void ParameterCache::setPoint(Combiner *cmb, int i) {
if ( !m_parametersLoaded ){
cout << "ParameterCache::setPoint() : ERROR : Can't set starting "
"point as no starting values have been loaded" << endl;
exit(1);
}
if ( i>=getNPoints() ) {
if (m_arg->debug) cout << "ParameterCache::setPoint() : ";
cout << " ERROR : parameter point number " << i+1 << " not found in file. Exit." << endl;
exit(1);
}
vector<TString> fixNames = getFixedNames(cmb->getConstVars());
RooWorkspace *w = cmb->getWorkspace();
if ( m_arg->debug ) cout << "ParameterCache::setPoint() : Setting parameter values for point " << i+1 << endl;
for (map<TString,double>::iterator it=startingValues[i].begin(); it!=startingValues[i].end(); it++){
TString name = it->first;
double val = it->second;
if ( find(fixNames.begin(), fixNames.end(), name) != fixNames.end() ) {
if (m_arg->debug) cout << "\tLeft " << Form("%-15s",name.Data()) << " = " << Form("%12.6f",w->var(name)->getVal()) << " constant" << endl;
continue;
}
if ( w->var(name) ) {
w->var(name)->setVal(val);
if (m_arg->debug) cout << "\tSet " << Form("%-15s",name.Data()) << " = " << Form("%12.6f",w->var(name)->getVal()) << endl;
}
}
}
Int_t TwoBody::CreateDimuonToyMc( void ){
//
// generate a toy di-muon dataset with systematics
// set mData accordingly
//
// generate expected number of events from its uncertainty
//RooDataSet * _ds = ws->pdf("syst_nbkg_dimuon")->generate(*ws->var("beta_nbkg_dimuon"), 1);
//Double_t _ntoy = ((RooRealVar *)(_ds->get(0)->first()))->getVal() * (ws->var("nbkg_est_dimuon")->getVal());
//delete _ds;
Double_t _beta = GetRandom("syst_nbkg_dimuon", "beta_nbkg_dimuon");
// Double_t _kappa = ws->var("nbkg_kappa_dimuon")->getVal();
Double_t _nbkg_est = ws->var("nbkg_est_dimuon")->getVal();
//Double_t _ntoy = pow(_kappa,_beta) * _nbkg_est;
Double_t _ntoy = _beta * _nbkg_est;
Int_t _n = r.Poisson(_ntoy);
// all nuisance parameters:
// beta_nsig_dimuon,
// beta_nbkg_dimuon,
// lumi_nuis
// create dataset
RooRealVar * _mass = ws->var("mass");
RooArgSet _vars(*_mass);
RooAbsPdf * _pdf = ws->pdf("bkgpdf_dimuon");
RooAbsPdf::GenSpec * _spec = _pdf->prepareMultiGen(_vars,
Name("toys"),
NumEvents(_n),
Extended(kFALSE),
Verbose(kTRUE));
//RooPlot* xframe = _mass->frame(Title("Gaussian p.d.f.")) ;
//realdata->plotOn(xframe,LineColor(kRed),MarkerColor(kRed));
delete data;
data = _pdf->generate(*_spec); // class member
delete _spec;
//data->plotOn(xframe);
//TCanvas* c = new TCanvas("test","rf101_basics",800,400) ;
//gPad->SetLeftMargin(0.15) ; xframe->GetYaxis()->SetTitleOffset(1.6) ; xframe->Draw() ;
//c->SaveAs("test.pdf");
Int_t n_generated_entries = (Int_t)(data->sumEntries());
// debug
std::cout << "!!!!!!!!!!!!!! _beta = " << _beta << std::endl;
//std::cout << "!!!!!!!!!!!!!! _kappa = " << _kappa << std::endl;
std::cout << "!!!!!!!!!!!!!! _nbkg_est = " << _nbkg_est << std::endl;
std::cout << "!!!!!!!!!!!!!! _ntoy = " << _ntoy << std::endl;
std::cout << "!!!!!!!!!!!!!! _n = " << _n << std::endl;
std::cout << "!!!!!!!!!!!!!! n_generated_entries = " << n_generated_entries << std::endl;
return n_generated_entries;
}
double TwoBody::GetPoiUpperSimple(std::string channel, Double_t peak){
//
// Estimate a good value for the upper boundary of the range of POI
// using just data in a window corresponding to the signal region
//
std::string legend = "[TwoBody::GetPoiUpperSimple]: ";
char buf[128];
// special handling needed for single-channel workspaces
bool b_single_channel;
if (channel.size()==0) b_single_channel = true; else b_single_channel = false;
double _range = 1.0;
// get data yield under the signal peak
ws->var("peak")->setVal(peak);
if (b_single_channel) sprintf(buf,"width");
else sprintf(buf,"width_%s",channel.c_str());
double _width = 0;//ws->function(buf)->getVal();
if (b_single_channel) sprintf(buf,"sigma");
else sprintf(buf,"sigma_%s",channel.c_str());
double _sigma = ws->function(buf)->getVal();
double c_min = peak - sqrt(_width*_width + _sigma*_sigma);
double c_max = peak + sqrt(_width*_width + _sigma*_sigma);
sprintf(buf, "mass>=%f && mass<=%f", c_min, c_max);
double n_count = data->sumEntries( buf );
// ad-hoc fix when there are no events in window
if (n_count < 0.3) n_count = 0.3;
std::cout << legend << "event yield in data in the window: "
<< n_count << std::endl;
// compute the corresponding POI range
if (b_single_channel) sprintf(buf,"nsig_scale");
else sprintf(buf,"nsig_scale_%s",channel.c_str());
double _nsig_scale = ws->var(buf)->getVal();
if (b_single_channel) sprintf(buf,"nz");
else sprintf(buf,"nz_%s",channel.c_str());
double _nz = ws->var(buf)->getVal();
if (b_single_channel) sprintf(buf,"eff");
else sprintf(buf,"eff_%s",channel.c_str());
double _eff = ws->function(buf)->getVal();
double n_excess = 3.0 * sqrt(n_count)/0.68; // let signal excess be ~ uncertainty on BG
_range = n_excess / _nsig_scale / _nz / _eff;
return _range;
}
void rf903_numintcache(Int_t mode=0)
{
// Mode = 0 : Run plain fit (slow)
// Mode = 1 : Generate workspace with precalculated integral and store it on file (prepare for accelerated running)
// Mode = 2 : Run fit from previously stored workspace including cached integrals (fast, requires run in mode=1 first)
// C r e a t e , s a v e o r l o a d w o r k s p a c e w i t h p . d . f .
// -----------------------------------------------------------------------------------
// Make/load workspace, exit here in mode 1
RooWorkspace* w = getWorkspace(mode) ;
if (mode==1) {
// Show workspace that was created
w->Print() ;
// Show plot of cached integral values
RooDataHist* hhcache = (RooDataHist*) w->expensiveObjectCache().getObj(1) ;
new TCanvas("rf903_numintcache","rf903_numintcache",600,600) ;
hhcache->createHistogram("a")->Draw() ;
return ;
}
// U s e p . d . f . f r o m w o r k s p a c e f o r g e n e r a t i o n a n d f i t t i n g
// -----------------------------------------------------------------------------------
// This is always slow (need to find maximum function value empirically in 3D space)
RooDataSet* d = w->pdf("model")->generate(RooArgSet(*w->var("x"),*w->var("y"),*w->var("z")),1000) ;
// This is slow in mode 0, but fast in mode 1
w->pdf("model")->fitTo(*d,Verbose(kTRUE),Timer(kTRUE)) ;
// Projection on x (always slow as 2D integral over Y,Z at fitted value of a is not cached)
RooPlot* framex = w->var("x")->frame(Title("Projection of 3D model on X")) ;
d->plotOn(framex) ;
w->pdf("model")->plotOn(framex) ;
// Draw x projection on canvas
new TCanvas("rf903_numintcache","rf903_numintcache",600,600) ;
framex->Draw() ;
// Make workspace available on command line after macro finishes
gDirectory->Add(w) ;
return ;
}
//#include <typeinfo.h>
void addFlatNuisances(std::string fi){
gSystem->Load("libHiggsAnalysisCombinedLimit.so");
TFile *fin = TFile::Open(fi.c_str());
RooWorkspace *wspace = (RooWorkspace*)fin->Get("w_hmumu");
wspace->Print("");
RooStats::ModelConfig *mc = (RooStats::ModelConfig*)wspace->genobj("ModelConfig");
RooArgSet *nuis = (RooArgSet*) mc->GetNuisanceParameters();
std::cout << "Before...." << std::endl;
nuis->Print();
RooRealVar *mgg = (RooRealVar*)wspace->var("mmm");
// Get all of the "flat" nuisances to be added to the nusiances:
RooArgSet pdfs = (RooArgSet) wspace->allVars();
RooAbsReal *pdf;
TIterator *it_pdf = pdfs.createIterator();
while ( (pdf=(RooAbsReal*)it_pdf->Next()) ){
if (!(std::string(pdf->GetName()).find("zmod") != std::string::npos )) {
if (!(std::string(pdf->GetName()).find("__norm") != std::string::npos )) {
continue;
}
}
pdf->Print();
RooArgSet* pdfpars = (RooArgSet*)pdf->getParameters(RooArgSet(*mgg));
pdfpars->Print();
std::string newname_pdf = (std::string("unconst_")+std::string(pdf->GetName()));
wspace->import(*pdf,RooFit::RenameVariable(pdf->GetName(),newname_pdf.c_str()));
pdf->SetName(newname_pdf.c_str());
nuis->add(*pdf);
