void plot_toys()
{
TFile* f = new TFile("/project/atlas/users/tlenz/HWWStatisticsCode_v31/CPmix_kHWW2dot65m_0j_trainv31_v31_allsys_topLumi_toys.root");
RooWorkspace* w = (RooWorkspace*)f->Get("combined");
RooDataSet* data = (RooDataSet*)w->data("obsData");
RooDataSet* toydata = (RooDataSet*)w->data("toyData");
RooDataSet* toydata2 = (RooDataSet*)w->data("toyData4");
RooDataSet* thisAsimovData = (RooDataSet*)w->data("asimivData_profiled_for_epsilon_0"); //asimivData_profiled_for_epsilon_0
RooPlot* frame1 = w->var("obs_x_em_signalLike_0j_2012")->frame();
// RooPlot* frame2 = w->var("obs_x_em_mainControl_0j_2012")->frame();
// RooPlot* frame3 = w->var("obs_x_em_zbox_0j_2012")->frame();
data->plotOn(frame1, Name("data"), DataError(RooAbsData::Poisson), Cut("merged_cat==merged_cat::em_signalLike_0j_2012"));
//data->plotOn(frame2, Name("data"), DataError(RooAbsData::Poisson), Cut("merged_cat==merged_cat::em_mainControl_0j_2012"));
//data->plotOn(frame3, Name("data"), DataError(RooAbsData::Poisson), Cut("merged_cat==merged_cat::em_zbox_0j_2012"));
toydata->plotOn(frame1, Name("toy1"), LineColor(kRed), MarkerStyle(21), MarkerColor(kRed), DataError(RooAbsData::Poisson), Cut("merged_cat==merged_cat::em_signalLike_0j_2012"));
//toydata->plotOn(frame2, Name("toy1"), LineColor(kRed), MarkerStyle(21), MarkerColor(kRed), DataError(RooAbsData::Poisson), Cut("merged_cat==merged_cat::em_mainControl_0j_2012"));
//toydata->plotOn(frame3, Name("toy1"), LineColor(kRed), MarkerStyle(21), MarkerColor(kRed), DataError(RooAbsData::Poisson), Cut("merged_cat==merged_cat::em_zbox_0j_2012"));
toydata2->plotOn(frame1, Name("toy4"), LineColor(kGreen), MarkerStyle(21), MarkerColor(kGreen), DataError(RooAbsData::Poisson), Cut("merged_cat==merged_cat::em_signalLike_0j_2012"));
//toydata2->plotOn(frame2, Name("toy4"), LineColor(kGreen), MarkerStyle(21), MarkerColor(kGreen), DataError(RooAbsData::Poisson), Cut("merged_cat==merged_cat::em_mainControl_0j_2012"));
//toydata2->plotOn(frame3, Name("toy4"), LineColor(kGreen), MarkerStyle(21), MarkerColor(kGreen), DataError(RooAbsData::Poisson), Cut("merged_cat==merged_cat::em_zbox_0j_2012"));
thisAsimovData->plotOn(frame1, Name("asimov"), LineColor(kBlue), MarkerStyle(22), MarkerColor(kBlue), DataError(RooAbsData::Poisson), Cut("merged_cat==merged_cat::em_signalLike_0j_2012"));
//thisAsimovData->plotOn(frame2, Name("asimov"), LineColor(kBlue), MarkerStyle(22), MarkerColor(kBlue), DataError(RooAbsData::Poisson), Cut("merged_cat==merged_cat::em_mainControl_0j_2012"));
//thisAsimovData->plotOn(frame3, Name("asimov"), LineColor(kBlue), MarkerStyle(22), MarkerColor(kBlue), DataError(RooAbsData::Poisson), Cut("merged_cat==merged_cat::em_zbox_0j_2012"));
TCanvas* c = new TCanvas("c","c",1800,600);
//c->Divide(3,1);
/*c->cd(1);*/ /*gPad->SetLogy();*/ frame1->Draw();
//c->cd(2); frame2->Draw();
//draw legend
TLegend *leg = new TLegend(0.48, 0.60, 0.84, 0.80, NULL,"brNDC");
leg->SetBorderSize(0);
leg->SetTextFont(62);
leg->SetTextSize(0.04);
leg->SetLineColor(1);
leg->SetLineStyle(1);
leg->SetLineWidth(1);
leg->SetFillColor(0);
leg->SetFillStyle(1001);
leg->SetNColumns(1);
leg->AddEntry(frame1->findObject("data"),"data","pl");
leg->AddEntry(frame1->findObject("toy1"),"toy1","pl");
leg->AddEntry(frame1->findObject("toy4"),"toy4","pl");
leg->AddEntry(frame1->findObject("asimov"),"asimov","pl");
leg->Draw();
//c->cd(3); frame3->Draw();
c->Print("toys_linear.pdf");
}
int main(){
RooMsgService::instance().setGlobalKillBelow(ERROR);
TFile *bkgFile = TFile::Open("comb_svn/hgg.inputbkgdata_8TeV_MVA.root");
RooWorkspace *bkgWS = (RooWorkspace*)bkgFile->Get("cms_hgg_workspace");
RooRealVar *mass = (RooRealVar*)bkgWS->var("CMS_hgg_mass");
RooDataSet *data = (RooDataSet*)bkgWS->data("data_mass_cat0");
RooRealVar *p1 = new RooRealVar("p1","p1",-2.,-10.,0.);
RooRealVar *p2 = new RooRealVar("p2","p2",-0.001,-0.01,0.01);
RooRealVar *p3 = new RooRealVar("p3","p3",-0.0001,-0.01,0.01);
//RooPowerLawSum *pow1 = new RooPowerLawSum("pow","pow",*mass,RooArgList(*p1));
//RooPowerLawSum *pow2 = new RooPowerLawSum("pow","pow",*mass,RooArgList(*p1,*p2));
//RooPowerLawSum *pow3 = new RooPowerLawSum("pow","pow",*mass,RooArgList(*p1,*p2,*p3));
RooExponentialSum *pow1 = new RooExponentialSum("pow1","pow1",*mass,RooArgList(*p1));
RooExponentialSum *pow2 = new RooExponentialSum("pow2","pow2",*mass,RooArgList(*p1,*p2));
RooExponentialSum *pow3 = new RooExponentialSum("pow3","pow3",*mass,RooArgList(*p1,*p2,*p3));
TCanvas *canv = new TCanvas();
RooPlot *frame = mass->frame();
data->plotOn(frame);
cout << "bus" << endl;
pow1->fitTo(*data,PrintEvalErrors(-1),PrintLevel(-1),Warnings(-1),Verbose(-1));
cout << "bus" << endl;
pow1->plotOn(frame);
pow2->fitTo(*data);
pow2->plotOn(frame,LineColor(kRed),LineStyle(kDashed));
pow3->fitTo(*data);
pow3->plotOn(frame,LineColor(kGreen),LineStyle(7));
frame->Draw();
canv->Print("test.pdf");
TFile *outFile = new TFile("test.root","RECREATE");
TTree *tree = new TTree("tree","tree");
vector<double> mu;
mu.push_back(1.);
mu.push_back(2.);
mu.push_back(3.);
mu.push_back(4.);
vector<string> label;
label.push_back("pol");
label.push_back("pow");
label.push_back("lau");
label.push_back("exp");
tree->Branch("mu",&mu);
tree->Branch("label",&label);
tree->Fill();
outFile->cd();
tree->Write();
outFile->Close();
return 0;
}
void setRange(RooWorkspace& myws, RooPlot* frame, string dsName, bool setLogScale, double dMuonYmin)
{
// Find maximum and minimum points of Plot to rescale Y axis
TH1* h = myws.data(dsName.c_str())->createHistogram("hist", *myws.var("ctau"), Binning(frame->GetNbinsX(),frame->GetXaxis()->GetXmin(),frame->GetXaxis()->GetXmax()));
Double_t YMax = h->GetBinContent(h->GetMaximumBin());
cout << YMax << endl;
// Double_t YMin = min( h->GetBinContent(h->FindFirstBinAbove(0.0)), h->GetBinContent(h->FindLastBinAbove(0.0)) );
Double_t YMin = 1e99;
for (int i=1; i<=h->GetNbinsX(); i++) if (h->GetBinContent(i)>0) YMin = min(YMin, h->GetBinContent(i));
bool isMC = false;
if (dsName.find("MC")!=std::string::npos) isMC = true;
Double_t Yup(0.),Ydown(0.);
if(setLogScale)
{
if (isMC) Ydown = YMin*0.3;
else Ydown = YMin/(TMath::Power((YMax/YMin), (0.1/(1.0-0.1-0.4))));
Yup = YMax*TMath::Power((YMax/YMin), (0.4/(1.0-0.1-0.4)));
}
else
{
Ydown = max(YMin-(YMax-YMin)*(0.1/(1.0-0.1-0.4)),0.0);
Yup = YMax+(YMax-YMin)*(0.4/(1.0-0.1-0.4));
}
cout << Ydown << " " << Yup << endl;
frame->GetYaxis()->SetRangeUser(Ydown,Yup);
delete h;
// Create line to indicate upper fitting range for MC
if (isMC)
{
if (dsName.find("JPSIP")!=std::string::npos)
{
TLine* line(0x0);
if (dMuonYmin >= 1.6) line = new TLine(3.32,Ydown,3.32,Yup);
else line = new TLine(3.26,Ydown,3.26,Yup);
line->SetLineStyle(2);
line->SetLineColor(1);
line->SetLineWidth(3);
frame->addObject(line);
}
else if (dsName.find("PSI2S")!=std::string::npos)
{
TLine* line(0x0);
if (dMuonYmin >= 1.6) line = new TLine(3.95,Ydown,3.95,Yup);
else line = new TLine(3.85,Ydown,3.85,Yup);
line->SetLineStyle(2);
line->SetLineColor(1);
line->SetLineWidth(3);
frame->addObject(line);
}
}
}
void makeFit( TString inf, TString outf ) {
TFile *tf = TFile::Open( inf );
RooWorkspace *w = (RooWorkspace*)tf->Get("w");
//w->factory( "Gaussian::dst_mass1( Dst_M, dst_mean[2005,2015], dst_sigma1[1,20] )" );
//w->factory( "Gaussian::dst_mass2( Dst_M, dst_mean, dst_sigma2[3,50] )" );
//w->factory( "Gaussian::dst_mass3( Dst_M, dst_mean, dst_sigma3[5,200] )" );
//w->factory( "SUM::dst_mass( dst_f[0.1,1.]*dst_mass1, dst_f2[0.1,1.]*dst_mass2, dst_mass3 )" );
//w->factory( "SUM::dst_mass_sig( dst_f[0.1,1.]*dst_mass1, dst_f2[0.1,1.]*dst_mass2, dst_mass3 )" );
w->factory( "Gaussian::dst_mass1( Dst_M, dst_mean[2005,2015], dst_sigma1[1,20] )" );
w->factory( "CBShape::dst_mass2( Dst_M, dst_mean, dst_sigma2[1,20], dst_alpha[0.1,10.], dst_n1[0.1,10.] )" );
w->factory( "SUM::dst_mass_sig( dst_f[0.1,1.]*dst_mass1, dst_mass2 )" );
w->factory( "Bernstein::dst_mass_bkg( Dst_M, {1.,dst_p0[0.,1.]} )" );
w->factory( "SUM::dst_mass( dst_mass_sy[0,10e8]*dst_mass_sig, dst_mass_by[0,10e2]*dst_mass_bkg )" );
//w->factory( "Gaussian::d0_mass1( D0_M, d0_mean[1862,1868], d0_sigma1[1,20] )" );
//w->factory( "Gaussian::d0_mass2( D0_M, d0_mean, d0_sigma2[3,50] )" );
//w->factory( "Gaussian::d0_mass3( D0_M, d0_mean, d0_sigma3[5,200] )" );
//w->factory( "SUM::d0_mass( d0_f[0.1,1.]*d0_mass1, d0_f2[0.1,1.]*d0_mass2, d0_mass3 )" );
//w->factory( "SUM::d0_mass( d0_f[0.1,1.]*d0_mass1, d0_f2[0.1,1.]*d0_mass2, d0_mass3 )" );
w->factory( "Gaussian::d0_mass1( D0_M, d0_mean[1862,1868], d0_sigma1[1,20] )" );
w->factory( "CBShape::d0_mass2( D0_M, d0_mean, d0_sigma2[1,20], d0_alpha[0.1,10.], d0_n1[0.1,10.] )" );
w->factory( "SUM::d0_mass_sig( d0_f[0.1,1.]*d0_mass1, d0_mass2 )" );
w->factory( "Bernstein::d0_mass_bkg( D0_M, {1.,d0_p0[0.,1.]} )" );
w->factory( "SUM::d0_mass( d0_mass_sy[0,10e8]*d0_mass_sig, d0_mass_by[0,10e1]*d0_mass_bkg )" );
w->factory( "d0_tau[0,1000.]" );
w->factory( "expr::d0_e( '-1/@0', d0_tau)" );
w->factory( "Exponential::d0_t( D0_LTIME_ps, d0_e )" );
w->pdf("dst_mass")->fitTo( *w->data("Data") , Range(1960,2060) );
w->pdf("d0_mass") ->fitTo( *w->data("Data") , Range(1820,1910) );
w->pdf("d0_t") ->fitTo( *w->data("Data") , Range(0.25,5.) );
tf->Close();
w->writeToFile(outf);
}
RooAbsData * Tprime::GetWorkspaceData( std::string datasetName ) {
//
// Return a pointer to a dataset from workspace.
// Class member pointer data set to point to the dataset.
// Caller does not take ownership.
//
//RooArgSet * pPoiSet = pMc
delete data;
data = (RooAbsData *)pWs->data(datasetName.c_str())->Clone();
return data;
}
vector<double> sigEvents(RooWorkspace *work, int m_hyp, int cat, string altSigFileName, int spin=false){
RooWorkspace *tempWork;
if (altSigFileName!=""){
TFile *temp = TFile::Open(altSigFileName.c_str());
tempWork = (RooWorkspace*)temp->Get("cms_hgg_workspace");
}
else {
tempWork = work;
}
vector<double> result;
RooDataSet *ggh = (RooDataSet*)tempWork->data(Form("sig_ggh_mass_m%d_cat%d",m_hyp,cat));
RooDataSet *vbf = (RooDataSet*)tempWork->data(Form("sig_vbf_mass_m%d_cat%d",m_hyp,cat));
RooDataSet *wzh = (RooDataSet*)tempWork->data(Form("sig_wzh_mass_m%d_cat%d",m_hyp,cat));
RooDataSet *tth = (RooDataSet*)tempWork->data(Form("sig_tth_mass_m%d_cat%d",m_hyp,cat));
double total;
if (!spin) {
total = ggh->sumEntries()+vbf->sumEntries()+wzh->sumEntries()+tth->sumEntries();
result.push_back(total);
result.push_back(100*ggh->sumEntries()/total);
result.push_back(100*vbf->sumEntries()/total);
result.push_back(100*wzh->sumEntries()/total);
result.push_back(100*tth->sumEntries()/total);
}
else {
ggh = (RooDataSet*)tempWork->data(Form("sig_mass_m%d_cat%d",m_hyp,cat));
total = ggh->sumEntries();
result.push_back(total);
result.push_back(100.);
result.push_back(0.);
result.push_back(0.);
result.push_back(0.);
}
return result;
}
void plotFromWorkspace() {
TFile* file = new TFile("card_m125_1JetIncl_XX_workspace.root");
RooWorkspace* w = (RooWorkspace*)file->Get("w");
RooRealVar* m = (RooRealVar*)w->var("CMS_hmumu_mass");
RooRealVar* e = (RooRealVar*)w->var("CMS_hmumu_merr");
RooDataSet* d = (RooDataSet*)w->data("data_pseudo");
RooAbsPdf * b = w->pdf("bkg_mass_merr_1JetIncl_XX_pdf");
RooAbsPdf * s = w->pdf("sig_mass_merr_ggH_1JetIncl_XX_pdf");
RooPlot* frame = m->frame();
d->plotOn(frame);
b->plotOn(frame);
//s->plotOn(frame, RooFit::ProjWData(*e, *d), RooFit::LineColor(kOrange+1));
//s->plotOn(frame, RooFit::LineColor(kOrange+1));
frame->Draw();
}
void workspaceMerger::combineWorkspaces(){
// Get names of objects inside RooContainer
std::vector<std::string> histogramNames = rooContainer->GetTH1FNames();
std::vector<std::string> datasetNames = rooContainer->GetDataSetNames();
// Loop Over the files and get the relevant pieces to Merge:
for (std::vector<std::string>::iterator it_comb=combineFileNames.begin()
;it_comb!=combineFileNames.end()
;it_comb++){
TFile *tmpFile = TFile::Open((*it_comb).c_str());
tmpFile->cd();
std::cout << "Combining Current File - " << (*it_comb) << std::endl;
for (std::vector<std::string>::iterator it_hist=histogramNames.begin()
;it_hist!=histogramNames.end()
;it_hist++) {
TH1F *histExtra = (TH1F*) tmpFile->Get(Form("th1f_%s",it_hist->c_str()));
rooContainer->AppendTH1F(*it_hist,histExtra);
}
RooWorkspace *work = (RooWorkspace*) tmpFile->Get("cms_hgg_workspace");
for (std::vector<std::string>::iterator it_data=datasetNames.begin()
;it_data!=datasetNames.end()
;it_data++) {
RooDataSet *dataExtra = (RooDataSet*) work->data(Form("%s",it_data->c_str()));
rooContainer->AppendDataSet(*it_data,dataExtra);
}
std::cout << "Finished Combining File - " << (*it_comb) << std::endl;
tmpFile->Close();
//delete tmpFile;
}
outPutFile->cd();
saveContainer();
}
void setMassFrom2DRange(RooWorkspace& myws, RooPlot* frame, string dsName, bool setLogScale)
{
// Find maximum and minimum points of Plot to rescale Y axis
TH1* h = myws.data(dsName.c_str())->createHistogram("hist", *myws.var("invMass"), Binning(frame->GetNbinsX(),frame->GetXaxis()->GetXmin(),frame->GetXaxis()->GetXmax()));
Double_t YMax = h->GetBinContent(h->GetMaximumBin());
// Double_t YMin = min( h->GetBinContent(h->FindFirstBinAbove(0.0)), h->GetBinContent(h->FindLastBinAbove(0.0)) );
Double_t YMin = 1e99;
for (int i=1; i<=h->GetNbinsX(); i++) if (h->GetBinContent(i)>0) YMin = min(YMin, h->GetBinContent(i));
Double_t Yup(0.),Ydown(0.);
if(setLogScale)
{
Ydown = YMin/(TMath::Power((YMax/YMin), (0.1/(1.0-0.1-0.4))));
Yup = YMax*TMath::Power((YMax/YMin), (0.4/(1.0-0.1-0.4)));
}
else
{
Ydown = max(YMin-(YMax-YMin)*(0.1/(1.0-0.1-0.4)),0.0);
Yup = YMax+(YMax-YMin)*(0.4/(1.0-0.1-0.4));
}
frame->GetYaxis()->SetRangeUser(Ydown,Yup);
delete h;
};
void setCtauFrom2DRange(RooWorkspace& myws, RooPlot* frame, string dsName, bool setLogScale, vector<double> rangeErr, double excEvts)
{
// Find maximum and minimum points of Plot to rescale Y axis
TH1* h = myws.data(dsName.c_str())->createHistogram("hist", *myws.var("ctau"), Binning(frame->GetNbinsX(),frame->GetXaxis()->GetXmin(),frame->GetXaxis()->GetXmax()));
Double_t YMax = h->GetBinContent(h->GetMaximumBin());
Double_t YMin = 1e99;
for (int i=1; i<=h->GetNbinsX(); i++) if (h->GetBinContent(i)>0) YMin = min(YMin, h->GetBinContent(i));
Double_t Yup(0.),Ydown(0.);
if(setLogScale)
{
Yup = YMax*TMath::Power((YMax/0.1), 0.5);
Ydown = 0.1;
}
else
{
Yup = YMax+(YMax-0.0)*0.5;
Ydown = 0.0;
}
frame->GetYaxis()->SetRangeUser(Ydown,Yup);
delete h;
if (excEvts>0.0) {
TLine *minline = new TLine(rangeErr[0], 0.0, rangeErr[0], (setLogScale?(Ydown*TMath::Power((Yup/Ydown),0.4)):(Ydown + (Yup-Ydown)*0.4)));
minline->SetLineStyle(2);
minline->SetLineColor(1);
minline->SetLineWidth(3);
frame->addObject(minline);
TLine *maxline = new TLine(rangeErr[1], 0.0, rangeErr[1], (setLogScale?(Ydown*TMath::Power((Yup/Ydown),0.4)):(Ydown + (Yup-Ydown)*0.4)));
maxline->SetLineStyle(2);
maxline->SetLineColor(1);
maxline->SetLineWidth(3);
frame->addObject(maxline);
}
};
int main(int argc, char* argv[]){
string fileName;
string fileNameZee;
string fileNameout;
string outDir;
int ncats;
int jcats;
int bins;
string outfilename;
string logfile;
bool verbose=false;
int mhLow;
int mhHigh;
po::options_description desc("Allowed options");
desc.add_options()
("help,h", "Show help")
("infilename,i", po::value<string>(&fileName)->default_value("CMS-HGG.root"), "In file name")
("infilenameZee,I", po::value<string>(&fileNameZee)->default_value("CMS-HGG_DY_fit.root"), "In file name Zee")
("Outfilename,o", po::value<string>(&fileNameout)->default_value("CMS-HGG_finalBkg.root"), "Out file name")
("outDir,D", po::value<string>(&outDir)->default_value("plots/FinalBackground"), "Out directory for plots")
("logfile,l", po::value<string>(&logfile)->default_value("BackgroundFit.log"), "log file of fit results")
("ncats,c", po::value<int>(&ncats)->default_value(4), "Number of categories")
("jcats,j", po::value<int>(&jcats)->default_value(0), "Start number of categories")
("mhLow,L", po::value<int>(&mhLow)->default_value(75), "Starting point for scan")
("mhHigh,H", po::value<int>(&mhHigh)->default_value(120), "End point for scan")
("bins,B", po::value<int>(&bins)->default_value(45), "Bins for the dataset")
("verbose,v", "Run with more output")
;
po::variables_map vm;
po::store(po::parse_command_line(argc,argv,desc),vm);
po::notify(vm);
if (vm.count("help")) { cout << desc << endl; exit(1); }
if (vm.count("verbose")) verbose=true;
if (!verbose) {
RooMsgService::instance().setGlobalKillBelow(RooFit::ERROR);
RooMsgService::instance().setSilentMode(true);
}
TFile *outputfile;
outputfile = new TFile(fileNameout.c_str(),"RECREATE");
RooWorkspace *outputws;
ofstream logfile_stream(logfile.c_str());
TFile *inFile = TFile::Open(fileName.c_str());
RooWorkspace *inWS = (RooWorkspace*)inFile->Get("cms_hgg_workspace");
outputws = (RooWorkspace*)inWS->Clone("cms_hgg_workspace");
std::string ext = "8TeV";
vector<pair<string,int> > funChoice; // <functionType,order>
funChoice.push_back(pair<string,int>("Bernstein",4)); //cat0
funChoice.push_back(pair<string,int>("Bernstein",5)); //cat1
funChoice.push_back(pair<string,int>("Bernstein",5)); //cat2
