///
/// Perform a couple of consistency checks to make it easier
/// to find bugs:
/// - check if all observables end with '_obs'
/// - check if all predicted observables end with '_th'
/// - check if the 'observables' and 'theory' lists are correctly ordered
///
bool PDF_Abs::checkConsistency()
{
if ( m_isCrossCorPdf ) return true;
bool allOk = true;
// check if all observables end with '_obs'
TIterator* it = observables->createIterator();
while ( RooRealVar* p = (RooRealVar*)it->Next() ){
TString pObsName = p->GetName();
pObsName.ReplaceAll(uniqueID,"");
if ( !pObsName.EndsWith("_obs") ){
cout << "PDF_Abs::checkConsistency() : " << name << " : observable " << p->GetName() << " doesn't end with '_obs'" << endl;
allOk = false;
}
}
// check if all predicted observables end with '_th'
delete it; it = theory->createIterator();
while ( RooRealVar* p = (RooRealVar*)it->Next() ){
TString pThName = p->GetName();
pThName.ReplaceAll(uniqueID,"");
if ( !pThName.EndsWith("_th") ){
cout << "PDF_Abs::checkConsistency() : " << name << " : theory " << p->GetName() << " doesn't end with '_th'" << endl;
allOk = false;
}
}
// check if the 'observables' and 'theory' lists are correctly ordered
for ( int i=0; i<nObs; i++ ){
RooAbsArg* pTh = theory->at(i);
TString base = pTh->GetName();
base.ReplaceAll("_th","");
base.ReplaceAll(uniqueID,"");
TString pObsName = observables->at(i)->GetName();
pObsName.ReplaceAll(uniqueID,"");
if ( pObsName != base+"_obs"){
cout << "PDF_Abs::checkConsistency() : " << name << " : " << pTh->GetName() << " doesn't match its observable." << endl;
cout << " Expected '" << base+"_obs" << "'. Found '" << pObsName << "'." << endl;
cout << " Check ordering of the 'theory' and 'observables' lists!" << endl;
allOk = false;
}
}
return allOk;
}
RooAbsArg *cloneRecursiveRename(RooAbsArg *arg, const char *postfix) {
RooAbsArg *clone = arg->cloneTree();
RooArgSet *clonecomps = clone->getComponents();
RooArgSet *clonevars = clone->getVariables();
RooArgList cloneargs;
cloneargs.add(*clonecomps);
cloneargs.add(*clonevars);
delete clonecomps;
delete clonevars;
for (int iarg=0; iarg<cloneargs.getSize(); ++iarg) {
cloneargs.at(iarg)->SetName(TString::Format("%s_%s",cloneargs.at(iarg)->GetName(),postfix));
}
return clone;
}
RooWorkspace* makeInvertedANFit(TTree* tree, float forceSigma=-1, bool constrainMu=false, float forceMu=-1) {
RooWorkspace *ws = new RooWorkspace("ws","");
std::vector< TString (*)(TString, RooRealVar&, RooWorkspace&) > bkgPdfList;
bkgPdfList.push_back(makeSingleExp);
bkgPdfList.push_back(makeDoubleExp);
#if DEBUG==0
//bkgPdfList.push_back(makeTripleExp);
bkgPdfList.push_back(makeModExp);
bkgPdfList.push_back(makeSinglePow);
bkgPdfList.push_back(makeDoublePow);
bkgPdfList.push_back(makePoly2);
bkgPdfList.push_back(makePoly3);
#endif
RooRealVar mgg("mgg","m_{#gamma#gamma}",103,160,"GeV");
mgg.setBins(38);
mgg.setRange("sideband_low", 103,120);
mgg.setRange("sideband_high",131,160);
mgg.setRange("signal",120,131);
RooRealVar MR("MR","",0,3000,"GeV");
MR.setBins(60);
RooRealVar Rsq("t1Rsq","",0,1,"GeV");
Rsq.setBins(20);
RooRealVar hem1_M("hem1_M","",-1,2000,"GeV");
hem1_M.setBins(40);
RooRealVar hem2_M("hem2_M","",-1,2000,"GeV");
hem2_M.setBins(40);
RooRealVar ptgg("ptgg","p_{T}^{#gamma#gamma}",0,500,"GeV");
ptgg.setBins(50);
RooDataSet data("data","",tree,RooArgSet(mgg,MR,Rsq,hem1_M,hem2_M,ptgg));
RooDataSet* blind_data = (RooDataSet*)data.reduce("mgg<121 || mgg>130");
std::vector<TString> tags;
//fit many different background models
for(auto func = bkgPdfList.begin(); func != bkgPdfList.end(); func++) {
TString tag = (*func)("bonly",mgg,*ws);
tags.push_back(tag);
ws->pdf("bonly_"+tag+"_ext")->fitTo(data,RooFit::Strategy(0),RooFit::Extended(kTRUE),RooFit::Range("sideband_low,sideband_high"));
RooFitResult* bres = ws->pdf("bonly_"+tag+"_ext")->fitTo(data,RooFit::Strategy(2),RooFit::Save(kTRUE),RooFit::Extended(kTRUE),RooFit::Range("sideband_low,sideband_high"));
bres->SetName(tag+"_bonly_fitres");
ws->import(*bres);
//make blinded fit
RooPlot *fmgg_b = mgg.frame();
blind_data->plotOn(fmgg_b,RooFit::Range("sideband_low,sideband_high"));
TBox blindBox(121,fmgg_b->GetMinimum()-(fmgg_b->GetMaximum()-fmgg_b->GetMinimum())*0.015,130,fmgg_b->GetMaximum());
blindBox.SetFillColor(kGray);
fmgg_b->addObject(&blindBox);
ws->pdf("bonly_"+tag+"_ext")->plotOn(fmgg_b,RooFit::LineColor(kRed),RooFit::Range("Full"),RooFit::NormRange("sideband_low,sideband_high"));
fmgg_b->SetName(tag+"_blinded_frame");
ws->import(*fmgg_b);
delete fmgg_b;
//set all the parameters constant
RooArgSet* vars = ws->pdf("bonly_"+tag)->getVariables();
RooFIter iter = vars->fwdIterator();
RooAbsArg* a;
while( (a = iter.next()) ){
if(string(a->GetName()).compare("mgg")==0) continue;
static_cast<RooRealVar*>(a)->setConstant(kTRUE);
}
//make the background portion of the s+b fit
(*func)("b",mgg,*ws);
RooRealVar sigma(tag+"_s_sigma","",5,0,100);
if(forceSigma!=-1) {
sigma.setVal(forceSigma);
sigma.setConstant(true);
}
RooRealVar mu(tag+"_s_mu","",126,120,132);
if(forceMu!=-1) {
mu.setVal(forceMu);
mu.setConstant(true);
}
RooGaussian sig(tag+"_sig_model","",mgg,mu,sigma);
RooRealVar Nsig(tag+"_sb_Ns","",5,0,100);
RooRealVar Nbkg(tag+"_sb_Nb","",100,0,100000);
RooRealVar HiggsMass("HiggsMass","",125.1);
RooRealVar HiggsMassError("HiggsMassError","",0.24);