}
wspace->var("MH")->setVal(125.0);
std::cout << "After..." << std::endl;
nuis->Print();
mc->SetNuisanceParameters(*nuis);
//RooWorkspace *wspace_new = wspace->Clone();
//mc->SetWorkspace(*wspace_new);
//wspace_new->import(*mc,true);
TFile *finew = new TFile((std::string(fin->GetName())+std::string("_unconst.root")).c_str(),"RECREATE");
//wspace_new->SetName("w");
finew->WriteTObject(wspace);
finew->Close();
}
Double_t TwoBody::GetRandom( std::string pdf, std::string var ){
//
// generates a random number using a pdf in the workspace
//
// generate a dataset with one entry
if (ws!=NULL) {
RooRealVar * _par = ws->var(var.c_str());
if (_par!=NULL) {
RooAbsPdf * _pdf=ws->pdf(pdf.c_str());
/*
RooPlot* xframe = _par->frame(Title("p.d.f")) ;
_pdf->plotOn(xframe);
TCanvas* c = new TCanvas("test","rf101_basics",800,400) ;
gPad->SetLeftMargin(0.15) ; xframe->GetYaxis()->SetTitleOffset(1.6) ; xframe->Draw() ;
c->SaveAs("syst_nbkg.pdf");
*/
if (_pdf!=NULL) return _pdf->generate(*_par, 1)->get(0)->getRealValue(var.c_str(),0);
else {
std::cerr<<"Cannot find RooPdf:"<<pdf<<std::endl;
}
}
else std::cerr<<"Cannot find RooVar:"<<var<<std::endl;
}
else std::cerr<<"[BUG]workspace is deleted??"<<var<<std::endl;
return 0;
}
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 simplePrintResults() {
vector<string> filenames;
filenames.push_back("Output/Test2/result/FIT_DATA_Psi2SJpsi_PPPrompt_Bkg_SecondOrderChebychev_pt65300_rap016_cent0200_262620_263757.root");
const char* parname = "N_Jpsi_PP";
vector<string>::iterator it = filenames.begin();
for (it; it<filenames.end(); it++) {
TFile *f = new TFile(it->c_str());
if (!f) {
cout << "Error, " << *it << " not found" << endl;
continue;
}
RooWorkspace *ws = (RooWorkspace*) f->Get("workspace");
if (!ws) {
cout << "Error, workspace not found in " << *it << endl;
continue;
}
RooRealVar *var = ws->var(parname);
if (!ws) {
cout << "Error, variable " << parname << " not found in " << *it << endl;
continue;
}
cout << *it << " " << var->getVal() << " +- " << var->getError() << endl;
}
}
void gen1(const char* output, const char* suffix) {
// S e t u p m o d e l
// ---------------------
gRandom = new TRandom();
gRandom->SetSeed(0);
RooWorkspace *ws = new RooWorkspace("workspace");
// Declare variables x,mean,sigma with associated name, title, initial value and allowed range
ws->factory("invMass[2,5]");
RooRealVar *invMass = ws->var("invMass");
RooRealVar *weight = new RooRealVar("weight","weight",1,0,1e6);
ws->factory(Form("Gaussian::siga_nonorm_%s(invMass,m_%s[3,2.5,3.5],sigmaa_%s[0.02,0.,0.5])",suffix,suffix,suffix));
ws->factory(Form("Gaussian::sigb_nonorm_%s(invMass,m_%s,sigmab_%s[0.1,0.,0.5])",suffix,suffix,suffix));
ws->factory(Form("SUM::sig_nonorm_%s(f_%s[0.8,0,1]*siga_nonorm_%s,sigb_nonorm_%s)",suffix,suffix,suffix,suffix));
ws->factory(Form("RooExtendPdf::sig_%s(sig_nonorm_%s,Nsig_%s[1e4,-1e5,1e5])",suffix,suffix,suffix));
ws->factory(Form("Gaussian::sig2_nonorm_%s(invMass,m2_%s[3.5,3.,4.],sigma2_%s[0.1,0.,0.5])",suffix,suffix,suffix));
ws->factory(Form("RooFormulaVar::Nsig2_%s('@0*@1',{Nsig_%s,frac_%s[0.5,-10,10]})",suffix,suffix,suffix));
ws->factory(Form("RooExtendPdf::sig2_%s(sig2_nonorm_%s,Nsig2_%s)",suffix,suffix,suffix));
ws->factory(Form("Chebychev::bkg_nonorm_%s(invMass,{lambda0_%s[0.1,-1.5,1.5],lambda1_%s[0.1,-1.5,1.5]})",suffix,suffix,suffix));
ws->factory(Form("RooExtendPdf::bkg_%s(bkg_nonorm_%s,Nbkg_%s[1e4,-1e5,1e5])",suffix,suffix,suffix));
// ws->factory(Form("SUM::tot_%s( sig_%s, bkg_%s)",suffix,suffix,suffix));
// RooAbsPdf *thepdf = ws->pdf(Form("tot_%s",suffix));
RooAbsPdf *thepdf = new RooAddPdf(Form("tot_%s",suffix), Form("tot_%s",suffix),
RooArgList(*ws->pdf(Form("sig_%s",suffix)), *ws->pdf(Form("sig2_%s",suffix)), *ws->pdf(Form("bkg_%s",suffix))));
ws->import(*thepdf);
// G e n e r a t e e v e n t s
// -----------------------------
// Generate a dataset of 1000 events in x from gauss
RooDataSet* data = thepdf->generate(*invMass,2e4,Name(Form("data_%s",suffix))) ;
ws->import(*data);
ws->writeToFile(output);
}
ModelConfig TwoBody::prepareDimuonRatioModel( std::string inputdir ){
//
// prepare workspace and ModelConfig for the dimuon xsec ratio limit
//
std::string _legend = "[TwoBody::prepareDimuonRatioModel]: ";
std::string _infile = inputdir+"ws_dimuon_ratio.root";
AddWorkspace(_infile.c_str(),
"myWS",
"dimuon",
"peak,mass,ratio");
ws->pdf("model_dimuon")->SetName("model");
//ws->Print();
// set all vars to const except <par>
std::set<std::string> par;
par.insert("mass");
par.insert("ratio");
par.insert("beta_nsig_dimuon");
// par.insert("beta_nbkg_dimuon");
//par.insert("beta_mass_dimuon");
FixVariables(par);
// POI
RooArgSet sPoi( *(ws->var("ratio")) );
// nuisance
RooArgSet sNuis( *(ws->var("beta_nsig_dimuon"))
//*(ws->var("beta_nbkg_dimuon")),
//*(ws->var("beta_mass_dimuon"))
);
// observables
RooArgSet sObs( *(ws->var("mass")) );
// prior
// ModelConfig
ModelConfig _mc("mc",ws);
_mc.SetPdf(*(ws->pdf("model")));
_mc.SetParametersOfInterest( sPoi );
_mc.SetPriorPdf( *(ws->pdf("prior_dimuon")) );
_mc.SetNuisanceParameters( sNuis );
_mc.SetObservables( sObs );
return _mc;
}
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 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");
}
void Zbi_Zgamma() {
// Make model for prototype on/off problem
// Pois(x | s+b) * Pois(y | tau b )
// for Z_Gamma, use uniform prior on b.
RooWorkspace* w = new RooWorkspace("w",true);
w->factory("Poisson::px(x[150,0,500],sum::splusb(s[0,0,100],b[100,0,300]))");
w->factory("Poisson::py(y[100,0,500],prod::taub(tau[1.],b))");
w->factory("Uniform::prior_b(b)");
// construct the Bayesian-averaged model (eg. a projection pdf)
// p'(x|s) = \int db p(x|s+b) * [ p(y|b) * prior(b) ]
w->factory("PROJ::averagedModel(PROD::foo(px|b,py,prior_b),b)") ;
// plot it, blue is averaged model, red is b known exactly
RooPlot* frame = w->var("x")->frame() ;
w->pdf("averagedModel")->plotOn(frame) ;
w->pdf("px")->plotOn(frame,LineColor(kRed)) ;
frame->Draw() ;
// compare analytic calculation of Z_Bi
// with the numerical RooFit implementation of Z_Gamma
// for an example with x = 150, y = 100
// numeric RooFit Z_Gamma
w->var("y")->setVal(100);
w->var("x")->setVal(150);
RooAbsReal* cdf = w->pdf("averagedModel")->createCdf(*w->var("x"));
cdf->getVal(); // get ugly print messages out of the way
cout << "Hybrid p-value = " << cdf->getVal() << endl;
cout << "Z_Gamma Significance = " <<
PValueToSignificance(1-cdf->getVal()) << endl;
// analytic Z_Bi
double Z_Bi = NumberCountingUtils::BinomialWithTauObsZ(150, 100, 1);
std::cout << "Z_Bi significance estimation: " << Z_Bi << std::endl;
// OUTPUT
// Hybrid p-value = 0.999058
// Z_Gamma Significance = 3.10804
// Z_Bi significance estimation: 3.10804
}
Double_t Tprime::GetRandom( std::string pdf, std::string var ) {
//
// generates a random number using a pdf in the workspace
//
// generate a dataset with one entry
RooDataSet * _ds = pWs->pdf(pdf.c_str())->generate(*pWs->var(var.c_str()), 1);
Double_t _result = ((RooRealVar *)(_ds->get(0)->first()))->getVal();
delete _ds;
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();
}
bool extractParameter(string fileName, const char* parName, pair<double,double>& value)
{
TFile *f = new TFile( fileName.c_str() );
if (!f) {
cout << "[Error] " << fileName << " not found" << endl; return false;
}
RooWorkspace *ws = (RooWorkspace*) f->Get("workspace");
if (!ws) {
cout << "[ERROR] Workspace not found in " << fileName << endl; return false;
}
RooRealVar *var = ws->var(parName);
if (!var) {
value = make_pair( -999.9 , -999.9 ); return true;
}
value = make_pair( var->getValV() , var->getError() );
return true;
}
///
/// Make an Asimov toy: set all observables set to truth values.
/// The Asimov point needs to be loaded in the combiner before.
