double Getmean(TString sys1, TString sys2, float cent1, float cent2){
gROOT->SetStyle("Plain");
TFile *infile = TFile::Open(Form("glau_%s%s_ntuple_1M.root",sys1.Data(),sys2.Data()));
infile->cd();
TH2F *pEcc2B = new TH2F("pEcc2B","#epsilon_{2} vs impact paramter in 200 GeV Collisions from Glauber MC;B;#epsilon_{n}",25200,-0.5,251.5,100,0,1);
if(sys2.Contains("smeared")){
TNtuple *nt = (TNtuple*)infile->Get("nt");
nt->Project("pEcc2B","Ecc3G:B");
}
else{
TNtuple *nt = (TNtuple*)infile->Get(Form("nt_%s_%s",sys1.Data(),sys2.Data()));
nt->Project("pEcc2B","Ecc2:B");
}
TH1D* hB = (TH1D*)pEcc2B->ProjectionX("hB",0,-1);
for(int ibin=0;ibin<hB->GetNbinsX();ibin++){
if(hB->Integral(0,ibin) >= cent1 /100. * hB->Integral()){ int bin1 = ibin; break;}
}
for(int ibin=0;ibin<hB->GetNbinsX();ibin++){
if(hB->Integral(0,ibin) >= cent2 /100. * hB->Integral()){ int bin2 = ibin; break;}
}
cout<< bin1 << "\t" << bin2 << endl;
TH1D* hEcc2 = (TH1D*)pEcc2B->ProjectionY("hEcc2",bin1,bin2);
// hEcc2->Draw();
cout << hEcc2 -> GetEntries() << endl;
double mean = hEcc2->GetMean();
return mean;
}
void createSysStatErrorHist(TH1D *hist_pre){
TH1D *histErr = (TH1D*) hist_pre->Clone("histErr");
hsyserr = (TH1D*) hist_pre->Clone("hsyserr"), hsyserr->Reset();
hsyserr->Sumw2();
cout<<""<<endl;
for(int i=0;i<histErr->GetNbinsX();i++){ // last bin is meaningless
double pt = histErr->GetBinCenter(i+1);
double statferr = histErr->GetBinError(i+1)/histErr->GetBinContent(i+1);
if(i==(histErr->GetNbinsX()-1)) statferr = 0.9;
//double sysferr = fsyserr->Eval(pt);
double sysferr = returnCombinedSysError(pt);
double sumferr = sqrt(statferr*statferr + sysferr*sysferr);
//double sumerr = 1.*(sumferr/100);
double sumerr = 1.*sumferr;
hsyserr->SetBinContent(i+1,1);
hsyserr->SetBinError(i+1,sumerr);
//hsyserr->SetBinError(i+1,0.5);
cout<<"[setSysStatError] stat err (frac): "<<statferr<<" syst err (fac): "<<sysferr<<" combined (frac): "<<sumferr<<endl;
}
//tsyserr = (TGraphErrors*) TgraphIt(hsyserr);
}
void loglikdistrib(Int_t ntrials = 10000, Bool_t print = kFALSE)
{
// compute distribution of log likelihood value
TH1D * hmc = gStack[gPadNr][gOrder[gPadNr][0]];
TH1D * hdata = gStack[gPadNr][gMaxProcess-1];
Int_t nbins = hmc->GetNbinsX();
Double_t loglik = loglikelihood(hmc, hdata, 1, nbins);
TH1D * htest = new TH1D(*hdata);
TH1D * lldistrib = new TH1D("lldistrib", "log(Likelihood) distribution",
1000, loglik-200, loglik+200);
setopt(lldistrib);
for (Int_t n = 0; n < ntrials; n++) {
// generate poisson around theorie
for (Int_t i = 1; i <= nbins; i++) {
htest->SetBinContent(i, gRandom->Poisson(hmc->GetBinContent(i)));
}
lldistrib->Fill(loglikelihood(hmc, htest, 1, nbins));
}
TCanvas * llcanvas = new TCanvas("llcanvas", "Log(Likelihood) distribution",
40, 40, 800, 600);
setopt(llcanvas);
lldistrib->SetFillColor(kYellow);
lldistrib->Draw();
lldistrib->GetYaxis()->SetTitle("Anzahl Ereignisse");
lldistrib->GetXaxis()->SetTitle("-ln L");
// autozoom
Int_t lowbin = 1;
while (lldistrib->GetBinContent(lowbin) == 0)
lowbin++;
Int_t highbin = lldistrib->GetNbinsX();
while (lldistrib->GetBinContent(highbin) == 0)
highbin--;
lldistrib->SetAxisRange(lldistrib->GetBinLowEdge(lowbin),
lldistrib->GetBinLowEdge(highbin));
TH1D * hworse = (TH1D *) lldistrib->Clone();
for (Int_t nbin = 1; nbin < 501; nbin++) {
hworse->SetBinContent(nbin, 0);
}
hworse->SetFillColor(95);
hworse->Draw("same");
Double_t pvalue = lldistrib->Integral(501,1000) / lldistrib->Integral();
TLatex * tex = new TLatex(0.18, 0.96, Form("-ln L_{obs} = %5.2f", loglik));
tex->SetNDC();
tex->SetTextAlign(13);
tex->Draw();
tex = new TLatex(0.18, 0.86, Form("CL_{obs} = %.3f", pvalue));
tex->SetNDC();
tex->SetTextAlign(13);
tex->Draw();
TLine * l = new TLine(loglik, 0, loglik, lldistrib->GetMaximum());
l->SetLineWidth(3);
l->SetLineColor(kBlue);
l->Draw();
llcanvas->Modified();
llcanvas->Update();
if (print)
llcanvas->Print("lldistrib.pdf");
cd(gPadNr+1);
}