RooGaussian HiggsMassConstraint("HiggsMassConstraint","",mu,HiggsMass,HiggsMassError);
RooAddPdf fitModel(tag+"_sb_model","",RooArgList( *ws->pdf("b_"+tag), sig ),RooArgList(Nbkg,Nsig));
RooFitResult* sbres;
RooAbsReal* nll;
if(constrainMu) {
fitModel.fitTo(data,RooFit::Strategy(0),RooFit::Extended(kTRUE),RooFit::ExternalConstraints(RooArgSet(HiggsMassConstraint)));
sbres = fitModel.fitTo(data,RooFit::Strategy(2),RooFit::Save(kTRUE),RooFit::Extended(kTRUE),RooFit::ExternalConstraints(RooArgSet(HiggsMassConstraint)));
nll = fitModel.createNLL(data,RooFit::NumCPU(4),RooFit::Extended(kTRUE),RooFit::ExternalConstraints(RooArgSet(HiggsMassConstraint)));
} else {
fitModel.fitTo(data,RooFit::Strategy(0),RooFit::Extended(kTRUE));
sbres = fitModel.fitTo(data,RooFit::Strategy(2),RooFit::Save(kTRUE),RooFit::Extended(kTRUE));
nll = fitModel.createNLL(data,RooFit::NumCPU(4),RooFit::Extended(kTRUE));
}
sbres->SetName(tag+"_sb_fitres");
ws->import(*sbres);
ws->import(fitModel);
RooPlot *fmgg = mgg.frame();
data.plotOn(fmgg);
fitModel.plotOn(fmgg);
ws->pdf("b_"+tag+"_ext")->plotOn(fmgg,RooFit::LineColor(kRed),RooFit::Range("Full"),RooFit::NormRange("Full"));
fmgg->SetName(tag+"_frame");
ws->import(*fmgg);
delete fmgg;
RooMinuit(*nll).migrad();
RooPlot *fNs = Nsig.frame(0,25);
fNs->SetName(tag+"_Nsig_pll");
RooAbsReal *pll = nll->createProfile(Nsig);
//nll->plotOn(fNs,RooFit::ShiftToZero(),RooFit::LineColor(kRed));
pll->plotOn(fNs);
ws->import(*fNs);
delete fNs;
RooPlot *fmu = mu.frame(125,132);
fmu->SetName(tag+"_mu_pll");
RooAbsReal *pll_mu = nll->createProfile(mu);
pll_mu->plotOn(fmu);
ws->import(*fmu);
delete fmu;
}
RooArgSet weights("weights");
RooArgSet pdfs_bonly("pdfs_bonly");
RooArgSet pdfs_b("pdfs_b");
RooRealVar minAIC("minAIC","",1E10);
//compute AIC stuff
for(auto t = tags.begin(); t!=tags.end(); t++) {
RooAbsPdf *p_bonly = ws->pdf("bonly_"+*t);
RooAbsPdf *p_b = ws->pdf("b_"+*t);
RooFitResult *sb = (RooFitResult*)ws->obj(*t+"_bonly_fitres");
RooRealVar k(*t+"_b_k","",p_bonly->getParameters(RooArgSet(mgg))->getSize());
RooRealVar nll(*t+"_b_minNll","",sb->minNll());
RooRealVar Npts(*t+"_b_N","",blind_data->sumEntries());
RooFormulaVar AIC(*t+"_b_AIC","2*@0+2*@1+2*@1*(@1+1)/(@2-@1-1)",RooArgSet(nll,k,Npts));
ws->import(AIC);
if(AIC.getVal() < minAIC.getVal()) {
minAIC.setVal(AIC.getVal());
}
//aicExpSum+=TMath::Exp(-0.5*AIC.getVal()); //we will need this precomputed for the next step
pdfs_bonly.add(*p_bonly);
pdfs_b.add(*p_b);
}
ws->import(minAIC);
//compute the AIC weight
float aicExpSum=0;
for(auto t = tags.begin(); t!=tags.end(); t++) {
RooFormulaVar *AIC = (RooFormulaVar*)ws->obj(*t+"_b_AIC");
aicExpSum+=TMath::Exp(-0.5*(AIC->getVal()-minAIC.getVal())); //we will need this precomputed for the next step
}
std::cout << "aicExpSum: " << aicExpSum << std::endl;
for(auto t = tags.begin(); t!=tags.end(); t++) {
RooFormulaVar *AIC = (RooFormulaVar*)ws->obj(*t+"_b_AIC");
RooRealVar *AICw = new RooRealVar(*t+"_b_AICWeight","",TMath::Exp(-0.5*(AIC->getVal()-minAIC.getVal()))/aicExpSum);
if( TMath::IsNaN(AICw->getVal()) ) {AICw->setVal(0);}
ws->import(*AICw);
std::cout << *t << ": " << AIC->getVal()-minAIC.getVal() << " " << AICw->getVal() << std::endl;
weights.add(*AICw);
}
RooAddPdf bonly_AIC("bonly_AIC","",pdfs_bonly,weights);
RooAddPdf b_AIC("b_AIC","",pdfs_b,weights);
//b_AIC.fitTo(data,RooFit::Strategy(0),RooFit::Extended(kTRUE),RooFit::Range("sideband_low,sideband_high"));
//RooFitResult* bres = b_AIC.fitTo(data,RooFit::Strategy(2),RooFit::Save(kTRUE),RooFit::Extended(kTRUE),RooFit::Range("sideband_low,sideband_high"));
//bres->SetName("AIC_b_fitres");
//ws->import(*bres);
//make blinded fit
RooPlot *fmgg_b = mgg.frame(RooFit::Range("sideband_low,sideband_high"));
blind_data->plotOn(fmgg_b,RooFit::Range("sideband_low,sideband_high"));
TBox blindBox(121,fmgg_b->GetMinimum()-(fmgg_b->GetMaximum()-fmgg_b->GetMinimum())*0.015,130,fmgg_b->GetMaximum());
blindBox.SetFillColor(kGray);
fmgg_b->addObject(&blindBox);
bonly_AIC.plotOn(fmgg_b,RooFit::LineColor(kRed),RooFit::Range("Full"),RooFit::NormRange("sideband_low,sideband_high"));
fmgg_b->SetName("AIC_blinded_frame");
ws->import(*fmgg_b);
delete fmgg_b;
#if 1
RooRealVar sigma("AIC_s_sigma","",5,0,100);
if(forceSigma!=-1) {
sigma.setVal(forceSigma);
sigma.setConstant(true);
}
RooRealVar mu("AIC_s_mu","",126,120,132);
if(forceMu!=-1) {
mu.setVal(forceMu);
mu.setConstant(true);
}
RooGaussian sig("AIC_sig_model","",mgg,mu,sigma);
RooRealVar Nsig("AIC_sb_Ns","",5,0,100);
RooRealVar Nbkg("AIC_sb_Nb","",100,0,100000);
RooRealVar HiggsMass("HiggsMass","",125.1);
RooRealVar HiggsMassError("HiggsMassError","",0.24);
RooGaussian HiggsMassConstraint("HiggsMassConstraint","",mu,HiggsMass,HiggsMassError);
RooAddPdf fitModel("AIC_sb_model","",RooArgList( b_AIC, sig ),RooArgList(Nbkg,Nsig));
RooFitResult* sbres;
RooAbsReal *nll;
if(constrainMu) {
fitModel.fitTo(data,RooFit::Strategy(0),RooFit::Extended(kTRUE),RooFit::ExternalConstraints(RooArgSet(HiggsMassConstraint)));
sbres = fitModel.fitTo(data,RooFit::Strategy(2),RooFit::Save(kTRUE),RooFit::Extended(kTRUE),RooFit::ExternalConstraints(RooArgSet(HiggsMassConstraint)));
nll = fitModel.createNLL(data,RooFit::NumCPU(4),RooFit::Extended(kTRUE),RooFit::ExternalConstraints(RooArgSet(HiggsMassConstraint)));
} else {
fitModel.fitTo(data,RooFit::Strategy(0),RooFit::Extended(kTRUE));