/// \param c - combiner which should be set to an asimov toy
///
void GammaComboEngine::setAsimovObservables(Combiner* c)
{
if ( !c->isCombined() ) {
cout << "GammaComboEngine::setAsimovObservables() : ERROR : Can't set an Asimov toy before "
"the combiner is combined. Call combine() first." << endl;
exit(1);
}
// set observables to asimov values in workspace
RooWorkspace* w = c->getWorkspace();
TIterator* itObs = c->getObservables()->createIterator();
while(RooRealVar* pObs = (RooRealVar*) itObs->Next()) {
// get theory name from the observable name
TString pThName = pObs->GetName();
pThName.ReplaceAll("obs","th");
// get the theory relation
RooAbsReal* th = w->function(pThName);
if ( th==0 ) {
cout << "GammaComboEngine::setAsimovObservables() : ERROR : theory relation not found in workspace: " << pThName << endl;
exit(1);
}
// set the observable to what the theory relation predicts
pObs->setVal(th->getVal());
}
delete itObs;
// write back the asimov values to the PDF object so that when
// the PDF is printed, the asimov values show up
for ( int i=0; i<c->getPdfs().size(); i++ ) {
PDF_Abs* pdf = c->getPdfs()[i];
pdf->setObservableSourceString("Asimov");
TIterator* itObs = pdf->getObservables()->createIterator();
while(RooRealVar* pObs = (RooRealVar*) itObs->Next()) {
RooAbsReal* obs = w->var(pObs->GetName());
if ( obs==0 ) {
cout << "GammaComboEngine::setAsimovObservables() : ERROR : observable not found in workspace: " << pObs->GetName() << endl;
exit(1);
}
pdf->setObservable(pObs->GetName(), obs->getVal());
}
delete itObs;
}
}
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);
}
};
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 buildModelUpsi2015(RooWorkspace& w, int signalModel, int bkgdModel){
// C r e a t e m o d e l
int nt=100000;
// cout << "you're building a model for the quarkonium resonance of mass = "<< M1S <<" GeV/c^{2},"endl;
RooRealVar *nsig1f = new RooRealVar("N_{ #varUpsilon(1S)}","nsig1S",0,nt*10);
RooRealVar* mass = (RooRealVar*) w.var("invariantMass");
RooRealVar *nsig2f = NULL;
RooRealVar *nsig3f = NULL;
RooRealVar *mean = new RooRealVar("m_{ #varUpsilon(1S)}","#Upsilon mean",M1S,M1S-0.2,M1S+0.2);
RooConstVar *rat2 = new RooConstVar("rat2", "rat2", M2S/M1S);
RooConstVar *rat3 = new RooConstVar("rat3", "rat3", M3S/M1S);
// scale mean and resolution by mass ratio
RooFormulaVar *mean1S = new RooFormulaVar("mean1S","@0",RooArgList(*mean));
RooFormulaVar *mean2S = new RooFormulaVar("mean2S","@0*@1", RooArgList(*mean,*rat2));
RooFormulaVar *mean3S = new RooFormulaVar("mean3S","@0*@1", RooArgList(*mean,*rat3));
// //detector resolution ?? where is this coming from?
RooRealVar *sigma1 = new RooRealVar("#sigma_{CB1}","#sigma_{CB1}",0.01,0.1); //
RooFormulaVar *sigma1S = new RooFormulaVar("sigma1S","@0" ,RooArgList(*sigma1));
RooFormulaVar *sigma2S = new RooFormulaVar("sigma2S","@0*@1",RooArgList(*sigma1,*rat2));
RooFormulaVar *sigma3S = new RooFormulaVar("sigma3S","@0*@1",RooArgList(*sigma1,*rat3));
RooRealVar *alpha = new RooRealVar("#alpha_{CB}","tail shift",0.1,10); // MC 5tev 1S pol2
RooRealVar *npow = new RooRealVar("n_{CB}","power order",0.1,10); // MC 5tev 1S pol2
RooRealVar *sigmaFraction = new RooRealVar("sigmaFraction","Sigma Fraction",0.,1.);
// scale the sigmaGaus with sigma1S*scale=sigmaGaus now.
RooRealVar *scaleWidth = new RooRealVar("#sigma_{CB2}/#sigma_{CB1}","scaleWidth",1.,2.5);
RooFormulaVar *sigmaGaus = new RooFormulaVar("sigmaGaus","@0*@1", RooArgList(*sigma1,*scaleWidth));
RooFormulaVar *sigmaGaus2 = new RooFormulaVar("sigmaGaus","@0*@1*@2", RooArgList(*sigma1,*scaleWidth,*rat2));
RooFormulaVar *sigmaGaus3 = new RooFormulaVar("sigmaGaus","@0*@1*@2", RooArgList(*sigma1,*scaleWidth,*rat3));
RooGaussian* gauss1 = new RooGaussian("gaus1s","gaus1s",
*nsig1f,
*mass, //mean
*sigmaGaus); //sigma
RooGaussian* gauss1b = new RooGaussian("gaus1sb","gaus1sb",
*nsig1f,
*mean, //mean
*sigma1); //sigma
// declarations
RooAbsPdf *cb1S_1 = NULL;
RooAbsPdf *cb1S_2 = NULL;
RooAbsPdf *cb2S_1 = NULL;
RooAbsPdf *cb2S_2 = NULL;
RooAbsPdf *cb3S_1 = NULL;
RooAbsPdf *cb3S_2 = NULL;
RooAbsPdf *sig1S = NULL;
RooAbsPdf *sig2S = NULL;
RooAbsPdf *sig3S = NULL;
switch(signalModel){
case 1: //crystal boule
sig1S = new RooCBShape("cb1S_1", "FSR cb 1s",
*mass,*mean1S,*sigma1,*alpha,*npow);
sig2S = new RooCBShape ("cb2S_1", "FSR cb 1s",
*mass,*mean2S,*sigma2S,*alpha,*npow);
sig3S = new RooCBShape ("cb3S_1", "FSR cb 1s",
*mass,*mean3S,*sigma3S,*alpha,*npow);
cout << "you're fitting each signal peak with a Crystal Ball function"<< endl;
break;
case 2: //Gaussein
sig1S = new RooGaussian ("g1", "gaus 1s",
*mass,*mean1S,*sigma1);
cout << "you're fitting 1 signal peak with a Gaussian function"<< endl;
break;
case 3: //Gaussein + crystal boule
cb1S_1 = new RooCBShape ("cb1S_1", "FSR cb 1s",
*mass,*mean1S,*sigma1,*alpha,*npow);
sig1S = new RooAddPdf ("cbg", "cbgaus 1s",
RooArgList(*gauss1,*cb1S_1),*sigmaFraction);
cout << "you're fitting 1 signal peak with a sum of a Gaussian and a Crystal Ball function"<< endl;
break;
case 4: //crystal boules
cb1S_1 = new RooCBShape ("cb1S_1", "FSR cb 1s",
*mass,*mean1S,*sigma1,*alpha,*npow);
cb1S_2 = new RooCBShape ("cb1S_2", "FSR cb 1s",
*mass,*mean1S,*sigmaGaus,*alpha,*npow);
sig1S = new RooAddPdf ("cbcb","1S mass pdf",
RooArgList(*cb1S_1,*cb1S_2),*sigmaFraction);
// /// Upsilon 2S
cb2S_1 = new RooCBShape ("cb2S_1", "FSR cb 2s",
*mass,*mean2S,*sigma2S,*alpha,*npow);
cb2S_2 = new RooCBShape ("cb2S_2", "FSR cb 2s",
*mass,*mean2S,*sigmaGaus2,*alpha,*npow);
sig2S = new RooAddPdf ("sig2S","2S mass pdf",
RooArgList(*cb2S_1,*cb2S_2),*sigmaFraction);
// /// Upsilon 3S
cb3S_1 = new RooCBShape ("cb3S_1", "FSR cb 3s",
*mass,*mean3S,*sigma3S,*alpha,*npow);
cb3S_2 = new RooCBShape ("cb3S_2", "FSR cb 3s",
*mass,*mean3S,*sigmaGaus3,*alpha,*npow);
sig3S = new RooAddPdf ("sig3S","3S mass pdf",
RooArgList(*cb3S_1,*cb3S_2),*sigmaFraction); // = cb3S1*sigmaFrac + cb3S2*(1-sigmaFrac)
cout << "you're fitting each signal peak with a Double Crystal Ball function"<< endl;
break;
case 5: //deux Gausseins
sig1S = new RooAddPdf ("cb1S_1", "cbgaus 1s",
RooArgList(*gauss1,*gauss1b),*sigmaFraction);
cout << "you're fitting each signal peak with a Double Gaussian function"<< endl;
break;
}
// bkg Chebychev
RooRealVar *nbkgd = new RooRealVar("n_{Bkgd}","nbkgd",0,nt);
RooRealVar *bkg_a1 = new RooRealVar("a1_bkg", "bkg_{a1}", 0, -5, 5);
RooRealVar *bkg_a2 = new RooRealVar("a2_Bkg", "bkg_{a2}", 0, -2, 2);
RooRealVar *bkg_a3 = new RooRealVar("a3_Bkg", "bkg_{a3}", 0, -0.9, 2);
// likesign
RooRealVar *nLikesignbkgd = new RooRealVar("NLikesignBkg","nlikesignbkgd",nt*0.75,0,10*nt);
// *************************************************** bkgModel
RooRealVar turnOn("turnOn","turnOn", 0,10);
RooRealVar width("width","width", 0.1,10);// MB 2.63
RooRealVar decay("decay","decay",0,10);// MB: 3.39
width.setConstant(false);
decay.setConstant(false);
turnOn.setConstant(false);
alpha->setConstant(false);
npow->setConstant(false);
sigma1->setConstant(false);
scaleWidth->setConstant(false);
sigmaFraction->setConstant(false);
//thisPdf: form of the bkg pdf
//pdf_combinedbkgd; // total bkg pdf. usually form*normalization (so that you can do extended ML fits)
RooAbsPdf *pdf_combinedbkgd = NULL;;
RooRealVar *fPol = new RooRealVar("F_{pol}","fraction of polynomial distribution",0.0,1);
RooAbsPdf *ChebPdf = NULL;
RooAbsPdf *ErrPdf = NULL;
RooAbsPdf* ExpPdf = NULL;
switch (bkgdModel)
{
case 3 : //use error function to fit the OS directly
bkg_a3->setConstant(true);
pdf_combinedbkgd = new RooGenericPdf("bkgPdf","bkgPdf",
"exp(-@0/decay)*(TMath::Erf((@0-turnOn)/width)+1)",
RooArgList(*mass,turnOn,width,decay));
break;
case 4 : //use pol 2+ErfExp to fit the OS directly
ChebPdf = new RooChebychev("ChebPdf","ChebPdf",
*mass, RooArgList(*bkg_a1,*bkg_a2));
ErrPdf = new RooGenericPdf("ErrPdf","ErrPdf",
"exp(-@0/decay)*(TMath::Erf((@0-turnOn)/width)+1)",
RooArgList(*mass,turnOn,width,decay));
pdf_combinedbkgd = new RooAddPdf ("bkgPdf","total combined background pdf",
RooArgList(*ChebPdf,*ErrPdf),
RooArgList(*fPol));
break;
case 5 : //use ( error function + polynomial 1) to fit the OS directly
bkg_a3->setConstant(true);
bkg_a2->setConstant(true);
ChebPdf = new RooChebychev("ChebPdf","ChebPdf",
*mass, RooArgList(*bkg_a1,*bkg_a2,*bkg_a3));
ErrPdf = new RooGenericPdf("ErrPdf","ErrPdf",
"exp(-@0/decay)*(TMath::Erf((@0-turnOn)/width)+1)",
RooArgList(*mass,turnOn,width,decay));
pdf_combinedbkgd = new RooAddPdf ("bkgPdf","total combined background pdf",
RooArgList(*ChebPdf,*ErrPdf),
RooArgList(*fPol));
break;
case 6: // NOT WORKING
ChebPdf = new RooChebychev("ChebPdf","ChebPdf",
*mass, RooArgList(*bkg_a1,*bkg_a2));
ExpPdf = new RooGenericPdf("ExpPdf","ExpPdf",
"exp(-@0/decay)",
RooArgList(*mass,decay));
pdf_combinedbkgd = new RooAddPdf ("bkgPdf","total combined background pdf",
RooArgList(*ChebPdf,*ExpPdf),
RooArgList(*fPol));
break;
default :
cout<<"Donno what you are talking about! Pick another fit option!"<<endl;
break;
}
//###### the nominal fit with default pdf
// can remove the double crystal ball in pbpb: just commenting out and copying an appropriate version
RooAbsPdf *pdf = new RooAddPdf ("pdf","total p.d.f.",
RooArgList(*sig1S,*sig2S,*sig3S,*pdf_combinedbkgd),
RooArgList(*nsig1f,*nsig2f,*nsig3f,*nbkgd));
// nsig3f->setVal(0); nsig3f->setConstant();
w.import(*pdf);
w.Print();
}
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));
}
/*
* Prepares the workspace to be used by the hypothesis test calculator
*/
void workspace_preparer(char *signal_file_name, char *signal_hist_name_in_file, char *background_file_name, char *background_hist_name_in_file, char *data_file_name, char *data_hist_name_in_file, char *config_file) {
// Include the config_reader class.