void takeDirectlyFromMC(TFile* fin, TFile* fout, TString gentype) {
TList* listOfDirs = fin->GetListOfKeys();
for (auto k : *listOfDirs) {
TString srname = k->GetName();
if (!srname.Contains("sr")) continue;
if (srname.Contains("base") || srname.Contains("incl") || srname.Contains("sb")) continue;
if (gentype == "_1lepW" && !srname.EndsWith("2") && !srname.EndsWith("3")) continue;
auto indir = (TDirectoryFile*) fin->Get(srname);
auto outdir = (TDirectory*) fout->mkdir(srname);
auto hlist = indir->GetListOfKeys();
for (auto h : *hlist) {
TString hname = h->GetName();
if (!hname.BeginsWith("h_metbins" + gentype)) continue;
TH1D* hin = (TH1D*) indir->Get(hname);
outdir->cd();
TH1D* hout = (TH1D*) hin->Clone(TString(hname).ReplaceAll(gentype, ""));
for (int i = 1; i <= hout->GetNbinsX(); ++i) {
// zero out negative yields
if (hout->GetBinContent(i) < 0) {
hout->SetBinContent(i, 0);
hout->SetBinError(i, 0);
}
}
hout->Write();
if (yearSeparateSyst && (hname.EndsWith("Up") || hname.EndsWith("Dn"))) {
for (int i = 1; i < 4; ++i) {
TH1D* hcen_yi = (TH1D*) fbkgs[i]->Get(srname+"/h_metbins"+gentype);
TH1D* hsys_yi = (TH1D*) fbkgs[i]->Get(srname+"/"+hname);
if (hsys_yi && !hcen_yi) {
cout << "Find " << srname+"/"+hname << " from " << fbkgs[i]->GetName() << " but not hcen " << srname+"/h_metbins"+gentype << " Should not happen?" << endl;
}
TH1D* hout_yi = (TH1D*) fin->Get(srname+"/h_metbins"+gentype)->Clone(TString(hname).Insert(hname.Length()-2, Form("%d", 15+i)).ReplaceAll(gentype, ""));
if (hcen_yi) hout_yi->Add(hcen_yi, -1);
if (hsys_yi) hout_yi->Add(hsys_yi);
hout_yi->Write();
}
}
}
if (!outdir->Get("h_metbins")) {
cout << "Didn't find yield hist for " << gentype << " in " << fin->GetName() << ":" << srname << "/. Faking a 0 one!" << endl;
outdir->cd();
// Get the MET binning from h_metbins, which shall always exist, and then set all bins to 0
TH1D* hout = (TH1D*) fin->Get(srname + "/h_metbins")->Clone("h_metbins");
for (int i = 1; i <= hout->GetNbinsX(); ++i) {
hout->SetBinContent(i, 0);
hout->SetBinError(i, 0);
}
hout->Write();
}
}
}
TH1D GetSOverSqrtB(TH1D sig, TH1D back){
if(sig.GetNbinsX()!=back.GetNbinsX()) return sig;
sig.GetYaxis()->SetTitle("S/#sqrt{B}");
for(int i(1); i<=sig.GetNbinsX(); ++i){
if(back.GetBinContent(i)>0.0 && sig.GetBinContent(i)>0.0){
sig.SetBinContent(i,sig.GetBinContent(i)/sqrt(back.GetBinContent(i)));
}else{
sig.SetBinContent(i,0.0);
}
}
return sig;
}
TH1D* getQCD(int rebinFact){
TString dir = "rootFiles/";
TFile* file = new TFile(dir +"qcdest.root");
TH1D* plot = (TH1D*) file->Get("muon_AbsEta_0btag");
// for(int i = 1; i <= plot->GetNbinsX(); i++){
// plot->SetBinError(i, 0.0);
// }
plot->SetFillColor(kYellow);
plot->SetLineColor(kYellow);
plot->SetMarkerStyle(1);
TH1D* copyplot = new TH1D("qcd plot", "qcd plot", 30, 0.0, 3.0);
for(int i = 1; i <= plot->GetNbinsX(); i++){
copyplot->SetBinContent(i, plot->GetBinContent(i));
//copyplot->SetBinError(i, plot->GetBinError(i));
}
copyplot->SetFillColor(kYellow);
copyplot->SetLineColor(kYellow);
copyplot->SetMarkerStyle(1);
copyplot->Scale(1./copyplot->Integral());
copyplot->Rebin(rebinFact);
//file->Close("R");
return copyplot;
//file->Close();
}
void QinvKstar (const char* filename, const char* histname) {
TFile* fileIn = new TFile(filename,"update");
TH1D* hist = (TH1D*)fileIn->Get(histname);
TH1D* histnew = new TH1D(Form("kstar_%s",histname),"",hist->GetNbinsX(),0,0.25);//(TH1D*)fileIn->Get(histname);
// for (int ibins = 1; ibins <= hist->GetNbinsX()*2; ibins++ ) {
// hist->SetBinContent(ibins, hist->GetBinContent(ibins));
// // hist->SetBinContent(ibins, hist->GetBinContent(ibins));
// }
int bin=2;//1
for (double kstar = 0.00375; kstar <= 0.25; kstar += 0.0025 ) {
// for (double kstar = 0.00375; kstar <= 0.25; kstar += 0.0025 ) {
// for (double kstar = 0.005; kstar <= 0.25; kstar += 0.01 ) {
// hist->Fill(kstar,hist->GetBinContent(hist->FindBin(kstar*2)));
histnew->SetBinContent(bin,hist->GetBinContent(hist->FindFixBin(kstar*2)));