sbres = fitModel.fitTo(data,RooFit::Strategy(2),RooFit::Save(kTRUE),RooFit::Extended(kTRUE));
nll = fitModel.createNLL(data,RooFit::NumCPU(4),RooFit::Extended(kTRUE));
}
assert(nll!=0);
sbres->SetName("AIC_sb_fitres");
ws->import(*sbres);
ws->import(fitModel);
RooPlot *fmgg = mgg.frame();
data.plotOn(fmgg);
fitModel.plotOn(fmgg);
ws->pdf("b_AIC")->plotOn(fmgg,RooFit::LineColor(kRed),RooFit::Range("Full"),RooFit::NormRange("Full"));
fmgg->SetName("AIC_frame");
ws->import(*fmgg);
delete fmgg;
RooMinuit(*nll).migrad();
RooPlot *fNs = Nsig.frame(0,25);
fNs->SetName("AIC_Nsig_pll");
RooAbsReal *pll = nll->createProfile(Nsig);
//nll->plotOn(fNs,RooFit::ShiftToZero(),RooFit::LineColor(kRed));
pll->plotOn(fNs);
ws->import(*fNs);
delete fNs;
RooPlot *fmu = mu.frame(125,132);
fmu->SetName("AIC_mu_pll");
RooAbsReal *pll_mu = nll->createProfile(mu);
pll_mu->plotOn(fmu);
ws->import(*fmu);
delete fmu;
std::cout << "min AIC: " << minAIC.getVal() << std::endl;
for(auto t = tags.begin(); t!=tags.end(); t++) {
RooFormulaVar *AIC = (RooFormulaVar*)ws->obj(*t+"_b_AIC");
RooRealVar *AICw = ws->var(*t+"_b_AICWeight");
RooRealVar* k = ws->var(*t+"_b_k");
printf("%s & %0.0f & %0.2f & %0.2f \\\\\n",t->Data(),k->getVal(),AIC->getVal()-minAIC.getVal(),AICw->getVal());
//std::cout << k->getVal() << " " << AIC->getVal()-minAIC.getVal() << " " << AICw->getVal() << std::endl;
}
#endif
return ws;
}
exampleScript()
{
gSystem->CompileMacro("betaHelperFunctions.h" ,"kO") ;
gSystem->CompileMacro("RooNormalFromFlatPdf.cxx" ,"kO") ;
gSystem->CompileMacro("RooBetaInverseCDF.cxx" ,"kO") ;
gSystem->CompileMacro("RooBetaPrimeInverseCDF.cxx" ,"kO") ;
gSystem->CompileMacro("RooCorrelatedBetaGeneratorHelper.cxx" ,"kO") ;
gSystem->CompileMacro("RooCorrelatedBetaPrimeGeneratorHelper.cxx" ,"kO") ;
gSystem->CompileMacro("rooFitBetaHelperFunctions.h","kO") ;
TFile betaTest("betaTest.root","RECREATE");
betaTest.cd();
RooWorkspace workspace("workspace");
TString correlatedName("testVariable");
TString observables("observables");
TString nuisances("nuisances");
RooAbsArg* betaOne = getCorrelatedBetaConstraint(workspace,"betaOne","",
0.5 , 0.1 ,
observables, nuisances,
correlatedName );
printf("\n\n *** constraint name is %s from betaOne and %s\n\n", betaOne->GetName(), correlatedName.Data() ) ;
RooAbsArg* betaTwo = getCorrelatedBetaConstraint(workspace,"betaTwo","",
0 , 0 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaThree = getCorrelatedBetaConstraint(workspace,"betaThree","",
0.2 , 0.01 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaFour = getCorrelatedBetaConstraint(workspace,"betaFour","",
0.7 , 0.1 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaFourC = getCorrelatedBetaConstraint(workspace,"betaFourC","",
0.7 , 0.1 ,
observables, nuisances,
correlatedName, kTRUE );
RooAbsArg* betaPrimeOne = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeOne","",
1.0 , 0.5 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaPrimeOneC = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeOneC","",
1.0 , 0.5 ,
observables, nuisances,
correlatedName, kTRUE );
RooAbsArg* betaPrimeTwo = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeTwo","",
0.7 , 0.5 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaPrimeThree = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeThree","",
0.1 , 0.05 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaPrimeFour = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeFour","",
7 , 1 ,
observables, nuisances,
correlatedName );
RooRealVar* correlatedParameter = workspace.var(correlatedName);
RooAbsPdf* normalFromFlat = workspace.pdf(correlatedName+"_Constraint");
RooDataSet* data = normalFromFlat->generate(RooArgSet(*correlatedParameter),1e5);
data->addColumn(*normalFromFlat);
data->addColumn(*betaOne);
data->addColumn(*betaTwo);
data->addColumn(*betaThree);
data->addColumn(*betaFour);
data->addColumn(*betaFourC);
data->addColumn(*betaPrimeOne);
data->addColumn(*betaPrimeTwo);
data->addColumn(*betaPrimeThree);
data->addColumn(*betaPrimeFour);
data->addColumn(*betaPrimeOneC);
data->Print("v");
workspace.Print() ;
//Setup Plotting Kluges:
RooRealVar normalPlotter (correlatedName+"_Constraint" , correlatedName+"_Constraint" ,0,1);
RooPlot* normalPlot = normalPlotter.frame();
data->plotOn(normalPlot);
RooRealVar betaOnePlotter ("betaOne_BetaInverseCDF" ,"betaOne_BetaInverseCDF" ,0,1);
RooRealVar betaTwoPlotter ("betaTwo_BetaInverseCDF" ,"betaTwo_BetaInverseCDF" ,0,1);
RooRealVar betaThreePlotter("betaThree_BetaInverseCDF","betaThree_BetaInverseCDF",0,1);
RooRealVar betaFourPlotter ("betaFour_BetaInverseCDF" ,"betaFour_BetaInverseCDF" ,0,1);
RooRealVar betaFourCPlotter ("betaFourC_BetaInverseCDF" ,"betaFourC_BetaInverseCDF" ,0,1);
RooRealVar betaPrimeOnePlotter ("betaPrimeOne_BetaPrimeInverseCDF" ,"betaPrimeOne_BetaPrimeInverseCDF" ,0,4);
RooRealVar betaPrimeOneCPlotter ("betaPrimeOneC_BetaPrimeInverseCDF" ,"betaPrimeOneC_BetaPrimeInverseCDF" ,0,4);
RooRealVar betaPrimeTwoPlotter ("betaPrimeTwo_BetaPrimeInverseCDF" ,"betaPrimeTwo_BetaPrimeInverseCDF" ,0,4);
RooRealVar betaPrimeThreePlotter("betaPrimeThree_BetaPrimeInverseCDF","betaPrimeThree_BetaPrimeInverseCDF",0,0.3);
RooRealVar betaPrimeFourPlotter ("betaPrimeFour_BetaPrimeInverseCDF" ,"betaPrimeFour_BetaPrimeInverseCDF" ,4,12);
RooPlot* betaOnePlot = betaOnePlotter .frame();