TString path = gSystem->GetIncludePath();
path.Append(" -I/home/max/cern/cls/mario");
gSystem->SetIncludePath(path);
gROOT->LoadMacro("config_reader.cxx");
// RooWorkspace used to store values.
RooWorkspace * pWs = new RooWorkspace("ws");
// Create a config_reader (see source for details) to read the config
// file.
config_reader reader(config_file, pWs);
// Read MR and RR bounds from the config file.
double MR_lower = reader.find_double("MR_lower");
double MR_upper = reader.find_double("MR_upper");
double RR_lower = reader.find_double("RR_lower");
double RR_upper = reader.find_double("RR_upper");
double MR_initial = (MR_lower + MR_upper)/2;
double RR_initial = (RR_lower + RR_upper)/2;
// Define the Razor Variables
RooRealVar MR = RooRealVar("MR", "MR", MR_initial, MR_lower, MR_upper);
RooRealVar RR = RooRealVar("RSQ", "RSQ", RR_initial, RR_lower, RR_upper);
// Argument lists
RooArgList pdf_arg_list(MR, RR, "input_args_list");
RooArgSet pdf_arg_set(MR, RR, "input_pdf_args_set");
/***********************************************************************/
/* PART 1: IMPORTING SIGNAL AND BACKGROUND HISTOGRAMS */
/***********************************************************************/
/*
* Get the signal's unextended pdf by converting the TH2D in the file
* into a RooHistPdf
*/
TFile *signal_file = new TFile(signal_file_name);
TH2D *signal_hist = (TH2D *)signal_file->Get(signal_hist_name_in_file);
RooDataHist *signal_RooDataHist = new RooDataHist("signal_roodatahist",
"signal_roodatahist",
pdf_arg_list,
signal_hist);
RooHistPdf *unextended_sig_pdf = new RooHistPdf("unextended_sig_pdf",
"unextended_sig_pdf",
pdf_arg_set,
*signal_RooDataHist);
/*
* Repeat this process for the background.
*/
TFile *background_file = new TFile(background_file_name);
TH2D *background_hist =
(TH2D *)background_file->Get(background_hist_name_in_file);
RooDataHist *background_RooDataHist =
new RooDataHist("background_roodatahist", "background_roodatahist",
pdf_arg_list, background_hist);
RooHistPdf *unextended_bkg_pdf = new RooHistPdf("unextended_bkg_pdf",
"unextended_bkg_pdf",
pdf_arg_set,
*background_RooDataHist);
/*
* Now, we want to create the bprime variable, which represents the
* integral over the background-only sample. We will perform the
* integral automatically (that's why this is the only nuisance
* parameter declared in this file - its value can be determined from
* the input histograms).
*/
ostringstream bprime_string;
ostringstream bprime_pdf_string;
bprime_string << "bprime[" << background_hist->Integral() << ", 0, 999999999]";
bprime_pdf_string << "Poisson::bprime_pdf(bprime, " << background_hist->Integral() << ")";
pWs->factory(bprime_string.str().c_str());
pWs->factory(bprime_pdf_string.str().c_str());
/*
* This simple command will create all values from the config file
* with 'make:' at the beginning and a delimiter at the end (see config
* _reader if you don't know what a delimiter is). In other
* words, the luminosity, efficiency, transfer factors, and their pdfs
* are created from this command. The declarations are contained in the
* config file to be changed easily without having to modify this code.
*/
reader.factory_all();
/*
* Now, we want to create the extended pdfs from the unextended pdfs, as
* well as from the S and B values we manufactured in the config file.
* S and B are the values by which the signal and background pdfs,
* respectively, are extended. Recall that they were put in the
* workspace in the reader.facotry_all() command.
*/
RooAbsReal *S = pWs->function("S");
RooAbsReal *B = pWs->function("B");
RooExtendPdf *signalpart = new RooExtendPdf("signalpart", "signalpart",
*unextended_sig_pdf, *S);
RooExtendPdf *backgroundpart =
new RooExtendPdf("backgroundpart", "backgroundpart",
*unextended_bkg_pdf, *B);
RooArgList *pdf_list = new RooArgList(*signalpart, *backgroundpart,
"list");
// Add the signal and background pdfs to make a TotalPdf
RooAddPdf *TotalPdf = new RooAddPdf("TotalPdf", "TotalPdf", *pdf_list);
RooArgList *pdf_prod_list = new RooArgList(*TotalPdf,
*pWs->pdf("lumi_pdf"),
*pWs->pdf("eff_pdf"),
*pWs->pdf("rho_pdf"),
*pWs->pdf("bprime_pdf"));
// This creates the final model pdf.
RooProdPdf *model = new RooProdPdf("model", "model", *pdf_prod_list);
/*
* Up until now, we have been using the workspace pWs to contain all of
* our values. Now, all of our values that we require are in use in the
* RooProdPdf called "model". So, we need to import "model" into a
* RooWorkspace. To avoid recopying values into the rooworkspace, when
* the values may already be present (which can cause problems), we will
* simply create a new RooWorkspace to avoid confusion and problems. The
* new RooWorkspace is created here.
*/
RooWorkspace *newworkspace = new RooWorkspace("newws");
newworkspace->import(*model);
// Immediately delete pWs, so we don't accidentally use it again.
delete pWs;
// Show off the newworkspace
newworkspace->Print();
// observables
RooArgSet obs(*newworkspace->var("MR"), *newworkspace->var("RSQ"), "obs");
// global observables
RooArgSet globalObs(*newworkspace->var("nom_lumi"), *newworkspace->var("nom_eff"), *newworkspace->var("nom_rho"));
//fix global observables to their nominal values
newworkspace->var("nom_lumi")->setConstant();
newworkspace->var("nom_eff")->setConstant();
newworkspace->var("nom_rho")->setConstant();
//Set Parameters of interest
RooArgSet poi(*newworkspace->var("sigma"), "poi");
//Set Nuisnaces
RooArgSet nuis(*newworkspace->var("prime_lumi"), *newworkspace->var("prime_eff"), *newworkspace->var("prime_rho"), *newworkspace->var("bprime"));
// priors (for Bayesian calculation)
newworkspace->factory("Uniform::prior_signal(sigma)"); // for parameter of interest
newworkspace->factory("Uniform::prior_bg_b(bprime)"); // for data driven nuisance parameter
newworkspace->factory("PROD::prior(prior_signal,prior_bg_b)"); // total prior
//Observed data is pulled from histogram.
//TFile *data_file = new TFile(data_file_name);
TFile *data_file = new TFile(data_file_name);
TH2D *data_hist = (TH2D *)data_file->Get(data_hist_name_in_file);
RooDataHist *pData = new RooDataHist("data", "data", obs, data_hist);
newworkspace->import(*pData);
// Now, we will draw our data from a RooDataHist.
