void GetFlow(){
gROOT->Reset();
gSystem->Load("getCorr_C.so");
Float_t PI=3.1415926535;
const Int_t NPt = 18;
const Int_t NCENT = 11;
const Int_t NYo = 9;
TH1F* hPsiPR[1][NCENT][NYo][NPt];
TH1F* hPsiAB[1][NCENT][NYo][NPt];
TH1F* hPsiEP[1][NCENT][NYo][NPt];
TH1F* hMulTr[1][NCENT][NYo][NPt];
InitgStyle();
flowhist flow;
//flow.ReadHist("/home/peter/Documents/WorkLocal/WorkFiles/HADES/pionflow/anaflow/12apr108.root");
/*for(Int_t iF=0;iF<1;iF++){
for(Int_t iC=0;iC<NCENT;iC++){
for(Int_t iY=0;iY<NYo;iY++){
for(Int_t iP=0;iP<NPt;iP++){
flow.GetPhiPR(iC,iY,iP,hPsiPR[iF][iC][iY][iP]);
flow.GetPhiAB(iC,iY,iP,hPsiAB[iF][iC][iY][iP]);
flow.GetPhiEP(iC,iY,iP,hPsiEP[iF][iC][iY][iP]);
flow.GetMulTr(iC,iY,iP,hMulTr[iF][iC][iY][iP]);
}
}
}
}*/
}
void
plot2DSignalAnalytisch(
TString filename,
TString histogramName,
TString xtitle = "x",
TString ytitle = "y",
double rebinx = 1,
double rebiny = 1,
double xtitleOffset = 1.1,
double ytitleOffset = 1.3
)
{
// {{{
InitgStyle();
//gStyle->SetOptStat(0);
//gCanvas = new TCanvas("gCanvas", "gCanvas", 0, 0, 800, 600);
LoadHistogramTH2D(histogramName , filename, 1.0, histogram);// Summe (SM
//gCanvas->Clear();
histogram->GetXaxis()->SetTitle(xtitle);
histogram->GetXaxis()->SetTitleOffset(xtitleOffset);
histogram->GetYaxis()->SetTitle(ytitle);
histogram->GetYaxis()->SetTitleOffset(ytitleOffset);
//histogram->GetZaxis()->SetTitle("d^{2}#sigma / dM_{#bar{t}}dM_{t} [pb]");
//histogram->GetZaxis()->SetTitleOffset(ytitleOffset);
// gCanvas->Update();
//TF2 *fitFunction = new TF2("fitFunction", HistoSum, -1, 1, -1, 1, 4); //allgemeine "return"-Varianten
//fitFunction->SetParameters(0.9,0.,0.);
TF2 *fitFunction = new TF2("fitFunction", HistoSum, -1, 1, -1, 1, 2);
histogram->Fit(fitFunction, "N");
// for(int i =1; i<=5;i++){
// for(int j=1;j<=5;j++){
// cout << "Bininhalt("<<i<<","<<j<<"): " << histogram->GetBinContent(i,j) << endl;
// }
// }
histogram->RebinX(rebinx);
histogram->RebinY(rebiny);
histogram->Draw("lego");
fitFunction->SetLineColor(kRed);
fitFunction->SetLineWidth(0.5);
fitFunction->Draw("same");
cout << fitFunction->GetChisquare()/fitFunction->GetNDF() << endl;
//gCanvas->Print(epsFilename(filename, histogramName)+".eps");
//cout << histogram[0]->Integral() << endl;
// }}}
};
//-----------------------------------------------------------
struct sample{
TString name;
TTree* tree;
double scale;
int color;
int style;
}
//-----------------------------------------------------------
void DYBackground(){
InitgStyle();
gStyle->SetPadRightMargin(0.2);
gStyle->SetTitleYOffset(1.0);
TCanvas * c1=new TCanvas("c1","c1");
// c1->Divide(1,3);
// c1->cd(1);
cout << "Files einlesen:" << endl;
TFile *fileZmumu = new TFile("CheckSelectionSaveFilters_Zmumu.root");
fileZmumu->cd("Analyze");
gDirectory->pwd();
TTree *TreeZmumu=0; gDirectory->GetObject("Event",TreeZmumu);
TFile *fileZee = new TFile("CheckSelectionSaveFilters_Zee.root");
fileZmumu->cd("Analyze");
gDirectory->pwd();
TTree *TreeZee=0; gDirectory->GetObject("Event",TreeZee);