funChoice.push_back(pair<string,int>("Bernstein",5)); //cat3
PdfModelBuilder pdfsModel;
RooRealVar *mass = (RooRealVar*)inWS->var("CMS_hgg_mass");
pdfsModel.setObsVar(mass);
//mass->setBins(bins);
//mass->setRange(85,110);
for (int cat=jcats; cat<ncats; cat++){
RooDataSet *data = (RooDataSet*)inWS->data(Form("data_mass_cat%d",cat));
//RooDataHist thisdataBinned(Form("roohist_data_mass_cat%d",cat),"data",*mass,*dataFull); //FAN Procedure (from an official script)
//RooDataSet *data = (RooDataSet*)&thisdataBinned;
RooAbsPdf *pdfZee;
TFile *inFileZee = TFile::Open(fileNameZee.c_str());
RooWorkspace *inWS_Zee = (RooWorkspace*)inFileZee->Get("Zpeak");
cout<<endl<<"///////////////////////////////////"<<endl;
inWS_Zee->Print();
cout<<"///////////////////////////////////"<<endl<<endl;
pdfZee = inWS_Zee->pdf(Form("hgg_bkg_%s_cat%d_DCB",ext.c_str(),cat));
cout<<endl<<"///////////////////////////////////"<<endl;
pdfZee->Print();
cout<<"///////////////////////////////////"<<endl<<endl;
//RooAbsPdf *pdfZeeFixed=pdfsModel.floatDoubleCB(pdfZee,data,Form("hgg_bkg_%s_cat%d_DCB",ext.c_str(),cat));
RooAbsPdf *pdfZeeFixed=pdfsModel.fixDoubleCB(pdfZee,data,Form("hgg_bkg_%s_cat%d_DCB",ext.c_str(),cat));
RooAbsPdf *bkgPdf;
RooAbsPdf *berComponent;
RooAbsPdf *dcbComponent;
string funcType = funChoice[cat].first;
int orderOff = funChoice[cat].second;
bkgPdf = pdfsModel.getFixedDoubleCBplusContinuum(funcType,Form("hgg_bkg_%s_cat%d",ext.c_str(),cat),orderOff,pdfZeeFixed,false).first;
berComponent = pdfsModel.getFixedDoubleCBplusContinuum(funcType,Form("hgg_bkg_%s_cat%d",ext.c_str(),cat),orderOff,pdfZeeFixed,false).second.first;
dcbComponent = pdfsModel.getFixedDoubleCBplusContinuum(funcType,Form("hgg_bkg_%s_cat%d",ext.c_str(),cat),orderOff,pdfZeeFixed,false).second.second;
cout<<endl<<"///////////////////////////////////"<<endl;
bkgPdf->Print();
cout<<"///////////////////////////////////"<<endl<<endl;
cout<<endl<<"///////////////////////////////////"<<endl;
bkgPdf->getParameters(data)->Print();
cout<<"///////////////////////////////////"<<endl<<endl;
int fitStatus = 0;
double thisNll=0.;
runFit(bkgPdf,data,&thisNll,&fitStatus,3,mhLow,mhHigh);
//RooFitResult *fitRes = bkgPdf->fitTo(*data,Save(true),Range(mhLow,mhHigh));
//plot(mass,bkgPdf,data,Form("%s/hgg_bkg_%s_cat%d",outDir.c_str(),ext.c_str(),cat),bins,mhLow,mhHigh);
//print results in log file
RooArgSet *params = bkgPdf->getParameters(*data);
float Mean = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_mean",ext.c_str(),cat)))->getValV();
float MeanErrorL = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_mean",ext.c_str(),cat)))->getErrorLo();
float MeanErrorH = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_mean",ext.c_str(),cat)))->getErrorHi();
float Sigma = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_sigma",ext.c_str(),cat)))->getValV();
float SigmaErrorL = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_sigma",ext.c_str(),cat)))->getErrorLo();
float SigmaErrorH = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_sigma",ext.c_str(),cat)))->getErrorHi();
float nCB1 = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_nCB1",ext.c_str(),cat)))->getValV();
float nCB1ErrorL = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_nCB1",ext.c_str(),cat)))->getErrorLo();
float nCB1ErrorH = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_nCB1",ext.c_str(),cat)))->getErrorHi();
float nCB2 = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_nCB2",ext.c_str(),cat)))->getValV();
float nCB2ErrorL = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_nCB2",ext.c_str(),cat)))->getErrorLo();
float nCB2ErrorH = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_nCB2",ext.c_str(),cat)))->getErrorHi();
float alphaCB1 = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_alphaCB1",ext.c_str(),cat)))->getValV();
float alphaCB2 = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_alphaCB2",ext.c_str(),cat)))->getValV();
logfile_stream << Form("**************** cat: %d ***************",cat) <<endl<<" nEntries "<<data->sumEntries() << endl << " Mean: " << Mean << " MeanErrorL: " << MeanErrorL << " MeanErrorH: "<< MeanErrorH << " Sigma: " << Sigma << " SigmaErrorL: " << SigmaErrorL << " SigmaErrorH: " << SigmaErrorH << " nCB1: " << nCB1 << " nCB1ErrorL: " << nCB1ErrorL << " nCB1ErrorH: " << nCB1ErrorH << " nCB2: " << nCB2 << " nCB2ErrorL: " << nCB2ErrorL << " nCB2ErrorH: " << nCB2ErrorH << " alphaCB1: " << alphaCB1 << " alphaCB2: " << alphaCB2 << endl;
float frac = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_frac_sum1",ext.c_str(),cat)))->getValV();
float fracErrorL = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_frac_sum1",ext.c_str(),cat)))->getErrorLo();
float fracErrorH = ((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_frac_sum1",ext.c_str(),cat)))->getErrorHi();
logfile_stream <<" Frac "<<frac<<" FracErrorL "<<fracErrorL<<" FracErrorH "<<fracErrorH<<endl;
for(int i=0;i<orderOff;i++){
RooRealVar *coeff=(RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_%s_p%i",ext.c_str(),cat,abbr(funcType).c_str(),i));
logfile_stream <<Form(" %s_%i: ",funcType.c_str(),i)<<coeff->getValV()<<Form(" %s_%i ErrorL: ",funcType.c_str(),i)<<coeff->getErrorLo()<<Form(" %s_%i ErrorH: ",funcType.c_str(),i)<<coeff->getErrorHi();
}
logfile_stream<<endl;
plot2(mass,bkgPdf,berComponent,dcbComponent,frac,data,Form("%s/hgg_bkg_%s_cat%d",outDir.c_str(),ext.c_str(),cat),bins,mhLow,mhHigh);
//Let the DCB parameter float within their uncertaincy range in combine ?
((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_mean",ext.c_str(),cat)))->setConstant(false);
((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_sigma",ext.c_str(),cat)))->setConstant(false);
((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_nCB1",ext.c_str(),cat)))->setConstant(false);
((RooRealVar*)params->find(Form("hgg_bkg_%s_cat%d_DCB_nCB2",ext.c_str(),cat)))->setConstant(false);
outputws->var(Form("pdf_data_pol_model_8TeV_cat%d_norm",cat))->SetName(Form("hgg_bkg_8TeV_cat%d_DCBplusBernstein_norm",cat));
outputws->import(*bkgPdf);
}
outputfile->cd();
outputws->Write();
cout<<endl<<"///////////////////////////////////"<<endl;
//outputws->Print();
cout<<"///////////////////////////////////"<<endl<<endl;
outputfile->Close();
}
int GetBayesianInterval( std::string filename = "workspace.root",
std::string wsname = "myWS" ){
//
// this function loads a workspace and computes
// a Bayesian upper limit
//
// open file with workspace for reading
TFile * pInFile = new TFile(filename.c_str(), "read");
// load workspace
RooWorkspace * pWs = (RooWorkspace *)pInFile->Get(wsname.c_str());
if (!pWs){
std::cout << "workspace " << wsname
<< " not found" << std::endl;
return -1;
}
// printout workspace content
pWs->Print();
// load and print data from workspace
RooAbsData * data = pWs->data("data");
data->Print();
// load and print S+B Model Config
RooStats::ModelConfig * pSbHypo = (RooStats::ModelConfig *)pWs->obj("SbHypo");
pSbHypo->Print();
// create RooStats Bayesian MCMC calculator and set parameters
// Metropolis-Hastings algorithm needs a proposal function
RooStats::SequentialProposal sp(10.0);
RooStats::MCMCCalculator mcmc( *data, *pSbHypo );
mcmc.SetConfidenceLevel(0.95);
mcmc.SetNumIters(100000); // Metropolis-Hastings algorithm iterations
mcmc.SetProposalFunction(sp);
mcmc.SetNumBurnInSteps(500); // first N steps to be ignored as burn-in
mcmc.SetLeftSideTailFraction(0.0);
mcmc.SetNumBins(40); // for plotting only - does not affect limit calculation
// estimate credible interval
// NOTE: unfortunate notation: the UpperLimit() name refers
// to the upper boundary of an interval,
// NOT to the upper limit on the parameter of interest
// (it just happens to be the same for the one-sided
// interval starting at 0)
RooStats::MCMCInterval * pMcmcInt = mcmc.GetInterval();
double upper_bound = pMcmcInt->UpperLimit( *pWs->var("xsec") );
double lower_bound = pMcmcInt->LowerLimit( *pWs->var("xsec") );
std::cout << "one-sided 95%.C.L. bayesian credible interval for xsec: "
<< "[" << lower_bound << ", " << upper_bound << "]"
<< std::endl;
// make posterior PDF plot for POI
TCanvas c1("posterior");
RooStats::MCMCIntervalPlot plot(*pMcmcInt);
plot.Draw();
c1.SaveAs("bayesian_mcmc_posterior.pdf");
// make scatter plots to visualise the Markov chain
TCanvas c2("xsec_vs_alpha_lumi");
plot.DrawChainScatter( *pWs->var("xsec"), *pWs->var("alpha_lumi"));
c2.SaveAs("scatter_mcmc_xsec_vs_alpha_lumi.pdf");
TCanvas c3("xsec_vs_alpha_efficiency");
plot.DrawChainScatter( *pWs->var("xsec"), *pWs->var("alpha_efficiency"));
c3.SaveAs("scatter_mcmc_xsec_vs_alpha_efficiency.pdf");
TCanvas c4("xsec_vs_alpha_nbkg");
plot.DrawChainScatter( *pWs->var("xsec"), *pWs->var("alpha_nbkg"));
c4.SaveAs("scatter_mcmc_xsec_vs_alpha_nbkg.pdf");
// clean up a little
delete pMcmcInt;
return 0;
}
//void RunToyScan5(TString fileName, double startVal, double stopVal, TString outFile) {
void frequentist(TString fileName) {
cout << "Starting frequentist " << time(NULL) << endl;
double startVal = 0;
double stopVal = 200;
TString outFile = "";
int nToys = 1 ;
int nscanpoints = 2 ;
/*
gROOT->LoadMacro("RooBetaPdf.cxx+") ;
gROOT->LoadMacro("RooRatio.cxx+") ;
gROOT->LoadMacro("RooPosDefCorrGauss.cxx+") ;
*/
// get relevant objects out of the "ws" file
TFile *file = TFile::Open(fileName);
if(!file){
cout <<"file not found" << endl;
return;
}
RooWorkspace* w = (RooWorkspace*) file->Get("workspace");
if(!w){
cout <<"workspace not found" << endl;
return;
}
ModelConfig* mc = (ModelConfig*) w->obj("S+B_model");
RooAbsData* data = w->data("data");
if( !data || !mc ){
w->Print();
cout << "data or ModelConfig was not found" <<endl;
return;
}
RooRealVar* myPOI = (RooRealVar*) mc->GetParametersOfInterest()->first();
myPOI->setRange(0, 1000.);
ModelConfig* bModel = (ModelConfig*) w->obj("B_model");
ModelConfig* sbModel = (ModelConfig*) w->obj("S+B_model");
ProfileLikelihoodTestStat profll(*sbModel->GetPdf());
profll.SetPrintLevel(2);
profll.SetOneSided(1);
TestStatistic * testStat = &profll;
HypoTestCalculatorGeneric * hc = 0;
hc = new FrequentistCalculator(*data, *bModel, *sbModel);
ToyMCSampler *toymcs = (ToyMCSampler*)hc->GetTestStatSampler();
toymcs->SetMaxToys(10000);
toymcs->SetNEventsPerToy(1);
toymcs->SetTestStatistic(testStat);
((FrequentistCalculator *)hc)->SetToys(nToys,nToys);
HypoTestInverter calc(*hc);
calc.SetConfidenceLevel(0.95);
calc.UseCLs(true);
//calc.SetVerbose(true);
calc.SetVerbose(2);
cout << "About to set fixed scan " << time(NULL) << endl;
calc.SetFixedScan(nscanpoints,startVal,stopVal);
cout << "About to do inverter " << time(NULL) << endl;
HypoTestInverterResult * res_toysCLs_calculator = calc.GetInterval();
cout << "CLs = " << res_toysCLs_calculator->UpperLimit()
<< " CLs_exp = " << res_toysCLs_calculator->GetExpectedUpperLimit(0)
<< " CLs_exp(-1s) = " << res_toysCLs_calculator->GetExpectedUpperLimit(-1)
<< " CLs_exp(+1s) = " << res_toysCLs_calculator->GetExpectedUpperLimit(1) << endl ;
/*
// dump results string to output file
ofstream outStream ;
outStream.open(outFile,ios::app) ;
outStream << "CLs = " << res_toysCLs_calculator->UpperLimit()
<< " CLs_exp = " << res_toysCLs_calculator->GetExpectedUpperLimit(0)
<< " CLs_exp(-1s) = " << res_toysCLs_calculator->GetExpectedUpperLimit(-1)
<< " CLs_exp(+1s) = " << res_toysCLs_calculator->GetExpectedUpperLimit(1) << endl ;
outStream.close() ;
*/
cout << "End of frequentist " << time(NULL) << endl;
return ;
}
void draw_data_mgg(TString folderName,bool blind=true,float min=103,float max=160)
{
TFile inputFile(folderName+"/data.root");
const int nCat = 5;
TString cats[5] = {"HighPt","Hbb","Zbb","HighRes","LowRes"};
TCanvas cv;
for(int iCat=0; iCat < nCat; iCat++) {
RooWorkspace *ws = (RooWorkspace*)inputFile.Get(cats[iCat]+"_mgg_workspace");
RooFitResult* res = (RooFitResult*)ws->obj("fitresult_pdf_data");
RooRealVar * mass = ws->var("mgg");
mass->setRange("all",min,max);
mass->setRange("blind",121,130);
mass->setRange("low",106,121);
mass->setRange("high",130,160);
mass->setUnit("GeV");
mass->SetTitle("m_{#gamma#gamma}");
RooAbsPdf * pdf = ws->pdf("pdf");
RooPlot *plot = mass->frame(min,max,max-min);
plot->SetTitle("");
RooAbsData* data = ws->data("data")->reduce(Form("mgg > %f && mgg < %f",min,max));
double nTot = data->sumEntries();
if(blind) data = data->reduce("mgg < 121 || mgg>130");
double nBlind = data->sumEntries();
double norm = nTot/nBlind; //normalization for the plot
data->plotOn(plot);
pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::Range("Full"),RooFit::LineWidth(0.1) );
plot->Print();
//add the fix error band
RooCurve* c = plot->getCurve("pdf_Norm[mgg]_Range[Full]_NormRange[Full]");
const int Nc = c->GetN();
//TGraphErrors errfix(Nc);
//TGraphErrors errfix2(Nc);
TGraphAsymmErrors errfix(Nc);
TGraphAsymmErrors errfix2(Nc);
Double_t *x = c->GetX();
Double_t *y = c->GetY();
double NtotalFit = ws->var("Nbkg1")->getVal()*ws->var("Nbkg1")->getVal() + ws->var("Nbkg2")->getVal()*ws->var("Nbkg2")->getVal();
for( int i = 0; i < Nc; i++ )
{
errfix.SetPoint(i,x[i],y[i]);
errfix2.SetPoint(i,x[i],y[i]);
mass->setVal(x[i]);
double shapeErr = pdf->getPropagatedError(*res)*NtotalFit;
//double totalErr = TMath::Sqrt( shapeErr*shapeErr + y[i] );
//total normalization error
double totalErr = TMath::Sqrt( shapeErr*shapeErr + y[i]*y[i]/NtotalFit );
if ( y[i] - totalErr > .0 )
{
errfix.SetPointError(i, 0, 0, totalErr, totalErr );
}
else
{
errfix.SetPointError(i, 0, 0, y[i] - 0.01, totalErr );
}
//2sigma
if ( y[i] - 2.*totalErr > .0 )
{
errfix2.SetPointError(i, 0, 0, 2.*totalErr, 2.*totalErr );
}
else
{
errfix2.SetPointError(i, 0, 0, y[i] - 0.01, 2.*totalErr );
}
/*
std::cout << x[i] << " " << y[i] << " "
<< " ,pdf get Val: " << pdf->getVal()
<< " ,pdf get Prop Err: " << pdf->getPropagatedError(*res)*NtotalFit
<< " stat uncertainty: " << TMath::Sqrt(y[i]) << " Ntot: " << NtotalFit << std::endl;
*/
}
errfix.SetFillColor(kYellow);
errfix2.SetFillColor(kGreen);
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kGreen),RooFit::Range("Full"), RooFit::VisualizeError(*res,2.0,kFALSE));
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kYellow),RooFit::Range("Full"), RooFit::VisualizeError(*res,1.0,kFALSE));
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kGreen),RooFit::Range("Full"), RooFit::VisualizeError(*res,2.0,kTRUE));
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kYellow),RooFit::Range("Full"), RooFit::VisualizeError(*res,1.0,kTRUE));
plot->addObject(&errfix,"4");
plot->addObject(&errfix2,"4");
plot->addObject(&errfix,"4");
data->plotOn(plot);
TBox blindBox(121,plot->GetMinimum()-(plot->GetMaximum()-plot->GetMinimum())*0.015,130,plot->GetMaximum());
blindBox.SetFillColor(kGray);
if(blind) {
plot->addObject(&blindBox);
pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kGreen),RooFit::Range("Full"), RooFit::VisualizeError(*res,2.0,kTRUE));
pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kYellow),RooFit::Range("Full"), RooFit::VisualizeError(*res,1.0,kTRUE));
}
//plot->addObject(&errfix,"4");
//data->plotOn(plot);
//pdf->plotOn(plot,RooFit::Normalization( norm ) );
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::Range("Full"),RooFit::LineWidth(1.5) );
pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::Range("Full"), RooFit::LineWidth(1));
data->plotOn(plot);
/*
pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::Range("all"),RooFit::LineWidth(0.8) );
//pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::FillColor(kGreen),RooFit::Range("all"), RooFit::VisualizeError(*res,2.0,kFALSE));
//pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::FillColor(kYellow),RooFit::Range("all"), RooFit::VisualizeError(*res,1.0,kFALSE));
pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::FillColor(kGreen),RooFit::Range("all"), RooFit::VisualizeError(*res,2.0,kTRUE));
pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::FillColor(kYellow),RooFit::Range("all"), RooFit::VisualizeError(*res,1.0,kTRUE));
data->plotOn(plot);
pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::Range("all"),RooFit::LineWidth(0.8) );
*/
TLatex lbl0(0.1,0.96,"CMS Preliminary");
lbl0.SetNDC();
lbl0.SetTextSize(0.042);
plot->addObject(&lbl0);
TLatex lbl(0.4,0.96,Form("%s Box",cats[iCat].Data()));
lbl.SetNDC();
lbl.SetTextSize(0.042);
plot->addObject(&lbl);
TLatex lbl2(0.6,0.96,"#sqrt{s}=8 TeV L = 19.78 fb^{-1}");
lbl2.SetNDC();
lbl2.SetTextSize(0.042);
plot->addObject(&lbl2);
int iObj=-1;
TNamed *obj;
while( (obj = (TNamed*)plot->getObject(++iObj)) ) {
obj->SetName(Form("Object_%d",iObj));
}
plot->Draw();
TString tag = (blind ? "_BLIND" : "");
cv.SaveAs(folderName+"/figs/mgg_data_"+cats[iCat]+tag+TString(Form("_%0.0f_%0.0f",min,max))+".png");
cv.SaveAs(folderName+"/figs/mgg_data_"+cats[iCat]+tag+TString(Form("_%0.0f_%0.0f",min,max))+".pdf");
cv.SaveAs(folderName+"/figs/mgg_data_"+cats[iCat]+tag+TString(Form("_%0.0f_%0.0f",min,max))+".C");
}
}
void plot( TString var, TString data, TString pdf, double low=-1, double high=-1 ) {
TFile *tf = TFile::Open( "root/FitOut.root" );
RooWorkspace *w = (RooWorkspace*)tf->Get("w");