/*TFile *data_file = new TFile(data_file_name);
TTree *data_tree = (TTree *) data_file->Get(data_hist_name_in_file);
RooDataSet *pData = new RooDataSet("data", "data", data_tree, obs);
newworkspace->import(*pData);*/
// Craft the signal+background model
ModelConfig * pSbModel = new ModelConfig("SbModel");
pSbModel->SetWorkspace(*newworkspace);
pSbModel->SetPdf(*newworkspace->pdf("model"));
pSbModel->SetPriorPdf(*newworkspace->pdf("prior"));
pSbModel->SetParametersOfInterest(poi);
pSbModel->SetNuisanceParameters(nuis);
pSbModel->SetObservables(obs);
pSbModel->SetGlobalObservables(globalObs);
// set all but obs, poi and nuisance to const
SetConstants(newworkspace, pSbModel);
newworkspace->import(*pSbModel);
// background-only model
// use the same PDF as s+b, with sig=0
// POI value under the background hypothesis
// (We will set the value to 0 later)
Double_t poiValueForBModel = 0.0;
ModelConfig* pBModel = new ModelConfig(*(RooStats::ModelConfig *)newworkspace->obj("SbModel"));
pBModel->SetName("BModel");
pBModel->SetWorkspace(*newworkspace);
newworkspace->import(*pBModel);
// find global maximum with the signal+background model
// with conditional MLEs for nuisance parameters
// and save the parameter point snapshot in the Workspace
// - safer to keep a default name because some RooStats calculators
// will anticipate it
RooAbsReal * pNll = pSbModel->GetPdf()->createNLL(*pData);
RooAbsReal * pProfile = pNll->createProfile(RooArgSet());
pProfile->getVal(); // this will do fit and set POI and nuisance parameters to fitted values
RooArgSet * pPoiAndNuisance = new RooArgSet();
if(pSbModel->GetNuisanceParameters())
pPoiAndNuisance->add(*pSbModel->GetNuisanceParameters());
pPoiAndNuisance->add(*pSbModel->GetParametersOfInterest());
cout << "\nWill save these parameter points that correspond to the fit to data" << endl;
pPoiAndNuisance->Print("v");
pSbModel->SetSnapshot(*pPoiAndNuisance);
delete pProfile;
delete pNll;
delete pPoiAndNuisance;
// Find a parameter point for generating pseudo-data
// with the background-only data.
// Save the parameter point snapshot in the Workspace
pNll = pBModel->GetPdf()->createNLL(*pData);
pProfile = pNll->createProfile(poi);
((RooRealVar *)poi.first())->setVal(poiValueForBModel);
pProfile->getVal(); // this will do fit and set nuisance parameters to profiled values
pPoiAndNuisance = new RooArgSet();
if(pBModel->GetNuisanceParameters())
pPoiAndNuisance->add(*pBModel->GetNuisanceParameters());
pPoiAndNuisance->add(*pBModel->GetParametersOfInterest());
cout << "\nShould use these parameter points to generate pseudo data for bkg only" << endl;
pPoiAndNuisance->Print("v");
pBModel->SetSnapshot(*pPoiAndNuisance);
delete pProfile;
delete pNll;
delete pPoiAndNuisance;
// save workspace to file
newworkspace->writeToFile("ws_twobin.root");
// clean up
delete newworkspace;
delete pData;
delete pSbModel;
delete pBModel;
} // ----- end of tutorial ----------------------------------------
void DrawSignalProperties(TString OPTION)
{
gROOT->ForceStyle();
const int NCAT = 7;
const int N = 5;
const int MASS[N] = {115,120,125,130,135};
int COLOR[N] = {kBlack,kGreen+1,kRed+1,kBlue,kMagenta};
int STYLE[N] = {20,21,22,23,24};
TFile *fSig = TFile::Open("workspace/signal_shapes_workspace_"+OPTION+".root");
RooWorkspace *wSig = (RooWorkspace*)fSig->Get("w");
float x[N],yMean[N][NCAT],ySigma[N][NCAT],yWidth[N][NCAT],eMean[N][NCAT],eSigma[N][NCAT];
TH1F *hWidth[N],*hMean[N],*hSigma[N];
TH2F *hFractionGF = new TH2F("FractionGF","FractionGF",NCAT,0,NCAT,N,0,N);
for(int icat=0;icat<NCAT;icat++) {
hFractionGF->GetXaxis()->SetBinLabel(icat+1,TString::Format("CAT%d",icat));
}
for(int im=0;im<N;im++) {
hFractionGF->GetYaxis()->SetBinLabel(im+1,TString::Format("%d",MASS[im]));
}
//---------------------------------------------------------------------
TCanvas *can = new TCanvas("SignalProperties","SignalProperties",900,600);
can->Divide(2,2);
TCanvas *can2 = new TCanvas("GFFraction","GFFraction",900,600);
TLegend *leg = new TLegend(0.18,0.2,0.9,0.9);
leg->SetFillColor(0);
leg->SetBorderSize(0);
leg->SetTextFont(42);
leg->SetTextSize(0.07);
for(int im=0;im<N;im++) {
hWidth[im] = new TH1F(TString::Format("width_m%d",MASS[im]),TString::Format("width_m%d",MASS[im]),NCAT,0,NCAT);
hMean[im] = new TH1F(TString::Format("mean_m%d",MASS[im]),TString::Format("mean_m%d",MASS[im]),NCAT,0,NCAT);
hSigma[im] = new TH1F(TString::Format("sigma_m%d",MASS[im]),TString::Format("sigma_m%d",MASS[im]),NCAT,0,NCAT);
hWidth[im]->SetLineColor(COLOR[im]);
hWidth[im]->SetMarkerColor(COLOR[im]);
hWidth[im]->SetMarkerStyle(STYLE[im]);
hMean[im]->SetLineColor(COLOR[im]);
hMean[im]->SetMarkerColor(COLOR[im]);
hMean[im]->SetMarkerStyle(STYLE[im]);
hSigma[im]->SetLineColor(COLOR[im]);
hSigma[im]->SetMarkerColor(COLOR[im]);
hSigma[im]->SetMarkerStyle(STYLE[im]);
x[im] = MASS[im];
for(int icat=0;icat<NCAT;icat++) {
if (im == 0) {
hWidth[im]->GetXaxis()->SetBinLabel(icat+1,TString::Format("CAT%d",icat));
hMean[im]->GetXaxis()->SetBinLabel(icat+1,TString::Format("CAT%d",icat));
hSigma[im]->GetXaxis()->SetBinLabel(icat+1,TString::Format("CAT%d",icat));
}
yMean[im][icat] = (RooRealVar*)wSig->var(TString::Format("mean_m%d_CAT%d",MASS[im],icat))->getValV();
eMean[im][icat] = (RooRealVar*)wSig->var(TString::Format("mean_m%d_CAT%d",MASS[im],icat))->getError();
ySigma[im][icat] = (RooRealVar*)wSig->var(TString::Format("sigma_m%d_CAT%d",MASS[im],icat))->getValV();
eSigma[im][icat] = (RooRealVar*)wSig->var(TString::Format("sigma_m%d_CAT%d",MASS[im],icat))->getError();
yWidth[im][icat] = (RooRealVar*)wSig->var(TString::Format("fwhm_m%d_CAT%d",MASS[im],icat))->getValV()/yMean[im][icat];
hWidth[im]->SetBinContent(icat+1,yWidth[im][icat]);
hMean[im]->SetBinContent(icat+1,yMean[im][icat]/x[im]);
hMean[im]->SetBinError(icat+1,eMean[im][icat]/x[im]);
hSigma[im]->SetBinContent(icat+1,ySigma[im][icat]/yMean[im][icat]);
hSigma[im]->SetBinError(icat+1,(ySigma[im][icat]/yMean[im][icat])*sqrt(pow(eMean[im][icat]/yMean[im][icat],2)+pow(eSigma[im][icat]/ySigma[im][icat],2)));
float gf = (RooRealVar*)wSig->var(TString::Format("yield_signalGF_mass%d_CAT%d",MASS[im],icat))->getValV();
float vbf = (RooRealVar*)wSig->var(TString::Format("yield_signalVBF_mass%d_CAT%d",MASS[im],icat))->getValV();
float f = gf/(gf+vbf);
hFractionGF->SetBinContent(icat+1,im+1,f);
}
leg->AddEntry(hWidth[im],TString::Format("M_{H} = %d GeV",MASS[im]),"P");
if (im == 0) {
hWidth[im]->GetYaxis()->SetRangeUser(0.1,0.3);
hWidth[im]->GetYaxis()->SetTitle("FWHM / m");
hMean[im]->GetYaxis()->SetRangeUser(0.9,1.1);
hMean[im]->GetYaxis()->SetTitle("m / M_{H}");
hSigma[im]->GetYaxis()->SetRangeUser(0.04,0.16);
hSigma[im]->GetYaxis()->SetTitle("#sigma / m");
can->cd(1);
hWidth[im]->Draw("LP");
can->cd(2);
hMean[im]->Draw("LP");
can->cd(3);
hSigma[im]->Draw("LP");
}
else {
can->cd(1);
hWidth[im]->Draw("LPsame");
can->cd(2);
hMean[im]->Draw("LPsame");
can->cd(3);
hSigma[im]->Draw("LPsame");
}
}
can->cd(4);
leg->Draw();
can2->cd();
gStyle->SetPalette(42,0);
gStyle->SetPaintTextFormat("1.2g");
hFractionGF->SetMarkerSize(2.0);
hFractionGF->GetYaxis()->SetTitle("Higgs mass (GeV)");
hFractionGF->GetXaxis()->SetTitle("Category");
hFractionGF->Draw("COL TEXT");
can->SaveAs(TString::Format("plots/properties/%s.png",can->GetName()));
can2->SaveAs(TString::Format("plots/properties/%s.png",can2->GetName()));
}
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 rf511_wsfactory_basic(Bool_t compact=kFALSE)
{
RooWorkspace* w = new RooWorkspace("w") ;
// C r e a t i n g a n d a d d i n g b a s i c p . d . f . s
// ----------------------------------------------------------------
// Remake example p.d.f. of tutorial rs502_wspacewrite.C:
//
// Basic p.d.f. construction: ClassName::ObjectName(constructor arguments)
// Variable construction : VarName[x,xlo,xhi], VarName[xlo,xhi], VarName[x]
// P.d.f. addition : SUM::ObjectName(coef1*pdf1,...coefM*pdfM,pdfN)
//
if (!compact) {
// Use object factory to build p.d.f. of tutorial rs502_wspacewrite
w->factory("Gaussian::sig1(x[-10,10],mean[5,0,10],0.5)") ;
w->factory("Gaussian::sig2(x,mean,1)") ;
w->factory("Chebychev::bkg(x,{a0[0.5,0.,1],a1[-0.2,0.,1.]})") ;
w->factory("SUM::sig(sig1frac[0.8,0.,1.]*sig1,sig2)") ;
w->factory("SUM::model(bkgfrac[0.5,0.,1.]*bkg,sig)") ;
} else {
// Use object factory to build p.d.f. of tutorial rs502_wspacewrite but
// - Contracted to a single line recursive expression,
// - Omitting explicit names for components that are not referred to explicitly later
w->factory("SUM::model(bkgfrac[0.5,0.,1.]*Chebychev::bkg(x[-10,10],{a0[0.5,0.,1],a1[-0.2,0.,1.]}),"
"SUM(sig1frac[0.8,0.,1.]*Gaussian(x,mean[5,0,10],0.5), Gaussian(x,mean,1)))") ;
}
// A d v a n c e d p . d . f . c o n s t r u c t o r a r g u m e n t s
// ----------------------------------------------------------------
//
// P.d.f. constructor arguments may by any type of RooAbsArg, but also
//
// Double_t --> converted to RooConst(...)