TFile *fileTtbar = new TFile("CheckSelectionSaveFilters_Ttbar.root");
fileTtbar->cd("Analyze");
gDirectory->pwd();
TTree *TreeTtbar=0; gDirectory->GetObject("Event",TreeTtbar);
cout << "Histogramme anlegen:" << endl;
int binNumber = 30;
TH1D * Histo_Zmumu = new TH1D("Histo_Zmumu","Histo_Zmumu",binNumber,50,150);
TH1D * Histo_Zee = new TH1D("Histo_Zee","Histo_Zee",binNumber,50,150);
TH1D * Histo_Signal = new TH1D("Histo_Signal","Histo_Signal",binNumber,50,150);
TH1D * Histo_TtbarBG = new TH1D("Histo_TtbarBG","Histo_TtbarBG",binNumber,50,150);
cout << "Histogramme fuellen:" << endl;
cout << "Zusaetzlicher MET > 35 - Cut auf Different Flavour Events um Kurvenverlaeufe moeglichst gleich zu haben." << endl;
std::string And = " && ";
std::string SelectionString = "p_Objects && p_OppositeCharge && p_Trigger && p_TwoJets && p_TwoLeptons";
std::string SignalString = "p_Dilepton";
std::string TtbarBGString = "!p_Dilepton";
std::string SameFlavString = "abs(sameFlavour) == 2 && Met > 35";
std::string DiffFlavString = "sameFlavour == 0 && Met > 35";
std::string OutString = "(InvM > 106. || InvM < 76.)";
std::string InString = "(InvM < 106. && InvM > 76.)";
TreeZmumu->Draw("InvM>>Histo_Zmumu", (SelectionString + And + SameFlavString).c_str(),"goff");
TreeZee->Draw("InvM>>Histo_Zee", (SelectionString + And + SameFlavString).c_str(),"goff");
TreeTtbar->Draw("InvM>>Histo_Signal", (SignalString + And + SelectionString + And + SameFlavString).c_str(),"goff");
TreeTtbar->Draw("InvM>>Histo_TtbarBG", (TtbarBGString + And + SelectionString + And + SameFlavString).c_str(),"goff");
cout << "Normierung auf 10pb-1:" << endl;
double ScaleZmumu = 1.056e-2;
double ScaleZee = 7.247e-3;
double ScaleTtbar = 7.268e-3;
Histo_Zmumu->Scale(ScaleZmumu);
Histo_Zee->Scale(ScaleZee);
Histo_Signal->Scale(ScaleTtbar);
Histo_TtbarBG->Scale(ScaleTtbar);
cout << "Different Flavour Histogramme anlegen und fuellen:" << endl;
TH1D * Histo_Zmumu_DF = new TH1D("Histo_Zmumu_DF","Histo_Zmumu_DF",binNumber,50,150);
TH1D * Histo_Zee_DF = new TH1D("Histo_Zee_DF","Histo_Zee_DF",binNumber,50,150);
TH1D * Histo_Signal_DF = new TH1D("Histo_Signal_DF","Histo_Signal_DF",binNumber,50,150);
TH1D * Histo_TtbarBG_DF = new TH1D("Histo_TtbarBG_DF","Histo_TtbarBG_DF",binNumber,50,150);
TreeZmumu->Draw("InvM>>Histo_Zmumu_DF", (SelectionString + And + DiffFlavString).c_str(),"goff");
TreeZee->Draw("InvM>>Histo_Zee_DF", (SelectionString + And + DiffFlavString).c_str(),"goff");
TreeTtbar->Draw("InvM>>Histo_Signal_DF", (SignalString + And + SelectionString + And + DiffFlavString).c_str(),"goff");
TreeTtbar->Draw("InvM>>Histo_TtbarBG_DF", (TtbarBGString + And + SelectionString + And + DiffFlavString).c_str(),"goff");
cout << "Histogramme malen:" << endl;
c1->SetLogy(true);
Histo_Zmumu->Add(Histo_Zee);
int LineWidth = 3;
Histo_Zmumu->SetXTitle("Invariante Masse [GeV]"); Histo_Zmumu->SetYTitle("Ereignisse pro 10pb^{-1}");
int upperLimit = 25.;
