SavePadToPDF(relativeErrorVariation);
Style(AddLegend(gPad));
relativeErrorVariation->Write();
+
+ // now smoothen the diced response error (as it is expected to be flat)
+ // this is done by fitting a constant to the diced resonse error histo
+ //
+ TF1* lin = new TF1("lin", "[0]", rangeLow, rangeUp);
+ relativeErrorVariationInUp->Fit(lin, "L", "", rangeLow, rangeUp);
+ if(!gMinuit->fISW[1] == 3) printf(" fit is NOT ok ! " );
+ for(Int_t i(0); i < relativeErrorVariationInUp->GetNbinsX(); i++) {
+ relativeErrorVariationInUp->SetBinContent(i+1, lin->GetParameter(0));
+ }
+ relativeErrorVariationInLow->Fit(lin, "L", "", rangeLow, rangeUp);
+ printf(" > Fit over diced resonse, new value for all bins is %.4f < \n ", lin->GetParameter(0));
+ for(Int_t i(0); i < relativeErrorVariationInUp->GetNbinsX(); i++) {
+ relativeErrorVariationInLow->SetBinContent(i+1, 0);//lin->GetParameter(0));
+ }
+ relativeErrorVariationOutUp->Fit(lin, "L", "", rangeLow, rangeUp);
+ printf(" > Fit over diced resonse, new value for all bins is %.4f < \n ", lin->GetParameter(0));
+ for(Int_t i(0); i < relativeErrorVariationInUp->GetNbinsX(); i++) {
+ relativeErrorVariationOutUp->SetBinContent(i+1, lin->GetParameter(0));
+ }
+ relativeErrorVariationOutLow->Fit(lin, "L", "", rangeLow, rangeUp);
+ printf(" > Fit over diced resonse, new value for all bins is %.4f < \n ", lin->GetParameter(0));
+ for(Int_t i(0); i < relativeErrorVariationInUp->GetNbinsX(); i++) {
+ relativeErrorVariationOutLow->SetBinContent(i+1, 0);//lin->GetParameter(0));
+ }
+
+
+
}
}
// call the functions for a second set of systematic sources
rangeLow,
rangeUp,
readMe,
- "recBin");
+ "recBin",
+ fRMS);
if(relativeErrorRecBinOutUp) {
// canvas with the error from regularization strength
TCanvas* relativeErrorRecBin(new TCanvas("relativeErrorRecBin"," relativeErrorRecBin"));
if(relativeErrorMethodInLow) dInLow = relativeErrorMethodInLow->GetBinContent(b+1);
if(relativeErrorMethodOutLow) dOutLow = relativeErrorMethodOutLow->GetBinContent(b+1);
if(fSymmRMS) { // take first category as symmetric
-// aInLow = aInUp*1.5;
-// aOutLow = aOutUp*1.5;
aInLow = aInUp;
aOutLow = aOutUp;
+ cInLow = cInUp;
+ cOutLow = cOutUp; // other sources
if(dInLow < dInUp) dInLow = dInUp;
if(dOutLow < dOutUp) dOutLow = dOutUp;
}
t->Draw("same");
return t;
}
- static TLatex* AddLogo(Bool_t logo, Double_t xmin = .59, Double_t ymax = .81) {
- return AddTLatex(xmin, ymax, logo ? "ALICE Preliminary" : "ALICE");
+ static TLatex* AddLogo(Int_t logo, Double_t xmin = .59, Double_t ymax = .81) {
+ if(logo == 0) return AddTLatex(xmin, ymax, "ALICE");
+ else if (logo == 1) return AddTLatex(xmin, ymax, "ALICE Preliminary");
+ else if (logo == 2) return AddTLatex(xmin, ymax, "ALICE Simulation");
+ return 0x0;
}
static TLatex* AddSystem() {
return AddTLatex(0.55, 87, "Pb-Pb #sqrt{#it{s}}}_{NN} = 2.76 TeV");
mgr->ConnectOutput (eTask, 1, mgr->CreateContainer(Form("%s_container", fileName.Data()), TList::Class(), AliAnalysisManager::kOutputContainer, fileName.Data()));
return eTask;
}
+
+namespace TaskJetFlowMC{
+ TF1* GetSpectrum() {
+ TF1* spectrum = new TF1("fspectrum", "[0]*(TMath::Power([1], 2)*x*TMath::Exp(-[1]*x))+(x>1)*[2]*(1.17676e-01*TMath::Sqrt(0.1396*0.1396+x*x)*TMath::Power(1.+1./[3]/8.21795e-01*TMath::Sqrt(0.1396*0.1396+x*x),-1.*[3]))*(1/(1 + TMath::Exp(-(x - [4])/[5])))", .2, 200.);
+ fspectrum->SetParameters(2434401791.20528 ,2.98507 ,10069622.25117 ,5.50000 ,2.80000 ,0.20000 );
+ return fspectrum;
+ }
+}