histnew->SetBinError(bin++,hist->GetBinError(hist->FindFixBin(kstar*2)));
// hist->SetBinContent(ibins, hist->GetBinContent(ibins));
// hist->SetBinContent(ibins, hist->GetBinContent(ibins));
}
TFile* fileOut = new TFile(Form("kstar_%s",filename), "update");
hist->Write();
histnew->Write();
}
// Merge same modes
int dmMerge(TObject *a1, TObject *b1,TList *keys)
{
TDecayMode *a=(TDecayMode*)a1;
TDecayMode *b=(TDecayMode*)b1;
TIter nexthist(keys);
TKey *key_hist=0;
while(key_hist=(TKey*)nexthist())
{
int cycle=-10;
if(strcmp(key_hist->GetClassName(),"TH1D")==0)
{
TH1D *h=0;
int cycleh=key_hist->GetCycle();
if(cycleh<cycle) { cout<<"Skipping..."<<endl; continue; }
if(cycle<cycleh) cycle=cycleh;
h=(TH1D*)key_hist->ReadObj();
if(!h)
{
cout<<"Cannot read: "<<key_hist->GetName()<<endl;
exit(-2);
}
TH1D *eh = (TH1D*) a->histograms->FindObject(h->GetName());
if(!eh) continue;
if(eh->GetNbinsX()!=h->GetNbinsX() ||
eh->GetXaxis()->GetXmax()!=h->GetXaxis()->GetXmax())
return -1;
eh->Add(h);
}
}
a->SetNEntries(a->GetNEntries()+b->GetNEntries());
a->SetSumw(a->GetSumw()+b->GetSumw());
a->SetSumw2(a->GetSumw2()+b->GetSumw2());
return 0;
}
std::pair<float,float> getFitRange(TH1D& hist) {
int maxBin = hist.GetMaximumBin();
float targetVal = hist.GetBinContent( maxBin ) /2.;
int nBins = hist.GetNbinsX();
std::pair<float,float> results = {hist.GetBinLowEdge(1),hist.GetBinLowEdge(nBins+1)};
int diff=0;
while( maxBin-(++diff) >0) {
if( hist.GetBinContent(maxBin-diff) < targetVal ){
results.first = hist.GetBinCenter(maxBin-diff);
break;
}
}
diff=0;
while( maxBin+(++diff) <=nBins) {
if( hist.GetBinContent(maxBin+diff) < targetVal ){
results.second = hist.GetBinCenter(maxBin+diff);
break;
}
}
return results;
}
void getStatPowerLoss() {
TFile* mc = TFile::Open("MyMCPileupHistogram.root");
TH1D* hmc = (TH1D*) mc->Get("pileup");
TFile* wgt = TFile::Open("MyRatioPileupHistogram.root");
TH1D* hwgt = (TH1D*) wgt->Get("pileup");
double old_sumx = 0;
double old_sumx2 = 0;
double new_sumx = 0;
double new_sumx2 = 0;
for (int i=0; i<=hmc->GetNbinsX()+1; i++) {
double val = hmc->GetBinContent(i);
double factor = hwgt->GetBinContent(i);
old_sumx += val;
old_sumx2 += val*val;
new_sumx += val*factor;
new_sumx2 += val*factor*val*factor;
}
double old_stat = old_sumx*old_sumx/old_sumx2;
double new_stat = new_sumx*new_sumx/new_sumx2;
double loss = 1-new_stat/old_stat;
cout << "The fractional loss in statistical power is " << std::setprecision(4) << loss*100 << "%" << endl;
mc->Close();
wgt->Close();
}
Double_t fTH1toTF1(Double_t *x, Double_t *par)
{
Double_t g4 = x[0]; // -> g^4 value
Int_t mll = (Int_t)par[0]; // -> dilepton invariant mass bin number
TH2D* h2 = (TH2D*)h2Template->Clone();
TH1D* hTmp = (TH1D*)TH2toTH1(h2,mll); // TH1 histogram of g^4 in the dilepton mass bin number mll
Int_t nbinsx = hTmp->GetNbinsX();
Double_t xval = -999.;
if(doInterpolation)
{
Int_t bin = hTmp->FindBin(g4);
if(bin==0 || bin==1) xval = hTmp->GetBinContent(1); // cannot interpolate on the first bin or the underflow
else if(bin==nbinsx+1) xval = hTmp->GetBinContent(bin-1); // cannot interpolate on the last bin or the overflow
else if(bin==nbinsx) xval = hTmp->GetBinContent(bin); // cannot interpolate on the last bin or the overflow
else xval = hTmp->Interpolate(g4); // interpolated dN/dg^4 at g^4, between the 2 adjacent bin centers
}
else
{
Int_t bin = hTmp->FindBin(g4);
if(bin==nbinsx+1) xval = hTmp->GetBinContent(bin-1); // overflow
else if(bin==0) xval = hTmp->GetBinContent(1); // underflow
else xval = hTmp->GetBinContent(bin); // normal
}
delete h2;
delete hTmp;
return xval;
}
/** Personalized
build a TGraphError starting from a TH1F
*/
TGraphErrors buildGEfromH_Personalized (const TH1D & histo)
{
TVectorF xV(histo.GetNbinsX());
TVectorF yV(histo.GetNbinsX());
TVectorF errxV(histo.GetNbinsX());
TVectorF erryV(histo.GetNbinsX());
for (int iBin = 0; iBin<histo.GetNbinsX(); iBin++){
xV[iBin] = histo.GetBinCenter(iBin);
yV[iBin] = histo.GetBinContent(iBin);