RooPlot* betaTwoPlot = betaTwoPlotter .frame();
RooPlot* betaThreePlot = betaThreePlotter.frame();
RooPlot* betaFourPlot = betaFourPlotter .frame();
RooPlot* betaFourCPlot = betaFourCPlotter .frame();
data->plotOn(betaOnePlot );
data->plotOn(betaTwoPlot );
data->plotOn(betaThreePlot);
data->plotOn(betaFourPlot );
data->plotOn(betaFourCPlot );
RooPlot* betaPrimeOnePlot = betaPrimeOnePlotter .frame();
RooPlot* betaPrimeOneCPlot = betaPrimeOneCPlotter .frame();
RooPlot* betaPrimeTwoPlot = betaPrimeTwoPlotter .frame();
RooPlot* betaPrimeThreePlot = betaPrimeThreePlotter.frame();
RooPlot* betaPrimeFourPlot = betaPrimeFourPlotter .frame();
data->plotOn(betaPrimeOnePlot );
data->plotOn(betaPrimeOneCPlot );
data->plotOn(betaPrimeTwoPlot );
data->plotOn(betaPrimeThreePlot);
data->plotOn(betaPrimeFourPlot );
TCanvas* underlyingVariable = new TCanvas("underlyingVariable","underlyingVariable",800,800);
underlyingVariable->Divide(2,2);
underlyingVariable->cd(1);
RooPlot* underlyingPlot = correlatedParameter->frame();
data->plotOn(underlyingPlot);
underlyingPlot->Draw();
underlyingVariable->cd(2);
normalPlot->Draw();
underlyingVariable->cd(3);
TH2F* underlying = data->createHistogram(*correlatedParameter,normalPlotter,50,50);
underlying->Draw("col");
TH2F* legoUnderlying = (TH2F*)underlying->Clone();
underlyingVariable->cd(4);
legoUnderlying->Draw("lego");
underlyingVariable->SaveAs("underlyingVariable.pdf");
TCanvas* betaCanvas = new TCanvas("betaCanvas","betaCanvas",800,800);
betaCanvas->Divide(3,2);
betaCanvas->cd(1);
betaOnePlot->Draw();
betaCanvas->cd(2);
betaTwoPlot->Draw();
betaCanvas->cd(3);
betaThreePlot->Draw();
betaCanvas->cd(4);
betaFourPlot->Draw();
betaCanvas->cd(5);
betaFourCPlot->Draw();
betaCanvas->SaveAs("betaVariables.pdf");
TCanvas* betaPrimeCanvas = new TCanvas("betaPrimeCanvas","betaPrimeCanvas",1200,800);
betaPrimeCanvas->Divide(3,2);
betaPrimeCanvas->cd(1);
betaPrimeOnePlot->Draw();
betaPrimeCanvas->cd(2);
betaPrimeTwoPlot->Draw();
betaPrimeCanvas->cd(3);
betaPrimeThreePlot->Draw();
betaPrimeCanvas->cd(4);
betaPrimeFourPlot->Draw();
betaPrimeCanvas->cd(5);
betaPrimeOneCPlot->Draw();
betaPrimeCanvas->SaveAs("betaPrimeVariables.pdf");
TCanvas* betaCorrelationsCanvas = new TCanvas("betaCorrelationsCanvas","betaCorrelationsCanvas",1600,800);
betaCorrelationsCanvas->Divide(4,2);
TH2F* oneTwo = data->createHistogram(betaOnePlotter,betaTwoPlotter,30,30);
TH2F* oneThree = data->createHistogram(betaOnePlotter,betaThreePlotter,30,30);
TH2F* oneFour = data->createHistogram(betaOnePlotter,betaFourPlotter,30,30);
TH2F* twoThree = data->createHistogram(betaTwoPlotter,betaThreePlotter,30,30);
TH2F* twoFour = data->createHistogram(betaTwoPlotter,betaFourPlotter,30,30);
TH2F* threeFour = data->createHistogram(betaThreePlotter,betaFourPlotter,30,30);
TH2F* twoFourC = data->createHistogram(betaTwoPlotter,betaFourCPlotter,30,30);
TH2F* fourFourC = data->createHistogram(betaFourPlotter,betaFourCPlotter,30,30);
betaCorrelationsCanvas->cd(1);
oneTwo->DrawCopy("lego");
betaCorrelationsCanvas->cd(2);
oneThree->DrawCopy("lego");
betaCorrelationsCanvas->cd(3);
oneFour->DrawCopy("lego");
betaCorrelationsCanvas->cd(4);
twoThree->DrawCopy("lego");
betaCorrelationsCanvas->cd(5);
twoFour->DrawCopy("lego");
betaCorrelationsCanvas->cd(6);
threeFour->DrawCopy("lego");
betaCorrelationsCanvas->cd(7);
twoFourC->DrawCopy("lego");
betaCorrelationsCanvas->cd(8);
fourFourC->DrawCopy("lego");
betaCorrelationsCanvas->SaveAs("betaCorrelations.pdf");
TCanvas* betaPrimeCorrelationsCanvas = new TCanvas("betaPrimeCorrelationsCanvas","betaPrimeCorrelationsCanvas",1600,800);
betaPrimeCorrelationsCanvas->Divide(4,2);
TH2F* oneTwo = data->createHistogram(betaPrimeOnePlotter,betaPrimeTwoPlotter,30,30);
TH2F* oneThree = data->createHistogram(betaPrimeOnePlotter,betaPrimeThreePlotter,30,30);
TH2F* oneFour = data->createHistogram(betaPrimeOnePlotter,betaPrimeFourPlotter,30,30);
TH2F* twoThree = data->createHistogram(betaPrimeTwoPlotter,betaPrimeThreePlotter,30,30);
TH2F* twoFour = data->createHistogram(betaPrimeTwoPlotter,betaPrimeFourPlotter,30,30);
TH2F* threeFour = data->createHistogram(betaPrimeThreePlotter,betaPrimeFourPlotter,30,30);
TH2F* oneOneC = data->createHistogram(betaPrimeOnePlotter,betaPrimeOneCPlotter,30,30);
betaPrimeCorrelationsCanvas->cd(1);
oneTwo->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(2);
oneThree->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(3);
oneFour->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(4);
twoThree->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(5);
twoFour->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(6);
threeFour->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(7);
oneOneC->DrawCopy("lego");
betaPrimeCorrelationsCanvas->SaveAs("betaPrimeCorrelations.pdf");
RooProdPdf totalPdf("totalPdf","totalPdf",workspace.allPdfs());
totalPdf.Print("v");
RooArgSet* observableSet = workspace.set("observables");
observableSet->Print();
RooDataSet* allDataOne = totalPdf.generate(*observableSet,1);
allDataOne->Print("v");
correlatedParameter->setVal(0.25);
RooDataSet* allDataTwo = totalPdf.generate(*observableSet,1);
allDataTwo->Print("v");
correlatedParameter->setVal(0.75);
RooDataSet* allDataThree = totalPdf.generate(*observableSet,1);
allDataThree->Print("v");
//Testing for extreme values!
