jj");
//
// // RooAbsPdf* bkg_fitAll = w->pdf("bkg_fit");
// RooAbsPdf* bkg_fitAll = w->pdf("bkg_fitAll");
//
// cout << "Progress plotting" << endl;
//
// //****************************//
// // Plot jj Fit results
// //****************************//
//
//
// Float_t minMassFit(MMIN),maxMassFit(MMAX);
// Float_t MASS(mass);
//
// Int_t nBinsMass(100);
//
// RooPlot* plotjjAll = mgg->frame(Range(minMassFit,maxMassFit),Bins(nBinsMass));
// signalAll->plotOn(plotjjAll,PrintEvalErrors(-1));
//
// gStyle->SetOptTitle(0);
// jjSigAll->plotOn(plotjjAll,PrintEvalErrors(-1));
// jjSigAll->plotOn(plotjjAll,Components("jjGaussSig"+signalname),LineStyle(kDashed),LineColor(kGreen),PrintEvalErrors(-1));
// jjSigAll->plotOn(plotjjAll,Components("jjCBSig"+signalname),LineStyle(kDashed),LineColor(kRed),PrintEvalErrors(-1));
//
// jjSigAll->paramOn(plotjjAll, ShowConstants(true), Layout(0.15,0.55,0.9), Format("NEU",AutoPrecision(2)));
// plotjjAll->getAttText()->SetTextSize(0.03);
//
// TCanvas* c1 = new TCanvas("c1","jj",0,0,500,500);
// c1->cd(1);
// plotjjAll->Draw();
//
//
// cout << "Progress plotting" << endl;
//********************************************//
// Plot jj signal fit results per categories
//********************************************//
// Plot Signal Categories
//****************************//
Float_t minMassFit(MMIN),maxMassFit(MMAX);
Float_t MASS(mass);
Int_t nBinsMass(100);
gStyle->SetOptTitle(0);
// TLatex *text = new TLatex();
// text->SetNDC();
// text->SetTextSize(0.04);
// TCanvas* c2 = new TCanvas("c2","jj Categories",0,0,1000,1000);
// c2->Divide(3,3);
RooPlot* plotjj[21];
// for (int c = 0; c < ncat; ++c) {
for (int c = ncat_min; c < ncat_min+ncat; ++c) {
plotjj[c] = mgg->frame(Range(minMassFit,maxMassFit),Bins(nBinsMass));
signal[c] ->plotOn(plotjj[c],LineColor(kWhite),MarkerColor(kWhite),PrintEvalErrors(-1));
jjSig[c] ->plotOn(plotjj[c],LineColor(col->GetColor("#636363")),PrintEvalErrors(-1));
jjSig[c] ->plotOn(plotjj[c],Components("jj_GaussSig"+signalname+TString::Format("_%s",cat_names.at(c).c_str())),LineStyle(kDashed),LineColor(col->GetColor("#99d8c9")),PrintEvalErrors(-1));
jjSig[c] ->plotOn(plotjj[c],Components("jj_CBSig" +signalname+TString::Format("_%s",cat_names.at(c).c_str())),LineStyle(kDashed),LineColor(col->GetColor("#fdbb84")),PrintEvalErrors(-1));
jjSig[c] ->paramOn(plotjj[c]);
signal[c] ->plotOn(plotjj[c],PrintEvalErrors(-1));
int W = 800;
int H = 600;
int H_ref = 600;
int W_ref = 800;
float T = 0.08*H_ref;
float B = 0.12*H_ref;
float L = 0.12*W_ref;
float R = 0.04*W_ref;
TCanvas* dummy = new TCanvas("dummy", "dummy",50,50,W,H);
dummy->SetFillColor(0);
dummy->SetBorderMode(0);
dummy->SetFrameFillStyle(0);
dummy->SetFrameBorderMode(0);
dummy->SetLeftMargin( L/W );
dummy->SetRightMargin( R/W );
dummy->SetTopMargin( T/H );
dummy->SetBottomMargin( B/H );
dummy->SetTickx(0);
dummy->SetTicky(0);
TH1F *hist = new TH1F("hist", "hist", 400, minMassFit, maxMassFit);
plotjj[c]->SetTitle("");
plotjj[c]->SetMinimum(0.0);
plotjj[c]->SetMaximum(1.40*plotjj[c]->GetMaximum());
plotjj[c]->GetXaxis()->SetTitle("Dijet invariant mass (GeV)");
plotjj[c]->GetYaxis()->SetTitleOffset(1.1);
TCanvas* ctmp = new TCanvas("ctmp","jj Background Categories",0,0,500,500);
plotjj[c]->Draw();
// hist->Draw("same");
plotjj[c]->Draw("SAME");
TLegend *legmc = new TLegend(0.570,0.72,0.85,0.87);
legmc->AddEntry(plotjj[c]->getObject(5),"CMS data","LPE");
legmc->AddEntry(plotjj[c]->getObject(1),"Total PDF","L");
legmc->AddEntry(plotjj[c]->getObject(3),"Crystal Ball comp.","L");