errxV[iBin] = 0;
// histo.GetBinWidth(iBin);
erryV[iBin] = histo.GetBinError(iBin);
}
TGraphErrors g (xV, yV, errxV, erryV) ;
return g ;
}
void makeGaussianSignals(SigData_t& m_sigdata)
{
//std::vector<TH1D *> vgsh(NUMCHAN);
std::vector<TH1D *> vcdfh(NUMCHAN);
if( m_sigdata.find("gs") == m_sigdata.end() ) {
cerr << "Gaussian signal data not found, not making CDF signal!" << endl;
return;
}
for (int ichan=0; ichan<NUMCHAN; ichan++) {
TH1D *cdfh;
TString channame(channames[ichan]);
TString name;
TH1D * gsh = m_sigdata["gs"].at(ichan);
assert(gsh) ;
#if 0
name = "Signalgs_"+channame;
gsh = (TH1D *)tch->Clone(name.Data());
assert(gsh);
gsh->SetTitle("Gaussian signal");
gsh->Reset();
TF1 *g = (TF1 *)gROOT->GetFunction("gaus");
g->SetParameters(1,gaussian_mean_mass_gev,gaussian_mass_sigma_gev);
gsh->FillRandom("gaus",100000);
// norm to 1pb signal with 1/fb integrated luminosity
double norm = 1000 * gseffxacc[ichan]/gsh->Integral(0,gsh->GetNbinsX()+1,"width");
//gsh->Scale(norm/eff_fudgefactor); // kludge: pre-undo the fudge in the next module
gsh->Scale(norm);
vgsh[ichan] = gsh;
#endif
// New CDF bump, same as Gauss but set to CDF (obs/theor)*(LHC theor) = 3.43pb
cdfh = (TH1D *)gsh->Clone("CDFbump");
cdfh->Scale(3.43);
vcdfh[ichan] = cdfh;
cdfh->Draw();
gsh->Draw("same");
} // channel loop
//m_sigdata["gs"] = vgsh;
m_sigdata["cdf"] = vcdfh;
} // makeGaussianSignals
void Normalize(TH1D &h, double normalization, bool norm_per_avg_width) {
int nbins = h.GetNbinsX();
double low = h.GetBinLowEdge(1);
double high = h.GetBinLowEdge(nbins+1);
double width = (high-low)/nbins;
if(norm_per_avg_width) normalization *= width;
double integral = h.Integral("width");
h.Scale(normalization/integral);
}
// Draw 1D histos
TH1D *plot1Dhisto(double intLumi,TFile *fileName,TString folderName,TString histoName,int color,int rebin,float xMin,float xMax,TString xName, TString yName,TString sampleName,bool mc) {
TH1D *hTemp = (TH1D*)fileName->Get(folderName+"/"+histoName);
hTemp->SetName(histoName+"_"+sampleName);
if (mc){
hTemp->Scale(intLumi/100.);
}
hTemp->Rebin(rebin);
hTemp->SetLineColor(color);
hTemp->SetLineWidth(5);
hTemp->GetXaxis()->SetRangeUser(xMin,xMax);
hTemp->GetXaxis()->SetTitle(xName);
hTemp->GetXaxis()->SetTitleSize(0.06);
hTemp->GetXaxis()->SetLabelSize(0.06);
hTemp->GetYaxis()->SetTitle(yName);
hTemp->GetYaxis()->SetTitleSize(0.06);
hTemp->GetYaxis()->SetLabelSize(0.06);
hTemp->SetTitleOffset(1.5, "Y");
// last/first bin: put over/underflow
hTemp->SetBinContent(hTemp->FindBin(xMax),hTemp->Integral(hTemp->FindBin(xMax),hTemp->GetNbinsX()+1));
hTemp->SetBinContent(hTemp->FindBin(xMin),hTemp->Integral(-1,hTemp->FindBin(xMin)));
hTemp->SetBinError(hTemp->FindBin(xMax),sqrt(hTemp->Integral(hTemp->FindBin(xMax),hTemp->GetNbinsX()+1)));
hTemp->SetBinError(hTemp->FindBin(xMin),sqrt(hTemp->Integral(-1,hTemp->FindBin(xMin))));
//fileName->Close();
/*
if (histoName != "LP_tot") {
if (histoName != "SumLepPt_tot") {
if ((folderName == "ANplots150_NOLP")) { hTemp->GetXaxis()->SetRangeUser(0.,300.); }
if ((folderName == "ANplots250_NOLP")) { hTemp->GetXaxis()->SetRangeUser(0.,400.); }
if ((folderName == "ANplots350_NOLP")) { hTemp->GetXaxis()->SetRangeUser(0.,500.); }
if ((folderName == "ANplots450_NOLP")) { hTemp->GetXaxis()->SetRangeUser(0.,1000.); }
}
else {
if ((folderName == "ANplots150_NOLP")) { hTemp->GetXaxis()->SetRangeUser(100.,300.); }
if ((folderName == "ANplots250_NOLP")) { hTemp->GetXaxis()->SetRangeUser(200.,400.); }
if ((folderName == "ANplots350_NOLP")) { hTemp->GetXaxis()->SetRangeUser(300.,500.); }
if ((folderName == "ANplots450_NOLP")) { hTemp->GetXaxis()->SetRangeUser(400.,1000.); }
}
}
*/
return hTemp;
} // ~ end of plot1Dhisto function
TH1D* Prediction::GetScaledHisto(TH1D* histo, float scale_fact, float scale_fact_err){
// takes histo, scale factor and uncertainty on scale factor
// and returns scaled and rebinned histo with 1 bin with uncertainty on scale factor propagated.