// {a,b,c} --> converted to RooArgSet() or RooArgList() depending on required ctor arg
// dataset name --> convered to RooAbsData reference for any dataset residing in the workspace
// enum --> Any enum label that belongs to an enum defined in the (base) class
// Make a dummy dataset p.d.f. 'model' and import it in the workspace
RooDataSet* data = w->pdf("model")->generate(*w->var("x"),1000) ;
w->import(*data,Rename("data")) ;
// Construct a KEYS p.d.f. passing a dataset name and an enum type defining the
// mirroring strategy
w->factory("KeysPdf::k(x,data,NoMirror,0.2)") ;
// Print workspace contents
w->Print() ;
// Make workspace visible on command line
gDirectory->Add(w) ;
}
vector<Double_t*> simFit(bool makeSoupFit_ = false,
const string tnp_ = "etoTauMargLooseNoCracks70",
const string category_ = "tauAntiEMVA",
const string bin_ = "abseta<1.5",
const float binCenter_ = 0.75,
const float binWidth_ = 0.75,
const float xLow_=60,
const float xHigh_=120,
bool SumW2_ = false,
bool verbose_ = true){
vector<Double_t*> out;
//return out;
//TFile *test = new TFile( outFile->GetName(),"UPDATE");
// output file
TFile *test = new TFile( Form("EtoTauPlotsFit_%s_%s_%f.root",tnp_.c_str(),category_.c_str(),binCenter_),"RECREATE");
test->mkdir(Form("bin%f",binCenter_));
TCanvas *c = new TCanvas("fitCanvas",Form("fitCanvas_%s_%s",tnp_.c_str(),bin_.c_str()),10,30,650,600);
c->SetGrid(0,0);
c->SetFillStyle(4000);
c->SetFillColor(10);
c->SetTicky();
c->SetObjectStat(0);
TCanvas *c2 = new TCanvas("fitCanvasTemplate",Form("fitCanvasTemplate_%s_%s",tnp_.c_str(),bin_.c_str()),10,30,650,600);
c2->SetGrid(0,0);
c2->SetFillStyle(4000);
c2->SetFillColor(10);
c2->SetTicky();
c2->SetObjectStat(0);
// input files
TFile fsup("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_soup.root");
TFile fbkg("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_soup_bkg.root");
TFile fsgn("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_soup_sgn.root");
TFile fdat("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_Data.root");
// data from 2iter:
//TFile fdat("/data_CMS/cms/lbianchini/35pb/testNewWriteFromPAT_Data.root");
//********************** signal only tree *************************/
TTree *fullTreeSgn = (TTree*)fsgn.Get((tnp_+"/fitter_tree").c_str());
TH1F* hSall = new TH1F("hSall","",1,0,150);
TH1F* hSPall = new TH1F("hSPall","",1,0,150);
TH1F* hS = new TH1F("hS","",1,0,150);
TH1F* hSP = new TH1F("hSP","",1,0,150);
fullTreeSgn->Draw("mass>>hS",Form("weight*(%s && mass>%f && mass<%f && mcTrue && signalPFChargedHadrCands<1.5)",bin_.c_str(),xLow_,xHigh_));
fullTreeSgn->Draw("mass>>hSall",Form("weight*(%s && mass>%f && mass<%f)",bin_.c_str(),xLow_,xHigh_));
float SGNtrue = hS->Integral();
float SGNall = hSall->Integral();
fullTreeSgn->Draw("mass>>hSP",Form("weight*(%s && %s>0 && mass>%f && mass<%f && mcTrue && signalPFChargedHadrCands<1.5 )",bin_.c_str(),category_.c_str(),xLow_,xHigh_));
fullTreeSgn->Draw("mass>>hSPall",Form("weight*(%s && %s>0 && mass>%f && mass<%f && signalPFChargedHadrCands<1.5 )",bin_.c_str(),category_.c_str(),xLow_,xHigh_));
float SGNtruePass = hSP->Integral();
float SGNallPass = hSPall->Integral();
//********************** background only tree *************************//
TTree *fullTreeBkg = (TTree*)fbkg.Get((tnp_+"/fitter_tree").c_str());
TH1F* hB = new TH1F("hB","",1,0,150);
TH1F* hBP = new TH1F("hBP","",1,0,150);
fullTreeBkg->Draw("mass>>hB",Form("weight*(%s && mass>%f && mass<%f && signalPFChargedHadrCands<1.5 )",bin_.c_str(),xLow_,xHigh_));
float BKG = hB->Integral();
float BKGUnWeighted = hB->GetEntries();
fullTreeBkg->Draw("mass>>hBP",Form("weight*(%s && %s>0 && mass>%f && mass<%f && signalPFChargedHadrCands<1.5 )",bin_.c_str(),category_.c_str(),xLow_,xHigh_));
float BKGPass = hBP->Integral();
float BKGUnWeightedPass = hBP->GetEntries();
float BKGFail = BKG-BKGPass;
cout << "*********** BKGFail " << BKGFail << endl;
//********************** soup tree *************************//
TTree *fullTreeSoup = (TTree*)fsup.Get((tnp_+"/fitter_tree").c_str());
//********************** data tree *************************//
TTree *fullTreeData = (TTree*)fdat.Get((tnp_+"/fitter_tree").c_str());
//********************** workspace ***********************//
RooWorkspace *w = new RooWorkspace("w","w");
// tree variables to be imported
w->factory("mass[30,120]");
w->factory("weight[0,10000]");
w->factory("abseta[0,2.5]");
w->factory("pt[0,200]");
w->factory("mcTrue[0,1]");
w->factory("signalPFChargedHadrCands[0,10]");
w->factory((category_+"[0,1]").c_str());
// background pass pdf for MC
w->factory("RooExponential::McBackgroundPdfP(mass,McCP[0,-10,10])");
// background fail pdf for MC
w->factory("RooExponential::McBackgroundPdfF(mass,McCF[0,-10,10])");
// background pass pdf for Data
w->factory("RooExponential::DataBackgroundPdfP(mass,DataCP[0,-10,10])");
// background fail pdf for Data
w->factory("RooExponential::DataBackgroundPdfF(mass,DataCF[0,-10,10])");
// fit parameters for background
w->factory("McEfficiency[0.04,0,1]");
w->factory("McNumSgn[0,1000000]");
w->factory("McNumBkgP[0,100000]");
w->factory("McNumBkgF[0,100000]");
w->factory("expr::McNumSgnP('McEfficiency*McNumSgn',McEfficiency,McNumSgn)");
w->factory("expr::McNumSgnF('(1-McEfficiency)*McNumSgn',McEfficiency,McNumSgn)");
w->factory("McPassing[pass=1,fail=0]");
// fit parameters for data
w->factory("DataEfficiency[0.1,0,1]");
w->factory("DataNumSgn[0,1000000]");
w->factory("DataNumBkgP[0,1000000]");
w->factory("DataNumBkgF[0,10000]");
w->factory("expr::DataNumSgnP('DataEfficiency*DataNumSgn',DataEfficiency,DataNumSgn)");
w->factory("expr::DataNumSgnF('(1-DataEfficiency)*DataNumSgn',DataEfficiency,DataNumSgn)");
w->factory("DataPassing[pass=1,fail=0]");
RooRealVar *weight = w->var("weight");
RooRealVar *abseta = w->var("abseta");
RooRealVar *pt = w->var("pt");
RooRealVar *mass = w->var("mass");
mass->setRange(xLow_,xHigh_);
RooRealVar *mcTrue = w->var("mcTrue");
RooRealVar *cut = w->var( category_.c_str() );
RooRealVar *signalPFChargedHadrCands = w->var("signalPFChargedHadrCands");
// build the template for the signal pass sample:
RooDataSet templateP("templateP","dataset for signal-pass template", RooArgSet(*mass,*weight,*abseta,*pt,*cut,*mcTrue,*signalPFChargedHadrCands), Import( *fullTreeSgn ), /*WeightVar( *weight ),*/ Cut( Form("(mcTrue && %s>0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()) ) );
// build the template for the signal fail sample:
RooDataSet templateF("templateF","dataset for signal-fail template", RooArgSet(*mass,*weight,*abseta,*pt,*cut,*mcTrue,*signalPFChargedHadrCands), Import( *fullTreeSgn ), /*WeightVar( *weight ),*/ Cut( Form("(mcTrue && %s<0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()) ) );
mass->setBins(24);
RooDataHist templateHistP("templateHistP","",RooArgSet(*mass), templateP, 1.0);
RooHistPdf TemplateSignalPdfP("TemplateSignalPdfP","",RooArgSet(*mass),templateHistP);
w->import(TemplateSignalPdfP);
mass->setBins(24);
RooDataHist templateHistF("templateHistF","",RooArgSet(*mass),templateF,1.0);
RooHistPdf TemplateSignalPdfF("TemplateSignalPdfF","",RooArgSet(*mass),templateHistF);
w->import(TemplateSignalPdfF);
mass->setBins(10000,"fft");
RooPlot* TemplateFrameP = mass->frame(Bins(24),Title("Template passing"));
templateP.plotOn(TemplateFrameP);
w->pdf("TemplateSignalPdfP")->plotOn(TemplateFrameP);
RooPlot* TemplateFrameF = mass->frame(Bins(24),Title("Template failing"));
templateF.plotOn(TemplateFrameF);
