void dumpElements(TVectorD& a)
{
cout << endl << endl;
a.Print();
cout << endl << endl;
return;
}
double operator() (double *x, double *p) {
// 4 parameters
int dim = X.GetNrows();
int k = 0;
for (int i = 0; i<dim; ++i) { X[i] = x[i] - p[k]; k++; }
for (int i = 0; i<dim; ++i) {
CovMat(i,i) = p[k]*p[k];
k++;
}
for (int i = 0; i<dim; ++i) {
for (int j = i+1; j<dim; ++j) {
// p now are the correlations N(N-1)/2
CovMat(i,j) = p[k]*sqrt(CovMat(i,i)*CovMat(j,j));
CovMat(j,i) = CovMat(i,j);
k++;
}
}
if (debug) {
X.Print();
CovMat.Print();
}
double det = CovMat.Determinant();
if (det <= 0) {
Fatal("GausND","Determinant is <= 0 det = %f",det);
CovMat.Print();
return 0;
}
double norm = std::pow( 2. * TMath::Pi(), dim/2) * sqrt(det);
// compute the gaussians
CovMat.Invert();
double fval = std::exp( - 0.5 * CovMat.Similarity(X) )/ norm;
if (debug) {
std::cout << "det " << det << std::endl;
std::cout << "norm " << norm << std::endl;
std::cout << "fval " << fval << std::endl;
}
return fval;
}
void ratioPlots_Zxx()
{
// llbb_Mass_reco mfJetEta_450_600 mfJetEta_250_300 lljjMass_reco mjj_HighMass_reco drll_HighMass_reco
TString Variable = "Zxx_Mass_reco";
// TString Variable2 = "Zbb_Mass_reco";
TString x_title = "M_{llxx}";
Int_t N_Rebin = 10;
Double_t yTopLimit = 3;
TFile *f1 = TFile::Open("/home/fynu/amertens/storage/test/MG_PY6_/output/MG_PY6_/MG_PY6v9.root");
TH1D *h1 = (TH1D*)f1->Get(Variable);
h1->Sumw2();
// h1->Add((TH1D*)f1->Get(Variable2));
h1->SetDirectory(0);
f1->Close();
TFile *f2 = TFile::Open("/home/fynu/amertens/storage/test/aMCNLO_PY8_/output/aMCNLO_PY8_/aMCNLO_PY8v9.root");
TH1D *h2 = (TH1D*)f2->Get(Variable);
h2->Sumw2();
// h2->Add((TH1D*)f2->Get(Variable2));
h2->SetDirectory(0);
f2->Close();
/*
TFile *f3 = TFile::Open("/home/fynu/amertens/storage/test/MG_PY8_/output/MG_PY8_/MG_PY8.root");
TH1D *h3 = (TH1D*)f3->Get(Variable);
h3->SetDirectory(0);
f3->Close();
*/
// h1->Sumw2();
// h2->Sumw2();
// h3->Sumw2();
cout << "MG_PY6 : " << h1->Integral() << endl;
cout << "aMC@NLO_PY8 : " << h2->Integral() << endl;
//h1->Scale(1.0/151456.0);
//h2->Scale(1.0/1.45192e+09);
//h2->Scale(1./12132.9);
h1->Scale(1.0/h1->Integral());
h2->Scale(1.0/h2->Integral());
h1->Sumw2();
h2->Sumw2();
// h3->Scale(1.0/h3->Integral());
h1->Rebin(N_Rebin);
h2->Rebin(N_Rebin);
// h3->Rebin(N_Rebin);
TH1D *h1c = h1->Clone();
h1c->Sumw2();
TH1D *h2c = h2->Clone();
h2c->Sumw2();
TH1D *h1c2 = h1->Clone();
h1c2->Sumw2();
h2c->Add(h1c,-1);
h2c->Divide(h1c);
h1->SetTitle("");
h2->SetTitle("");
// h3->SetTitle("");
h1->SetLineColor(kRed);
// h3->SetLineColor(kGreen);
TCanvas *c1 = new TCanvas("c1","example",600,700);