TH1D *h = (TH1D*) histo->Clone(histo->GetName());
h->Rebin(h->GetNbinsX());
h->SetBinError(1, sqrt(h->GetBinError(1)* h->GetBinError(1) *scale_fact *scale_fact +
h->GetBinContent(1)*h->GetBinContent(1) *scale_fact_err*scale_fact_err));
h->SetBinContent(1, h->GetBinContent(1)*scale_fact);
return h;
}
// Called just after the main event loop
// Can be used to write things out, dump a summary etc
// Return non-zero to indicate a problem
int TemplateCreator::AfterLastEntry(TGlobalData* gData, const TSetupData* setup){
// Print extra info if we're debugging this module:
if(Debug()){
cout<<"-----I'm debugging TemplateCreator::AfterLastEntry()"<<endl;
}
// Print to stdout the percentage of successful fit for each channel
StringPulseIslandMap::const_iterator it;
for(it = gData->fPulseIslandToChannelMap.begin(); it != gData->fPulseIslandToChannelMap.end(); ++it){
std::string bankname = it->first;
std::string detname = setup->GetDetectorName(bankname);
TH1D* hTemplate = fTemplates[detname];
if (!hTemplate) { // if there's no template been created for this channel
continue;
}
int& n_fit_attempts = fNFitAttempts[detname]; // number of pulses we try to fit to
int& n_successful_fits = fNSuccessfulFits[detname];
std::cout << "TemplateCreator: " << detname << ": " << n_fit_attempts << " fits attempted with " << n_successful_fits << " successful (" << ((double)n_successful_fits/(double)n_fit_attempts)*100 << "%)" << std::endl;
// Normalise the template so that it has pedestal=0 and amplitude=1
// Work out the pedestal of the template from the first 5 bins
int n_bins_for_template_pedestal = 5;
double total = 0;
for (int iBin = 1; iBin <= n_bins_for_template_pedestal; ++iBin) {
total += hTemplate->GetBinContent(iBin);
}
double template_pedestal = total / n_bins_for_template_pedestal;
// std::cout << detname << ": Template Pedestal = " << template_pedestal << std::endl;
// Subtract off the pedesal
for (int iBin = 1; iBin <= hTemplate->GetNbinsX(); ++iBin) {
double old_value = hTemplate->GetBinContent(iBin);
double new_value = old_value - template_pedestal;
hTemplate->SetBinContent(iBin, new_value);
}
// Integrate over the histogram and scale to give an area of 1
double integral = std::fabs(hTemplate->Integral()); // want the absolute value for the integral because of the negative polarity pulses
hTemplate->Scale(1.0/integral);
integral = std::fabs(hTemplate->Integral());
// Save the template to the file
fTemplateArchive->SaveTemplate(hTemplate);
}
// Clean up the template archive
delete fTemplateArchive;
return 0;
}
void testIntegration(){
TFile* infile = new TFile("/Users/keithlandry/Desktop/testPtHist.root");
TH1D * h = infile->Get("Pt");
int bmin = 751;
int bmax = bmin+1;
double binval = 0;
int numberOfPairs = 0;
cout << "starting at bmin = " << bmin << " bmax = " << bmax << endl;
cout << (double)h->GetEntries()/9.0 << endl;
for (int i=0; i < h->GetNbinsX()-bmin; i++)
{
bmax++;
cout << " i = " << i << " bmax = " << bmax << endl;
int integ = h->Integral(bmin,bmax);
cout << bmax << " " << integ << endl;
binval += h->GetBinContent(bmax)*h->GetBinCenter(bmax);
numberOfPairs += h->GetBinContent(bmax);
if (integ > (double)h->GetEntries()/9.0)
{
cout << bmax << " " << integ << endl;
lastI = i;
break;
}
if (bmax == 1000)
{
break;
}
}
cout << "avg val of bin " << (double)binval/numberOfPairs << endl;
cout << " Pt = " << h->GetBinCenter(bmax) << endl;
}
void FindMCToDataScaleFactor() {
std::string data_filename = "~/data/out/v92/total.root";
TFile* data_file = new TFile(data_filename.c_str(), "READ");
std::string data_plotname = "TME_Al50_EvdE/all_particles/SiL_EvdE";
TH2F* hEvdE_data = (TH2F*) data_file->Get(data_plotname.c_str());
hEvdE_data->SetDirectory(0);
data_file->Close();
std::string MC_filename = "plots.root";
TFile* MC_file = new TFile(MC_filename.c_str(), "READ");
std::string MC_plotname = "hAll_EvdE_SiL";
TH2F* hEvdE_MC = (TH2F*) MC_file->Get(MC_plotname.c_str());
hEvdE_MC->SetDirectory(0);
MC_file->Close();
double energy_slice = 3000;
int energy_slice_bin = hEvdE_data->GetXaxis()->FindBin(energy_slice);