Histo_Zmumu->GetYaxis()->SetRangeUser(0.01,upperLimit);
Histo_Zmumu->GetXaxis()->SetTitleOffset(1.1);
Histo_Zmumu->GetYaxis()->SetTitleOffset(1.1);
Histo_Zmumu->SetLineWidth(LineWidth);
Histo_Zmumu->SetLineColor(kRed);
Histo_Zmumu->Draw("");
Histo_Signal->SetLineWidth(LineWidth);
Histo_Signal->SetLineColor(kGreen+2);
Histo_Signal->Draw("same");
Histo_TtbarBG->SetLineWidth(LineWidth);
Histo_TtbarBG->SetLineColor(kBlue);
Histo_TtbarBG->Draw("same");
cout << "Different Flavour Histogramme malen:" << endl;
Histo_Zmumu_DF->Scale(ScaleZmumu);
Histo_Zee_DF->Scale(ScaleZee);
Histo_Signal_DF->Scale(ScaleTtbar);
Histo_TtbarBG_DF->Scale(ScaleTtbar);
Histo_Zmumu_DF->Add(Histo_Zee_DF);
Histo_Zmumu_DF->SetLineWidth(LineWidth);
Histo_Zmumu_DF->SetLineColor(kRed);
Histo_Zmumu_DF->SetLineStyle(2);
Histo_Zmumu_DF->Draw("same");
Histo_Signal_DF->SetLineWidth(LineWidth);
Histo_Signal_DF->SetLineColor(kGreen+2);
Histo_Signal_DF->SetLineStyle(2);
Histo_Signal_DF->Draw("same");
Histo_TtbarBG_DF->SetLineWidth(LineWidth);
Histo_TtbarBG_DF->SetLineColor(kBlue);
Histo_TtbarBG_DF->SetLineStyle(2);
Histo_TtbarBG_DF->Draw("same");
left = new TLine(76.,-0.5,76.,upperLimit);
right = new TLine(106.,-0.5,106.,upperLimit);
left->SetLineWidth(LineWidth);
left->SetLineColor(34);
left->SetLineStyle(2);
right->SetLineWidth(LineWidth);
right->SetLineColor(34);
right->SetLineStyle(2);
left->Draw();
right->Draw();
//Legende
TH1D * Histo_Dummy1 = new TH1D("Histo_Dummy1","Histo_Dummy1",binNumber,50,150);
Histo_Dummy1->SetLineWidth(LineWidth);
Histo_Dummy1->SetLineColor(kBlack);
Histo_Dummy1->SetLineStyle(1);
TH1D * Histo_Dummy2 = new TH1D("Histo_Dummy2","Histo_Dummy2",binNumber,50,150);
Histo_Dummy2->SetLineWidth(LineWidth);
Histo_Dummy2->SetLineColor(kBlack);
Histo_Dummy2->SetLineStyle(2);
TLegend *legende1 = new TLegend(0.53,0.76,0.88,0.89);
legende1->AddEntry(Histo_Signal,"Signal","l");
legende1->AddEntry(Histo_Zmumu,"Drell-Yan","l");
legende1->AddEntry(Histo_TtbarBG,"andere t #bar{t}","l");
legende1->SetEntrySeparation(0.1);
legende1->Draw();
TLegend *legende2 = new TLegend(0.53,0.65,0.88,0.75);
legende2->AddEntry(Histo_Dummy1,"ee/#mu#mu-Events","l");
legende2->AddEntry(Histo_Dummy2,"e#mu-Events","l");
legende2->SetEntrySeparation(0.1);
legende2->Draw();
cout << "Berechne die Zahlenwerte:" << endl;
// double Zmumu_out = TreeZmumu->GetEntries((SelectionString + And + SameFlavString + And + OutString).c_str()) * ScaleZmumu;
// double Zee_out = TreeZee->GetEntries((SelectionString + And + SameFlavString + And + OutString).c_str()) * ScaleZee;
// double Zmumu_in = TreeZmumu->GetEntries((SelectionString + And + SameFlavString + And + InString).c_str()) * ScaleZmumu;
// double Zee_in = TreeZee->GetEntries((SelectionString + And + SameFlavString + And + InString).c_str()) * ScaleZee;
// double Routin = (Zmumu_out + Zee_out) / (Zmumu_in + Zee_in);
// cout << "Zmumu: There are " << Zmumu_out << " Events outside and " << Zmumu_in << " Events inside the Z-Peak." << endl;