for(int i = 0; i< 101; i++)
{
correlatedParameter->setVal((double)i/100.);
cout << "Correlation parameter has value of " << correlatedParameter->getVal();
cout << " and the pdf has an unnormalized value of " << normalFromFlat->getVal() << endl;
}
}
void rf506_msgservice()
{
// C r e a t e p d f
// --------------------
// Construct gauss(x,m,s)
RooRealVar x("x","x",-10,10) ;
RooRealVar m("m","m",0,-10,10) ;
RooRealVar s("s","s",1,-10,10) ;
RooGaussian gauss("g","g",x,m,s) ;
// Construct poly(x,p0)
RooRealVar p0("p0","p0",0.01,0.,1.) ;
RooPolynomial poly("p","p",x,p0) ;
// Construct model = f*gauss(x) + (1-f)*poly(x)
RooRealVar f("f","f",0.5,0.,1.) ;
RooAddPdf model("model","model",RooArgSet(gauss,poly),f) ;
RooDataSet* data = model.generate(x,10) ;
// P r i n t c o n f i g u r a t i o n o f m e s s a g e s e r v i c e
// ---------------------------------------------------------------------------
// Print streams configuration
RooMsgService::instance().Print() ;
cout << endl ;
// A d d i n g I n t e g r a t i o n t o p i c t o e x i s t i n g I N F O s t r e a m
// -----------------------------------------------------------------------------------------------
// Print streams configuration
RooMsgService::instance().Print() ;
cout << endl ;
// Add Integration topic to existing INFO stream
RooMsgService::instance().getStream(1).addTopic(Integration) ;
// Construct integral over gauss to demonstrate new message stream
RooAbsReal* igauss = gauss.createIntegral(x) ;
igauss->Print() ;
// Print streams configuration in verbose, which also shows inactive streams
cout << endl ;
RooMsgService::instance().Print() ;
cout << endl ;
// Remove stream
RooMsgService::instance().getStream(1).removeTopic(Integration) ;
// E x a m p l e s o f p d f v a l u e t r a c i n g s t r e a m
// -----------------------------------------------------------------------
// Show DEBUG level message on function tracing, trace RooGaussian only
RooMsgService::instance().addStream(DEBUG,Topic(Tracing),ClassName("RooGaussian")) ;
// Perform a fit to generate some tracing messages
model.fitTo(*data,Verbose(kTRUE)) ;
// Reset message service to default stream configuration
RooMsgService::instance().reset() ;
// Show DEBUG level message on function tracing on all objects, redirect output to file
RooMsgService::instance().addStream(DEBUG,Topic(Tracing),OutputFile("rf506_debug.log")) ;
// Perform a fit to generate some tracing messages
model.fitTo(*data,Verbose(kTRUE)) ;
// Reset message service to default stream configuration
RooMsgService::instance().reset() ;
// E x a m p l e o f a n o t h e r d e b u g g i n g s t r e a m
// ---------------------------------------------------------------------
// Show DEBUG level messages on client/server link state management
RooMsgService::instance().addStream(DEBUG,Topic(LinkStateMgmt)) ;
RooMsgService::instance().Print("v") ;
// Clone composite pdf g to trigger some link state management activity
RooAbsArg* gprime = gauss.cloneTree() ;
gprime->Print() ;
// Reset message service to default stream configuration
RooMsgService::instance().reset() ;
}
/***********************************************************************
***********************************************************************
* CONSTRUCTOR MAKES ALLLLLLLL
*******************************************************************
*************************************************
*****************************
*****
*/
Tbroomfit(double xlow, double xhi, TH1 *h2, int npeak, double *peak, double *sigm, const char *chpol="p0"){
int iq=0;
printf("constructor - %d %ld", iq++, (int64_t)h2 );
h2->Print();
/*
* get global area, ranges for sigma, x
*/
npeaks=npeak; // class defined int
// double areah2=h2->Integral( int(xlow), int(xhi) ); // WRONG - BINS
min= h2->GetXaxis()->GetFirst();
printf("constructor - %d %f", iq++, min );
max= h2->GetXaxis()->GetLast();
printf("constructor - %d %f", iq++, max );
double areah2=h2->Integral( min, max );
printf("constructor - %d %f", iq++, areah2 );
min=xlow;
max=xhi;
double sigmamin=(max-min)/300;
double sigmamax=(max-min)/4;
double areamin=0;
double areamax=2*areah2;
printf("x:(%f,%f) s:(%f,%f) a:(%f,%f) \n", min,max,sigmamin, sigmamax,areamin, areamax );
/*
* definition of variables..............
*
*/
RooRealVar x("x", "x", min, max);
int MAXPEAKS=6; // later from 5 to 6 ???
printf("RooFit: npeaks=%d\n", npeaks );
// ABOVE: RooRealVar *msat[14][5]; // POINTERS TO ALL variables
// 0 m Mean
// 1 s Sigma
// 2 a Area
// 3 t Tail
// 4 [0] nalpha
// 5 [0] n1
for (int ii=0;ii<14;ii++){
for (int jj=0;jj<MAXPEAKS;jj++){
msat[ii][jj]=NULL;
msat_values[ii][jj]=0.0;
} //for for
}// for for
printf("delete fitresult, why crash?\n%s","");
fitresult=NULL;
printf("delete fitresult, no crash?\n%s","");
RooRealVar mean1("mean1", "mean", 1*(max-min)/(npeaks+1)+min, min,max);msat[0][0]=&mean1;
RooRealVar mean2("mean2", "mean", 2*(max-min)/(npeaks+1)+min, min,max);msat[0][1]=&mean2;
RooRealVar mean3("mean3", "mean", 3*(max-min)/(npeaks+1)+min, min,max);msat[0][2]=&mean3;
RooRealVar mean4("mean4", "mean", 4*(max-min)/(npeaks+1)+min, min,max);msat[0][3]=&mean4;
RooRealVar mean5("mean5", "mean", 5*(max-min)/(npeaks+1)+min, min,max);msat[0][4]=&mean5;
RooRealVar mean6("mean6", "mean", 6*(max-min)/(npeaks+1)+min, min,max);msat[0][5]=&mean6;
RooRealVar sigma1("sigma1","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][0]=&sigma1;
RooRealVar sigma2("sigma2","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][1]=&sigma2;
RooRealVar sigma3("sigma3","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][2]=&sigma3;
RooRealVar sigma4("sigma4","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][3]=&sigma4;
RooRealVar sigma5("sigma5","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][4]=&sigma5;
RooRealVar sigma6("sigma6","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][5]=&sigma6;
RooRealVar area1("area1", "area", areah2/npeaks, areamin, areamax );msat[2][0]=&area1;
RooRealVar area2("area2", "area", areah2/npeaks, areamin, areamax );msat[2][1]=&area2;
RooRealVar area3("area3", "area", areah2/npeaks, areamin, areamax );msat[2][2]=&area3;
RooRealVar area4("area4", "area", areah2/npeaks, areamin, areamax );msat[2][3]=&area4;
RooRealVar area5("area5", "area", areah2/npeaks, areamin, areamax );msat[2][4]=&area5;
RooRealVar area6("area6", "area", areah2/npeaks, areamin, areamax );msat[2][5]=&area6;
RooRealVar bgarea("bgarea", "bgarea", areah2/5, 0, 2*areah2);
double tailstart=-1.0;// tune the tails....
double tailmin=-1e+4;
double tailmax=1e+4;
RooRealVar tail1("tail1", "tail", tailstart, tailmin, tailmax );msat[3][0]=&tail1;
RooRealVar tail2("tail2", "tail", tailstart, tailmin, tailmax );msat[3][1]=&tail2;
RooRealVar tail3("tail3", "tail", tailstart, tailmin, tailmax );msat[3][2]=&tail3;
RooRealVar tail4("tail4", "tail", tailstart, tailmin, tailmax );msat[3][3]=&tail4;
RooRealVar tail5("tail5", "tail", tailstart, tailmin, tailmax );msat[3][4]=&tail5;
RooRealVar tail6("tail6", "tail", tailstart, tailmin, tailmax );msat[3][5]=&tail6;
// for CBShape
RooRealVar nalpha1("nalpha1", "nalpha", 1.3, 0, 100 );msat[4][0]=&nalpha1;
RooRealVar n1("n1", "n", 5.1, 0, 100 ); msat[5][0]=&n1;
/*
* initial values for peak positions................