TH1D* hDataProjection = hEvdE_data->ProjectionY("_py", energy_slice_bin, energy_slice_bin);
energy_slice_bin = hEvdE_MC->GetXaxis()->FindBin(energy_slice);
TH1D* hMCProjection = hEvdE_MC->ProjectionY("_py", energy_slice_bin, energy_slice_bin);
TFitResultPtr data_fit_result = hDataProjection->Fit("gaus", "S");
TFitResultPtr MC_fit_result = hMCProjection->Fit("gaus", "S");
hDataProjection->SetLineColor(kBlack);
hDataProjection->GetXaxis()->SetRangeUser(0, energy_slice);
hDataProjection->Draw();
hMCProjection->SetLineColor(kRed);
hMCProjection->GetXaxis()->SetRangeUser(0, energy_slice);
hMCProjection->Draw("SAME");
//EvdE_data->Draw("COLZ");
double data_mean = data_fit_result->Parameter(1);
double MC_mean = MC_fit_result->Parameter(1);
double scale_factor = data_mean / MC_mean;
std::cout << "data / MC = " << data_mean << " / " << MC_mean << " = " << scale_factor << std::endl;
// Go through the MC projection and scale each bin by the scale factor
int n_bins = hMCProjection->GetNbinsX();
double min_x = hMCProjection->GetXaxis()->GetXmin();
double max_x = hMCProjection->GetXaxis()->GetXmax();
TH1F* hMCProjection_scaled = new TH1F("hMCProjection_scaled", "", n_bins,min_x,max_x);
for (int i_bin = 1; i_bin <= n_bins; ++i_bin) {
double old_energy = hMCProjection->GetBinLowEdge(i_bin);
double new_energy = old_energy * scale_factor;
double old_bin_content = hMCProjection->GetBinContent(i_bin);
hMCProjection_scaled->Fill(new_energy, old_bin_content);
}
hMCProjection_scaled->Draw();
hDataProjection->Draw("SAME");
}
//################################################################################################################################
// Get the 68% confindence interval of mu1/mu2
void getPoissonIntervalls(double mu1, double mu2){
double result = mu1/mu2;
TH1D *expHist = new TH1D("mu1/mu2","mu1/mu2",1000,0,1);
TRandom3 rand1(0);
TRandom3 rand2(0);
cout<<"mu1 = "<<mu1<<endl;
cout<<"mu2 = "<<mu2<<endl;
cout<<"ratio = "<<result<<endl;
for(int i=0; i<10000000; i++){
expHist->Fill(1.*rand1.Poisson(mu1)/rand2.Poisson(mu2));
}
// Get now the 68% upper and lower interval
double errUp = 0;
double errLow = 0;
for(int i=1; i<=expHist->GetNbinsX();i++){
double upperIntegral = expHist->Integral(i,expHist->GetNbinsX());
double lowerIntegral = expHist->Integral(1,i);
if(abs(upperIntegral/expHist->Integral()-0.32)<0.02){
cout<<"upper bound = "<<expHist->GetBinCenter(i)<<endl;
errUp = expHist->GetBinCenter(i)-result;
}
if(abs(lowerIntegral/expHist->Integral()-0.32)<0.02){
cout<<"lower bound = "<<expHist->GetBinCenter(i)<<endl;
errLow = result - expHist->GetBinCenter(i);
}
}
cout<<"error Up = "<<errUp<<endl;
cout<<"error Low = "<<errLow<<endl;
TCanvas *c = new TCanvas("cExp","cExp",0,0,500,500);
c->cd();
expHist->Draw();
}
TH1D* Prediction::GetScaledHisto(TH1D* histo, float scale_fact, float scale_fact_err, int ngroup){
// takes histo, scale factor and uncertainty on scale factor
// and returns scaled and rebinned histo with ngroup bins merged into 1 with uncertainty on scale factor propagated.
if(ngroup>=histo->GetNbinsX()) ngroup=histo->GetNbinsX();
TH1D *h = (TH1D*) histo->Clone(histo->GetName());
h->Rebin(ngroup);
for(int i=1; i<=h->GetNbinsX(); ++i){
h->SetBinError(i, sqrt(h->GetBinError(i)* h->GetBinError(i) *scale_fact *scale_fact +
h->GetBinContent(i)*h->GetBinContent(i) *scale_fact_err*scale_fact_err));
h->SetBinContent(i, h->GetBinContent(i)*scale_fact);
}
return h;
}
TH1D *
GetITSTPCSpectrum(TFile *file, Int_t part, Int_t charge, Int_t cent)
{
TList *list = (TList *)file->Get("output");
TH1D *hin = (TH1D *)list->FindObject(Form("h_%s_%s_cen_%d", ITSTPCPartName[part], ITSTPCChargeName[charge], cent + 1));
if (!hin) return NULL;
TH1D *h = new TH1D(Form("hITSTPC_cent%d_%s_%s", cent, AliPID::ParticleName(part), chargeName[charge]), "ITSTPC", NptBins, ptBin);
Double_t pt, width, value, error;
Int_t bin;
for (Int_t ipt = 0; ipt < NptBins; ipt++) {
/* get input bin */
pt = h->GetBinCenter(ipt + 1);
width = h->GetBinWidth(ipt + 1);
bin = hin->FindBin(pt);
/* sanity check */
if (TMath::Abs(hin->GetBinCenter(bin) - pt) > 0.001 ||
TMath::Abs(hin->GetBinWidth(bin) - width) > 0.001)
continue;