TCanvas *canv = new TCanvas("c","c",800,800);
TPad *upperPad = new TPad(Form("%s_upper",canv->GetName()),"",0.,0.33,1.,1.);
TPad *lowerPad = new TPad(Form("%s_lower",canv->GetName()),"",0.,0.,1.,0.33);
canv->cd();
upperPad->Draw();
lowerPad->Draw();
if ( low < 0 ) low = w->var(var)->getMin();
if ( high < 0 ) high = w->var(var)->getMax();
RooPlot *plot = w->var(var)->frame(Range(low,high));
w->data(data)->plotOn(plot);
w->pdf(pdf)->plotOn(plot);
RooHist *underHist = plot->pullHist();
underHist->GetXaxis()->SetRangeUser(plot->GetXaxis()->GetXmin(), plot->GetXaxis()->GetXmax());
underHist->GetXaxis()->SetTitle(plot->GetXaxis()->GetTitle());
underHist->GetYaxis()->SetTitle("Pull");
underHist->GetXaxis()->SetLabelSize(0.12);
underHist->GetYaxis()->SetLabelSize(0.12);
underHist->GetXaxis()->SetTitleSize(0.2);
underHist->GetXaxis()->SetTitleOffset(0.7);
underHist->GetYaxis()->SetTitleSize(0.18);
underHist->GetYaxis()->SetTitleOffset(0.38);
plot->GetXaxis()->SetTitle("");
upperPad->SetBottomMargin(0.1);
upperPad->cd();
plot->Draw();
canv->cd();
lowerPad->SetTopMargin(0.05);
lowerPad->SetBottomMargin(0.35);
lowerPad->cd();
underHist->Draw("AP");
double ymin = underHist->GetYaxis()->GetXmin();
double ymax = underHist->GetYaxis()->GetXmax();
double yrange = Max( Abs( ymin ), Abs( ymax ) );
underHist->GetYaxis()->SetRangeUser( -1.*yrange, 1.*yrange );
double xmin = plot->GetXaxis()->GetXmin();
double xmax = plot->GetXaxis()->GetXmax();
TColor *mycol3sig = gROOT->GetColor( kGray );
mycol3sig->SetAlpha(0.5);
TColor *mycol2sig = gROOT->GetColor( kGray+1 );
mycol2sig->SetAlpha(0.5);
TColor *mycol1sig = gROOT->GetColor( kGray+2 );
mycol1sig->SetAlpha(0.5);
TBox box3sig;
box3sig.SetFillColor( mycol3sig->GetNumber() );
//box3sig.SetFillColorAlpha( kGray, 0.5 );
box3sig.SetFillStyle(1001);
box3sig.DrawBox( xmin, -3., xmax, 3.);
TBox box2sig;
box2sig.SetFillColor( mycol2sig->GetNumber() );
//box2sig.SetFillColorAlpha( kGray+1, 0.5 );
box2sig.SetFillStyle(1001);
box2sig.DrawBox( xmin, -2., xmax, 2.);
TBox box1sig;
box1sig.SetFillColor( mycol1sig->GetNumber() );
//box1sig.SetFillColorAlpha( kGray+2, 0.5 );
box1sig.SetFillStyle(1001);
box1sig.DrawBox( xmin, -1., xmax, 1.);
TLine lineErr;
lineErr.SetLineWidth(1);
lineErr.SetLineColor(kBlue-9);
lineErr.SetLineStyle(2);
lineErr.DrawLine(plot->GetXaxis()->GetXmin(),1.,plot->GetXaxis()->GetXmax(),1.);
lineErr.DrawLine(plot->GetXaxis()->GetXmin(),-1.,plot->GetXaxis()->GetXmax(),-1.);
lineErr.DrawLine(plot->GetXaxis()->GetXmin(),2.,plot->GetXaxis()->GetXmax(),2.);
lineErr.DrawLine(plot->GetXaxis()->GetXmin(),-2.,plot->GetXaxis()->GetXmax(),-2.);
lineErr.DrawLine(plot->GetXaxis()->GetXmin(),3.,plot->GetXaxis()->GetXmax(),3.);
lineErr.DrawLine(plot->GetXaxis()->GetXmin(),-3.,plot->GetXaxis()->GetXmax(),-3.);
TLine line;
line.SetLineWidth(3);
line.SetLineColor(kBlue);
line.DrawLine(plot->GetXaxis()->GetXmin(),0.,plot->GetXaxis()->GetXmax(),0.);
underHist->Draw("Psame");
RooHist *redPull = new RooHist();
int newp=0;
for (int p=0; p<underHist->GetN(); p++) {
double x,y;
underHist->GetPoint(p,x,y);
if ( TMath::Abs(y)>3 ) {
redPull->SetPoint(newp,x,y);
redPull->SetPointError(newp,0.,0.,underHist->GetErrorYlow(p),underHist->GetErrorYhigh(p));
newp++;
}
}
redPull->SetLineWidth(underHist->GetLineWidth());
redPull->SetMarkerStyle(underHist->GetMarkerStyle());
redPull->SetMarkerSize(underHist->GetMarkerSize());
redPull->SetLineColor(kRed);
redPull->SetMarkerColor(kRed);
redPull->Draw("Psame");
canv->Print(Form("tmp/%s.pdf",var.Data()));
tf->Close();
}
void StandardBayesianNumericalDemo(const char* infile = "",
const char* workspaceName = "combined",
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData") {
// option definitions
double confLevel = optBayes.confLevel;
TString integrationType = optBayes.integrationType;
int nToys = optBayes.nToys;
bool scanPosterior = optBayes.scanPosterior;
int nScanPoints = optBayes.nScanPoints;
int intervalType = optBayes.intervalType;
int maxPOI = optBayes.maxPOI;
double nSigmaNuisance = optBayes.nSigmaNuisance;
/////////////////////////////////////////////////////////////
// First part is just to access a user-defined file
// or create the standard example file if it doesn't exist
////////////////////////////////////////////////////////////
const char* filename = "";
if (!strcmp(infile,"")) {
filename = "results/example_combined_GaussExample_model.root";
bool fileExist = !gSystem->AccessPathName(filename); // note opposite return code
// if file does not exists generate with histfactory
if (!fileExist) {
#ifdef _WIN32
cout << "HistFactory file cannot be generated on Windows - exit" << endl;
return;
#endif
// Normally this would be run on the command line
cout <<"will run standard hist2workspace example"<<endl;
gROOT->ProcessLine(".! prepareHistFactory .");
gROOT->ProcessLine(".! hist2workspace config/example.xml");
cout <<"\n\n---------------------"<<endl;
cout <<"Done creating example input"<<endl;
cout <<"---------------------\n\n"<<endl;
}
}
else
filename = infile;
// Try to open the file
TFile *file = TFile::Open(filename);
// if input file was specified byt not found, quit
if(!file ){
cout <<"StandardRooStatsDemoMacro: Input file " << filename << " is not found" << endl;
return;
}
/////////////////////////////////////////////////////////////
// Tutorial starts here
////////////////////////////////////////////////////////////
// get the workspace out of the file
RooWorkspace* w = (RooWorkspace*) file->Get(workspaceName);
if(!w){
cout <<"workspace not found" << endl;
return;
}
// get the modelConfig out of the file
ModelConfig* mc = (ModelConfig*) w->obj(modelConfigName);
// get the modelConfig out of the file
RooAbsData* data = w->data(dataName);
// make sure ingredients are found
if(!data || !mc){
w->Print();
cout << "data or ModelConfig was not found" <<endl;
return;
}
/////////////////////////////////////////////
// create and use the BayesianCalculator
// to find and plot the 95% credible interval
// on the parameter of interest as specified
// in the model config
// before we do that, we must specify our prior
// it belongs in the model config, but it may not have
// been specified
RooUniform prior("prior","",*mc->GetParametersOfInterest());
w->import(prior);
mc->SetPriorPdf(*w->pdf("prior"));
// do without systematics
//mc->SetNuisanceParameters(RooArgSet() );
if (nSigmaNuisance > 0) {
RooAbsPdf * pdf = mc->GetPdf();
assert(pdf);
RooFitResult * res = pdf->fitTo(*data, Save(true), Minimizer(ROOT::Math::MinimizerOptions::DefaultMinimizerType().c_str()), Hesse(true),
PrintLevel(ROOT::Math::MinimizerOptions::DefaultPrintLevel()-1) );
res->Print();
RooArgList nuisPar(*mc->GetNuisanceParameters());
for (int i = 0; i < nuisPar.getSize(); ++i) {
RooRealVar * v = dynamic_cast<RooRealVar*> (&nuisPar[i] );
assert( v);
v->setMin( TMath::Max( v->getMin(), v->getVal() - nSigmaNuisance * v->getError() ) );
v->setMax( TMath::Min( v->getMax(), v->getVal() + nSigmaNuisance * v->getError() ) );
std::cout << "setting interval for nuisance " << v->GetName() << " : [ " << v->getMin() << " , " << v->getMax() << " ]" << std::endl;
}
}
BayesianCalculator bayesianCalc(*data,*mc);
bayesianCalc.SetConfidenceLevel(confLevel); // 95% interval
// default of the calculator is central interval. here use shortest , central or upper limit depending on input
// doing a shortest interval might require a longer time since it requires a scan of the posterior function
if (intervalType == 0) bayesianCalc.SetShortestInterval(); // for shortest interval
if (intervalType == 1) bayesianCalc.SetLeftSideTailFraction(0.5); // for central interval
if (intervalType == 2) bayesianCalc.SetLeftSideTailFraction(0.); // for upper limit
if (!integrationType.IsNull() ) {
bayesianCalc.SetIntegrationType(integrationType); // set integrationType
bayesianCalc.SetNumIters(nToys); // set number of ietrations (i.e. number of toys for MC integrations)
}
// in case of toyMC make a nnuisance pdf
if (integrationType.Contains("TOYMC") ) {
RooAbsPdf * nuisPdf = RooStats::MakeNuisancePdf(*mc, "nuisance_pdf");
cout << "using TOYMC integration: make nuisance pdf from the model " << std::endl;
nuisPdf->Print();
bayesianCalc.ForceNuisancePdf(*nuisPdf);
scanPosterior = true; // for ToyMC the posterior is scanned anyway so used given points
}
// compute interval by scanning the posterior function
if (scanPosterior)
bayesianCalc.SetScanOfPosterior(nScanPoints);
RooRealVar* poi = (RooRealVar*) mc->GetParametersOfInterest()->first();
if (maxPOI != -999 && maxPOI > poi->getMin())
poi->setMax(maxPOI);
SimpleInterval* interval = bayesianCalc.GetInterval();
// print out the iterval on the first Parameter of Interest
cout << "\n>>>> RESULT : " << confLevel*100 << "% interval on " << poi->GetName()<<" is : ["<<
interval->LowerLimit() << ", "<<
interval->UpperLimit() <<"] "<<endl;
// make a plot
// since plotting may take a long time (it requires evaluating
// the posterior in many points) this command will speed up
// by reducing the number of points to plot - do 50
// ignore errors of PDF if is zero
RooAbsReal::setEvalErrorLoggingMode(RooAbsReal::Ignore) ;
cout << "\nDrawing plot of posterior function....." << endl;
// always plot using numer of scan points
bayesianCalc.SetScanOfPosterior(nScanPoints);
RooPlot * plot = bayesianCalc.GetPosteriorPlot();
plot->Draw();
}
void StandardProfileLikelihoodDemo(const char* infile = "",
const char* workspaceName = "combined",
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData"){
double confLevel = optPL.confLevel;
double nScanPoints = optPL.nScanPoints;
bool plotAsTF1 = optPL.plotAsTF1;
double poiXMin = optPL.poiMinPlot;
double poiXMax = optPL.poiMaxPlot;
bool doHypoTest = optPL.doHypoTest;
double nullParamValue = optPL.nullValue;
// -------------------------------------------------------
// First part is just to access a user-defined file
// or create the standard example file if it doesn't exist
const char* filename = "";
if (!strcmp(infile,"")) {
filename = "results/example_combined_GaussExample_model.root";
bool fileExist = !gSystem->AccessPathName(filename); // note opposite return code
// if file does not exists generate with histfactory
if (!fileExist) {
#ifdef _WIN32
cout << "HistFactory file cannot be generated on Windows - exit" << endl;
return;
#endif
// Normally this would be run on the command line
cout <<"will run standard hist2workspace example"<<endl;
gROOT->ProcessLine(".! prepareHistFactory .");
gROOT->ProcessLine(".! hist2workspace config/example.xml");
cout <<"\n\n---------------------"<<endl;
cout <<"Done creating example input"<<endl;
cout <<"---------------------\n\n"<<endl;
}
}
else
filename = infile;
// Try to open the file
TFile *file = TFile::Open(filename);
// if input file was specified byt not found, quit
if(!file ){
cout <<"StandardRooStatsDemoMacro: Input file " << filename << " is not found" << endl;
return;
}
// -------------------------------------------------------
// Tutorial starts here
// -------------------------------------------------------
// get the workspace out of the file
RooWorkspace* w = (RooWorkspace*) file->Get(workspaceName);
if(!w){
cout <<"workspace not found" << endl;
return;
}
// get the modelConfig out of the file
ModelConfig* mc = (ModelConfig*) w->obj(modelConfigName);
// get the modelConfig out of the file
RooAbsData* data = w->data(dataName);
// make sure ingredients are found
if(!data || !mc){
w->Print();
cout << "data or ModelConfig was not found" <<endl;
return;
}
// ---------------------------------------------
// create and use the ProfileLikelihoodCalculator
// to find and plot the 95% confidence interval
// on the parameter of interest as specified
// in the model config
ProfileLikelihoodCalculator pl(*data,*mc);
pl.SetConfidenceLevel(confLevel); // 95% interval
LikelihoodInterval* interval = pl.GetInterval();
// print out the interval on the first Parameter of Interest
RooRealVar* firstPOI = (RooRealVar*) mc->GetParametersOfInterest()->first();
cout << "\n>>>> RESULT : " << confLevel*100 << "% interval on " <<firstPOI->GetName()<<" is : ["<<
interval->LowerLimit(*firstPOI) << ", "<<
interval->UpperLimit(*firstPOI) <<"]\n "<<endl;
// make a plot
cout << "making a plot of the profile likelihood function ....(if it is taking a lot of time use less points or the TF1 drawing option)\n";
LikelihoodIntervalPlot plot(interval);
plot.SetNPoints(nScanPoints); // do not use too many points, it could become very slow for some models
if (poiXMin < poiXMax) plot.SetRange(poiXMin, poiXMax);
TString opt;
if (plotAsTF1) opt += TString("tf1");
plot.Draw(opt); // use option TF1 if too slow (plot.Draw("tf1")
// if requested perform also an hypothesis test for the significance
if (doHypoTest) {
RooArgSet nullparams("nullparams");
nullparams.addClone(*firstPOI);
nullparams.setRealValue(firstPOI->GetName(), nullParamValue);
pl.SetNullParameters(nullparams);
std::cout << "Perform Test of Hypothesis : null Hypothesis is " << firstPOI->GetName() << nullParamValue << std::endl;
auto result = pl.GetHypoTest();
std::cout << "\n>>>> Hypotheis Test Result \n";
result->Print();
}
}
void FitterUtilsSimultaneousExpOfPolyTimesX::fit(bool wantplot, bool constPartReco,
double fracPartReco_const,
ofstream& out, TTree* t, bool update, string plotsfile)
{
//***************Get the PDFs from the workspace
TFile fw(workspacename.c_str());
RooWorkspace* workspace = (RooWorkspace*)fw.Get("workspace");
RooRealVar *B_plus_M = workspace->var("B_plus_M");
RooRealVar *misPT = workspace->var("misPT");
RooRealVar *l1Kee = workspace->var("l1Kee");
RooRealVar *l2Kee = workspace->var("l2Kee");
RooRealVar *l3Kee = workspace->var("l3Kee");
RooRealVar *l4Kee = workspace->var("l4Kee");
RooRealVar *l5Kee = workspace->var("l5Kee");
RooRealVar *l1KeeGen = workspace->var("l1KeeGen");
RooRealVar *l2KeeGen = workspace->var("l2KeeGen");
RooRealVar *l3KeeGen = workspace->var("l3KeeGen");
RooRealVar *l4KeeGen = workspace->var("l4KeeGen");
RooRealVar *l5KeeGen = workspace->var("l5KeeGen");
RooRealVar *fractionalErrorJpsiLeak = workspace->var("fractionalErrorJpsiLeak");
RooRealVar l1Kemu(*l1Kee);
l1Kemu.SetName("l1Kemu"); l1Kemu.SetTitle("l1Kemu");
RooRealVar l2Kemu(*l2Kee);
l2Kemu.SetName("l2Kemu"); l2Kemu.SetTitle("l2Kemu");
RooRealVar l3Kemu(*l3Kee);
l3Kemu.SetName("l3Kemu"); l3Kemu.SetTitle("l3Kemu");
RooRealVar l4Kemu(*l4Kee);
l4Kemu.SetName("l4Kemu"); l4Kemu.SetTitle("l4Kemu");
RooRealVar l5Kemu(*l5Kee);
l5Kemu.SetName("l5Kemu"); l5Kemu.SetTitle("l5Kemu");
RooHistPdf *histPdfSignalZeroGamma = (RooHistPdf *) workspace->pdf("histPdfSignalZeroGamma");
RooHistPdf *histPdfSignalOneGamma = (RooHistPdf *) workspace->pdf("histPdfSignalOneGamma");
RooHistPdf *histPdfSignalTwoGamma = (RooHistPdf *) workspace->pdf("histPdfSignalTwoGamma");
RooHistPdf *histPdfPartReco = (RooHistPdf *) workspace->pdf("histPdfPartReco");
RooHistPdf *histPdfJpsiLeak(0);
if(nGenJpsiLeak>0) histPdfJpsiLeak = (RooHistPdf *) workspace->pdf("histPdfJpsiLeak");
//Here set in the Kemu PDF the parameters that have to be shared
RooExpOfPolyTimesX* combPDF = new RooExpOfPolyTimesX("combPDF", "combPDF", *B_plus_M, *misPT, *l1Kee, *l2Kee, *l3Kee, *l4Kee, *l5Kee);
RooExpOfPolyTimesX* KemuPDF = new RooExpOfPolyTimesX("kemuPDF", "kemuPDF", *B_plus_M, *misPT, l1Kemu, *l2Kee, *l3Kee, *l4Kee, *l5Kee);
RooWorkspace* workspaceGen = (RooWorkspace*)fw.Get("workspaceGen");
RooDataSet* dataGenSignalZeroGamma = (RooDataSet*)workspaceGen->data("dataGenSignalZeroGamma");
RooDataSet* dataGenSignalOneGamma = (RooDataSet*)workspaceGen->data("dataGenSignalOneGamma");
RooDataSet* dataGenSignalTwoGamma = (RooDataSet*)workspaceGen->data("dataGenSignalTwoGamma");
RooDataSet* dataGenPartReco = (RooDataSet*)workspaceGen->data("dataGenPartReco");
RooDataSet* dataGenComb = (RooDataSet*)workspaceGen->data("dataGenComb");
RooDataSet* dataGenKemu = (RooDataSet*)workspaceGen->data("dataGenKemu");
RooDataSet* dataGenJpsiLeak(0);
if(nGenJpsiLeak>0) dataGenJpsiLeak = (RooDataSet*)workspaceGen->data("dataGenJpsiLeak");
if(wantplot)
{
//**************Must get the datasets
RooDataSet* dataSetSignalZeroGamma = (RooDataSet*)workspace->data("dataSetSignalZeroGamma");
RooDataSet* dataSetSignalOneGamma = (RooDataSet*)workspace->data("dataSetSignalOneGamma");
RooDataSet* dataSetSignalTwoGamma = (RooDataSet*)workspace->data("dataSetSignalTwoGamma");
RooDataSet* dataSetPartReco = (RooDataSet*)workspace->data("dataSetPartReco");
RooDataSet* dataSetComb = (RooDataSet*)workspace->data("dataSetComb");
RooDataSet* dataSetJpsiLeak = (RooDataSet*)workspace->data("dataSetJpsiLeak");
//**************Plot all the different components
cout<<"dataGenSignalZeroGamma: "<<dataGenSignalZeroGamma<<endl;
PlotShape(*dataSetSignalZeroGamma, *dataGenSignalZeroGamma, *histPdfSignalZeroGamma, plotsfile, "cSignalZeroGamma", *B_plus_M, *misPT);
PlotShape(*dataSetSignalOneGamma, *dataGenSignalOneGamma, *histPdfSignalOneGamma, plotsfile, "cSignalOneGamma", *B_plus_M, *misPT);
PlotShape(*dataSetSignalTwoGamma, *dataGenSignalTwoGamma, *histPdfSignalTwoGamma, plotsfile, "cSignalTwoGamma", *B_plus_M, *misPT);