*/
if (npeaks>=1) {mean1=peak[0];sigma1=sigm[0];}
if (npeaks>=2) {mean2=peak[1];sigma2=sigm[1];}
if (npeaks>=3) {mean3=peak[2];sigma3=sigm[2];}
if (npeaks>=4) {mean4=peak[3];sigma4=sigm[3];}
if (npeaks>=5) {mean5=peak[4];sigma5=sigm[4];}
if (npeaks>=6) {mean6=peak[5];sigma6=sigm[5];}
/*
* RooAbsPdf -> RooGaussian
* RooNovosibirsk
* RooLandau
*/
RooAbsPdf *pk[6]; // MAXIMUM PEAKS ==5 6 NOW!!
RooAbsPdf *pk_dicto[14][6]; // ALL DICTIONARY OF PEAKS..........
// Abstract Class.... carrefuly
RooGaussian gauss1("gauss1","gauss(x,mean,sigma)", x, mean1, sigma1);pk_dicto[0][0]=&gauss1;
RooGaussian gauss2("gauss2","gauss(x,mean,sigma)", x, mean2, sigma2);pk_dicto[0][1]=&gauss2;
RooGaussian gauss3("gauss3","gauss(x,mean,sigma)", x, mean3, sigma3);pk_dicto[0][2]=&gauss3;
RooGaussian gauss4("gauss4","gauss(x,mean,sigma)", x, mean4, sigma4);pk_dicto[0][3]=&gauss4;
RooGaussian gauss5("gauss5","gauss(x,mean,sigma)", x, mean5, sigma5);pk_dicto[0][4]=&gauss5;
RooGaussian gauss6("gauss6","gauss(x,mean,sigma)", x, mean6, sigma6);pk_dicto[0][5]=&gauss6;
RooNovosibirsk ns1("ns1","novosib(x,mean,sigma,tail)", x, mean1,sigma1, tail1 );pk_dicto[1][0]=&ns1;
RooNovosibirsk ns2("ns2","novosib(x,mean,sigma,tail)", x, mean2,sigma2, tail2 );pk_dicto[1][1]=&ns2;
RooNovosibirsk ns3("ns3","novosib(x,mean,sigma,tail)", x, mean3,sigma3, tail3 );pk_dicto[1][2]=&ns3;
RooNovosibirsk ns4("ns4","novosib(x,mean,sigma,tail)", x, mean4,sigma4, tail4 );pk_dicto[1][3]=&ns4;
RooNovosibirsk ns5("ns5","novosib(x,mean,sigma,tail)", x, mean5,sigma5, tail5 );pk_dicto[1][4]=&ns5;
// BreitWiegner is Lorentzian...?
RooBreitWigner bw1("bw1","BreitWigner(x,mean,sigma)", x, mean1, sigma1 );pk_dicto[2][0]=&bw1;
RooBreitWigner bw2("bw2","BreitWigner(x,mean,sigma)", x, mean2, sigma2 );pk_dicto[2][1]=&bw2;
RooBreitWigner bw3("bw3","BreitWigner(x,mean,sigma)", x, mean3, sigma3 );pk_dicto[2][2]=&bw3;
RooBreitWigner bw4("bw4","BreitWigner(x,mean,sigma)", x, mean4, sigma4 );pk_dicto[2][3]=&bw4;
RooBreitWigner bw5("bw5","BreitWigner(x,mean,sigma)", x, mean5, sigma5 );pk_dicto[2][4]=&bw5;
RooCBShape cb1("cb1","CBShape(x,mean,sigma)", x, mean1, sigma1, nalpha1, n1 );pk_dicto[3][0]=&cb1;
RooCBShape cb2("cb2","CBShape(x,mean,sigma)", x, mean2, sigma2, nalpha1, n1 );pk_dicto[3][1]=&cb2;
RooCBShape cb3("cb3","CBShape(x,mean,sigma)", x, mean3, sigma3, nalpha1, n1 );pk_dicto[3][2]=&cb3;
RooCBShape cb4("cb4","CBShape(x,mean,sigma)", x, mean4, sigma4, nalpha1, n1 );pk_dicto[3][3]=&cb4;
RooCBShape cb5("cb5","CBShape(x,mean,sigma)", x, mean5, sigma5, nalpha1, n1 );pk_dicto[3][4]=&cb5;
RooCBShape cb6("cb6","CBShape(x,mean,sigma)", x, mean6, sigma6, nalpha1, n1 );pk_dicto[3][5]=&cb6;
/*
* PEAK TYPES BACKGROUND TYPE ......... COMMAND BOX OPTIONS ......
*/
/****************************************************************************
* PLAY WITH THE DEFINITION COMMANDLINE...................... POLYNOM + PEAKS
*/
// CALSS DECLARED TString s;
s=chpol;
/*
* peaks+bg== ALL BEFORE ; or : (after ... it is a conditions/options)
*/
TString command;
int comstart=s.Index(":"); if (comstart<0){ comstart=s.Index(";");}
if (comstart<0){ command="";}else{
command=s(comstart+1, s.Length()-comstart -1 ); // without ;
s=s(0,comstart); // without ;
printf("COMMANDLINE : %s\n", command.Data() );
if (TPRegexp("scom").Match(command)!=0){
}// COMMANDS -
}// there is some command
/*************************************************
* PLAY WITH peaks+bg.................. s
*/
s.Append("+"); s.Prepend("+"); s.ReplaceAll(" ","+");
s.ReplaceAll("++++","+"); s.ReplaceAll("+++","+"); s.ReplaceAll("++","+");s.ReplaceAll("++","+");
printf (" regextp = %s\n", s.Data() );
if (TPRegexp("\\+p[\\dn]\\+").Match(s)==0){ // no match
printf("NO polynomial demanded =>: %s\n", "appending pn command" ); s.Append("pn+");
}
TString spk=s; TString sbg=s;
TPRegexp("\\+p[\\dn]\\+").Substitute(spk,"+"); // remove +p.+
TPRegexp(".+(p[\\dn]).+").Substitute(sbg,"$1"); // remove all but +p+
printf ("PEAKS=%s BG=%s\n", spk.Data() , sbg.Data() );
spk.ReplaceAll("+",""); // VARIANT 1 ------- EACH LETTER MEANS ONE PEAK
/************************************************************************
* PREPARE PEAKS FOLLOWING THE COMMAND BOX................
*/
//default PEAK types
pk[0]=&gauss1;
pk[1]=&gauss2;
pk[2]=&gauss3;
pk[3]=&gauss4;
pk[4]=&gauss5;
pk[5]=&gauss6;
int maxi=spk.Length();
if (maxi>npeaks){maxi=npeaks;}
for (int i=0;i<maxi;i++){
if (spk[i]=='n'){
pk[i]=pk_dicto[1][i];//novosibirsk
printf("PEAK #%d ... Novosibirsk\n", i );
}else if(spk[i]=='b'){
pk[i]=pk_dicto[2][i];//BreitWiegner
printf("PEAK #%d ... BreitWigner\n", i );
}else if(spk[i]=='c'){
pk[i]=pk_dicto[3][i];//CBShape
printf("PEAK #%d ... CBShape\n", i );
}else if(spk[i]=='y'){
}else if(spk[i]=='z'){
}else{
pk[i]=pk_dicto[0][i]; //gauss
printf("PEAK #%d ... Gaussian\n", i );
}// ELSE CHAIN
}//i to maxi
for (int i=0;i<npeaks;i++){ printf("Peak %d at %f s=%f: PRINT:\n " , i, peak[i], sigm[i] );pk[i]->Print();}
/******************************************************** BACKGROUND pn-p4
* a0 == level - also skew
* a1 == p2
* a2 == p3
*/
// Build Chebychev polynomial p.d.f.