/* copy bin */
value = hin->GetBinContent(bin);
error = hin->GetBinError(bin);
h->SetBinContent(ipt + 1, value);
h->SetBinError(ipt + 1, error);
}
#if 0
/* add systematic error */
Double_t sys;
if (part == 2) sys = 0.5;
else sys = 0.1;
Double_t cont, conte;
for (Int_t ipt = 0; ipt < h->GetNbinsX(); ipt++) {
cont = h->GetBinContent(ipt + 1);
conte = h->GetBinError(ipt + 1);
conte = TMath::Sqrt(conte * conte + sys * sys * cont * cont);
h->SetBinError(ipt + 1, conte);
}
#endif
h->SetTitle("ITSTPC");
h->SetLineWidth(1);
h->SetLineColor(1);
h->SetMarkerStyle(21);
h->SetMarkerColor(2);
h->SetFillStyle(0);
h->SetFillColor(0);
return h;
}
void Yield1S_1D(){
TFile *f = new TFile("SigmaDATA_RapInt_3SBin.root");
TH1D *H;
H = (TH1D*)gFile->Get("hYield1S");
double tot(0.); double totE(0.);
ofstream OUT("Yield_1S_1D.tex");
OUT << "% ----------------------------------------------------------------------" << endl;
OUT << "% -- Yields" << endl;
for ( int x = 1; x <= H->GetNbinsX(); ++x ){
OUT << Form("\\vdef{%iS_bin%iLowEdge} {\\ensuremath{ {%.2f } } }",1, x, H->GetXaxis()->GetBinLowEdge(x) ) << endl;
if ( x == H->GetNbinsX() ) OUT << Form("\\vdef{%iS_bin%iHighEdge} {\\ensuremath{ {%.2f } } }",1 , x, H->GetXaxis()->GetBinUpEdge(x) ) << endl;
OUT << Form("\\vdef{%iS_bin%iContent} {\\ensuremath{ {%.0f } } }",1, x, H->GetBinContent(x) ) << endl;
OUT << Form("\\vdef{%iS_bin%iError} {\\ensuremath{ {%.0f } } }",1, x, H->GetBinError(x) ) << endl;
tot += H->GetBinContent(x);
totE += (H->GetBinError(x)*H->GetBinError(x));
}
OUT << Form("\\vdef{sum%iS} {\\ensuremath{ {%.0f } } }",1, tot) << endl;
OUT << Form("\\vdef{sum%iSError} {\\ensuremath{ {%.0f } } }",1 , TMath::Sqrt(totE) ) << endl;
OUT.close();
}
void fitpapvar(const char* infilename, const char* histname) {
TFile* infile = new TFile(Form("%s",infilename),"read");
TH1D* hcf = (TH1D*)infile->Get(histname);
hcf->GetXaxis()->SetRangeUser(0,2);
TF1 *fc2 = new TF1("fc2","[3]+[2]*TMath::Gaus(x,[0],[1])",0.4,1);
fc2->SetParameters(1.5,0.3,-0.2,1);
// TF1 *fc2 = new TF1("fc2","[1]+[0]*x*x",0,1);
// fc2->SetParameters(-0.01,1.0);
// TF1 *fc2 = new TF1("fc2","[2]+[1]*x*x*x*x*x",0,1);
// fc2->SetParameters(-0.01,0.01,1.0);
// TF1 *fc2 = new TF1("fc2","[3]+[2]*x*x+[1]*x*x*x+[0]*x*x*x*x",0.,1);
// fc2->SetParameters(-0.01,0.01,1.0,1.0);
hcf->Fit("fc2","r","",0.3,1);
TH1D* hnew = new TH1D("hnew","hnew",hcf->GetNbinsX(),0,1);
for(int i=1;i<=hcf->GetNbinsX();++i){
// cout << i << endl;
// cout << hcf->GetBinContent(i)/fc2->Eval(2.*i/hcf->GetNbinsX()) << endl;
// cout << hcf->GetBinContent(i) << endl;
// cout << fc2->Eval(2.*i/hcf->GetNbinsX()) << endl << endl;
hnew->SetBinContent(i, hcf->GetBinContent(i)/fc2->Eval(1.*i/hcf->GetNbinsX()));
hnew->SetBinError(i, hcf->GetBinError(i));
}
hnew->Draw("same");
fc2->Draw("same");
hnew->SetName(Form("divp4%s",histname));
TFile* ofile = new TFile(Form("divp4%s",infilename),"update");
hnew->Write();
hcf->Write();
ofile->Close();
}
void MergeOverflow(TH1D &h, bool merge_underflow, bool merge_overflow) {
if(merge_underflow) {
h.SetBinContent(1, h.GetBinContent(0)+h.GetBinContent(1));
h.SetBinContent(0, 0.);
h.SetBinError(1, hypot(h.GetBinError(0), h.GetBinError(1)));
h.SetBinError(0, 0.);
}
int nbins = h.GetNbinsX();
if(merge_overflow) {
h.SetBinContent(nbins, h.GetBinContent(nbins)+h.GetBinContent(nbins+1));
h.SetBinContent(nbins+1, 0.);
h.SetBinError(nbins, hypot(h.GetBinError(nbins), h.GetBinError(nbins+1)));
h.SetBinError(nbins+1, 0.);
}
}
TH1D *getpuweights(TFile *file, TH1D *target) {
TDirectory *dirmcpv = (TDirectory*)file->FindObjectAny("AnaFwkMod");
TH1D *hnpu = (TH1D*)dirmcpv->Get("hNPU");
TH1D *hpumc = (TH1D*)hnpu->Clone();
hpumc->Sumw2();
hpumc->Scale(1.0/hpumc->Integral(0,hpumc->GetNbinsX()+1));
TH1D *htargettmp = new TH1D("htargettmp","", hpumc->GetNbinsX(), hpumc->GetXaxis()->GetXmin(), hpumc->GetXaxis()->GetXmax());
htargettmp->Sumw2();
for (int ibin = 0; ibin<=(htargettmp->GetNbinsX()+1); ++ibin) {
htargettmp->Fill(htargettmp->GetBinCenter(ibin),target->GetBinContent(target->FindFixBin(htargettmp->GetBinCenter(ibin))));
}
htargettmp->Scale(1.0/htargettmp->Integral(0,htargettmp->GetNbinsX()+1));