PlotShape(*dataSetPartReco, *dataGenPartReco, *histPdfPartReco, plotsfile, "cPartReco", *B_plus_M, *misPT);
PlotShape(*dataSetComb, *dataGenComb, *combPDF, plotsfile, "cComb", *B_plus_M, *misPT);
if(nGenJpsiLeak>1) PlotShape(*dataSetJpsiLeak, *dataGenJpsiLeak, *histPdfJpsiLeak, plotsfile, "cJpsiLeak", *B_plus_M, *misPT);
}
//***************Merge datasets
RooDataSet* dataGenTot(dataGenPartReco);
dataGenTot->append(*dataGenSignalZeroGamma);
dataGenTot->append(*dataGenSignalOneGamma);
dataGenTot->append(*dataGenSignalTwoGamma);
dataGenTot->append(*dataGenComb);
if(nGenJpsiLeak>0) dataGenTot->append(*dataGenJpsiLeak);
//**************Create index category and join samples
RooCategory category("category", "category");
category.defineType("Kee");
category.defineType("Kemu");
RooDataSet dataGenSimultaneous("dataGenSimultaneous", "dataGenSimultaneous", RooArgSet(*B_plus_M, *misPT), Index(category), Import("Kee", *dataGenTot), Import("Kemu", *dataGenKemu));
//**************Prepare fitting function
RooRealVar nSignal("nSignal", "#signal events", 1.*nGenSignal, nGenSignal-7*sqrt(nGenSignal), nGenSignal+7*sqrt(nGenSignal));
RooRealVar nPartReco("nPartReco", "#nPartReco", 1.*nGenPartReco, nGenPartReco-7*sqrt(nGenPartReco), nGenPartReco+7*sqrt(nGenPartReco));
RooRealVar nComb("nComb", "#nComb", 1.*nGenComb, nGenComb-7*sqrt(nGenComb), nGenComb+7*sqrt(nGenComb));
RooRealVar nKemu("nKemu", "#nKemu", 1.*nGenKemu, nGenKemu-7*sqrt(nGenKemu), nGenKemu+7*sqrt(nGenKemu));
RooRealVar nJpsiLeak("nJpsiLeak", "#nJpsiLeak", 1.*nGenJpsiLeak, nGenJpsiLeak-7*sqrt(nGenJpsiLeak), nGenJpsiLeak+7*sqrt(nGenJpsiLeak));
RooRealVar fracZero("fracZero", "fracZero",0.5,0,1);
RooRealVar fracOne("fracOne", "fracOne",0.5, 0,1);
RooFormulaVar fracPartReco("fracPartReco", "nPartReco/nSignal", RooArgList(nPartReco,nSignal));
RooFormulaVar fracOneRec("fracOneRec", "(1-fracZero)*fracOne", RooArgList(fracZero, fracOne));
RooAddPdf histPdfSignal("histPdfSignal", "histPdfSignal", RooArgList(*histPdfSignalZeroGamma, *histPdfSignalOneGamma, *histPdfSignalTwoGamma), RooArgList(fracZero, fracOneRec));
RooArgList pdfList(histPdfSignal, *histPdfPartReco, *combPDF);
RooArgList yieldList(nSignal, nPartReco, nComb);
if(nGenJpsiLeak>0)
{
pdfList.add(*histPdfJpsiLeak);
yieldList.add(nJpsiLeak);
}
RooAddPdf totPdf("totPdf", "totPdf", pdfList, yieldList);
RooExtendPdf totKemuPdf("totKemuPdf", "totKemuPdf", *KemuPDF, nKemu);
//**************** Prepare simultaneous PDF
RooSimultaneous simPdf("simPdf", "simPdf", category);
simPdf.addPdf(totPdf, "Kee");
simPdf.addPdf(totKemuPdf, "Kemu");
//**************** Constrain the fraction of zero and one photon
int nGenSignalZeroGamma(floor(nGenFracZeroGamma*nGenSignal));
int nGenSignalOneGamma(floor(nGenFracOneGamma*nGenSignal));
int nGenSignalTwoGamma(floor(nGenSignal-nGenSignalZeroGamma-nGenSignalOneGamma));
RooRealVar fracZeroConstMean("fracZeroConstMean", "fracZeroConstMean", nGenSignalZeroGamma*1./nGenSignal);
RooRealVar fracZeroConstSigma("fracZeroConstSigma", "fracZeroConstSigma", sqrt(nGenSignalZeroGamma)/nGenSignal);
RooGaussian fracZeroConst("fracZeroConst", "fracZeroConst", fracZero, fracZeroConstMean, fracZeroConstSigma);
RooRealVar fracOneConstMean("fracOneConstMean", "fracOneConstMean", nGenSignalOneGamma*1./nGenSignal/(1-fracZeroConstMean.getVal()));
RooRealVar fracOneConstSigma("fracOneConstSigma", "fracOneConstSigma", sqrt(nGenSignalOneGamma)/nGenSignal/(1-fracZeroConstMean.getVal()));
RooGaussian fracOneConst("fracOneConst", "fracOneConst", fracOne, fracOneConstMean, fracOneConstSigma);
RooRealVar fracPartRecoMean("fracPartRecoMean", "fracPartRecoMean", nGenPartReco/(1.*nGenSignal));
RooRealVar fracPartRecoSigma("fracPartRecoSigma", "fracPartRecoSigma", fracPartReco_const*fracPartRecoMean.getVal());
RooGaussian fracPartRecoConst("fracPartRecoConst", "fracPartRecoConst", fracPartReco, fracPartRecoMean, fracPartRecoSigma);
RooRealVar JpsiLeakMean("JpsiLeakMean", "JpsiLeakMean", nGenJpsiLeak);
RooRealVar JpsiLeakSigma("JpsiLeakSigma", "JpsiLeakSigma", nGenJpsiLeak*fractionalErrorJpsiLeak->getVal());
RooGaussian JpsiLeakConst("JpsiLeakConst", "JpsiLeakConst", nJpsiLeak, JpsiLeakMean, JpsiLeakSigma);
//**************** fit
RooAbsReal::defaultIntegratorConfig()->setEpsAbs(1e-8) ;
RooAbsReal::defaultIntegratorConfig()->setEpsRel(1e-8) ;
initiateParams(nGenSignalZeroGamma, nGenSignalOneGamma, nGenSignalTwoGamma,
nKemu, nSignal, nPartReco, nComb, fracZero, fracOne,
nJpsiLeak, constPartReco, fracPartRecoSigma,
*l1Kee, *l2Kee, *l3Kee, *l4Kee, *l5Kee, l1Kemu, l2Kemu, l3Kemu, l4Kemu, l5Kemu,
*l1KeeGen, *l2KeeGen, *l3KeeGen, *l4KeeGen, *l5KeeGen);
RooArgSet constraints(fracZeroConst, fracOneConst);
if (constPartReco) constraints.add(fracPartRecoConst);
if(nGenJpsiLeak>0) constraints.add(JpsiLeakConst);
RooAbsReal* nll = simPdf.createNLL(dataGenSimultaneous, Extended(), ExternalConstraints(constraints));
RooMinuit minuit(*nll);
minuit.setStrategy(2);
int migradRes(1);
int hesseRes(4);
vector<int> migradResVec;
vector<int> hesseResVec;
double edm(10);
int nrefit(0);
RooFitResult* fitRes(0);
vector<RooFitResult*> fitResVec;
bool hasConverged(false);
for(int i(0); (i<15) && !hasConverged ; ++i)
{
initiateParams(nGenSignalZeroGamma, nGenSignalOneGamma, nGenSignalTwoGamma,
nKemu, nSignal, nPartReco, nComb, fracZero, fracOne,
nJpsiLeak, constPartReco, fracPartRecoSigma,
*l1Kee, *l2Kee, *l3Kee, *l4Kee, *l5Kee, l1Kemu, l2Kemu, l3Kemu, l4Kemu, l5Kemu,
*l1KeeGen, *l2KeeGen, *l3KeeGen, *l4KeeGen, *l5KeeGen);
cout<<"FITTING: starting with nsignal = "<<nSignal.getValV()<<" refit nbr. "<<i<<endl;
//if(fitRes != NULL && fitRes != 0) delete fitRes;
migradRes = minuit.migrad();
hesseRes = minuit.hesse();
fitRes = minuit.save();
edm = fitRes->edm();
fitResVec.push_back(fitRes);
migradResVec.push_back(migradRes);
hesseResVec.push_back(hesseRes);
if( migradRes == 0 && hesseRes == 0 && edm < 1e-3 ) hasConverged = true;
++nrefit;
cout<<"Fitting nbr "<<i<<" done. Hesse: "<<hesseRes<<" migrad: "<<migradRes<<" edm: "<<edm<<" minNll: "<<fitRes->minNll()<<endl;
}
if(!hasConverged)
{
double minNll(1e20);
int minIndex(-1);
for(unsigned int i(0); i<fitResVec.size(); ++i)
{
if( fitResVec.at(i)->minNll() < minNll)
{
minIndex = i;
minNll = fitResVec[i]->minNll();
}
}
migradRes = migradResVec.at(minIndex);
hesseRes = hesseResVec.at(minIndex);
cout<<"Fit not converged, choose fit "<<minIndex<<". Hesse: "<<hesseRes<<" migrad: "<<migradRes<<" edm: "<<edm<<" minNll: "<<fitRes->minNll()<<endl;
}
fillTreeResult(t, fitRes, update, migradRes, hesseRes, hasConverged);
for(unsigned int i(0); i<fitResVec.size(); ++i) delete fitResVec.at(i);
//totPdf.fitTo(*dataGenTot, Extended(), Save(), Warnings(false));
//*************** output fit status
int w(12);
out<<setw(w)<<migradRes<<setw(w)<<hesseRes<<setw(w)<<edm<<setw(w)<<nrefit<<endl;
if(wantplot) plot_fit_result(plotsfile, totPdf, *dataGenTot);
if(wantplot) plot_kemu_fit_result(plotsfile, totKemuPdf, *dataGenKemu);
fw.Close();
//delete and return
delete nll;
delete workspace;
delete workspaceGen;
delete combPDF;
delete KemuPDF;
}
void drawCtauMass2DPlot(RooWorkspace& myws, // Local workspace
string outputDir, // Output directory
struct KinCuts cut, // Variable with current kinematic cuts
string plotLabel, // The label used to define the output file name
// Select the type of datasets to fit
string DSTAG, // Specifies the type of datasets: i.e, DATA, MCJPSINP, ...
bool isPbPb, // Define if it is PbPb (True) or PP (False)\
// Select the drawing options
map<string, double> binWidth={} // User-defined Location of the fit results
)
{
gStyle->SetOptStat(0);
if (DSTAG.find("_")!=std::string::npos) DSTAG.erase(DSTAG.find("_"));
double minRangeCtau = -0.5;
double maxRangeCtau = 2.0;
int nBinsCtau = min(int( round((maxRangeCtau - minRangeCtau)/binWidth["CTAU"]*2) ), 1000);
// myws.var("ctau")->setBin(nBinsCtau, Binning(nBinsCtau, minRangeCtau, maxRangeCtau));
double minRangeMass = cut.dMuon.M.Min;
double maxRangeMass = cut.dMuon.M.Max;
int nBinsMass = min(int( round((maxRangeMass - minRangeMass)/binWidth["MASS"]) ), 1000);
// myws.var("invMass")->setBin(nBinsCtau, Binning(nBinsCtau, minRangeCtau, maxRangeCtau));
string pdfTotName = Form("pdfCTAUMASS_Tot_%s", (isPbPb?"PbPb":"PP"));
TH1* hPDF = ((RooAbsReal*)myws.pdf(pdfTotName.c_str()))->createHistogram("PDF 2D",*myws.var("ctau"), Extended(kTRUE), Binning(nBinsCtau, minRangeCtau, maxRangeCtau), YVar(*myws.var("invMass"), Binning(nBinsMass, minRangeMass, maxRangeMass)));
string dsOSName = Form("dOS_%s_%s", DSTAG.c_str(), (isPbPb?"PbPb":"PP"));
TH1* hDATA = ((RooDataSet*)myws.data(dsOSName.c_str()))->createHistogram("DATA 2D",*myws.var("ctau"), Binning(nBinsCtau, minRangeCtau, maxRangeCtau), YVar(*myws.var("invMass"), Binning(nBinsMass, minRangeMass, maxRangeMass)));
// Create the main canvas
TCanvas *cFigPDF = new TCanvas(Form("cCtauMassPDF_%s", (isPbPb?"PbPb":"PP")), "cCtauMassPDF",2000,2000);
cFigPDF->cd();
hPDF->GetYaxis()->CenterTitle(kTRUE);
hPDF->GetYaxis()->SetTitleOffset(2.1);
hPDF->GetYaxis()->SetTitleSize(0.035);
hPDF->GetYaxis()->SetLabelSize(0.025);
hPDF->GetYaxis()->SetTitle("Mass [GeV/c]");
hPDF->GetXaxis()->CenterTitle(kTRUE);
hPDF->GetXaxis()->SetTitleOffset(2.1);
hPDF->GetXaxis()->SetTitleSize(0.035);
hPDF->GetXaxis()->SetLabelSize(0.025);
hPDF->GetXaxis()->SetTitle("#font[12]{l}_{J/#psi} (mm)");
hPDF->GetZaxis()->SetTitleOffset(2.0);
hPDF->GetZaxis()->SetTitleSize(0.035);
hPDF->GetZaxis()->SetLabelSize(0.025);
hPDF->GetYaxis()->SetRangeUser(minRangeMass, maxRangeMass);
hPDF->GetXaxis()->SetRangeUser(minRangeCtau, maxRangeCtau);
cFigPDF->SetLogz(kTRUE);
hPDF->Draw("LEGO2");
gSystem->mkdir(Form("%sctauMass/%s/plot/pdf2D/", outputDir.c_str(), DSTAG.c_str()), kTRUE);
cFigPDF->SaveAs(Form("%sctauMass/%s/plot/pdf2D/PLOT_%s_%s_%s%s_pt%.0f%.0f_rap%.0f%.0f_cent%d%d.pdf", outputDir.c_str(), DSTAG.c_str(), "CTAUMASSPDF", DSTAG.c_str(), (isPbPb?"PbPb":"PP"), plotLabel.c_str(), (cut.dMuon.Pt.Min*10.0), (cut.dMuon.Pt.Max*10.0), (cut.dMuon.AbsRap.Min*10.0), (cut.dMuon.AbsRap.Max*10.0), cut.Centrality.Start, cut.Centrality.End));
cFigPDF->Clear();
cFigPDF->Close();
// Create the main canvas
TCanvas *cFigDATA = new TCanvas(Form("cCtauMassPDF_%s", (isPbPb?"PbPb":"PP")), "cCtauMassPDF",2000,2000);
cFigDATA->cd();
hDATA->GetYaxis()->CenterTitle(kTRUE);
hDATA->GetYaxis()->SetTitleOffset(2.1);
hDATA->GetYaxis()->SetTitleSize(0.035);
hDATA->GetYaxis()->SetLabelSize(0.025);
hDATA->GetYaxis()->SetTitle("Mass [GeV/c]");
hDATA->GetXaxis()->CenterTitle(kTRUE);
hDATA->GetXaxis()->SetTitleOffset(2.1);
hDATA->GetXaxis()->SetTitleSize(0.035);
hDATA->GetXaxis()->SetLabelSize(0.025);
hDATA->GetXaxis()->SetTitle("#font[12]{l}_{J/#psi} (mm)");
hDATA->GetZaxis()->SetTitleOffset(2.0);
hDATA->GetZaxis()->SetTitleSize(0.035);
hDATA->GetZaxis()->SetLabelSize(0.025);
hDATA->GetYaxis()->SetRangeUser(minRangeMass, maxRangeMass);
hDATA->GetXaxis()->SetRangeUser(minRangeCtau, maxRangeCtau);
cFigDATA->SetLogz(kTRUE);
hDATA->Draw("LEGO2");
gSystem->mkdir(Form("%sctauMass/%s/plot/pdf2D/", outputDir.c_str(), DSTAG.c_str()), kTRUE);
cFigDATA->SaveAs(Form("%sctauMass/%s/plot/pdf2D/PLOT_%s_%s_%s%s_pt%.0f%.0f_rap%.0f%.0f_cent%d%d.pdf", outputDir.c_str(), DSTAG.c_str(), "CTAUMASSDATA", DSTAG.c_str(), (isPbPb?"PbPb":"PP"), plotLabel.c_str(), (cut.dMuon.Pt.Min*10.0), (cut.dMuon.Pt.Max*10.0), (cut.dMuon.AbsRap.Min*10.0), (cut.dMuon.AbsRap.Max*10.0), cut.Centrality.Start, cut.Centrality.End));
cFigDATA->Clear();
cFigDATA->Close();
delete hPDF;
delete hDATA;
};
void drawMassFrom2DPlot(RooWorkspace& myws, // Local workspace
string outputDir, // Output directory
struct InputOpt opt, // Variable with run information (kept for legacy purpose)
struct KinCuts cut, // Variable with current kinematic cuts
map<string, string> parIni, // Variable containing all initial parameters
string plotLabel, // The label used to define the output file name
// Select the type of datasets to fit
string DSTAG, // Specifies the type of datasets: i.e, DATA, MCJPSINP, ...
bool isPbPb, // Define if it is PbPb (True) or PP (False)
// Select the type of object to fit
bool incJpsi, // Includes Jpsi model
bool incPsi2S, // Includes Psi(2S) model
bool incBkg, // Includes Background model
// Select the fitting options
// Select the drawing options
bool setLogScale, // Draw plot with log scale
bool incSS, // Include Same Sign data
double binWidth, // Bin width
bool paperStyle=false // if true, print less info
)
{
RooMsgService::instance().getStream(0).removeTopic(Caching);
RooMsgService::instance().getStream(1).removeTopic(Caching);
RooMsgService::instance().getStream(0).removeTopic(Plotting);
RooMsgService::instance().getStream(1).removeTopic(Plotting);
RooMsgService::instance().getStream(0).removeTopic(Integration);
RooMsgService::instance().getStream(1).removeTopic(Integration);
RooMsgService::instance().setGlobalKillBelow(RooFit::WARNING) ;
if (DSTAG.find("_")!=std::string::npos) DSTAG.erase(DSTAG.find("_"));
int nBins = min(int( round((cut.dMuon.M.Max - cut.dMuon.M.Min)/binWidth) ), 1000);
string pdfTotName = Form("pdfCTAUMASS_Tot_%s", (isPbPb?"PbPb":"PP"));
string pdfJpsiPRName = Form("pdfCTAUMASS_JpsiPR_%s", (isPbPb?"PbPb":"PP"));
string pdfJpsiNoPRName = Form("pdfCTAUMASS_JpsiNoPR_%s", (isPbPb?"PbPb":"PP"));
string pdfPsi2SPRName = Form("pdfCTAUMASS_Psi2SPR_%s", (isPbPb?"PbPb":"PP"));
string pdfPsi2SNoPRName = Form("pdfCTAUMASS_Psi2SNoPR_%s", (isPbPb?"PbPb":"PP"));
string dsOSName = Form("dOS_%s_%s", DSTAG.c_str(), (isPbPb?"PbPb":"PP"));
string dsOSNameCut = dsOSName+"_CTAUCUT";
string dsSSName = Form("dSS_%s_%s", DSTAG.c_str(), (isPbPb?"PbPb":"PP"));
bool isWeighted = myws.data(dsOSName.c_str())->isWeighted();
bool isMC = (DSTAG.find("MC")!=std::string::npos);
double normDSTot = 1.0; if (myws.data(dsOSNameCut.c_str())) { normDSTot = myws.data(dsOSName.c_str())->sumEntries()/myws.data(dsOSNameCut.c_str())->sumEntries(); }
// Create the main plot of the fit
RooPlot* frame = myws.var("invMass")->frame(Bins(nBins), Range(cut.dMuon.M.Min, cut.dMuon.M.Max));
myws.data(dsOSName.c_str())->plotOn(frame, Name("dOS"), DataError(RooAbsData::SumW2), XErrorSize(0), MarkerColor(kBlack), LineColor(kBlack), MarkerSize(1.2));
if (paperStyle) TGaxis::SetMaxDigits(3); // to display powers of 10
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("BKG"),Components(RooArgSet(*myws.pdf(Form("pdfMASS_Bkg_%s", (isPbPb?"PbPb":"PP"))))),
FillStyle(paperStyle ? 0 : 1001), FillColor(kAzure-9), VLines(), DrawOption("LCF"), LineColor(kBlue), LineStyle(kDashed)
);
if (!paperStyle) {
if (incJpsi) {
if ( myws.pdf(Form("pdfCTAUMASS_JpsiPR_%s", (isPbPb?"PbPb":"PP"))) ) {
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("JPSIPR"),Components(RooArgSet(*myws.pdf(Form("pdfCTAUMASS_JpsiPR_%s", (isPbPb?"PbPb":"PP"))), *myws.pdf(Form("pdfCTAUMASS_Bkg_%s", (isPbPb?"PbPb":"PP"))))),
ProjWData(RooArgSet(*myws.var("ctauErr")), *myws.data(dsOSName.c_str()), kTRUE),
Normalization(normDSTot, RooAbsReal::NumEvent),
LineColor(kRed+3), LineStyle(1), Precision(1e-4), NumCPU(32)
);
}
if ( myws.pdf(Form("pdfCTAUMASS_JpsiNoPR_%s", (isPbPb?"PbPb":"PP"))) ) {
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("JPSINOPR"),Components(RooArgSet(*myws.pdf(Form("pdfCTAUMASS_JpsiNoPR_%s", (isPbPb?"PbPb":"PP"))), *myws.pdf(Form("pdfCTAUMASS_Bkg_%s", (isPbPb?"PbPb":"PP"))))),
ProjWData(RooArgSet(*myws.var("ctauErr")), *myws.data(dsOSName.c_str()), kTRUE),
Normalization(normDSTot, RooAbsReal::NumEvent),
LineColor(kGreen+3), LineStyle(1), Precision(1e-4), NumCPU(32)
);
}
}
if (incPsi2S) {
if ( myws.pdf(Form("pdfCTAUMASS_Psi2SPR_%s", (isPbPb?"PbPb":"PP"))) ) {
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("PSI2SPR"),Components(RooArgSet(*myws.pdf(Form("pdfCTAUMASS_Psi2SPR_%s", (isPbPb?"PbPb":"PP"))))),
ProjWData(RooArgSet(*myws.var("ctauErr")), *myws.data(dsOSName.c_str()), kTRUE),
Normalization(normDSTot, RooAbsReal::NumEvent),
LineColor(kRed+3), LineStyle(1), Precision(1e-4), NumCPU(32)
);
}
if ( myws.pdf(Form("pdfCTAUMASS_Psi2SNoPR_%s", (isPbPb?"PbPb":"PP"))) ) {
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("PSI2SNOPR"),Components(RooArgSet(*myws.pdf(Form("pdfCTAUMASS_Psi2SNoPR_%s", (isPbPb?"PbPb":"PP"))))),
ProjWData(RooArgSet(*myws.var("ctauErr")), *myws.data(dsOSName.c_str()), kTRUE),
Normalization(normDSTot, RooAbsReal::NumEvent),
LineColor(kGreen+3), LineStyle(1), Precision(1e-4), NumCPU(32)
);
}
}
}
if (incSS) {
myws.data(dsSSName.c_str())->plotOn(frame, Name("dSS"), MarkerColor(kRed), LineColor(kRed), MarkerSize(1.2));
}
myws.data(dsOSName.c_str())->plotOn(frame, Name("dOS"), DataError(RooAbsData::SumW2), XErrorSize(0), MarkerColor(kBlack), LineColor(kBlack), MarkerSize(1.2));
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("PDF"),
ProjWData(RooArgSet(*myws.var("ctauErr")), *myws.data(dsOSName.c_str()), kTRUE),
Normalization(normDSTot, RooAbsReal::NumEvent),
LineColor(kBlack), NumCPU(32)
);
// Create the pull distribution of the fit
RooPlot* frameTMP = (RooPlot*)frame->Clone("TMP");
int nBinsTMP = nBins;
RooHist *hpull = frameTMP->pullHist(0, 0, true);
hpull->SetName("hpull");