// RooRealVar a0("a0","a0", 0.) ;
RooRealVar a0("a0","a0", 0., -10, 10) ;
RooRealVar a1("a1","a1", 0., -10, 10) ;
RooRealVar a2("a2","a2", 0., -10, 10) ;
RooRealVar a3("a3","a3", 0., -10, 10) ;
RooArgSet setcheb;
if ( sbg=="pn" ){ setcheb.add(a0); a0=0.; a0.setConstant(kTRUE);bgarea=0.; bgarea.setConstant(kTRUE);}
if ( sbg=="p0" ){ setcheb.add(a0); a0=0.; a0.setConstant(kTRUE); }
if ( sbg=="p1" ){ setcheb.add(a0); }
if ( sbg=="p2" ){ setcheb.add(a1); setcheb.add(a0); }
if ( sbg=="p3" ){ setcheb.add(a2); setcheb.add(a1); setcheb.add(a0); }
if ( sbg=="p4" ){ setcheb.add(a3);setcheb.add(a2); setcheb.add(a1); setcheb.add(a0); }
// RooChebychev bkg("bkg","Background",x,RooArgSet(a0,a1,a2,a3) ) ;
RooChebychev bkg("bkg","Background",x, setcheb ) ;
/**********************************************************************
* MODEL
*/
RooArgList rl;
if (npeaks>0)rl.add( *pk[0] );
if (npeaks>1)rl.add( *pk[1] );
if (npeaks>2)rl.add( *pk[2] );
if (npeaks>3)rl.add( *pk[3] );
if (npeaks>4)rl.add( *pk[4] );
if (npeaks>5)rl.add( *pk[5] );
rl.add( bkg );
RooArgSet rs;
if (npeaks>0)rs.add( area1 );
if (npeaks>1)rs.add( area2 );
if (npeaks>2)rs.add( area3 );
if (npeaks>3)rs.add( area4 );
if (npeaks>4)rs.add( area5 );
if (npeaks>5)rs.add( area6 );
rs.add( bgarea );
RooAddPdf modelV("model","model", rl, rs );
/*
* WITH CUSTOMIZER - I can change parameters inside. But
* - then all is a clone and I dont know how to reach it
*/
RooCustomizer cust( modelV ,"cust");
/*
* Possibility to fix all sigma or tails....
*/
if (TPRegexp("scom").Match(command)!=0){//----------------------SCOM
printf("all sigma have common values.....\n%s", "");
if (npeaks>1)cust.replaceArg(sigma2,sigma1) ;
if (npeaks>2)cust.replaceArg(sigma3,sigma1) ;
if (npeaks>3)cust.replaceArg(sigma4,sigma1) ;
if (npeaks>4)cust.replaceArg(sigma5,sigma1) ;
if (npeaks>5)cust.replaceArg(sigma6,sigma1) ;
}
if (TPRegexp("tcom").Match(command)!=0){//----------------------TCOM
printf("all tails have common values.....\n%s", "");
if (npeaks>1)cust.replaceArg(tail2,tail1) ;
if (npeaks>2)cust.replaceArg(tail3,tail1) ;
if (npeaks>3)cust.replaceArg(tail4,tail1) ;
if (npeaks>4)cust.replaceArg(tail5,tail1) ;
if (npeaks>5)cust.replaceArg(tail6,tail1) ;
}
/* if (TPRegexp("tcom").Match(command)!=0){//----------------------TCOM Neni dalsi ACOM,NCOM pro CB...
printf("all tails have common values.....\n%s", "");
if (npeaks>1)cust.replaceArg(tail2,tail1) ;
if (npeaks>2)cust.replaceArg(tail3,tail1) ;
if (npeaks>3)cust.replaceArg(tail4,tail1) ;
if (npeaks>4)cust.replaceArg(tail5,tail1) ;
}
*/
if (TPRegexp("p1fix").Match(command)!=0){//----------------------
mean1.setConstant();printf("position 1 set constant%s\n","");
}
if (TPRegexp("p2fix").Match(command)!=0){//----------------------
mean2.setConstant();printf("position 2 set constant%s\n","");
}
if (TPRegexp("p3fix").Match(command)!=0){//----------------------
mean3.setConstant();printf("position 3 set constant%s\n","");
}
if (TPRegexp("p4fix").Match(command)!=0){//----------------------
mean4.setConstant();printf("position 4 set constant%s\n","");
}
if (TPRegexp("p5fix").Match(command)!=0){//----------------------
mean5.setConstant();printf("position 5 set constant%s\n","");
}
if (TPRegexp("p6fix").Match(command)!=0){//----------------------
mean6.setConstant();printf("position 6 set constant%s\n","");
}
if (TPRegexp("s1fix").Match(command)!=0){//----------------------
sigma1.setConstant();printf("sigma 1 set constant%s\n","");
}
if (TPRegexp("s2fix").Match(command)!=0){//----------------------
sigma2.setConstant();printf("sigma 2 set constant%s\n","");
}
if (TPRegexp("s3fix").Match(command)!=0){//----------------------
sigma3.setConstant();printf("sigma 3 set constant%s\n","");
}
if (TPRegexp("s4fix").Match(command)!=0){//----------------------
sigma4.setConstant();printf("sigma 4 set constant%s\n","");
}
if (TPRegexp("s5fix").Match(command)!=0){//----------------------
sigma5.setConstant();printf("sigma 5 set constant%s\n","");
}
if (TPRegexp("s6fix").Match(command)!=0){//----------------------
sigma6.setConstant();printf("sigma 6 set constant%s\n","");
}
RooAbsPdf* model = (RooAbsPdf*) cust.build(kTRUE) ; //build a clone...comment on changes...
// model->Print("t") ;
//delete model ; // eventualy delete the model...
/*
* DISPLAY RESULTS >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
*/
TPad *orig_gpad=(TPad*)gPad;
TCanvas *c;
c=(TCanvas*)gROOT->GetListOfCanvases()->FindObject("fitresult");
if (c==NULL){
printf("making new canvas\n%s","");
c=new TCanvas("fitresult",h2->GetName(),1000,700);
}else{
printf("using old canvas\n%s","");
c->SetTitle( h2->GetName() );
}
c->Clear();
printf(" canvas cleared\n%s","");
c->Divide(1,2) ;
printf(" canvas divided\n%s","");
c->Modified();c->Update();
RooDataHist datah("datah","datah with x",x,h2);
RooPlot* xframe = x.frame();
datah.plotOn(xframe, DrawOption("logy") );
// return;
if (TPRegexp("chi2").Match(command)!=0){//----------------------CHI2
//from lorenzo moneta
// TH1 * h1 = datah.createHistogram(x);
// TF1 * f = model->asTF(RooArgList(x) , parameters ); //???
// h2->Fit(f);
//It will work but you need to create a THNSparse and fit it
//or use directly the ROOT::Fit::BinData class to create a ROOT::Fit::Chi2Function to minimize.
// THIS CANNOT DO ZERO BINS
fitresult = model->chi2FitTo( datah , Save() );
}else{
// FIT FIT FIT FIT FIT FIT FIT FIT FIT FIT
fitresult = model->fitTo( datah , Save() );
}
fitresult->SetTitle( h2->GetName() ); // I PUT histogram name to global fitresult
// will be done by printResult ... fitresult->Print("v") ;
//duplicite fitresult->floatParsFinal().Print("s") ;
// later - after parsfinale .... : printResult();
// model->Print(); // not interesting........
model->plotOn(xframe, LineColor(kRed), DrawOption("l0z") );
//,Minos(kFALSE)
/*
* Posledni nakreslena vec je vychodiskem pro xframe->resid...?