w->pdf("TemplateSignalPdfF")->plotOn(TemplateFrameF);
//w->factory("RooFFTConvPdf::McSignalPdfP(mass,TemplateSignalPdfP,RooTruthModel::McResolModP(mass))");
//w->factory("RooFFTConvPdf::McSignalPdfF(mass,TemplateSignalPdfF,RooTruthModel::McResolModF(mass))");
// FOR GREGORY: PROBLEM WHEN TRY TO USE THE PURE TEMPLATE =>
RooHistPdf McSignalPdfP("McSignalPdfP","McSignalPdfP",RooArgSet(*mass),templateHistP);
RooHistPdf McSignalPdfF("McSignalPdfF","McSignalPdfF",RooArgSet(*mass),templateHistF);
w->import(McSignalPdfP);
w->import(McSignalPdfF);
// FOR GREGORY: FOR DATA, CONVOLUTION IS OK =>
w->factory("RooFFTConvPdf::DataSignalPdfP(mass,TemplateSignalPdfP,RooGaussian::DataResolModP(mass,DataMeanResP[0.0,-5.,5.],DataSigmaResP[0.5,0.,10]))");
w->factory("RooFFTConvPdf::DataSignalPdfF(mass,TemplateSignalPdfF,RooGaussian::DataResolModF(mass,DataMeanResF[-5.,-10.,10.],DataSigmaResF[0.5,0.,10]))");
//w->factory("RooCBShape::DataSignalPdfF(mass,DataMeanF[91.2,88,95.],DataSigmaF[3,0.5,8],DataAlfaF[1.8,0.,10],DataNF[1.0,1e-06,10])");
//w->factory("RooFFTConvPdf::DataSignalPdfF(mass,RooVoigtian::DataVoigF(mass,DataMeanF[85,80,95],DataWidthF[2.49],DataSigmaF[3,0.5,10]),RooCBShape::DataResolModF(mass,DataMeanResF[0.5,0.,10.],DataSigmaResF[0.5,0.,10],DataAlphaResF[0.5,0.,10],DataNResF[1.0,1e-06,10]))");
//w->factory("SUM::DataSignalPdfF(fVBP[0.5,0,1]*RooBifurGauss::bifF(mass,DataMeanResF[91.2,80,95],sigmaLF[10,0.5,40],sigmaRF[0.]), RooVoigtian::voigF(mass, DataMeanResF, widthF[2.49], sigmaVoigF[5,0.1,10]) )" );
// composite model pass for MC
w->factory("SUM::McModelP(McNumSgnP*McSignalPdfP,McNumBkgP*McBackgroundPdfP)");
w->factory("SUM::McModelF(McNumSgnF*McSignalPdfF,McNumBkgF*McBackgroundPdfF)");
// composite model pass for data
w->factory("SUM::DataModelP(DataNumSgnP*DataSignalPdfP,DataNumBkgP*DataBackgroundPdfP)");
w->factory("SUM::DataModelF(DataNumSgnF*DataSignalPdfF,DataNumBkgF*DataBackgroundPdfF)");
// simultaneous fir for MC
w->factory("SIMUL::McModel(McPassing,pass=McModelP,fail=McModelF)");
// simultaneous fir for data
w->factory("SIMUL::DataModel(DataPassing,pass=DataModelP,fail=DataModelF)");
w->Print("V");
w->saveSnapshot("clean", w->allVars());
w->loadSnapshot("clean");
/****************** sim fit to soup **************************/
///////////////////////////////////////////////////////////////
TFile *f = new TFile("dummySoup.root","RECREATE");
TTree* cutTreeSoupP = fullTreeSoup->CopyTree(Form("(%s>0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
TTree* cutTreeSoupF = fullTreeSoup->CopyTree(Form("(%s<0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
RooDataSet McDataP("McDataP","dataset pass for the soup", RooArgSet(*mass), Import( *cutTreeSoupP ) );
RooDataSet McDataF("McDataF","dataset fail for the soup", RooArgSet(*mass), Import( *cutTreeSoupF ) );
RooDataHist McCombData("McCombData","combined data for the soup", RooArgSet(*mass), Index(*(w->cat("McPassing"))), Import("pass", *(McDataP.createHistogram("histoP",*mass)) ), Import("fail",*(McDataF.createHistogram("histoF",*mass)) ) ) ;
RooPlot* McFrameP = 0;
RooPlot* McFrameF = 0;
RooRealVar* McEffFit = 0;
if(makeSoupFit_){
cout << "**************** N bins in mass " << w->var("mass")->getBins() << endl;
RooFitResult* ResMcCombinedFit = w->pdf("McModel")->fitTo(McCombData, Extended(1), Minos(1), Save(1), SumW2Error( SumW2_ ), Range(xLow_,xHigh_), NumCPU(4) /*, ExternalConstraints( *(w->pdf("ConstrainMcNumBkgF")) )*/ );
test->cd(Form("bin%f",binCenter_));
ResMcCombinedFit->Write("McFitResults_Combined");
RooArgSet McFitParam(ResMcCombinedFit->floatParsFinal());
McEffFit = (RooRealVar*)(&McFitParam["McEfficiency"]);
RooRealVar* McNumSigFit = (RooRealVar*)(&McFitParam["McNumSgn"]);
RooRealVar* McNumBkgPFit = (RooRealVar*)(&McFitParam["McNumBkgP"]);
RooRealVar* McNumBkgFFit = (RooRealVar*)(&McFitParam["McNumBkgF"]);
McFrameP = mass->frame(Bins(24),Title("MC: passing sample"));
McCombData.plotOn(McFrameP,Cut("McPassing==McPassing::pass"));
w->pdf("McModel")->plotOn(McFrameP,Slice(*(w->cat("McPassing")),"pass"), ProjWData(*(w->cat("McPassing")),McCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameP,Slice(*(w->cat("McPassing")),"pass"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McSignalPdfP"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameP,Slice(*(w->cat("McPassing")),"pass"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McBackgroundPdfP"), LineColor(kGreen),Range(xLow_,xHigh_));
McFrameF = mass->frame(Bins(24),Title("MC: failing sample"));
McCombData.plotOn(McFrameF,Cut("McPassing==McPassing::fail"));
w->pdf("McModel")->plotOn(McFrameF,Slice(*(w->cat("McPassing")),"fail"), ProjWData(*(w->cat("McPassing")),McCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameF,Slice(*(w->cat("McPassing")),"fail"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McSignalPdfF"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameF,Slice(*(w->cat("McPassing")),"fail"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McBackgroundPdfF"), LineColor(kGreen),Range(xLow_,xHigh_));
}
///////////////////////////////////////////////////////////////
/****************** sim fit to data **************************/
///////////////////////////////////////////////////////////////
TFile *f2 = new TFile("dummyData.root","RECREATE");
TTree* cutTreeDataP = fullTreeData->CopyTree(Form("(%s>0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
TTree* cutTreeDataF = fullTreeData->CopyTree(Form("(%s<0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
RooDataSet DataDataP("DataDataP","dataset pass for the soup", RooArgSet(*mass), Import( *cutTreeDataP ) );
RooDataSet DataDataF("DataDataF","dataset fail for the soup", RooArgSet(*mass), Import( *cutTreeDataF ) );
RooDataHist DataCombData("DataCombData","combined data for the soup", RooArgSet(*mass), Index(*(w->cat("DataPassing"))), Import("pass",*(DataDataP.createHistogram("histoDataP",*mass))),Import("fail",*(DataDataF.createHistogram("histoDataF",*mass)))) ;
RooFitResult* ResDataCombinedFit = w->pdf("DataModel")->fitTo(DataCombData, Extended(1), Minos(1), Save(1), SumW2Error( SumW2_ ), Range(xLow_,xHigh_), NumCPU(4));
test->cd(Form("bin%f",binCenter_));
ResDataCombinedFit->Write("DataFitResults_Combined");
RooArgSet DataFitParam(ResDataCombinedFit->floatParsFinal());
RooRealVar* DataEffFit = (RooRealVar*)(&DataFitParam["DataEfficiency"]);
RooRealVar* DataNumSigFit = (RooRealVar*)(&DataFitParam["DataNumSgn"]);
RooRealVar* DataNumBkgPFit = (RooRealVar*)(&DataFitParam["DataNumBkgP"]);
RooRealVar* DataNumBkgFFit = (RooRealVar*)(&DataFitParam["DataNumBkgF"]);
RooPlot* DataFrameP = mass->frame(Bins(24),Title("Data: passing sample"));
DataCombData.plotOn(DataFrameP,Cut("DataPassing==DataPassing::pass"));
w->pdf("DataModel")->plotOn(DataFrameP,Slice(*(w->cat("DataPassing")),"pass"), ProjWData(*(w->cat("DataPassing")),DataCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameP,Slice(*(w->cat("DataPassing")),"pass"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataSignalPdfP"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameP,Slice(*(w->cat("DataPassing")),"pass"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataBackgroundPdfP"), LineColor(kGreen),LineStyle(kDashed),Range(xLow_,xHigh_));
RooPlot* DataFrameF = mass->frame(Bins(24),Title("Data: failing sample"));
DataCombData.plotOn(DataFrameF,Cut("DataPassing==DataPassing::fail"));