TPad *pad1 = new TPad("pad1","pad1",0,0.5,1,1);
pad1->SetBottomMargin(0);
gStyle->SetOptStat(0);
pad1->Draw();
pad1->cd();
h2->DrawCopy();
// h3->DrawCopy("same");
h1->GetYaxis()->SetLabelSize(0.1);
h1->GetYaxis()->SetRangeUser(0, 0.2);// ,yTopLimit);
h1->GetYaxis()->SetTitleSize(0.06);
h1->GetYaxis()->SetTitleOffset(0.7);
h1->Draw("same");
TLegend *leg = new TLegend(0.6,0.7,0.89,0.89);
leg->SetLineColor(0);
leg->SetFillColor(0);
//leg->AddEntry(h1,"t#bar{t} uncertainty","f");
leg->AddEntry(h1,"MG5 + PY6","l");
leg->AddEntry(h2,"aMC@NLO + PY8","l");
// leg->AddEntry(h3,"MG5 + PY8","l");
leg->Draw();
c1->cd();
TPad *pad2 = new TPad("pad2","pad2",0,0,1,0.5);
pad2->SetTopMargin(0);
pad2->SetBottomMargin(0.4);
pad2->Draw();
pad2->cd();
pad2->SetGrid();
h2->SetStats(0);
h2->Divide(h1);
//h2->SetMarkerStyle(21);
h2->Draw("ep");
h2->GetYaxis()->SetLabelSize(0.1);
h2->GetYaxis()->SetRangeUser(-0.5, 2.5);// ,yTopLimit);
h2->GetYaxis()->SetTitle("aMC@NLO+PY8 / MG5+PY6");
h2->GetYaxis()->SetTitleSize(0.06);
h2->GetYaxis()->SetTitleOffset(0.7);
h2->GetXaxis()->SetLabelSize(0.1);
h2->GetXaxis()->SetTitle(x_title);
h2->GetXaxis()->SetTitleSize(0.16);
h2->GetXaxis()->SetTitleOffset(0.9);
// Double_t matrix[4][4];
h2->Fit("pol3","","",50.0,1200.0);
TF1 *ratio = h2->GetFunction("pol3");
TVirtualFitter *fitter = TVirtualFitter::GetFitter();
TMatrixD matrix(4,4,fitter->GetCovarianceMatrix());
Double_t errorPar00 = fitter->GetCovarianceMatrixElement(0,0);
Double_t errorPar11 = fitter->GetCovarianceMatrixElement(1,1);
Double_t errorPar22 = fitter->GetCovarianceMatrixElement(2,2);
Double_t errorPar33 = fitter->GetCovarianceMatrixElement(3,3);
// c1->cd();
matrix.Print();
//const TMatrixDSym m = matrix;
const TMatrixDEigen eigen(matrix);
const TMatrixD eigenVal = eigen.GetEigenValues();
const TMatrixD V = eigen.GetEigenVectors();
cout << "V" << endl;
V.Print();
cout << "eigenVal" << endl;
eigenVal.Print();
cout << "Recomputed diag" << endl;
//const TMatrixD Vt(TMatrixD::kTransposed,V);
//const TMatrixD Vinv = V.Invert();
const TMatrixD Vt(TMatrixD::kTransposed,V);
//cout << "V-1" << endl;
//Vinv.Print();
cout << "Vt" << endl;
Vt.Print();
const TMatrixD VAVt = Vt*matrix*V;
VAVt.Print();
const TVectorD FittedParam(4);
FittedParam(0) = fitter->GetParameter(0);
FittedParam(1) = fitter->GetParameter(1);
FittedParam(2) = fitter->GetParameter(2);
FittedParam(3) = fitter->GetParameter(3);
FittedParam.Print();
//const TVectorD FittedParamNB(4);
const TVectorD PNb = V*FittedParam;
cout << "Pnb" << endl;
PNb.Print();
cout << " Generating other parameters values " << endl;