TH1D *puweights = new TH1D((*htargettmp)/(*hpumc));
delete htargettmp;
return puweights;
}
double countDataError(TChain* chain, TCut cut)
{
// Create temporary histogram
TH1D* tmp = new TH1D("tmp", "tmp", 30, 0, 1000);
double DataError = 0;
tmp->Sumw2();
chain->Draw("Njet>>tmp", cut, "goff");
for(int i=0; i<=(tmp->GetNbinsX()+1); i++)
DataError += tmp->GetBinError(i);
delete tmp;
return DataError;
}
void AdjustDensityForBinWidth(TH1D &h) {
double entries = h.GetEntries();
int nbins = h.GetNbinsX();
double low = h.GetBinLowEdge(1);
double high = h.GetBinLowEdge(nbins+1);
double width = (high-low)/nbins;
for(int bin = 1; bin <= nbins; ++bin) {
double content = h.GetBinContent(bin);
double error = h.GetBinError(bin);
double this_width = h.GetBinWidth(bin);
double scale = width/this_width;
h.SetBinContent(bin, content*scale);
h.SetBinError(bin, error*scale);
}
h.SetEntries(entries);
}
//=== FUNCTION DEFINITIONS ======================================================================================
TTree* toyHist(int iNToys, bool iDoMu,std::string iName,TH1D *iData,TH1D *iW,TH1D *iEWK,TH1D *iAntiData,TH1D *iAntiW,TH1D *iAntiEWK,double *iOriginalResults) {
TCanvas *c = 0;
TTree *tree = new TTree(("Toys"+iName).c_str(),("Toys"+iName).c_str());
float *vals = new float[16];
for(int i0 = 0; i0 < 16; i0++) vals[i0] = 0.;
tree->Branch("nsig" ,&vals[0] ,"Val0/F");
tree->Branch("newk" ,&vals[1] ,"Val1/F");
tree->Branch("nqcd" ,&vals[2] ,"Val2/F");
tree->Branch("nantisig" ,&vals[3] ,"Val3/F");
tree->Branch("nantiewk" ,&vals[4] ,"Val4/F");
tree->Branch("nantiqcd" ,&vals[5] ,"Val5/F");
tree->Branch("sigma" ,&vals[6] ,"Val6/F");
tree->Branch("a1" ,&vals[7] ,"Val7/F");
tree->Branch("nsig_e" ,&vals[8] ,"Val8/F");
tree->Branch("newk_e" ,&vals[9] ,"Val9/F");
tree->Branch("nqcd_e" ,&vals[10],"Val10/F");
tree->Branch("nantisig_e",&vals[11],"Val11/F");
tree->Branch("nantiewk_e",&vals[12],"Val12/F");
tree->Branch("nantiqcd_e",&vals[13],"Val13/F");
tree->Branch("sigma_e" ,&vals[14],"Val14/F");
tree->Branch("a1_e" ,&vals[15],"Val15/F");
//Set The first entry of the tree to be the default values
for(int i1 = 0; i1 < 16; i1++) vals[i1] = float(iOriginalResults[i1]);
tree->Fill();
TH1D *pData = 0;
TH1D *pAntiData = 0;
for(int i0 = 0; i0 < iNToys; i0++) {
std::stringstream pSS;
pSS << "Hist" << i0;
pData = (TH1D*) iData ->Clone((pSS.str()+"A").c_str());
pAntiData = (TH1D*) iAntiData->Clone((pSS.str()+"B").c_str());
for(int i1 = 0; i1 < pData ->GetNbinsX()+1; i1++) pData ->SetBinContent(i1,0);
for(int i1 = 0; i1 < pAntiData->GetNbinsX()+1; i1++) pAntiData->SetBinContent(i1,0);
pData ->FillRandom(iData, iData ->Integral());
pAntiData->FillRandom(iAntiData,iAntiData->Integral());
cout <<"==> " << pData->Integral() << " -- " << iData->Integral() << endl;
double* pVals = fitHist(c,iDoMu,0,pSS.str(),pData,iW,iEWK,pAntiData,iAntiW,iAntiEWK,100,100,100,100);
for(int i1 = 0; i1 < 16; i1++) vals[i1] = float(pVals[i1]);
tree->Fill();
delete pData;
delete pAntiData;
}
return tree;
}
TH1D *HistoRatio (TH1D *hisNum, TH1D *hisDen){
//Graph Ratio Clone
TH1D *Ratio;
Ratio = (TH1D*)hisNum->Clone();
Ratio->Divide(hisDen);
for(int ibin=1;ibin<=Ratio->GetNbinsX();ibin++) {
if (Ratio->GetBinContent(ibin) == 0.0 ) {
Ratio->SetBinContent(ibin, 1.0);
Ratio->SetBinError(ibin, 0.0);
}
}
Ratio->SetFillColor(0);
Ratio->SetLineColor(kGray+2);
// Ratio->SetLineColor(kMagenta-5);
Ratio->SetLineWidth(1);
Ratio->SetTitle("");
Ratio->GetYaxis()->SetTitle("Obs/Exp");
Ratio->GetYaxis()->CenterTitle();
Ratio->GetYaxis()->SetTitleFont(42);
Ratio->GetYaxis()->SetTitleSize(0.135);
Ratio->GetYaxis()->SetTitleOffset(0.28);
Ratio->GetYaxis()->SetLabelFont(42);
Ratio->GetYaxis()->SetLabelSize(0.115);
Ratio->GetYaxis()->SetNdivisions(402);
Ratio->GetXaxis()->SetTitle("CSVv2 bin");
Ratio->GetXaxis()->SetNdivisions(509); //(402)
Ratio->GetXaxis()->SetTitleOffset(1.1);
Ratio->GetXaxis()->SetTitleFont(42);
Ratio->GetXaxis()->SetTitleSize(0.16);
Ratio->GetXaxis()->SetTitleFont(42);
Ratio->GetXaxis()->SetLabelSize(0.14);
Ratio->SetMinimum(0.4);
Ratio->SetMaximum(1.6);
return Ratio;
}