w->pdf("DataModel")->plotOn(DataFrameF,Slice(*(w->cat("DataPassing")),"fail"), ProjWData(*(w->cat("DataPassing")),DataCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameF,Slice(*(w->cat("DataPassing")),"fail"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataSignalPdfF"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameF,Slice(*(w->cat("DataPassing")),"fail"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataBackgroundPdfF"), LineColor(kGreen),LineStyle(kDashed),Range(xLow_,xHigh_));
///////////////////////////////////////////////////////////////
if(makeSoupFit_) c->Divide(2,2);
else c->Divide(2,1);
c->cd(1);
DataFrameP->Draw();
c->cd(2);
DataFrameF->Draw();
if(makeSoupFit_){
c->cd(3);
McFrameP->Draw();
c->cd(4);
McFrameF->Draw();
}
c->Draw();
test->cd(Form("bin%f",binCenter_));
c->Write();
c2->Divide(2,1);
c2->cd(1);
TemplateFrameP->Draw();
c2->cd(2);
TemplateFrameF->Draw();
c2->Draw();
test->cd(Form("bin%f",binCenter_));
c2->Write();
// MINOS errors, otherwise HESSE quadratic errors
float McErrorLo = 0;
float McErrorHi = 0;
if(makeSoupFit_){
McErrorLo = McEffFit->getErrorLo()<0 ? McEffFit->getErrorLo() : (-1)*McEffFit->getError();
McErrorHi = McEffFit->getErrorHi()>0 ? McEffFit->getErrorHi() : McEffFit->getError();
}
float DataErrorLo = DataEffFit->getErrorLo()<0 ? DataEffFit->getErrorLo() : (-1)*DataEffFit->getError();
float DataErrorHi = DataEffFit->getErrorHi()>0 ? DataEffFit->getErrorHi() : DataEffFit->getError();
float BinomialError = TMath::Sqrt(SGNtruePass/SGNtrue*(1-SGNtruePass/SGNtrue)/SGNtrue);
Double_t* truthMC = new Double_t[6];
Double_t* tnpMC = new Double_t[6];
Double_t* tnpData = new Double_t[6];
truthMC[0] = binCenter_;
truthMC[1] = binWidth_;
truthMC[2] = binWidth_;
truthMC[3] = SGNtruePass/SGNtrue;
truthMC[4] = BinomialError;
truthMC[5] = BinomialError;
if(makeSoupFit_){
tnpMC[0] = binCenter_;
tnpMC[1] = binWidth_;
tnpMC[2] = binWidth_;
tnpMC[3] = McEffFit->getVal();
tnpMC[4] = (-1)*McErrorLo;
tnpMC[5] = McErrorHi;
}
tnpData[0] = binCenter_;
tnpData[1] = binWidth_;
tnpData[2] = binWidth_;
tnpData[3] = DataEffFit->getVal();
tnpData[4] = (-1)*DataErrorLo;
tnpData[5] = DataErrorHi;
out.push_back(truthMC);
out.push_back(tnpData);
if(makeSoupFit_) out.push_back(tnpMC);
test->Close();
//delete c; delete c2;
if(verbose_) cout << "returning from bin " << bin_ << endl;
return out;
}
void FitBias(TString CAT,TString CUT,float SIG,float BKG,int NTOYS)
{
gROOT->ForceStyle();
RooMsgService::instance().setSilentMode(kTRUE);
RooMsgService::instance().setStreamStatus(0,kFALSE);
RooMsgService::instance().setStreamStatus(1,kFALSE);
// -----------------------------------------
TFile *fTemplates = TFile::Open("templates_"+CUT+"_"+CAT+"_workspace.root");
RooWorkspace *wTemplates = (RooWorkspace*)fTemplates->Get("w");
RooRealVar *x = (RooRealVar*)wTemplates->var("mTop");
RooAbsPdf *pdf_signal = (RooAbsPdf*)wTemplates->pdf("ttbar_pdf_Nominal");
RooAbsPdf *pdf_bkg = (RooAbsPdf*)wTemplates->pdf("qcdCor_pdf");
TRandom *rnd = new TRandom();
rnd->SetSeed(0);
x->setBins(250);
RooPlot *frame;
TFile *outf;
if (NTOYS > 1) {
outf = TFile::Open("FitBiasToys_"+CUT+"_"+CAT+".root","RECREATE");
}
float nSigInj,nBkgInj,nSigFit,nBkgFit,eSigFit,eBkgFit,nll;
TTree *tr = new TTree("toys","toys");
tr->Branch("nSigInj",&nSigInj,"nSigInj/F");
tr->Branch("nSigFit",&nSigFit,"nSigFit/F");
tr->Branch("nBkgInj",&nBkgInj,"nBkgInj/F");
tr->Branch("nBkgFit",&nBkgFit,"nBkgFit/F");
tr->Branch("eSigFit",&eSigFit,"eSigFit/F");
tr->Branch("eBkgFit",&eBkgFit,"eBkgFit/F");
tr->Branch("nll" ,&nll ,"nll/F");
for(int itoy=0;itoy<NTOYS;itoy++) {
// generate pseudodataset
nSigInj = rnd->Poisson(SIG);
nBkgInj = rnd->Poisson(BKG);
RooRealVar *nSig = new RooRealVar("nSig","nSig",nSigInj);
RooRealVar *nBkg = new RooRealVar("nBkg","nBkg",nBkgInj);
RooAddPdf *model = new RooAddPdf("model","model",RooArgList(*pdf_signal,*pdf_bkg),RooArgList(*nSig,*nBkg));
RooDataSet *data = model->generate(*x,nSigInj+nBkgInj);
RooDataHist *roohist = new RooDataHist("roohist","roohist",RooArgList(*x),*data);
// build fit model
RooRealVar *nFitSig = new RooRealVar("nFitSig","nFitSig",SIG,0,10*SIG);
RooRealVar *nFitBkg = new RooRealVar("nFitBkg","nFitBkg",BKG,0,10*BKG);
RooAddPdf *modelFit = new RooAddPdf("modelFit","modelFit",RooArgList(*pdf_signal,*pdf_bkg),RooArgList(*nFitSig,*nFitBkg));
// fit the pseudo dataset
RooFitResult *res = modelFit->fitTo(*roohist,RooFit::Save(),RooFit::Extended(kTRUE));
//res->Print();
nSigFit = nFitSig->getVal();
nBkgFit = nFitBkg->getVal();
eSigFit = nFitSig->getError();
eBkgFit = nFitBkg->getError();
nll = res->minNll();
tr->Fill();
if (itoy % 100 == 0) {
cout<<"Toy #"<<itoy<<": injected = "<<nSigInj<<", fitted = "<<nSigFit<<", error = "<<eSigFit<<endl;
}
if (NTOYS == 1) {
frame = x->frame();
roohist->plotOn(frame);
model->plotOn(frame);
}
}
if (NTOYS == 1) {
TCanvas *can = new TCanvas("Toy","Toy",900,600);
frame->Draw();
}
else {
outf->cd();
tr->Write();
outf->Close();
fTemplates->Close();
}
}
int main (int argc, char **argv)
{
const char* chInFile = "ws.root";
const char* chOutFile = "ws_data.root";
const char* chRootFile = "BDT20.root";
const char* chCut = "";
char option_char;
while ( (option_char = getopt(argc,argv, "i:o:r:c:")) != EOF )
switch (option_char)
{
case 'i': chInFile = optarg; break;
case 'o': chOutFile = optarg; break;
case 'r': chRootFile = optarg; break;
case 'c': chCut = optarg; break;
case '?': fprintf (stderr,
"usage: %s [i<input file> o<output file>]\n", argv[0]);
}
cout << "In Ws = " << chInFile << endl;
cout << "Out Ws = " << chOutFile << endl;
cout << "Data From = " << chRootFile << endl;
cout << "Extra Cut = " << chCut << endl;
TFile* in_file = new TFile(chInFile);
RooWorkspace *rws = (RooWorkspace*) in_file->Get("rws");
TFile* tree_file = new TFile(chRootFile);
TTree* tree = (TTree*) tree_file->Get("tree");
TFile* out_file = new TFile(chOutFile, "RECREATE");
RooArgSet allVars(*rws->var("m"),*rws->var("t"),*rws->var("et"),*rws->var("cpsi"),*rws->var("ctheta"),*rws->var("phi"),*rws->var("d"));
RooDataSet* data = new RooDataSet("data","data",allVars);
RooDataSet* dataBkg = new RooDataSet("dataBkg","dataBkg",allVars);
TCut* cut = new TCut("5.17<bs_mass && bs_mass<5.57 && bs_epdl<0.02 && bs_pdl<0.40 && bs_pdl>-0.15 && 1.01<phi_mass && phi_mass<1.03");
*cut += chCut;
tree->Draw(">>entry_list", *cut, "entrylist");
TEntryList* event_list = (TEntryList*) out_file->Get("entry_list");
Double_t dM, dT, dEt, dCpsi, dCtheta, dPhi, dd;
Int_t ddDefined;
tree->SetBranchAddress("bs_mass", &dM);
tree->SetBranchAddress("bs_pdl", &dT);
tree->SetBranchAddress("bs_epdl", &dEt);
tree->SetBranchAddress("bs_angle_cpsi", &dCpsi);
tree->SetBranchAddress("bs_angle_ctheta", &dCtheta);
tree->SetBranchAddress("bs_angle_phi", &dPhi);
tree->SetBranchAddress("newtag_ost", &dd);
tree->SetBranchAddress("newtag_ost_defined", &ddDefined);
for (Long_t i=0; i<event_list->GetN(); i++){
tree->GetEntry(event_list->GetEntry(i));
*rws->var("m")=dM;
*rws->var("t")=dT/0.0299792458;
*rws->var("et")=dEt/0.0299792458;
*rws->var("cpsi")=dCpsi;
*rws->var("ctheta")=dCtheta;
*rws->var("phi")=dPhi;
*rws->var("d")=0;
////rws->cat("dilution")->setIndex(0);
if ( ddDefined==1 ){
////rws->cat("dilution")->setIndex(1);
*rws->var("d")=dd;
}
data->add(allVars);
if (dM<5.29 || dM>5.44)
dataBkg->add(allVars);
}
rws->import(*data);
rws->import(*dataBkg);
rws->Write("rws");
out_file->Close();
in_file->Close();
tree_file->Close();
cout << endl << "Done." << endl;
}
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;
}