RooPlot* frame2 = myws.var("invMass")->frame(Title("Pull Distribution"), Bins(nBins), Range(cut.dMuon.M.Min, cut.dMuon.M.Max));
frame2->addPlotable(hpull, "PX");
// set the CMS style
setTDRStyle();
// Create the main canvas
TCanvas *cFig = new TCanvas(Form("cMassFig_%s", (isPbPb?"PbPb":"PP")), "cMassFig",800,800);
TPad *pad1 = new TPad(Form("pad1_%s", (isPbPb?"PbPb":"PP")),"",0,paperStyle ? 0 : 0.23,1,1);
TPad *pad2 = new TPad(Form("pad2_%s", (isPbPb?"PbPb":"PP")),"",0,0,1,.228);
TLine *pline = new TLine(cut.dMuon.M.Min, 0.0, cut.dMuon.M.Max, 0.0);
// TPad *pad4 = new TPad("pad4","This is pad4",0.55,0.46,0.97,0.87);
TPad *pad4 = new TPad("pad4","This is pad4",0.55,paperStyle ? 0.29 : 0.36,0.97,paperStyle ? 0.70 : 0.77);
pad4->SetFillStyle(0);
pad4->SetLeftMargin(0.28);
pad4->SetRightMargin(0.10);
pad4->SetBottomMargin(0.21);
pad4->SetTopMargin(0.072);
frame->SetTitle("");
frame->GetXaxis()->CenterTitle(kTRUE);
if (!paperStyle) {
frame->GetXaxis()->SetTitle("");
frame->GetXaxis()->SetTitleSize(0.045);
frame->GetXaxis()->SetTitleFont(42);
frame->GetXaxis()->SetTitleOffset(3);
frame->GetXaxis()->SetLabelOffset(3);
frame->GetYaxis()->SetLabelSize(0.04);
frame->GetYaxis()->SetTitleSize(0.04);
frame->GetYaxis()->SetTitleOffset(1.7);
frame->GetYaxis()->SetTitleFont(42);
} else {
frame->GetXaxis()->SetTitle("m_{#mu^{+}#mu^{-}} (GeV/c^{2})");
frame->GetXaxis()->SetTitleOffset(1.1);
frame->GetYaxis()->SetTitleOffset(1.45);
frame->GetXaxis()->SetTitleSize(0.05);
frame->GetYaxis()->SetTitleSize(0.05);
}
setMassFrom2DRange(myws, frame, dsOSName, setLogScale);
if (paperStyle) {
double Ydown = 0.;//frame->GetMinimum();
double Yup = 0.9*frame->GetMaximum();
frame->GetYaxis()->SetRangeUser(Ydown,Yup);
}
cFig->cd();
pad2->SetTopMargin(0.02);
pad2->SetBottomMargin(0.4);
pad2->SetFillStyle(4000);
pad2->SetFrameFillStyle(4000);
if (!paperStyle) pad1->SetBottomMargin(0.015);
//plot fit
pad1->Draw();
pad1->cd();
frame->Draw();
printMassFrom2DParameters(myws, pad1, isPbPb, pdfTotName, isWeighted);
pad1->SetLogy(setLogScale);
// Drawing the text in the plot
TLatex *t = new TLatex(); t->SetNDC(); t->SetTextSize(0.032);
float dy = 0;
t->SetTextSize(0.03);
if (!paperStyle) { // do not print selection details for paper style
t->DrawLatex(0.20, 0.86-dy, "2015 HI Soft Muon ID"); dy+=0.045;
if (isPbPb) {
t->DrawLatex(0.20, 0.86-dy, "HLT_HIL1DoubleMu0_v1"); dy+=2.0*0.045;
} else {
t->DrawLatex(0.20, 0.86-dy, "HLT_HIL1DoubleMu0_v1"); dy+=2.0*0.045;
}
}
if (cut.dMuon.AbsRap.Min>0.1) {t->DrawLatex(0.5175, 0.86-dy, Form("%.1f < |y^{#mu#mu}| < %.1f",cut.dMuon.AbsRap.Min,cut.dMuon.AbsRap.Max)); dy+=0.045;}
else {t->DrawLatex(0.5175, 0.86-dy, Form("|y^{#mu#mu}| < %.1f",cut.dMuon.AbsRap.Max)); dy+=0.045;}
t->DrawLatex(0.5175, 0.86-dy, Form("%g < p_{T}^{#mu#mu} < %g GeV/c",cut.dMuon.Pt.Min,cut.dMuon.Pt.Max)); dy+=0.045;
if (isPbPb) {t->DrawLatex(0.5175, 0.86-dy, Form("Cent. %d-%d%%", (int)(cut.Centrality.Start/2), (int)(cut.Centrality.End/2))); dy+=0.045;}
// Drawing the Legend
double ymin = 0.7602;
if (incPsi2S && incJpsi && incSS) { ymin = 0.7202; }
if (incPsi2S && incJpsi && !incSS) { ymin = 0.7452; }
if (paperStyle) { ymin = 0.72; }
TLegend* leg = new TLegend(0.5175, ymin, 0.7180, 0.8809); leg->SetTextSize(0.03);
if (frame->findObject("dOS")) { leg->AddEntry(frame->findObject("dOS"), (incSS?"Opposite Charge":"Data"),"pe"); }
if (incSS) { leg->AddEntry(frame->findObject("dSS"),"Same Charge","pe"); }
if (frame->findObject("PDF")) { leg->AddEntry(frame->findObject("PDF"),"Total fit","l"); }
if (frame->findObject("JPSIPR")) { leg->AddEntry(frame->findObject("JPSIPR"),"Prompt J/#psi","l"); }
if (frame->findObject("JPSINOPR")) { leg->AddEntry(frame->findObject("JPSINOPR"),"Non-Prompt J/#psi","l"); }
if (incBkg && frame->findObject("BKG")) { leg->AddEntry(frame->findObject("BKG"),"Background",paperStyle ? "l" : "fl"); }
leg->Draw("same");
//Drawing the title
TString label;
if (isPbPb) {
if (opt.PbPb.RunNb.Start==opt.PbPb.RunNb.End){
label = Form("PbPb Run %d", opt.PbPb.RunNb.Start);
} else {
label = Form("%s [%s %d-%d]", "PbPb", "HIOniaL1DoubleMu0", opt.PbPb.RunNb.Start, opt.PbPb.RunNb.End);
}
} else {
if (opt.pp.RunNb.Start==opt.pp.RunNb.End){
label = Form("PP Run %d", opt.pp.RunNb.Start);
} else {
label = Form("%s [%s %d-%d]", "PP", "DoubleMu0", opt.pp.RunNb.Start, opt.pp.RunNb.End);
}
}
// CMS_lumi(pad1, isPbPb ? 105 : 104, 33, label);
CMS_lumi(pad1, isPbPb ? 108 : 107, 33, "");
if (!paperStyle) gStyle->SetTitleFontSize(0.05);
pad1->Update();
cFig->cd();
if (!paperStyle) {
//---plot pull
pad2->Draw();
pad2->cd();
frame2->SetTitle("");
frame2->GetYaxis()->CenterTitle(kTRUE);
frame2->GetYaxis()->SetTitleOffset(0.4);
frame2->GetYaxis()->SetTitleSize(0.1);
frame2->GetYaxis()->SetLabelSize(0.1);
frame2->GetYaxis()->SetTitle("Pull");
frame2->GetXaxis()->CenterTitle(kTRUE);
frame2->GetXaxis()->SetTitleOffset(1);
frame2->GetXaxis()->SetTitleSize(0.12);
frame2->GetXaxis()->SetLabelSize(0.1);
frame2->GetXaxis()->SetTitle("m_{#mu^{+}#mu^{-}} (GeV/c^{2})");
frame2->GetYaxis()->SetRangeUser(-7.0, 7.0);
frame2->Draw();
// *** Print chi2/ndof
printChi2(myws, pad2, frameTMP, "invMass", dsOSName.c_str(), pdfTotName.c_str(), nBinsTMP, false);
pline->Draw("same");
pad2->Update();
}
// Save the plot in different formats
gSystem->mkdir(Form("%sctauMass/%s/plot/root/", outputDir.c_str(), DSTAG.c_str()), kTRUE);
cFig->SaveAs(Form("%sctauMass/%s/plot/root/PLOT_%s_%s_%s%s_pt%.0f%.0f_rap%.0f%.0f_cent%d%d.root", outputDir.c_str(), DSTAG.c_str(), "MASS", DSTAG.c_str(), (isPbPb?"PbPb":"PP"), plotLabel.c_str(), (cut.dMuon.Pt.Min*10.0), (cut.dMuon.Pt.Max*10.0), (cut.dMuon.AbsRap.Min*10.0), (cut.dMuon.AbsRap.Max*10.0), cut.Centrality.Start, cut.Centrality.End));
gSystem->mkdir(Form("%sctauMass/%s/plot/png/", outputDir.c_str(), DSTAG.c_str()), kTRUE);
cFig->SaveAs(Form("%sctauMass/%s/plot/png/PLOT_%s_%s_%s%s_pt%.0f%.0f_rap%.0f%.0f_cent%d%d.png", outputDir.c_str(), DSTAG.c_str(), "MASS", DSTAG.c_str(), (isPbPb?"PbPb":"PP"), plotLabel.c_str(), (cut.dMuon.Pt.Min*10.0), (cut.dMuon.Pt.Max*10.0), (cut.dMuon.AbsRap.Min*10.0), (cut.dMuon.AbsRap.Max*10.0), cut.Centrality.Start, cut.Centrality.End));
gSystem->mkdir(Form("%sctauMass/%s/plot/pdf/", outputDir.c_str(), DSTAG.c_str()), kTRUE);
cFig->SaveAs(Form("%sctauMass/%s/plot/pdf/PLOT_%s_%s_%s%s_pt%.0f%.0f_rap%.0f%.0f_cent%d%d.pdf", outputDir.c_str(), DSTAG.c_str(), "MASS", DSTAG.c_str(), (isPbPb?"PbPb":"PP"), plotLabel.c_str(), (cut.dMuon.Pt.Min*10.0), (cut.dMuon.Pt.Max*10.0), (cut.dMuon.AbsRap.Min*10.0), (cut.dMuon.AbsRap.Max*10.0), cut.Centrality.Start, cut.Centrality.End));
cFig->Clear();
cFig->Close();
};
void StandardFeldmanCousinsDemo(const char* infile = "",
const char* workspaceName = "combined",
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData"){
// -------------------------------------------------------
// First part is just to access a user-defined file
// or create the standard example file if it doesn't exist
const char* filename = "";
if (!strcmp(infile,"")) {
filename = "results/example_combined_GaussExample_model.root";
bool fileExist = !gSystem->AccessPathName(filename); // note opposite return code
// if file does not exists generate with histfactory
if (!fileExist) {
#ifdef _WIN32
cout << "HistFactory file cannot be generated on Windows - exit" << endl;
return;
#endif
// Normally this would be run on the command line
cout <<"will run standard hist2workspace example"<<endl;
gROOT->ProcessLine(".! prepareHistFactory .");
gROOT->ProcessLine(".! hist2workspace config/example.xml");
cout <<"\n\n---------------------"<<endl;
cout <<"Done creating example input"<<endl;
cout <<"---------------------\n\n"<<endl;
}
}
else
filename = infile;
// Try to open the file
TFile *file = TFile::Open(filename);
// if input file was specified byt not found, quit
if(!file ){
cout <<"StandardRooStatsDemoMacro: Input file " << filename << " is not found" << endl;
return;
}
// -------------------------------------------------------
// Tutorial starts here
// -------------------------------------------------------
// get the workspace out of the file
RooWorkspace* w = (RooWorkspace*) file->Get(workspaceName);
if(!w){
cout <<"workspace not found" << endl;
return;
}
// get the modelConfig out of the file
ModelConfig* mc = (ModelConfig*) w->obj(modelConfigName);
// get the modelConfig out of the file
RooAbsData* data = w->data(dataName);
// make sure ingredients are found
if(!data || !mc){
w->Print();
cout << "data or ModelConfig was not found" <<endl;
return;
}
// -------------------------------------------------------
// create and use the FeldmanCousins tool
// to find and plot the 95% confidence interval
// on the parameter of interest as specified
// in the model config
FeldmanCousins fc(*data,*mc);
fc.SetConfidenceLevel(0.95); // 95% interval
//fc.AdditionalNToysFactor(0.1); // to speed up the result
fc.UseAdaptiveSampling(true); // speed it up a bit
fc.SetNBins(10); // set how many points per parameter of interest to scan
fc.CreateConfBelt(true); // save the information in the belt for plotting
// Since this tool needs to throw toy MC the PDF needs to be
// extended or the tool needs to know how many entries in a dataset
// per pseudo experiment.
// In the 'number counting form' where the entries in the dataset
// are counts, and not values of discriminating variables, the
// datasets typically only have one entry and the PDF is not
// extended.
if(!mc->GetPdf()->canBeExtended()){
if(data->numEntries()==1)
fc.FluctuateNumDataEntries(false);
else
cout <<"Not sure what to do about this model" <<endl;
}
// We can use PROOF to speed things along in parallel
// ProofConfig pc(*w, 1, "workers=4", kFALSE);
// ToyMCSampler* toymcsampler = (ToyMCSampler*) fc.GetTestStatSampler();
// toymcsampler->SetProofConfig(&pc); // enable proof
// Now get the interval
PointSetInterval* interval = fc.GetInterval();
ConfidenceBelt* belt = fc.GetConfidenceBelt();
// print out the iterval on the first Parameter of Interest
RooRealVar* firstPOI = (RooRealVar*) mc->GetParametersOfInterest()->first();
cout << "\n95% interval on " <<firstPOI->GetName()<<" is : ["<<
interval->LowerLimit(*firstPOI) << ", "<<
interval->UpperLimit(*firstPOI) <<"] "<<endl;
// ---------------------------------------------
// No nice plots yet, so plot the belt by hand
// Ask the calculator which points were scanned
RooDataSet* parameterScan = (RooDataSet*) fc.GetPointsToScan();
RooArgSet* tmpPoint;
// make a histogram of parameter vs. threshold
TH1F* histOfThresholds = new TH1F("histOfThresholds","",
parameterScan->numEntries(),
firstPOI->getMin(),
firstPOI->getMax());
// loop through the points that were tested and ask confidence belt
// what the upper/lower thresholds were.
// For FeldmanCousins, the lower cut off is always 0
for(Int_t i=0; i<parameterScan->numEntries(); ++i){
tmpPoint = (RooArgSet*) parameterScan->get(i)->clone("temp");
double arMax = belt->GetAcceptanceRegionMax(*tmpPoint);
double arMin = belt->GetAcceptanceRegionMax(*tmpPoint);
double poiVal = tmpPoint->getRealValue(firstPOI->GetName()) ;
histOfThresholds->Fill(poiVal,arMax);
}
histOfThresholds->SetMinimum(0);
histOfThresholds->Draw();
}
void OneSidedFrequentistUpperLimitWithBands(const char* infile = "",
const char* workspaceName = "combined",
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData") {
double confidenceLevel=0.95;
int nPointsToScan = 20;
int nToyMC = 200;
// -------------------------------------------------------
// First part is just to access a user-defined file
// or create the standard example file if it doesn't exist
const char* filename = "";
if (!strcmp(infile,"")) {
filename = "results/example_combined_GaussExample_model.root";
bool fileExist = !gSystem->AccessPathName(filename); // note opposite return code
// if file does not exists generate with histfactory
if (!fileExist) {
#ifdef _WIN32
cout << "HistFactory file cannot be generated on Windows - exit" << endl;
return;
#endif
// Normally this would be run on the command line
cout <<"will run standard hist2workspace example"<<endl;
gROOT->ProcessLine(".! prepareHistFactory .");
gROOT->ProcessLine(".! hist2workspace config/example.xml");
cout <<"\n\n---------------------"<<endl;
cout <<"Done creating example input"<<endl;
cout <<"---------------------\n\n"<<endl;
}
}
else
filename = infile;
// Try to open the file
TFile *file = TFile::Open(filename);
// if input file was specified byt not found, quit
if(!file ){
cout <<"StandardRooStatsDemoMacro: Input file " << filename << " is not found" << endl;
return;
}
// -------------------------------------------------------
// Now get the data and workspace
// get the workspace out of the file
RooWorkspace* w = (RooWorkspace*) file->Get(workspaceName);
if(!w){
cout <<"workspace not found" << endl;
return;
}
// get the modelConfig out of the file
ModelConfig* mc = (ModelConfig*) w->obj(modelConfigName);
// get the modelConfig out of the file
RooAbsData* data = w->data(dataName);
// make sure ingredients are found
if(!data || !mc){
w->Print();
cout << "data or ModelConfig was not found" <<endl;
return;
}
// -------------------------------------------------------
// Now get the POI for convenience
// you may want to adjust the range of your POI
RooRealVar* firstPOI = (RooRealVar*) mc->GetParametersOfInterest()->first();
/* firstPOI->setMin(0);*/
/* firstPOI->setMax(10);*/
// --------------------------------------------
// Create and use the FeldmanCousins tool
// to find and plot the 95% confidence interval
// on the parameter of interest as specified
// in the model config
// REMEMBER, we will change the test statistic
// so this is NOT a Feldman-Cousins interval
FeldmanCousins fc(*data,*mc);
fc.SetConfidenceLevel(confidenceLevel);
/* fc.AdditionalNToysFactor(0.25); // degrade/improve sampling that defines confidence belt*/
/* fc.UseAdaptiveSampling(true); // speed it up a bit, don't use for expected limits*/
fc.SetNBins(nPointsToScan); // set how many points per parameter of interest to scan
fc.CreateConfBelt(true); // save the information in the belt for plotting
// -------------------------------------------------------
// Feldman-Cousins is a unified limit by definition
// but the tool takes care of a few things for us like which values
// of the nuisance parameters should be used to generate toys.
// so let's just change the test statistic and realize this is
// no longer "Feldman-Cousins" but is a fully frequentist Neyman-Construction.
/* ProfileLikelihoodTestStatModified onesided(*mc->GetPdf());*/
/* fc.GetTestStatSampler()->SetTestStatistic(&onesided);*/
/* ((ToyMCSampler*) fc.GetTestStatSampler())->SetGenerateBinned(true); */
ToyMCSampler* toymcsampler = (ToyMCSampler*) fc.GetTestStatSampler();
ProfileLikelihoodTestStat* testStat = dynamic_cast<ProfileLikelihoodTestStat*>(toymcsampler->GetTestStatistic());
testStat->SetOneSided(true);
// Since this tool needs to throw toy MC the PDF needs to be
// extended or the tool needs to know how many entries in a dataset
// per pseudo experiment.
// In the 'number counting form' where the entries in the dataset
// are counts, and not values of discriminating variables, the
// datasets typically only have one entry and the PDF is not
// extended.
if(!mc->GetPdf()->canBeExtended()){
if(data->numEntries()==1)
fc.FluctuateNumDataEntries(false);
else
cout <<"Not sure what to do about this model" <<endl;
}
// We can use PROOF to speed things along in parallel
// However, the test statistic has to be installed on the workers
// so either turn off PROOF or include the modified test statistic
// in your `$ROOTSYS/roofit/roostats/inc` directory,
// add the additional line to the LinkDef.h file,
// and recompile root.
if (useProof) {
ProofConfig pc(*w, nworkers, "", false);
toymcsampler->SetProofConfig(&pc); // enable proof
}
if(mc->GetGlobalObservables()){
cout << "will use global observables for unconditional ensemble"<<endl;
mc->GetGlobalObservables()->Print();
toymcsampler->SetGlobalObservables(*mc->GetGlobalObservables());
}
// Now get the interval
PointSetInterval* interval = fc.GetInterval();
ConfidenceBelt* belt = fc.GetConfidenceBelt();
// print out the interval on the first Parameter of Interest
cout << "\n95% interval on " <<firstPOI->GetName()<<" is : ["<<
interval->LowerLimit(*firstPOI) << ", "<<
interval->UpperLimit(*firstPOI) <<"] "<<endl;
// get observed UL and value of test statistic evaluated there
RooArgSet tmpPOI(*firstPOI);
double observedUL = interval->UpperLimit(*firstPOI);
firstPOI->setVal(observedUL);
double obsTSatObsUL = fc.GetTestStatSampler()->EvaluateTestStatistic(*data,tmpPOI);
// Ask the calculator which points were scanned
RooDataSet* parameterScan = (RooDataSet*) fc.GetPointsToScan();
RooArgSet* tmpPoint;
// make a histogram of parameter vs. threshold
TH1F* histOfThresholds = new TH1F("histOfThresholds","",
parameterScan->numEntries(),
firstPOI->getMin(),
firstPOI->getMax());
histOfThresholds->GetXaxis()->SetTitle(firstPOI->GetName());
histOfThresholds->GetYaxis()->SetTitle("Threshold");
// loop through the points that were tested and ask confidence belt
// what the upper/lower thresholds were.