// cout << "Zee: There are " << Zee_out << " Events outside and " << Zee_in << " Events inside the Z-Peak." << endl;
// cout << "Sum: There are " << Zee_out + Zmumu_out << " Events outside and " << Zee_in + Zmumu_in << " Events inside the Z-Peak." << endl;
// cout << "Routin = " << Routin << endl;
cout << "MonteCarlo:" << endl;
fehlerrechnung Zmumu_out, Zmumu_in, Zee_out, Zee_in, ROutIn;
Zmumu_out = fehlerrechnung(TreeZmumu->GetEntries((SelectionString + And + SameFlavString + And + OutString).c_str()),"poisson") * ScaleZmumu;
Zee_out = fehlerrechnung(TreeZee->GetEntries((SelectionString + And + SameFlavString + And + OutString).c_str()),"poisson") * ScaleZee;
Zmumu_in = fehlerrechnung( TreeZmumu->GetEntries((SelectionString + And + SameFlavString + And + InString).c_str()),"poisson") * ScaleZmumu;
Zee_in = fehlerrechnung( TreeZee->GetEntries((SelectionString + And + SameFlavString + And + InString).c_str()),"poisson") * ScaleZee;
ROutIn = (Zmumu_out + Zee_out) / (Zmumu_in + Zee_in);
//cprint(" DY-Events im Datenbereich: ", (Zmumu_out + Zee_out));
cprint("R_outin = ",ROutIn, 3);
cprint("DY innerhalb unskaliert: ", (Zmumu_in/ScaleZmumu)+(Zee_in/ScaleZee));
cprint("DY ausserhalb unskaliert: ", (Zmumu_out/ScaleZmumu)+(Zee_out/ScaleZee));
fehlerrechnung Ttbar_in, Total_in, Ttbar_in_DF, Zmumu_in_DF, Zee_in_DF, Total_in_DF,DYinPeak, DYinData;
Ttbar_in = fehlerrechnung(TreeTtbar->GetEntries((SelectionString + And + SameFlavString + And + InString).c_str()),"poisson") * ScaleTtbar;
cprint("Ttbar-SameFlavor-Events im Z-Peak unskaliert: ", Ttbar_in /ScaleTtbar);
cprint("Ttbar-SameFlavor-Events im Z-Peak: ", Ttbar_in);
Total_in = Ttbar_in + Zmumu_in + Zee_in;
Ttbar_in_DF = fehlerrechnung(TreeTtbar->GetEntries((SelectionString + And + DiffFlavString + And + InString).c_str()),"poisson") * ScaleTtbar;
cprint("Ttbar-DiffFlavor-Events im Z-Peak unskaliert: ", Ttbar_in_DF /ScaleTtbar);
cprint("Ttbar-DiffFlavor-Events im Z-Peak: ", Ttbar_in_DF);
cprint("Quotient (sollte 1 sein): ", Ttbar_in/Ttbar_in_DF);
Zmumu_in_DF = fehlerrechnung(TreeZmumu->GetEntries((SelectionString + And + DiffFlavString + And + InString).c_str()),"poisson") * ScaleZmumu;
Zee_in_DF = fehlerrechnung(TreeZee->GetEntries((SelectionString + And + DiffFlavString + And + InString).c_str()),"poisson") * ScaleZee;
Total_in_DF = Ttbar_in_DF + Zmumu_in_DF + Zee_in_DF;
DYinPeak = Total_in - Total_in_DF;
cprint("In MC-Daten wirklich vorhandene Events innerhalb des Peaks: ", (Zmumu_in + Zee_in));
cprint("Aus \"Daten\": DY-Ereignisse innerhalb des Peaks: ", DYinPeak);
DYinData = ROutIn * DYinPeak;
cprint("Vorhersage der Methode fuer DY-Events im Datenbereich: ", DYinData);
cprint("In MC-Daten wirklich vorhandene Events im Datenbereich: ", (Zmumu_out + Zee_out));
cprint("Differenz Rekonstruktion - Wahrheit: ", (DYinData - Zmumu_out - Zee_out));
fehlerrechnung Ttbar_out, Ttbar_out_DF;
Ttbar_out = fehlerrechnung(TreeTtbar->GetEntries((SelectionString + And + SameFlavString + And + OutString).c_str()),"poisson") * ScaleTtbar;