* NA PORADI ZALEZI....
*/
//unused RooHist* hresid = xframe->residHist() ;
RooHist* hpull = xframe->pullHist() ;
// RooPlot* xframe2 = x.frame(Title("Residual Distribution")) ;
// xframe2->addPlotable(hresid,"P") ;
// Construct a histogram with the pulls of the data w.r.t the curve
RooPlot* xframe3 = x.frame(Title("Pull Distribution")) ;
xframe3->addPlotable(hpull,"P") ;
/*
* plot components at the end.... PLOT >>>>>>>>>>>>>>>>
*/
int colorseq[10]={kRed,kGreen,kBlue,kYellow,kCyan,kMagenta,kViolet,kAzure,kGray,kOrange};
// RooArgSet* model_params = model->getParameters(x); // this returns all parameters
RooArgSet* model_params = model->getComponents();
TIterator* iter = model_params->createIterator() ;
RooAbsArg* arg ; int icomp=0, ipeak=0;
// printf("ENTERING COMPONENT ITERATOR x%dx.....................\n", icomp );
while((arg=(RooAbsArg*)iter->Next())) {
// printf("printing COMPONENT %d\n", icomp );
// arg->Print();
// printf("NAME==%s\n", arg->Class_Name() ); //This returns only RooAbsArg
// printf("NAME==%s\n", arg->ClassName() ); //This RooGaussian RooChebychev
if ( IsPeak( arg->ClassName() )==1 ){
pk[ipeak]=(RooAbsPdf*)arg; //?
// pk[ipeak]->Print();
ipeak++;
// printf("adresses ... %d - %d - %d\n", pk[0], pk[1], pk[2] );
}// yes peak.
icomp++;
}//iterations over all components
model->plotOn(xframe, Components(bkg), LineColor(kRed), LineStyle(kDashed), DrawOption("l0z") );
for (int i=0;i<npeaks;i++){
// printf("plotting %d. peak, color %d\n", i, colorseq[i+1] );
// printf("adresses ... %d - %d - %d\n", pk[0], pk[1], pk[2] );
// pk[i]->Print();
model->plotOn(xframe, Components( RooArgSet(*pk[i],bkg) ), LineColor(colorseq[i+1]), LineStyle(kDashed),
DrawOption("l0z") );
// DrawOption("pz"),DataError(RooAbsData::SumW2) );??? pz removes complains...warnings
// model.plotOn(xframe, Components( RooArgSet(*pk[i],bkg) ), LineColor(colorseq[i+1]), LineStyle(kDashed));
}
// WE SET THE 1st PAD in "fitresult" to LOGY.... 1
// ..... if the original window is LOGY..... :)
//
// printf("########### ORIGPAD LOGY==%d #########3\n", orig_gpad->GetLogy() );
c->cd(1); xframe->Draw(); gPad->SetLogy( orig_gpad->GetLogy() );
// c->cd(2); xframe2->Draw();
c->cd(2); xframe3->Draw();
c->Modified();c->Update();
orig_gpad->cd();
// printf("msat reference to peak 0 0 = %d, (%f)\n", msat[0][0] , msat[0][0]->getVal() );
for (int ii=0;ii<14;ii++){
for (int jj=0;jj<MAXPEAKS;jj++){
if ( msat[ii][jj]!=NULL){
msat_values[ii][jj]=msat[ii][jj]->getVal();
}//if
} //for for
}// for for
printf("at the total end of the constructor....%s\n","");
// done in pirntResult .. fitresult->floatParsFinal().Print("s") ;
printResult();
}; // constructor
void DrawChannelCompatibility(double rMin = -5,double rMax=5)
{
gROOT->ForceStyle();
TFile *inf = TFile::Open("higgsCombineZ.ChannelCompatibilityCheck.mH120.root");
RooFitResult *fit_nominal = (RooFitResult *)inf->Get("fit_nominal");
RooFitResult *fit_alternate = (RooFitResult *)inf->Get("fit_alternate");
RooRealVar *rFit = (RooRealVar*)fit_nominal->floatParsFinal().find("r");
TString prefix = TString::Format("_ChannelCompatibilityCheck_%s_","r");
int nChann = 0;
TIterator *iter = fit_alternate->floatParsFinal().createIterator();
for (RooAbsArg *a = (RooAbsArg *) iter->Next(); a != 0; a = (RooAbsArg *) iter->Next()) {
if (TString(a->GetName()).Index(prefix) == 0) nChann++;
}
TH2F *frame = new TH2F("frame",";best fit #sigma/#sigma_{SM};",1,rMin,rMax,nChann,0,nChann);
iter->Reset();
int iChann = 0;
TGraphAsymmErrors *points = new TGraphAsymmErrors(nChann);
float chi2(0.0);
for (RooAbsArg *a = (RooAbsArg *) iter->Next(); a != 0; a = (RooAbsArg *) iter->Next()) {
if (TString(a->GetName()).Index(prefix) == 0) {
RooRealVar *ri = (RooRealVar *) a;
TString channel = a->GetName();
channel.ReplaceAll(prefix,"");
points->SetPoint(iChann,ri->getVal(),iChann+0.5);
cout<<channel<<" "<<ri->getVal()<<" "<<ri->getAsymErrorLo()<<" +"<<ri->getAsymErrorHi()<<endl;
chi2 += pow((ri->getVal()-rFit->getVal())/ri->getError(),2);
points->SetPointError(iChann,-ri->getAsymErrorLo(),ri->getAsymErrorHi(),0,0);
//points->SetPointError(iChann,ri->getAsymErrorHi(),ri->getAsymErrorHi(),0,0);
iChann++;
frame->GetYaxis()->SetBinLabel(iChann, channel);
}
}
cout<<"Combined fit: "<<rFit->getVal()<<" "<<rFit->getAsymErrorLo()<<" +"<<rFit->getAsymErrorHi()<<endl;
cout<<"chi2 = "<<chi2<<endl;
points->SetLineColor(kRed);
points->SetLineWidth(3);
points->SetMarkerStyle(21);
TCanvas *can = new TCanvas("ChannelCompatibility_Z","ChannelCompatibility_Z",900,600);
frame->GetXaxis()->SetNdivisions(505);
frame->GetXaxis()->SetTitleSize(0.06);
frame->GetXaxis()->SetTitleOffset(0.9);
frame->GetXaxis()->SetLabelSize(0.05);
frame->GetYaxis()->SetLabelSize(0.1);
frame->Draw();
//gStyle->SetOptStat(0);
TBox globalFitBand(rFit->getVal()+rFit->getAsymErrorLo(), 0, rFit->getVal()+rFit->getAsymErrorHi(), nChann);
//TBox globalFitBand(rFit->getVal()-rFit->getAsymErrorHi(), 0, rFit->getVal()+rFit->getAsymErrorHi(), nChann);
globalFitBand.SetFillStyle(3013);
globalFitBand.SetFillColor(65);
globalFitBand.SetLineStyle(0);
globalFitBand.DrawClone();
TLine globalFitLine(rFit->getVal(), 0, rFit->getVal(), nChann);
globalFitLine.SetLineWidth(4);
globalFitLine.SetLineColor(214);
globalFitLine.DrawClone();
points->Draw("P SAME");
gPad->Update();
TLine *ln0 = new TLine(1,gPad->GetFrame()->GetY1(),1,gPad->GetFrame()->GetY2());
ln0->SetLineColor(kBlack);
ln0->SetLineWidth(1);
ln0->SetLineStyle(2);
ln0->Draw("same");
}