// For FeldmanCousins, the lower cut off is always 0
for(Int_t i=0; i<parameterScan->numEntries(); ++i){
tmpPoint = (RooArgSet*) parameterScan->get(i)->clone("temp");
//cout <<"get threshold"<<endl;
double arMax = belt->GetAcceptanceRegionMax(*tmpPoint);
double poiVal = tmpPoint->getRealValue(firstPOI->GetName()) ;
histOfThresholds->Fill(poiVal,arMax);
}
TCanvas* c1 = new TCanvas();
c1->Divide(2);
c1->cd(1);
histOfThresholds->SetMinimum(0);
histOfThresholds->Draw();
c1->cd(2);
// -------------------------------------------------------
// Now we generate the expected bands and power-constraint
// First: find parameter point for mu=0, with conditional MLEs for nuisance parameters
RooAbsReal* nll = mc->GetPdf()->createNLL(*data);
RooAbsReal* profile = nll->createProfile(*mc->GetParametersOfInterest());
firstPOI->setVal(0.);
profile->getVal(); // this will do fit and set nuisance parameters to profiled values
RooArgSet* poiAndNuisance = new RooArgSet();
if(mc->GetNuisanceParameters())
poiAndNuisance->add(*mc->GetNuisanceParameters());
poiAndNuisance->add(*mc->GetParametersOfInterest());
w->saveSnapshot("paramsToGenerateData",*poiAndNuisance);
RooArgSet* paramsToGenerateData = (RooArgSet*) poiAndNuisance->snapshot();
cout << "\nWill use these parameter points to generate pseudo data for bkg only" << endl;
paramsToGenerateData->Print("v");
RooArgSet unconditionalObs;
unconditionalObs.add(*mc->GetObservables());
unconditionalObs.add(*mc->GetGlobalObservables()); // comment this out for the original conditional ensemble
double CLb=0;
double CLbinclusive=0;
// Now we generate background only and find distribution of upper limits
TH1F* histOfUL = new TH1F("histOfUL","",100,0,firstPOI->getMax());
histOfUL->GetXaxis()->SetTitle("Upper Limit (background only)");
histOfUL->GetYaxis()->SetTitle("Entries");
for(int imc=0; imc<nToyMC; ++imc){
// set parameters back to values for generating pseudo data
// cout << "\n get current nuis, set vals, print again" << endl;
w->loadSnapshot("paramsToGenerateData");
// poiAndNuisance->Print("v");
RooDataSet* toyData = 0;
// now generate a toy dataset
if(!mc->GetPdf()->canBeExtended()){
if(data->numEntries()==1)
toyData = mc->GetPdf()->generate(*mc->GetObservables(),1);
else
cout <<"Not sure what to do about this model" <<endl;
} else{
// cout << "generating extended dataset"<<endl;
toyData = mc->GetPdf()->generate(*mc->GetObservables(),Extended());
}
// generate global observables
// need to be careful for simpdf
// RooDataSet* globalData = mc->GetPdf()->generate(*mc->GetGlobalObservables(),1);
RooSimultaneous* simPdf = dynamic_cast<RooSimultaneous*>(mc->GetPdf());
if(!simPdf){
RooDataSet *one = mc->GetPdf()->generate(*mc->GetGlobalObservables(), 1);
const RooArgSet *values = one->get();
RooArgSet *allVars = mc->GetPdf()->getVariables();
*allVars = *values;
delete allVars;
delete values;
delete one;
} else {
//try fix for sim pdf
TIterator* iter = simPdf->indexCat().typeIterator() ;
RooCatType* tt = NULL;
while((tt=(RooCatType*) iter->Next())) {
// Get pdf associated with state from simpdf
RooAbsPdf* pdftmp = simPdf->getPdf(tt->GetName()) ;
// Generate only global variables defined by the pdf associated with this state
RooArgSet* globtmp = pdftmp->getObservables(*mc->GetGlobalObservables()) ;
RooDataSet* tmp = pdftmp->generate(*globtmp,1) ;
// Transfer values to output placeholder
*globtmp = *tmp->get(0) ;
// Cleanup
delete globtmp ;
delete tmp ;
}
}
// globalData->Print("v");
// unconditionalObs = *globalData->get();
// mc->GetGlobalObservables()->Print("v");
// delete globalData;
// cout << "toy data = " << endl;
// toyData->get()->Print("v");
// get test stat at observed UL in observed data
firstPOI->setVal(observedUL);
double toyTSatObsUL = fc.GetTestStatSampler()->EvaluateTestStatistic(*toyData,tmpPOI);
// toyData->get()->Print("v");
// cout <<"obsTSatObsUL " <<obsTSatObsUL << "toyTS " << toyTSatObsUL << endl;
if(obsTSatObsUL < toyTSatObsUL) // not sure about <= part yet
CLb+= (1.)/nToyMC;
if(obsTSatObsUL <= toyTSatObsUL) // not sure about <= part yet
CLbinclusive+= (1.)/nToyMC;
// loop over points in belt to find upper limit for this toy data
double thisUL = 0;
for(Int_t i=0; i<parameterScan->numEntries(); ++i){
tmpPoint = (RooArgSet*) parameterScan->get(i)->clone("temp");
double arMax = belt->GetAcceptanceRegionMax(*tmpPoint);
firstPOI->setVal( tmpPoint->getRealValue(firstPOI->GetName()) );
// double thisTS = profile->getVal();
double thisTS = fc.GetTestStatSampler()->EvaluateTestStatistic(*toyData,tmpPOI);
// cout << "poi = " << firstPOI->getVal()
// << " max is " << arMax << " this profile = " << thisTS << endl;
// cout << "thisTS = " << thisTS<<endl;
if(thisTS<=arMax){
thisUL = firstPOI->getVal();
} else{
break;
}
}
/*
// loop over points in belt to find upper limit for this toy data
double thisUL = 0;
for(Int_t i=0; i<histOfThresholds->GetNbinsX(); ++i){
tmpPoint = (RooArgSet*) parameterScan->get(i)->clone("temp");
cout <<"---------------- "<<i<<endl;
tmpPoint->Print("v");
cout << "from hist " << histOfThresholds->GetBinCenter(i+1) <<endl;
double arMax = histOfThresholds->GetBinContent(i+1);
// cout << " threhold from Hist = aMax " << arMax<<endl;
// double arMax2 = belt->GetAcceptanceRegionMax(*tmpPoint);
// cout << "from scan arMax2 = "<< arMax2 << endl; // not the same due to TH1F not TH1D
// cout << "scan - hist" << arMax2-arMax << endl;
firstPOI->setVal( histOfThresholds->GetBinCenter(i+1));
// double thisTS = profile->getVal();
double thisTS = fc.GetTestStatSampler()->EvaluateTestStatistic(*toyData,tmpPOI);
// cout << "poi = " << firstPOI->getVal()
// << " max is " << arMax << " this profile = " << thisTS << endl;
// cout << "thisTS = " << thisTS<<endl;
// NOTE: need to add a small epsilon term for single precision vs. double precision
if(thisTS<=arMax + 1e-7){
thisUL = firstPOI->getVal();
} else{
break;
}
}
*/
histOfUL->Fill(thisUL);
// for few events, data is often the same, and UL is often the same
// cout << "thisUL = " << thisUL<<endl;
delete toyData;
}
histOfUL->Draw();
c1->SaveAs("one-sided_upper_limit_output.pdf");
// if you want to see a plot of the sampling distribution for a particular scan point:
/*
SamplingDistPlot sampPlot;
int indexInScan = 0;
tmpPoint = (RooArgSet*) parameterScan->get(indexInScan)->clone("temp");
firstPOI->setVal( tmpPoint->getRealValue(firstPOI->GetName()) );
toymcsampler->SetParametersForTestStat(tmpPOI);
SamplingDistribution* samp = toymcsampler->GetSamplingDistribution(*tmpPoint);
sampPlot.AddSamplingDistribution(samp);
sampPlot.Draw();
*/
// Now find bands and power constraint
Double_t* bins = histOfUL->GetIntegral();
TH1F* cumulative = (TH1F*) histOfUL->Clone("cumulative");
cumulative->SetContent(bins);
double band2sigDown, band1sigDown, bandMedian, band1sigUp,band2sigUp;
for(int i=1; i<=cumulative->GetNbinsX(); ++i){
if(bins[i]<RooStats::SignificanceToPValue(2))
band2sigDown=cumulative->GetBinCenter(i);
if(bins[i]<RooStats::SignificanceToPValue(1))
band1sigDown=cumulative->GetBinCenter(i);
if(bins[i]<0.5)
bandMedian=cumulative->GetBinCenter(i);
if(bins[i]<RooStats::SignificanceToPValue(-1))
band1sigUp=cumulative->GetBinCenter(i);
if(bins[i]<RooStats::SignificanceToPValue(-2))
band2sigUp=cumulative->GetBinCenter(i);
}
cout << "-2 sigma band " << band2sigDown << endl;
cout << "-1 sigma band " << band1sigDown << " [Power Constraint)]" << endl;
cout << "median of band " << bandMedian << endl;
cout << "+1 sigma band " << band1sigUp << endl;
cout << "+2 sigma band " << band2sigUp << endl;
// print out the interval on the first Parameter of Interest
cout << "\nobserved 95% upper-limit "<< interval->UpperLimit(*firstPOI) <<endl;
cout << "CLb strict [P(toy>obs|0)] for observed 95% upper-limit "<< CLb <<endl;
cout << "CLb inclusive [P(toy>=obs|0)] for observed 95% upper-limit "<< CLbinclusive <<endl;
delete profile;
delete nll;
}
void FitterUtils::fit(bool wantplot, bool constPartReco,
double fracPartReco_const,
ofstream& out, TTree* t, bool update, string plotsfile)
{
//***************Get the PDFs from the workspace
TFile fw(workspacename.c_str());
RooWorkspace* workspace = (RooWorkspace*)fw.Get("workspace");
RooRealVar *B_plus_M = workspace->var("B_plus_M");
RooRealVar *misPT = workspace->var("misPT");
RooRealVar *T = workspace->var("T");
RooRealVar *n = workspace->var("n");
RooRealVar *expoConst = workspace->var("expoConst");
RooRealVar *trueExp = workspace->var("trueExp");
RooRealVar *fractionalErrorJpsiLeak = workspace->var("fractionalErrorJpsiLeak");
cout<<"VALUE OF T IN FIT: "<<T->getVal()<<" +- "<<T->getError()<<endl;
cout<<"VALUE OF n IN FIT: "<<n->getVal()<<" +- "<<n->getError()<<endl;
RooHistPdf *histPdfSignalZeroGamma = (RooHistPdf *) workspace->pdf("histPdfSignalZeroGamma");
RooHistPdf *histPdfSignalOneGamma = (RooHistPdf *) workspace->pdf("histPdfSignalOneGamma");
RooHistPdf *histPdfSignalTwoGamma = (RooHistPdf *) workspace->pdf("histPdfSignalTwoGamma");
RooHistPdf *histPdfPartReco = (RooHistPdf *) workspace->pdf("histPdfPartReco");
RooHistPdf *histPdfJpsiLeak(0);
if(nGenJpsiLeak>0) histPdfJpsiLeak = (RooHistPdf *) workspace->pdf("histPdfJpsiLeak");
RooAbsPdf *combPDF;
if (fit2D)
{
combPDF = new RooPTMVis("combPDF", "combPDF", *misPT, *B_plus_M, *T, *n, *expoConst);
}
else
{
combPDF = new RooExponential("combPDF", "combPDF", *B_plus_M, *expoConst);
}
expoConst->setVal(trueExp->getVal());
RooWorkspace* workspaceGen = (RooWorkspace*)fw.Get("workspaceGen");
RooDataSet* dataGenSignalZeroGamma = (RooDataSet*)workspaceGen->data("dataGenSignalZeroGamma");
RooDataSet* dataGenSignalOneGamma = (RooDataSet*)workspaceGen->data("dataGenSignalOneGamma");
RooDataSet* dataGenSignalTwoGamma = (RooDataSet*)workspaceGen->data("dataGenSignalTwoGamma");
RooDataSet* dataGenPartReco = (RooDataSet*)workspaceGen->data("dataGenPartReco");
RooDataSet* dataGenComb = (RooDataSet*)workspaceGen->data("dataGenComb");
RooDataSet* dataGenJpsiLeak(0);
if(nGenJpsiLeak>0) dataGenJpsiLeak = (RooDataSet*)workspaceGen->data("dataGenJpsiLeak");
if(wantplot)
{
//**************Must get the datasets
RooDataSet* dataSetSignalZeroGamma = (RooDataSet*)workspace->data("dataSetSignalZeroGamma");
RooDataSet* dataSetSignalOneGamma = (RooDataSet*)workspace->data("dataSetSignalOneGamma");
RooDataSet* dataSetSignalTwoGamma = (RooDataSet*)workspace->data("dataSetSignalTwoGamma");
RooDataSet* dataSetPartReco = (RooDataSet*)workspace->data("dataSetPartReco");
RooDataSet* dataSetComb = (RooDataSet*)workspace->data("dataSetComb");
RooDataSet* dataSetJpsiLeak = (RooDataSet*)workspace->data("dataSetJpsiLeak");
//**************Plot all the different components
cout<<"dataGenSignalZeroGamma: "<<dataGenSignalZeroGamma<<endl;
PlotShape(*dataSetSignalZeroGamma, *dataGenSignalZeroGamma, *histPdfSignalZeroGamma, plotsfile, "cSignalZeroGamma", *B_plus_M, *misPT);
PlotShape(*dataSetSignalOneGamma, *dataGenSignalOneGamma, *histPdfSignalOneGamma, plotsfile, "cSignalOneGamma", *B_plus_M, *misPT);
PlotShape(*dataSetSignalTwoGamma, *dataGenSignalTwoGamma, *histPdfSignalTwoGamma, plotsfile, "cSignalTwoGamma", *B_plus_M, *misPT);
PlotShape(*dataSetPartReco, *dataGenPartReco, *histPdfPartReco, plotsfile, "cPartReco", *B_plus_M, *misPT);
PlotShape(*dataSetComb, *dataGenComb, *combPDF, plotsfile, "cComb", *B_plus_M, *misPT);
if(nGenJpsiLeak>1) PlotShape(*dataSetJpsiLeak, *dataGenJpsiLeak, *histPdfJpsiLeak, plotsfile, "cJpsiLeak", *B_plus_M, *misPT);
}
//***************Merge datasets
RooDataSet* dataGenTot(dataGenPartReco);
dataGenTot->append(*dataGenSignalZeroGamma);
dataGenTot->append(*dataGenSignalOneGamma);
dataGenTot->append(*dataGenSignalTwoGamma);
dataGenTot->append(*dataGenComb);
if(nGenJpsiLeak>0) dataGenTot->append(*dataGenJpsiLeak);
//**************Prepare fitting function
RooRealVar nSignal("nSignal", "#signal events", 1.*nGenSignal, nGenSignal-7*sqrt(nGenSignal), nGenSignal+7*sqrt(nGenSignal));
RooRealVar nPartReco("nPartReco", "#nPartReco", 1.*nGenPartReco, nGenPartReco-7*sqrt(nGenPartReco), nGenPartReco+7*sqrt(nGenPartReco));
RooRealVar nComb("nComb", "#nComb", 1.*nGenComb, nGenComb-7*sqrt(nGenComb), nGenComb+7*sqrt(nGenComb));
RooRealVar nJpsiLeak("nJpsiLeak", "#nJpsiLeak", 1.*nGenJpsiLeak, nGenJpsiLeak-7*sqrt(nGenJpsiLeak), nGenJpsiLeak+7*sqrt(nGenJpsiLeak));
RooRealVar fracZero("fracZero", "fracZero",0.5,0,1);
RooRealVar fracOne("fracOne", "fracOne",0.5, 0,1);
RooFormulaVar fracPartReco("fracPartReco", "nPartReco/nSignal", RooArgList(nPartReco,nSignal));
RooFormulaVar fracOneRec("fracOneRec", "(1-fracZero)*fracOne", RooArgList(fracZero, fracOne));
RooAddPdf histPdfSignal("histPdfSignal", "histPdfSignal", RooArgList(*histPdfSignalZeroGamma, *histPdfSignalOneGamma, *histPdfSignalTwoGamma), RooArgList(fracZero, fracOneRec));
RooArgList pdfList(histPdfSignal, *histPdfPartReco, *combPDF);
RooArgList yieldList(nSignal, nPartReco, nComb);
if(nGenJpsiLeak>0)
{
pdfList.add(*histPdfJpsiLeak);
yieldList.add(nJpsiLeak);
}
RooAddPdf totPdf("totPdf", "totPdf", pdfList, yieldList);
//**************** Constrain the fraction of zero and one photon
int nGenSignalZeroGamma(floor(nGenFracZeroGamma*nGenSignal));
int nGenSignalOneGamma(floor(nGenFracOneGamma*nGenSignal));
int nGenSignalTwoGamma(floor(nGenSignal-nGenSignalZeroGamma-nGenSignalOneGamma));
RooRealVar fracZeroConstMean("fracZeroConstMean", "fracZeroConstMean", nGenSignalZeroGamma*1./nGenSignal);
RooRealVar fracZeroConstSigma("fracZeroConstSigma", "fracZeroConstSigma", sqrt(nGenSignalZeroGamma)/nGenSignal);
RooGaussian fracZeroConst("fracZeroConst", "fracZeroConst", fracZero, fracZeroConstMean, fracZeroConstSigma);
RooRealVar fracOneConstMean("fracOneConstMean", "fracOneConstMean", nGenSignalOneGamma*1./nGenSignal/(1-fracZeroConstMean.getVal()));
RooRealVar fracOneConstSigma("fracOneConstSigma", "fracOneConstSigma", sqrt(nGenSignalOneGamma)/nGenSignal/(1-fracZeroConstMean.getVal()));
RooGaussian fracOneConst("fracOneConst", "fracOneConst", fracOne, fracOneConstMean, fracOneConstSigma);
RooRealVar fracPartRecoMean("fracPartRecoMean", "fracPartRecoMean", nGenPartReco/(1.*nGenSignal));
RooRealVar fracPartRecoSigma("fracPartRecoSigma", "fracPartRecoSigma", fracPartReco_const*fracPartRecoMean.getVal());
RooGaussian fracPartRecoConst("fracPartRecoConst", "fracPartRecoConst", fracPartReco, fracPartRecoMean, fracPartRecoSigma);
RooRealVar JpsiLeakMean("JpsiLeakMean", "JpsiLeakMean", nGenJpsiLeak);
RooRealVar JpsiLeakSigma("JpsiLeakSigma", "JpsiLeakSigma", nGenJpsiLeak*fractionalErrorJpsiLeak->getVal());
RooGaussian JpsiLeakConst("JpsiLeakConst", "JpsiLeakConst", nJpsiLeak, JpsiLeakMean, JpsiLeakSigma);
//Extra TEST CONSTRAINT
//RooRealVar combConstMean("combConstMean", "combConstMean", nGenComb);
//RooRealVar combConstSigma("combConstSigma", "combConstSigma", 7.7);
//RooGaussian combConst("combConst", "combConst", nComb, combConstMean, combConstSigma);
//**************** fit
RooAbsReal::defaultIntegratorConfig()->setEpsAbs(1e-8) ;
RooAbsReal::defaultIntegratorConfig()->setEpsRel(1e-8) ;
RooArgSet *par_set = totPdf.getParameters(dataGenTot);
initiateParams(nGenSignalZeroGamma, nGenSignalOneGamma, nGenSignalTwoGamma,
*trueExp, nSignal, nPartReco, nComb, fracZero, fracOne, *expoConst, nJpsiLeak, constPartReco, fracPartRecoSigma);
RooArgSet constraints(fracZeroConst, fracOneConst);
if (constPartReco) constraints.add(fracPartRecoConst);
if(nGenJpsiLeak>0) constraints.add(JpsiLeakConst);
RooAbsReal* nll = totPdf.createNLL(*dataGenTot, Extended(), ExternalConstraints(constraints));
RooMinuit minuit(*nll);
minuit.setStrategy(2);
int migradRes(1);
int hesseRes(4);
vector<int> migradResVec;
vector<int> hesseResVec;
double edm(10);
int nrefit(0);
RooFitResult* fitRes(0);
vector<RooFitResult*> fitResVec;
bool hasConverged(false);
for(int i(0); (i<10) && !hasConverged ; ++i)
{
initiateParams(nGenSignalZeroGamma, nGenSignalOneGamma, nGenSignalTwoGamma,
*trueExp, nSignal, nPartReco, nComb, fracZero, fracOne, *expoConst, nJpsiLeak, constPartReco, fracPartRecoSigma);
cout<<"FITTING: starting with nsignal = "<<nSignal.getValV()<<" refit nbr. "<<i<<endl;
//if(fitRes != NULL && fitRes != 0) delete fitRes;
migradRes = minuit.migrad();
hesseRes = minuit.hesse();
fitRes = minuit.save();
edm = fitRes->edm();
fitResVec.push_back(fitRes);
migradResVec.push_back(migradRes);
hesseResVec.push_back(hesseRes);
if( migradRes == 0 && hesseRes == 0 && edm < 1e-4 ) hasConverged = true;
++nrefit;
cout<<"Fitting nbr "<<i<<" done. Hesse: "<<hesseRes<<" migrad: "<<migradRes<<" edm: "<<edm<<" minNll: "<<fitRes->minNll()<<endl;
}
if(!hasConverged)
{
double minNll(1e20);
int minIndex(-1);
for(unsigned int i(0); i<fitResVec.size(); ++i)
{
if( fitResVec.at(i)->minNll() < minNll)
{
minIndex = i;
minNll = fitResVec[i]->minNll();
}
}
migradRes = migradResVec.at(minIndex);
hesseRes = hesseResVec.at(minIndex);
cout<<"Fit not converged, choose fit "<<minIndex<<". Hesse: "<<hesseRes<<" migrad: "<<migradRes<<" edm: "<<edm<<" minNll: "<<fitRes->minNll()<<endl;
}
fillTreeResult(t, fitRes, update, migradRes, hesseRes, hasConverged);
for(unsigned int i(0); i<fitResVec.size(); ++i) delete fitResVec.at(i);
//totPdf.fitTo(*dataGenTot, Extended(), Save(), Warnings(false));
//*************** output fit status
int w(12);
out<<setw(w)<<migradRes<<setw(w)<<hesseRes<<setw(w)<<edm<<setw(w)<<nrefit<<endl;
if(wantplot) plot_fit_result(plotsfile, totPdf, *dataGenTot);
fw.Close();
//delete and return
delete nll;
delete par_set;
delete workspace;
delete workspaceGen;
delete combPDF;
}
int main (int argc, char **argv)
{
const char* chInFile = "ws.root";
const char* chOutFile = "ws_gen.root";
int numSignal = 10000;
int numBkg = 100000;
char option_char;
while ( (option_char = getopt(argc,argv, "i:o:s:b:")) != EOF )
switch (option_char)
{
case 'i': chInFile = optarg; break;
case 'o': chOutFile = optarg; break;
case 's': numSignal = atoi(optarg); break;
case 'b': numBkg = atoi(optarg); break;
case '?': fprintf (stderr,
"usage: %s [i<input file> o<output file>]\n", argv[0]);
}
cout << "In File = " << chInFile << endl;
cout << "Out File = " << chOutFile << endl;
cout << "Signal Events = " << numSignal << endl;
cout << "Bkg Events = " << numBkg << endl;
TFile inFile(chInFile,"READ");
RooWorkspace* ws = (RooWorkspace*) inFile.Get("rws");
TFile outFile(chOutFile,"RECREATE");
/*
ws->var("tau")->setVal(1.417);
ws->var("DG")->setVal(0.151);
ws->var("beta")->setVal(0.25);
ws->var("A02")->setVal(0.553);
ws->var("A1")->setVal(0.487);
ws->var("delta_l")->setVal(3.15);
ws->var("fs")->setVal(0.147);
*/
// ws->var("delta_l")->setConstant(kTRUE);
// ws->var("delta_p")->setConstant(kTRUE);
// ws->var("Dm")->setConstant(kTRUE);
//*ws->var("xs") = numSignal/(numSignal+numBkg);
// int numSignal = numEvents * ws->var("xs")->getVal();
// int numBkg = numEvents - numSignal;
ws->factory("Gaussian::dilutionGauss(d,0,0.276)");
//ws->factory("SUM::dSignalPDF(xds[0.109]*dilutionGauss,TruthModel(d))");
//ws->factory("SUM::dBkgPDF(xdb[0.109]*dilutionGauss,TruthModel(d))");
ws->factory("SUM::dSignalPDF(xds[1]*dilutionGauss,TruthModel(d))");
ws->factory("SUM::dBkgPDF(xdb[1]*dilutionGauss,TruthModel(d))");
/*
ws->factory("GaussModel::xetGaussianS(et,meanGaussEtS,sigmaGaussEtS)");
ws->factory("Decay::xerrorSignal(et,tauEtS,xetGaussianS,SingleSided]");
ws->factory("PROD::xsignalTimeAngle(timeAngle|et,xerrorSignal");
ws->factory("PROD::xsignal(massSignal,xsignalTimeAngle,DmConstraint)");
*/
RooDataSet* dSignalData = ws->pdf("dSignalPDF")->generate(RooArgSet(*ws->var("d")),numSignal);