cprint("Ttbar-SameFlavor-Events !im Z-Peak unskaliert: ", Ttbar_out /ScaleTtbar);
cprint("Ttbar-SameFlavor-Events !im Z-Peak: ", Ttbar_out);
Ttbar_out_DF = fehlerrechnung(TreeTtbar->GetEntries((SelectionString + And + DiffFlavString + And + OutString).c_str()),"poisson") * ScaleTtbar;
cprint("Ttbar-DiffFlavor-Events !im Z-Peak unskaliert: ", Ttbar_out_DF /ScaleTtbar);
cprint("Ttbar-DiffFlavor-Events !im Z-Peak: ", Ttbar_out_DF);
cprint("Quotient (sollte 1 sein): ", Ttbar_out/Ttbar_out_DF);
// TCanvas *c2 = new TCanvas("c2","c2",100,100,900,900);
// // TH1D * Histo_Diff = new TH1D("Histo_Diff","Histo_Diff",binNumber,50,150);
// Histo_Signal->Add(Histo_TtbarBG);
// Histo_Signal_DF->Add(Histo_TtbarBG_DF);
// // Histo_Signal->Add(Histo_Signal_DF,-1.);
// Histo_Signal->Divide(Histo_Signal_DF);
// Histo_Signal->Draw("");
// // Histo_Diff->(Histo_Signal,Histo_Signal_DF,1,-1);
// // Histo_Diff->Draw("");
// left->Draw();
// right->Draw();
}
void
plot2DSignalHisto(
TString filename1,
TString filename2,
TString histogramName,
// TString drawopts = "",
TString xtitle = "x",
TString ytitle = "y",
double xtitleOffset = 1.1,
double ytitleOffset = 1.3
)
{
// {{{
InitgStyle();
//gStyle->SetOptStat(0);
//gCanvas = new TCanvas("gCanvas", "gCanvas", 0, 0, 800, 600);
TFile *outputFile = new TFile("FitErgebnisse.root","RECREATE");
TH2D *histogram__DiffAbs = new TH2D("histogram__DiffAbs","Differenz Fit - Input (Absolut)", 5, -1, 1, 5, -1, 1);
TH2D *histogram__DiffRel = new TH2D("histogram__DiffRel","Differenz Fit - Input (Relativ)", 5, -1, 1, 5, -1, 1);
TH2D *histogram__FitResult = new TH2D("histogram__FitResult ", "Ergebnis-Histogramm des Fits", 5, -1, 1, 5, -1, 1);
// LoadHistogramTH2D(histogramName , filename1, 1.0, histogram);// Summe (SM)
LoadHistogramTH2D("histogram__Correlation"+histogramName , filename1, 1.0, histogram);// Summe (SM
//LoadHistogramTH2D(histogramName+"_LL" , filename2, 1.0, histo1); // LL
//LoadHistogramTH2D(histogramName+"_LR" , filename2, 1.0, histo2); // LR
//LoadHistogramTH2D(histogramName+"_RL" , filename2, 1.0, histo3); // RL
//LoadHistogramTH2D(histogramName+"_RR" , filename2, 1.0, histo4); // RR
//LoadHistogramTH2D("histogram__gen_N" , filename2, 1.0, histo1);
//LoadHistogramTH2D("histogram__gen_A" , filename2, 1.0, histo2);
LoadHistogramTH2D("histogram__N"+histogramName , filename2, 1.0, histo1);
LoadHistogramTH2D("histogram__A"+histogramName , filename2, 1.0, histo2);
//gCanvas->Clear();
histogram->GetXaxis()->SetTitle(xtitle);
histogram->GetXaxis()->SetTitleOffset(xtitleOffset);
histogram->GetYaxis()->SetTitle(ytitle);
histogram->GetYaxis()->SetTitleOffset(ytitleOffset);
//histogram->GetZaxis()->SetTitle("d^{2}#sigma / dM_{#bar{t}}dM_{t} [pb]");
//histogram->GetZaxis()->SetTitleOffset(ytitleOffset);
// gCanvas->Update();
/*
histo1->Scale(1.0/histo4->Integral());
histo2->Scale(1.0/histo4->Integral());
histo3->Scale(1.0/histo4->Integral());
histo4->Scale(1.0/histo4->Integral());