RooDataSet *dataSignal = ws->pdf("signal")->generate(RooArgSet(*ws->var("m"),*ws->var("t"),*ws->var("et"),*ws->var("cpsi"),*ws->var("ctheta"),*ws->var("phi")), RooFit::ProtoData(*dSignalData));
ws->factory("GaussModel::xetGaussianPR(et,meanGaussEtPR,sigmaGaussEtPR)");
ws->factory("Decay::xerrBkgPR(et,tauEtPR,xetGaussianPR,SingleSided]");
ws->factory("GaussModel::xetGaussianNP(et,meanGaussEtNP,sigmaGaussEtNP)");
ws->factory("Decay::xerrBkgNP(et,tauEtNP,xetGaussianNP,SingleSided]");
/* Time */
ws->factory("GaussModel::xresolution(t,0,scale,et)");
ws->factory("Decay::xnegativeDecay(t,tauNeg,xresolution,Flipped)");
ws->factory("Decay::xpositiveDecay(t,tauPos,xresolution,SingleSided)");
ws->factory("Decay::xpositiveLongDecay(t,tauLngPos,xresolution,SingleSided)");
ws->factory("RSUM::xtBkgNP(xn*xnegativeDecay,xp*xpositiveDecay,xpositiveLongDecay");
/* Promt and Non-Prompt */
ws->factory("PROD::xtimeBkgNP(xtBkgNP|et,xerrBkgNP)");
ws->factory("PROD::xtimeBkgPR(xresolution|et,xerrBkgPR)");
ws->factory("PROD::xPrompt(massBkgPR,xtimeBkgPR,anglePR)");
ws->factory("PROD::xNonPrompt(massBkgNP,xtimeBkgNP,angleNP)");
ws->factory("SUM::xbackground(xprompt*xPrompt,xNonPrompt)");
RooDataSet* dBkgData = ws->pdf("dBkgPDF")->generate(RooArgSet(*ws->var("d")),numBkg);
RooDataSet* dataBkg = ws->pdf("xbackground")->generate(RooArgSet(*ws->var("m"),*ws->var("t"),*ws->var("et"),*ws->var("cpsi"),*ws->var("ctheta"),*ws->var("phi")), numBkg);
dataBkg->merge(dBkgData);
dataSignal->SetName("dataGenSignal");
dataBkg->SetName("dataGenBkg");
ws->import(*dataSignal);
ws->import(*dataBkg);
////ws->import(*dataBkg,RooFit::Rename("dataGenBkg"));
dataSignal->append(*dataBkg);
dataSignal->SetName("dataGen");
ws->import(*dataSignal);
//RooFitResult *fit_result = ws->pdf("model")->fitTo(*ws->data("data"), RooFit::Save(kTRUE), RooFit::ConditionalObservables(*ws->var("d")), RooFit::NumCPU(2), RooFit::PrintLevel(3));
/*
gROOT->SetStyle("Plain");
TCanvas canvas("canvas", "canvas", 400,400);
RooPlot *m_frame = ws->var("t")->frame();
dataSignal->plotOn(m_frame, RooFit::MarkerSize(0.3));
m_frame->Draw();
canvas.SaveAs("m_toy_plot.png");
*/
/*
gROOT->SetStyle("Plain");
TCanvas canvas("canvas", "canvas", 800,400);
canvas.Divide(2);
canvas.cd(1);
RooPlot *t_frame = ws->var("t")->frame();
ws->data("data")->plotOn(t_frame, RooFit::MarkerSize(0.3));
gPad->SetLogy(1);
t_frame->Draw();
canvas.cd(2);
RooPlot *et_frame = ws->var("et")->frame();
ws->data("data")->plotOn(et_frame,RooFit::MarkerSize(0.2));
ws->pdf("errorSignal")->plotOn(et_frame);
gPad->SetLogy(1);
et_frame->Draw();
canvas.SaveAs("t.png");
canvas.cd(2);
gPad->SetLogy(0);
RooPlot *cpsi_frame = ws.var("cpsi")->frame();
data->plotOn(cpsi_frame,RooFit::MarkerSize(0.2), RooFit::Rescale(1));
data2->plotOn(cpsi_frame,
RooFit::LineColor(kBlue), RooFit::DrawOption("L"));
cpsi_frame->Draw();
canvas.cd(3);
RooPlot *ctheta_frame = ws.var("ctheta")->frame();
data->plotOn(ctheta_frame,RooFit::MarkerSize(0.2), RooFit::Rescale(1));
data2->plotOn(ctheta_frame,
RooFit::LineColor(kBlue), RooFit::DrawOption("L"));
ctheta_frame->Draw();
canvas.cd(4);
RooPlot *phi_frame = ws.var("phi")->frame();
data->plotOn(phi_frame,RooFit::MarkerSize(0.2), RooFit::Rescale(1));
data2->plotOn(phi_frame,
RooFit::LineColor(kBlue), RooFit::DrawOption("L"));
phi_frame->Draw();
canvas.SaveAs("t.png");
*/
ws->data("dataGen")->Print();
ws->data("dataGenSignal")->Print();
ws->data("dataGenBkg")->Print();
ws->Write("rws");
outFile.Close();
inFile.Close();
}
void StandardProfileInspectorDemo(const char* infile = "",
const char* workspaceName = "combined",
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData"){
/////////////////////////////////////////////////////////////
// First part is just to access a user-defined file
// or create the standard example file if it doesn't exist
////////////////////////////////////////////////////////////
const char* filename = "";
if (!strcmp(infile,""))
filename = "results/example_combined_GaussExample_model.root";
else
filename = infile;
// Check if example input file exists
TFile *file = TFile::Open(filename);
// if input file was specified byt not found, quit
if(!file && strcmp(infile,"")){
cout <<"file not found" << endl;
return;
}
// if default file not found, try to create it
if(!file ){
// Normally this would be run on the command line
cout <<"will run standard hist2workspace example"<<endl;
gROOT->ProcessLine(".! prepareHistFactory .");
gROOT->ProcessLine(".! hist2workspace config/example.xml");
cout <<"\n\n---------------------"<<endl;
cout <<"Done creating example input"<<endl;
cout <<"---------------------\n\n"<<endl;
}
// now try to access the file again
file = TFile::Open(filename);
if(!file){
// if it is still not there, then we can't continue
cout << "Not able to run hist2workspace to create example input" <<endl;
return;
}
/////////////////////////////////////////////////////////////
// Tutorial starts here
////////////////////////////////////////////////////////////
// get the workspace out of the file
RooWorkspace* w = (RooWorkspace*) file->Get(workspaceName);
if(!w){
cout <<"workspace not found" << endl;
return;
}
// get the modelConfig out of the file
ModelConfig* mc = (ModelConfig*) w->obj(modelConfigName);
// get the modelConfig out of the file
RooAbsData* data = w->data(dataName);
// make sure ingredients are found
if(!data || !mc){
w->Print();
cout << "data or ModelConfig was not found" <<endl;
return;
}
//////////////////////////////////////////////
// now use the profile inspector
ProfileInspector p;
TList* list = p.GetListOfProfilePlots(*data,mc);
// now make plots
TCanvas* c1 = new TCanvas("c1","ProfileInspectorDemo"); //,800,200);
c1->Divide(4,4);
// const RooArgSet* nuis_params = mc->GetNuisanceParameters();
for(int i=0; i<list->GetSize(); ++i){
c1->cd(i+1);
//RooRealVar* nuis = (RooRealVar*) nuis_params->At(i);
TGraph* graph = (TGraph*) list->At(i);
std::string y_title = graph->GetYaxis()->GetTitle();
y_title = "Profiled value of: " + y_title;
graph->GetYaxis()->SetTitle(y_title.c_str());
graph->GetYaxis()->SetTitleSize(0.05);
graph->GetYaxis()->SetTitleOffset(0.8);
//std::string poi_name = graph->GetXaxis()->GetTitle();
//graph->GetYaxis()->SetTitle(var->GetName());
graph->GetXaxis()->SetTitleSize(0.05);
graph->GetXaxis()->SetTitleOffset(0.8);
graph->Draw("al");
//list->At(i)->Draw("al");
}
c1->Print("ProfileInspector.eps");
c1->Print("ProfileInspector.pdf");
cout << endl;
}
void FitterUtilsSimultaneousExpOfPolyTimesX::generate(bool wantPlots, string plotsfile)
{
FitterUtilsExpOfPolyTimesX::generate(wantPlots, plotsfile);
TFile fw(workspacename.c_str(), "UPDATE");
RooWorkspace* workspace = (RooWorkspace*)fw.Get("workspace");
RooRealVar *B_plus_M = workspace->var("B_plus_M");
RooRealVar *misPT = workspace->var("misPT");
RooDataSet* dataSetCombExt = (RooDataSet*)workspace->data("dataSetCombExt");
RooDataSet* dataSetComb = (RooDataSet*)workspace->data("dataSetComb");
// RooRealVar *l1KeeGen = workspace->var("l1KeeGen");
// RooRealVar *l2KeeGen = workspace->var("l2KeeGen");
// RooRealVar *l3KeeGen = workspace->var("l3KeeGen");
// RooRealVar *l4KeeGen = workspace->var("l4KeeGen");
// RooRealVar *l5KeeGen = workspace->var("l5KeeGen");
//
//
// RooExpOfPolyTimesX kemuPDF("kemuPDF", "kemuPDF", *B_plus_M, *misPT, *l1KeeGen, *l2KeeGen, *l3KeeGen, *l4KeeGen, *l5KeeGen);
//
// RooAbsPdf::GenSpec* GenSpecKemu = kemuPDF.prepareMultiGen(RooArgSet(*B_plus_M, *misPT), RooFit::Extended(1), NumEvents(nGenKemu));
//
// cout<<"Generating Kemu"<<endl;
// RooDataSet* dataGenKemu = kemuPDF.generate(*GenSpecKemu);//(argset, 100, false, true, "", false, true);
// dataGenKemu->SetName("dataGenKemu"); dataGenKemu->SetTitle("dataGenKemu");
//
//
// RooWorkspace* workspaceGen = (RooWorkspace*)fw.Get("workspaceGen");
// workspaceGen->import(*dataGenKemu);
//
// workspaceGen->Write("", TObject::kOverwrite);
// fw.Close();
// delete dataGenKemu;
// delete GenSpecKemu;
TVectorD rho(2);
rho[0] = 2.5;
rho[1] = 1.5;
misPT->setRange(-2000, 5000);
RooNDKeysPdf kemuPDF("kemuPDF", "kemuPDF", RooArgList(*B_plus_M, *misPT), *dataSetCombExt, rho, "ma",3, true);
misPT->setRange(0, 5000);
RooAbsPdf::GenSpec* GenSpecKemu = kemuPDF.prepareMultiGen(RooArgSet(*B_plus_M, *misPT), RooFit::Extended(1), NumEvents(nGenKemu));
cout<<"Generating Kemu"<<endl;
RooDataSet* dataGenKemu = kemuPDF.generate(*GenSpecKemu);//(argset, 100, false, true, "", false, true);
dataGenKemu->SetName("dataGenKemu"); dataGenKemu->SetTitle("dataGenKemu");
RooWorkspace* workspaceGen = (RooWorkspace*)fw.Get("workspaceGen");
workspaceGen->import(*dataGenKemu);
if(wantPlots) PlotShape(*dataSetComb, *dataGenKemu, kemuPDF, plotsfile, "cKemuKeys", *B_plus_M, *misPT);
fw.cd();
workspaceGen->Write("", TObject::kOverwrite);
fw.Close();
delete dataGenKemu;
delete GenSpecKemu;
}
void splitws(string inFolderName, double mass, string channel) {
cout << "Splitting workspace in " << channel << endl;
int flatInterpCode = 4;
int shapeInterpCode = 4;
bool do2011 = 0;
if (inFolderName.find("2011") != string::npos) do2011 = 1;
bool conditionalAsimov = 0;
bool doData = 1;
//if (inFolderName.find("_blind_") != string::npos) {
//conditionalAsimov = 0;
//}
//else {
//conditionalAsimov = 1;
//}
set<string> channelNames;
if (channel == "01j") {
channelNames.insert("em_signalLike1_0j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike2_0j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike1_0j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike2_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_AfrecSR_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_ASR_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_AfrecSR_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_ASR_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CfrecZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CfrecZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike1_1j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike2_1j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike1_1j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike2_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_AfrecSR_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_ASR_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_AfrecSR_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_ASR_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CfrecZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CfrecZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":""));
}
else if (channel == "0j") {
channelNames.insert("em_signalLike1_0j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike2_0j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike1_0j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike2_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_AfrecSR_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_ASR_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_AfrecSR_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_ASR_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CfrecZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CfrecZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":""));
}
else if (channel == "1j") {
channelNames.insert("em_signalLike1_1j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike2_1j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike1_1j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike2_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_AfrecSR_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_ASR_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_AfrecSR_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_ASR_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CfrecZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CfrecZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":""));
}
else if (channel == "OF01j") {
channelNames.insert("em_signalLike1_0j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike2_0j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike1_0j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike2_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_sscr_0j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike1_1j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike2_1j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike1_1j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike2_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_sscr_1j"+string(!do2011?"_2012":""));
}
else if (channel == "OF0j") {
channelNames.insert("em_signalLike1_0j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike2_0j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike1_0j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike2_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_sscr_0j"+string(!do2011?"_2012":""));
}
else if (channel == "OF1j") {
channelNames.insert("em_signalLike1_1j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike2_1j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike1_1j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike2_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_sscr_1j"+string(!do2011?"_2012":""));
}
else if (channel == "SF01j") {
channelNames.insert("SF_AfrecSR_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_ASR_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_AfrecSR_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_ASR_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CfrecZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CfrecZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_AfrecSR_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_ASR_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_AfrecSR_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_ASR_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CfrecZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CfrecZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":""));
}
else if (channel == "SF0j") {
channelNames.insert("SF_AfrecSR_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_ASR_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_AfrecSR_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_ASR_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CfrecZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CfrecZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":""));
}
else if (channel == "SF1j") {
channelNames.insert("SF_AfrecSR_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_ASR_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_AfrecSR_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_ASR_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CfrecZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CfrecZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":""));
}
else if (channel == "2j") {
channelNames.insert("em_signalLike1_2j"+string(!do2011?"_2012":""));
channelNames.insert("ee_signalLike1_2j"+string(!do2011?"_2012":""));
channelNames.insert("SF_topbox_2j"+string(!do2011?"_2012":""));
}
else if (channel == "OF2j") {
channelNames.insert("em_signalLike1_2j"+string(!do2011?"_2012":""));
channelNames.insert("SF_topbox_2j"+string(!do2011?"_2012":""));
}
else if (channel == "SF2j") {
channelNames.insert("ee_signalLike1_2j"+string(!do2011?"_2012":""));
channelNames.insert("SF_topbox_2j"+string(!do2011?"_2012":""));
}
else if (channel == "OF") {
channelNames.insert("em_signalLike1_0j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike2_0j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike1_0j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike2_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike1_1j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike2_1j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike1_1j"+string(!do2011?"_2012":""));
channelNames.insert("me_signalLike2_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":""));
channelNames.insert("em_signalLike1_2j"+string(!do2011?"_2012":""));
channelNames.insert("SF_topbox_2j"+string(!do2011?"_2012":""));
}
else if (channel == "SF") {
channelNames.insert("SF_AfrecSR_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_ASR_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_AfrecSR_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_ASR_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CfrecZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CfrecZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CZpeak_0j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":""));
channelNames.insert("SF_AfrecSR_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_ASR_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_AfrecSR_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_ASR_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CfrecZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("SF_CZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CfrecZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_CZpeak_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":""));
channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":""));
channelNames.insert("ee_signalLike1_2j"+string(!do2011?"_2012":""));
channelNames.insert("SF_topbox_2j"+string(!do2011?"_2012":""));
}
else {
cout << "Channel " << channel << " not defined. Please check!" << endl;
exit(1);
}
// bool fix = 1;
stringstream inFileName;
inFileName << "workspaces/" << inFolderName << "/" << mass << ".root";
TFile f(inFileName.str().c_str());
RooWorkspace* w = (RooWorkspace*)f.Get("combWS");
if (!w) w = (RooWorkspace*)f.Get("combined");
RooDataSet* data = (RooDataSet*)w->data("combData");
if (!data) data = (RooDataSet*)w->data("obsData");
ModelConfig* mc = (ModelConfig*)w->obj("ModelConfig");
RooRealVar* weightVar = w->var("weightVar");
RooRealVar* mu = (RooRealVar*)mc->GetParametersOfInterest()->first();
if (!mu) mu = w->var("SigXsecOverSM");
const RooArgSet* mc_obs = mc->GetObservables();
const RooArgSet* mc_nuis = mc->GetNuisanceParameters();
const RooArgSet* mc_globs = mc->GetGlobalObservables();
const RooArgSet* mc_poi = mc->GetParametersOfInterest();
RooArgSet nuis = *mc_nuis;
RooArgSet antiNuis = *mc_nuis;
RooArgSet globs = *mc_globs;
RooArgSet antiGlobs = *mc_globs;
RooArgSet allParams;
RooSimultaneous* simPdf = (RooSimultaneous*)mc->GetPdf();
RooCategory* cat = (RooCategory*)&simPdf->indexCat();
RooArgSet nuis_tmp = nuis;
RooArgSet fullConstraints = *simPdf->getAllConstraints(*mc_obs,nuis_tmp,false);
vector<string> foundChannels;
vector<string> skippedChannels;
cout << "Getting constraints" << endl;
map<string, RooDataSet*> data_map;
map<string, RooAbsPdf*> pdf_map;
RooCategory* decCat = new RooCategory("dec_channel","dec_channel");
// int i = 0;
TIterator* catItr = cat->typeIterator();
RooCatType* type;
RooArgSet allConstraints;
while ((type = (RooCatType*)catItr->Next())) {
RooAbsPdf* pdf = simPdf->getPdf(type->GetName());
string typeName(type->GetName());
if (channelNames.size() && channelNames.find(typeName) == channelNames.end()) {
skippedChannels.push_back(typeName);
continue;
}
cout << "On channel " << type->GetName() << endl;
foundChannels.push_back(typeName);
decCat->defineType(type->GetName());
// pdf->getParameters(*data)->Print("v");
RooArgSet nuis_tmp1 = nuis;
RooArgSet nuis_tmp2 = nuis;
RooArgSet* constraints = pdf->getAllConstraints(*mc_obs, nuis_tmp1, true);
constraints->Print();
allConstraints.add(*constraints);
}
catItr->Reset();
while ((type = (RooCatType*)catItr->Next())) {
RooAbsPdf* pdf = simPdf->getPdf(type->GetName());
string typeName(type->GetName());
cout << "Considering type " << typeName << endl;
if (channelNames.size() && channelNames.find(typeName) == channelNames.end()) continue;
cout << "On channel " << type->GetName() << endl;
RooArgSet nuis_tmp1 = nuis;
RooArgSet nuis_tmp2 = nuis;
RooArgSet* constraints = pdf->getAllConstraints(*mc_obs, nuis_tmp1, true);
cout << "Adding pdf to map: " << typeName << " = " << pdf->GetName() << endl;
pdf_map[typeName] = pdf;
RooProdPdf prod("prod","prod",*constraints);
RooArgSet* params = pdf->getParameters(*data);
antiNuis.remove(*params);
antiGlobs.remove(*params);
allParams.add(*params);
// cout << type->GetName() << endl;
}
// return;
RooArgSet decNuis;
TIterator* nuiItr = mc_nuis->createIterator();
TIterator* parItr = allParams.createIterator();
RooAbsArg* nui, *par;
while ((par = (RooAbsArg*)parItr->Next())) {
nuiItr->Reset();
while ((nui = (RooAbsArg*)nuiItr->Next())) {
if (par == nui) decNuis.add(*nui);
}
}
RooArgSet decGlobs;
TIterator* globItr = mc_globs->createIterator();
parItr->Reset();
RooAbsArg* glob;
while ((par = (RooAbsArg*)parItr->Next())) {
globItr->Reset();
while ((glob = (RooAbsArg*)globItr->Next())) {
if (par == glob) decGlobs.add(*glob);
}
}
// antiNuis.Print();
// nuis.Print();
// globs.Print();
// i = 0;
TList* datalist = data->split(*cat, true);
TIterator* dataItr = datalist->MakeIterator();
RooAbsData* ds;
while ((ds = (RooAbsData*)dataItr->Next())) {
string typeName(ds->GetName());
if (channelNames.size() && channelNames.find(typeName) == channelNames.end()) continue;
cout << "Adding dataset to map: " << ds->GetName() << endl;
data_map[string(ds->GetName())] = (RooDataSet*)ds;
cout << ds->GetName() << endl;
}
RooSimultaneous* decPdf = new RooSimultaneous("decPdf","decPdf",pdf_map,*decCat);
RooArgSet decObs = *decPdf->getObservables(data);
// decObs.add(*(RooAbsArg*)weightVar);
decObs.add(*(RooAbsArg*)decCat);
decObs.Print();
nuis.remove(antiNuis);
globs.remove(antiGlobs);
// nuis.Print("v");
RooDataSet* decData = new RooDataSet("obsData","obsData",RooArgSet(decObs,*(RooAbsArg*)weightVar),Index(*decCat),Import(data_map),WeightVar(*weightVar));
decData->Print();
RooArgSet poi(*(RooAbsArg*)mu);
RooWorkspace decWS("combined");
ModelConfig decMC("ModelConfig",&decWS);
decMC.SetPdf(*decPdf);
decMC.SetObservables(decObs);
decMC.SetNuisanceParameters(decNuis);
decMC.SetGlobalObservables(decGlobs);
decMC.SetParametersOfInterest(poi);
decMC.Print();
decWS.import(*decPdf);
decWS.import(decMC);
decWS.import(*decData);
// decWS.Print();
ModelConfig* mcInWs = (ModelConfig*)decWS.obj("ModelConfig");
decPdf = (RooSimultaneous*)mcInWs->GetPdf();
// setup(mcInWs);
// return;
mcInWs->GetNuisanceParameters()->Print("v");
mcInWs->GetGlobalObservables()->Print("v");
// decData->tree()->Scan("*");
// Make asimov data
RooArgSet funcs = decWS.allFunctions();
TIterator* it = funcs.createIterator();
TObject* tempObj = 0;
while((tempObj=it->Next()))
{
FlexibleInterpVar* flex = dynamic_cast<FlexibleInterpVar*>(tempObj);
if(flex) {
flex->setAllInterpCodes(flatInterpCode);
}
PiecewiseInterpolation* piece = dynamic_cast<PiecewiseInterpolation*>(tempObj);
if(piece) {
piece->setAllInterpCodes(shapeInterpCode);
}
}
RooDataSet* dataInWs = (RooDataSet*)decWS.data("obsData");
makeAsimovData(mcInWs, conditionalAsimov && doData, &decWS, mcInWs->GetPdf(), dataInWs, 0);
makeAsimovData(mcInWs, conditionalAsimov && doData, &decWS, mcInWs->GetPdf(), dataInWs, 1);
makeAsimovData(mcInWs, conditionalAsimov && doData, &decWS, mcInWs->GetPdf(), dataInWs, 2);
system(("mkdir -vp workspaces/"+inFolderName+"_"+channel).c_str());
stringstream outFileName;
outFileName << "workspaces/" << inFolderName << "_" << channel << "/" << mass << ".root";
cout << "Exporting" << endl;
decWS.writeToFile(outFileName.str().c_str());
cout << "\nIncluded the following channels: " << endl;
for (int i=0;i<(int)foundChannels.size();i++) {
cout << "-> " << foundChannels[i] << endl;
}
cout << "\nSkipping the following channels: " << endl;
for (int i=0;i<(int)skippedChannels.size();i++) {
cout << "-> " << skippedChannels[i] << endl;
}
cout << "Done" << endl;
// decPdf->fitTo(*decData, Hesse(0), Minos(0), PrintLevel(0));
}
void compute_p0(const char* inFileName,
const char* wsName = "combined",
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData",
const char* asimov1DataName = "asimovData_1",
const char* conditional1Snapshot = "conditionalGlobs_1",
const char* nominalSnapshot = "nominalGlobs",
string smass = "130",
string folder = "test")
{
double mass;
stringstream massStr;
massStr << smass;
massStr >> mass;
double mu_profile_value = 1; // mu value to profile the obs data at wbefore generating the expected
bool doConditional = 1; // do conditional expected data
bool remakeData = 0; // handle unphysical pdf cases in H->ZZ->4l
bool doUncap = 1; // uncap p0
bool doInj = 0; // setup the poi for injection study (zero is faster if you're not)
bool doObs = 1; // compute median significance
bool doMedian = 1; // compute observed significance
TStopwatch timer;
timer.Start();
TFile f(inFileName);
RooWorkspace* ws = (RooWorkspace*)f.Get(wsName);
if (!ws)
{
cout << "ERROR::Workspace: " << wsName << " doesn't exist!" << endl;
return;
}
ModelConfig* mc = (ModelConfig*)ws->obj(modelConfigName);
if (!mc)
{
cout << "ERROR::ModelConfig: " << modelConfigName << " doesn't exist!" << endl;
return;
}
RooDataSet* data = (RooDataSet*)ws->data(dataName);
if (!data)
{
cout << "ERROR::Dataset: " << dataName << " doesn't exist!" << endl;
return;
}
mc->GetNuisanceParameters()->Print("v");
ROOT::Math::MinimizerOptions::SetDefaultMinimizer("Minuit2");
ROOT::Math::MinimizerOptions::SetDefaultStrategy(0);
ROOT::Math::MinimizerOptions::SetDefaultPrintLevel(1);
cout << "Setting max function calls" << endl;
ws->loadSnapshot("conditionalNuis_0");
RooArgSet nuis(*mc->GetNuisanceParameters());
RooRealVar* mu = (RooRealVar*)mc->GetParametersOfInterest()->first();
RooAbsPdf* pdf = mc->GetPdf();
string condSnapshot(conditional1Snapshot);
RooArgSet nuis_tmp2 = *mc->GetNuisanceParameters();
RooNLLVar* obs_nll = doObs ? (RooNLLVar*)pdf->createNLL(*data, Constrain(nuis_tmp2)) : NULL;
RooDataSet* asimovData1 = (RooDataSet*)ws->data(asimov1DataName);
RooRealVar* emb = (RooRealVar*)mc->GetNuisanceParameters()->find("ATLAS_EMB");
if (!asimovData1 || (string(inFileName).find("ic10") != string::npos && emb))
{
if (emb) emb->setVal(0.7);
cout << "Asimov data doesn't exist! Please, allow me to build one for you..." << endl;
string mu_str, mu_prof_str;
asimovData1 = makeAsimovData(mc, doConditional, ws, obs_nll, 1, &mu_str, &mu_prof_str, mu_profile_value, true);
condSnapshot="conditionalGlobs"+mu_prof_str;
}
if (!doUncap) mu->setRange(0, 40);
else mu->setRange(-40, 40);
RooAbsPdf* pdf = mc->GetPdf();
RooArgSet nuis_tmp1 = *mc->GetNuisanceParameters();
RooNLLVar* asimov_nll = (RooNLLVar*)pdf->createNLL(*asimovData1, Constrain(nuis_tmp1));
//do asimov
mu->setVal(1);
mu->setConstant(0);
if (!doInj) mu->setConstant(1);
int status,sign;
double med_sig=0,obs_sig=0,asimov_q0=0,obs_q0=0;
if (doMedian)
{
ws->loadSnapshot(condSnapshot.c_str());
if (doInj) ws->loadSnapshot("conditionalNuis_inj");
else ws->loadSnapshot("conditionalNuis_1");
mc->GetGlobalObservables()->Print("v");
mu->setVal(0);
mu->setConstant(1);
status = minimize(asimov_nll, ws);
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(asimov_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double asimov_nll_cond = asimov_nll->getVal();
mu->setVal(1);
if (doInj) ws->loadSnapshot("conditionalNuis_inj");
else ws->loadSnapshot("conditionalNuis_1");
if (doInj) mu->setConstant(0);
status = minimize(asimov_nll, ws);
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(asimov_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double asimov_nll_min = asimov_nll->getVal();
asimov_q0 = 2*(asimov_nll_cond - asimov_nll_min);
if (doUncap && mu->getVal() < 0) asimov_q0 = -asimov_q0;
sign = int(asimov_q0 != 0 ? asimov_q0/fabs(asimov_q0) : 0);
med_sig = sign*sqrt(fabs(asimov_q0));
ws->loadSnapshot(nominalSnapshot);
}
if (doObs)
{
ws->loadSnapshot("conditionalNuis_0");
mu->setVal(0);
mu->setConstant(1);
status = minimize(obs_nll, ws);
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(obs_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double obs_nll_cond = obs_nll->getVal();
mu->setConstant(0);
status = minimize(obs_nll, ws);
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(obs_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double obs_nll_min = obs_nll->getVal();
obs_q0 = 2*(obs_nll_cond - obs_nll_min);
if (doUncap && mu->getVal() < 0) obs_q0 = -obs_q0;
sign = int(obs_q0 == 0 ? 0 : obs_q0 / fabs(obs_q0));
if (!doUncap && (obs_q0 < 0 && obs_q0 > -0.1 || mu->getVal() < 0.001)) obs_sig = 0;
else obs_sig = sign*sqrt(fabs(obs_q0));
}
// Report results
cout << "obs: " << obs_sig << endl;
cout << "Observed significance: " << obs_sig << endl;
cout << "Corresponding to a p-value of " << (1-ROOT::Math::gaussian_cdf( obs_sig )) << endl;
if (med_sig)
{
cout << "Median test stat val: " << asimov_q0 << endl;
cout << "Median significance: " << med_sig << endl;
}
f.Close();
stringstream fileName;
fileName << "root-files/" << folder << "/" << mass << ".root";
system(("mkdir -vp root-files/" + folder).c_str());
TFile f2(fileName.str().c_str(),"recreate");
TH1D* h_hypo = new TH1D("hypo","hypo",2,0,2);
h_hypo->SetBinContent(1, obs_sig);
h_hypo->SetBinContent(2, med_sig);
f2.Write();
f2.Close();
timer.Stop();
timer.Print();
}
int DiagnosisMacro(int Nbins = 10, int Nsigma = 10, int CPUused = 1, TString Filename = "FIT_DATA_Psi2SJpsi_PPPrompt_Bkg_SecondOrderChebychev_pt65300_rap016_cent0200_262620_263757.root", TString Outputdir = "./")
//Nbins: Number of points for which to calculate profile likelihood. Time required is about (1/CPU) minutes per point per parameter. 0 means do plain likelihood only
//Nsigma: The range in which the scan is performed (value-Nsigma*sigma, value+Nsigma*sigma)
//CPUused: anything larger than 1 causes weird fit results on my laptop, runs fine on lxplus with more (16)
{
// R e a d w o r k s p a c e f r o m f i l e
// -----------------------------------------------
// Open input file with workspace
//Filename = "FIT_DATA_Psi2SJpsi_PP_Jpsi_DoubleCrystalBall_Psi2S_DoubleCrystalBall_Bkg_Chebychev2_pt6590_rap016_cent0200.root";
//Filename = "FIT_DATA_Psi2SJpsi_PbPb_Jpsi_DoubleCrystalBall_Psi2S_DoubleCrystalBall_Bkg_Chebychev1_pt6590_rap016_cent0200.root";
TFile *f = new TFile(Filename);
// Retrieve workspace from file
RooWorkspace* w = (RooWorkspace*)f->Get("workspace");
// Retrieve x,model and data from workspace
RooRealVar* x = w->var("invMass");
RooAbsPdf* model = w->pdf("simPdf_syst");
if (model == 0) {
model = w->pdf("simPdf");
}
if (model == 0) {
model = w->pdf("pdfMASS_Tot_PP");
}
if (model == 0) {
model = w->pdf("pdfMASS_Tot_PbPb");
}
if (model == 0) {
cout << "[ERROR] pdf failed to load from the workspace" << endl;
return false;
}
RooAbsData* data = w->data("dOS_DATA");
if (data == 0) {
data = w->data("dOS_DATA_PP");
}
if (data == 0) {
data = w->data("dOS_DATA_PbPb");
}
if (data == 0) {
cout << "[ERROR] data failed to load from the workspace" << endl;
return false;
}
// Print structure of composite p.d.f.
model->Print("t");
/*
// P l o t m o d e l
// ---------------------------------------------------------
// Plot data and PDF overlaid
RooPlot* xframe = x->frame(Title("J/psi Model and Data"));
data->plotOn(xframe);
model->plotOn(xframe);
// Draw the frame on the canvas
TCanvas* c2 = new TCanvas("PlotModel", "PlotModel", 1000, 1000);
gPad->SetLeftMargin(0.15);
xframe->GetYaxis()->SetTitleOffset(2.0);
xframe->Draw();//*/
///// Check parameters
RooArgSet* paramSet1 = model->getDependents(data);
paramSet1->Print("v"); // Just check
RooArgSet* paramSet2 = model->getParameters(data);
paramSet2->Print("v");
int Nparams = paramSet2->getSize();
cout << "Number of parameters: " << Nparams<<endl<<endl;
// C o n s t r u c t p l a i n l i k e l i h o o d
// ---------------------------------------------------
// Construct unbinned likelihood
RooAbsReal* nll = model->createNLL(*data, NumCPU(CPUused));
// Minimize likelihood w.r.t all parameters before making plots
RooMinuit(*nll).migrad();
//////////////////////////////////////////////////////
/////////////////// L O O P O V E R P A R A M E T E R S
/////////////////////////////////////////////////////
/// Set up loop over parameters
TString ParamName;
double ParamValue;
double ParamError;
double ParamLimitLow;
double ParamLimitHigh;
double FitRangeLow;
double FitRangeHigh;
RooRealVar* vParam;
int counter = 0;
// Loop start
TIterator* iter = paramSet2->createIterator();
TObject* var = iter->Next();
while (var != 0) {
counter++;
ParamName = var->GetName();
vParam = w->var(ParamName);
ParamValue = vParam->getVal();
ParamError = vParam->getError();
ParamLimitLow = vParam->getMin();
ParamLimitHigh = vParam->getMax();
cout << ParamName << " has value " << ParamValue << " with error: " << ParamError << " and limits: " << ParamLimitLow << " to " << ParamLimitHigh << endl << endl;
if (ParamError == 0) { //Skipping fixed parameters
cout << "Parameter was fixed, skipping its fitting" << endl;
cout << endl << "DONE WITH " << counter << " PARAMETER OUT OF " << Nparams << endl << endl;
var = iter->Next();
continue;
}
// determining fit range: Nsigma sigma on each side unless it would be outside of parameter limits
if ((ParamValue - Nsigma * ParamError) > ParamLimitLow) {
FitRangeLow = (ParamValue - Nsigma * ParamError);
}
else {
FitRangeLow = ParamLimitLow;
}
if ((ParamValue + Nsigma * ParamError) < ParamLimitHigh) {
FitRangeHigh = (ParamValue + Nsigma * ParamError);
}
else {
FitRangeHigh = ParamLimitHigh;
}
// P l o t p l a i n l i k e l i h o o d a n d C o n s t r u c t p r o f i l e l i k e l i h o o d
// ---------------------------------------------------
RooPlot* frame1;
RooAbsReal* pll=NULL;
if (Nbins != 0) {
frame1 = vParam->frame(Bins(Nbins), Range(FitRangeLow, FitRangeHigh), Title(TString::Format("LL and profileLL in %s", ParamName.Data())));
nll->plotOn(frame1, ShiftToZero());
pll = nll->createProfile(*vParam);
// Plot the profile likelihood
pll->plotOn(frame1, LineColor(kRed), RooFit::Precision(-1));
}
else { //Skip profile likelihood
frame1 = vParam->frame(Bins(10), Range(FitRangeLow, FitRangeHigh), Title(TString::Format("LL and profileLL in %s", ParamName.Data())));
nll->plotOn(frame1, ShiftToZero());
}
// D r a w a n d s a v e p l o t s
// -----------------------------------------------------------------------
// Adjust frame maximum for visual clarity
frame1->SetMinimum(0);
frame1->SetMaximum(20);
TCanvas* c = new TCanvas("CLikelihoodResult", "CLikelihoodResult", 800, 600);
c->cd(1);
gPad->SetLeftMargin(0.15);
frame1->GetYaxis()->SetTitleOffset(1.4);
frame1->Draw();
TLegend* leg = new TLegend(0.70, 0.70, 0.95, 0.88, "");
leg->SetFillColor(kWhite);
leg->SetBorderSize(0);
leg->SetTextSize(0.035);
TLegendEntry *le1 = leg->AddEntry(nll, "Plain likelihood", "l");
le1->SetLineColor(kBlue);
le1->SetLineWidth(3);
TLegendEntry *le2 = leg->AddEntry(pll, "Profile likelihood", "l");
le2->SetLineColor(kRed);
le2->SetLineWidth(3);
leg->Draw("same");
//Save plot
TString StrippedName = TString(Filename(Filename.Last('/')+1,Filename.Length()));
StrippedName = StrippedName.ReplaceAll(".root","");
cout << StrippedName << endl;
gSystem->mkdir(Form("%s/root/%s", Outputdir.Data(), StrippedName.Data()), kTRUE);
c->SaveAs(Form("%s/root/%s/Likelihood_scan_%s.root", Outputdir.Data(), StrippedName.Data(), ParamName.Data()));
gSystem->mkdir(Form("%s/pdf/%s", Outputdir.Data(), StrippedName.Data()), kTRUE);
c->SaveAs(Form("%s/pdf/%s/Likelihood_scan_%s.pdf", Outputdir.Data(), StrippedName.Data(), ParamName.Data()));
gSystem->mkdir(Form("%s/png/%s", Outputdir.Data(), StrippedName.Data()), kTRUE);
c->SaveAs(Form("%s/png/%s/Likelihood_scan_%s.png", Outputdir.Data(), StrippedName.Data(), ParamName.Data()));
delete c;
delete frame1;
if (pll) delete pll;
cout << endl << "DONE WITH " << counter << " PARAMETER OUT OF " << Nparams << endl << endl;
//if (counter == 2){ break; } //Exit - for testing
var = iter->Next();
} // End of the loop
return true;
}
int main() {
TFile *tf = TFile::Open("root/MassFitResult.root");
RooWorkspace *w = (RooWorkspace*)tf->Get("w");
RooDataSet *data = (RooDataSet*)w->data("Data2012HadronTOS");
//w->loadSnapshot("bs2kstkst_mc_pdf_fit");
//RooRealVar *bs2kstkst_l = new RooRealVar("bs2kstkst_l" , "", -5., -20., 0.);
//RooConstVar *bs2kstkst_zeta = new RooConstVar("bs2kstkst_zeta" , "", 0.);
//RooConstVar *bs2kstkst_fb = new RooConstVar("bs2kstkst_fb" , "", 0.);
//RooRealVar *bs2kstkst_sigma = new RooRealVar("bs2kstkst_sigma" , "", 15, 10, 100);
//RooRealVar *bs2kstkst_mu = new RooRealVar("bs2kstkst_mu" , "", 5350, 5400 );
//RooRealVar *bs2kstkst_a = new RooRealVar("bs2kstkst_a" , "", 2.5,0,10);
//RooRealVar *bs2kstkst_n = new RooRealVar("bs2kstkst_n" , "", 2.5,0,10);
//RooRealVar *bs2kstkst_a2 = new RooRealVar("bs2kstkst_a2" , "", 2.5,0,10);
//RooRealVar *bs2kstkst_n2 = new RooRealVar("bs2kstkst_n2" , "", 2.5,0,10);
//RooIpatia2 *sig = new RooIpatia2("sig","",*w->var("B_s0_DTF_B_s0_M"), *bs2kstkst_l, *bs2kstkst_zeta, *bs2kstkst_fb, *bs2kstkst_sigma, *bs2kstkst_mu, *bs2kstkst_a, *bs2kstkst_n, *bs2kstkst_a2, *bs2kstkst_n2);
//RooAbsPdf *sig = (RooAbsPdf*)w->pdf("bs2kstkst_mc_pdf");
RooIpatia2 *sig = new RooIpatia2("bs2kstkst_mc_pdf","bs2kstkst_mc_pdf",*w->var("B_s0_DTF_B_s0_M"),*w->var("bs2kstkst_l"),*w->var("bs2kstkst_zeta"),*w->var("bs2kstkst_fb"),*w->var("bs2kstkst_sigma"),*w->var("bs2kstkst_mu"),*w->var("bs2kstkst_a"),*w->var("bs2kstkst_n"),*w->var("bs2kstkst_a2"),*w->var("bs2kstkst_n2"));
RooAbsPdf *bkg = (RooAbsPdf*)w->pdf("bkg_pdf_HadronTOS2012");
RooRealVar *sY = (RooRealVar*)w->var("bs2kstkst_y_HadronTOS2012");
RooRealVar *bY = (RooRealVar*)w->var("bkg_y_HadronTOS2012");
cout << sig << bkg << sY << bY << endl;
RooAddPdf *pdf = new RooAddPdf("test","test", RooArgList(*sig,*bkg), RooArgList(*sY,*bY) );
pdf->fitTo(*data, Extended() );
// my sw
double syVal = sY->getVal();
double byVal = bY->getVal();
// loop events
int numevents = data->numEntries();
sY->setVal(0.);
bY->setVal(0.);
RooArgSet *pdfvars = pdf->getVariables();
vector<double> fsvals;
vector<double> fbvals;
for ( int ievt=0; ievt<numevents; ievt++ ) {
RooStats::SetParameters(data->get(ievt), pdfvars);
sY->setVal(1.);
double f_s = pdf->getVal( RooArgSet(*w->var("B_s0_DTF_B_s0_M")) );
fsvals.push_back(f_s);
sY->setVal(0.);
bY->setVal(1.);
double f_b = pdf->getVal( RooArgSet(*w->var("B_s0_DTF_B_s0_M")) );
fbvals.push_back(f_b);
bY->setVal(0.);
//cout << f_s << " " << f_b << endl;
}
TMatrixD covInv(2,2);
covInv[0][0] = 0;
covInv[0][1] = 0;
covInv[1][0] = 0;
covInv[1][1] = 0;
for ( int ievt=0; ievt<numevents; ievt++ ) {
data->get(ievt);
double dsum=0;
dsum += fsvals[ievt] * syVal;
dsum += fbvals[ievt] * byVal;
covInv[0][0] += fsvals[ievt]*fsvals[ievt] / (dsum*dsum);
covInv[0][1] += fsvals[ievt]*fbvals[ievt] / (dsum*dsum);
covInv[1][0] += fbvals[ievt]*fsvals[ievt] / (dsum*dsum);
covInv[1][1] += fbvals[ievt]*fbvals[ievt] / (dsum*dsum);
}
covInv.Print();
cout << covInv.Determinant() << endl;
TMatrixD covMatrix(TMatrixD::kInverted,covInv);
covMatrix.Print();
RooStats::SPlot *sD = new RooStats::SPlot("sD","sD",*data,pdf,RooArgSet(*sY,*bY),RooArgSet(*w->var("eventNumber")));
}