*/
//faktor = 1.0;
faktor=Double_t(histogram->Integral())/Double_t(histo1->Integral());
cout<<faktor<<endl;
TF2 *fitFunction = new TF2("fitFunction", HistoSum, -1, 1, -1, 1, 2); //allgemeine "return"-Varianten
//fitFunction->SetParameters(0.9,0.,0.);
//fitFunction->SetLineColor(kRed);
histogram->Fit(fitFunction, "N");
fitFunction->SetNpx(5);
fitFunction->SetNpy(5);
double p0 = fitFunction->GetParameter(0);
double p1 = fitFunction->GetParameter(1);
// double p2 = fitFunction->GetParameter(2);
// double p3 = fitFunction->GetParameter(3);
for(int i =1; i <= 5; i++)
{
for(int j = 1; j <= 5; j++)
{
//double sigmaLL = p0*faktor*histo1->GetBinError(i,j);
//double sigmaLR = p1*faktor*histo2->GetBinError(i,j);
//double sigmaRL = p2*faktor*histo3->GetBinError(i,j);
//double sigmaRR = p3*faktor*histo4->GetBinError(i,j);
double sigmaN = p0*faktor*histo1->GetBinError(i,j);
double sigmaA = p1*faktor*histo2->GetBinError(i,j);
//histogram->SetBinError(i,j, sqrt( histogram->GetBinContent(i,j) + pow(sigmaLL,2) + pow(sigmaRR,2) + pow(sigmaRL,2) + pow(sigmaLR, 2) ));
histogram->SetBinError(i,j, sqrt( histogram->GetBinContent(i,j) + pow(sigmaN,2) + pow(sigmaA,2) ));
}
}
histogram->Fit(fitFunction, "NE");
p0 = fitFunction->GetParameter(0);
p1 = fitFunction->GetParameter(1);
for(int i =1; i <= 5; i++)
{
for(int j = 1; j <= 5; j++)
{
//double sigmaLL = p0*faktor*histo1->GetBinError(i,j);
//double sigmaLR = p1*faktor*histo2->GetBinError(i,j);
//double sigmaRL = p2*faktor*histo3->GetBinError(i,j);
//double sigmaRR = p3*faktor*histo4->GetBinError(i,j);
double sigmaN = p0*faktor*histo1->GetBinError(i,j);
double sigmaA = p1*faktor*histo2->GetBinError(i,j);
//histogram->SetBinError(i,j, sqrt( histogram->GetBinContent(i,j) + pow(sigmaLL,2) + pow(sigmaRR,2) + pow(sigmaRL,2) + pow(sigmaLR, 2) ));
histogram->SetBinError(i,j, sqrt( histogram->GetBinContent(i,j) + pow(sigmaN,2) + pow(sigmaA,2) ));
}
}
histogram->Fit(fitFunction, "NE");
//histogram->Draw("lego1");
//fitFunction->Draw("lego");
cout << fitFunction->GetChisquare()/fitFunction->GetNDF() << endl;
for(int i = 1; i <= 5; i++)
{
for(int j = 1; j <= 5; j++)
{
histogram__DiffAbs->SetBinContent(i,j, fitFunction->Eval(histogram->GetXaxis()->GetBinCenter(i),histogram->GetYaxis()->GetBinCenter(j))-histogram->GetBinContent(i,j) );
histogram__DiffRel->SetBinContent(i,j, (fitFunction->Eval(histogram->GetXaxis()->GetBinCenter(i),histogram->GetYaxis()->GetBinCenter(j))-histogram->GetBinContent(i,j))/histogram->GetBinContent(i,j) );
histogram__FitResult->SetBinContent(i,j, fitFunction->Eval(histogram->GetXaxis()->GetBinCenter(i),histogram->GetYaxis()->GetBinCenter(j)));
}
}
outputFile->cd("");
histogram__DiffAbs->Write("histogram__DiffAbs");
histogram__DiffRel->Write("histogram__DiffRel");
histogram__FitResult->Write("histogram__FitResult");
outputFile->Close();
delete outputFile;
//gCanvas->Print(epsFilename(filename, histogramName)+".eps");
//cout << histogram[0]->Integral() << endl;
// }}}
};