cout <<" V " << V(0,0) << endl;
TRandom3 r;
const TVectorD NewP(4);
TH1D *hist100 = new TH1D("h100","h100",200,-5,5);
TH1D *hist200 = new TH1D("h200","h200",200,-5,5);
TH1D *hist400 = new TH1D("h400","h400",200,-5,5);
TH1D *hist600 = new TH1D("h600","h600",100,-5,5);
TH1D *hist800 = new TH1D("h800","h800",100,-5,5);
TH1D *hist1000 = new TH1D("h1000","h1000",100,-5,5);
TH1D *histp0 = new TH1D("p0","p0",100,-0.2,0.3);
TH1D *histp1 = new TH1D("p1","p1",100,0.0,0.01);
TH1D *histp2 = new TH1D("p2","p2",100,-0.00001,0);
TH1D *histp3 = new TH1D("p3","p3",100,0,0.000000002);
for (Int_t i = 0; i< 500; i++){
NewP(0) = r.Gaus(PNb(0),sqrt(eigenVal(0,0)));
NewP(1) = r.Gaus(PNb(1),sqrt(eigenVal(1,1)));
NewP(2) = r.Gaus(PNb(2),sqrt(eigenVal(2,2)));
NewP(3) = r.Gaus(PNb(3),sqrt(eigenVal(3,3)));
//NewP.Print();
//FittedParam.Print();
const TVectorD NewP2 = Vt*NewP;
//NewP2.Print();
histp0->Fill(NewP2(0));
histp1->Fill(NewP2(1));
histp2->Fill(NewP2(2));
histp3->Fill(NewP2(3));
TF1 *newFit=new TF1("test","[0]+x*[1]+[2]*pow(x,2)+[3]*pow(x,3)",0,1400);
newFit->SetParameters(NewP2(0),NewP2(1),NewP2(2),NewP2(3));
newFit->SetLineColor(kBlue);
Double_t area=0;
for(Int_t it=1; it < 16; it++){
//cout << "bin : " << it << " " << h1c2->GetBinContent(it) << endl;
area += h1c2->GetBinContent(it)*newFit->Eval(100*it+50);
}
//newFit->Draw("same");
//cout <<"val: " << newFit->Eval(200) << endl;
hist100->Fill(newFit->Eval(100)/area);
hist200->Fill(newFit->Eval(200)/area);
hist400->Fill(newFit->Eval(400)/area);
hist600->Fill(newFit->Eval(600)/area);
hist800->Fill(newFit->Eval(800)/area);
hist1000->Fill(newFit->Eval(1000)/area);
}
c1->cd();
TCanvas *c2 = new TCanvas("c2","c2",1000,1000);
c2->cd();
c2->Divide(3,2);
c2->cd(1);
hist100->Draw();
c2->cd(2);
hist200->Draw();
c2->cd(3);
hist400->Draw();
c2->cd(4);
hist600->Draw();
c2->cd(5);
hist800->Draw();
c2->cd(6);
hist1000->Draw();
Double_t m_100,m_200,m_400,m_600,m_800,m_1000;
Double_t s_100,s_200,s_400,s_600,s_800,s_1000;
hist100->Fit("gaus","","",0.3,1.2);
TVirtualFitter *fitter = TVirtualFitter::GetFitter();
m_100 = fitter->GetParameter(1);
s_100 = fitter->GetParameter(2);
hist200->Fit("gaus","","",0.5,1.2);
TVirtualFitter *fitter = TVirtualFitter::GetFitter();
m_200 = fitter->GetParameter(1);
s_200 = fitter->GetParameter(2);
hist400->Fit("gaus","","",0.8,1.2);
TVirtualFitter *fitter = TVirtualFitter::GetFitter();
m_400 = fitter->GetParameter(1);
s_400 = fitter->GetParameter(2);
hist600->Fit("gaus","","",0.8,1.3);
TVirtualFitter *fitter = TVirtualFitter::GetFitter();
m_600 = fitter->GetParameter(1);
s_600 = fitter->GetParameter(2);
hist800->Fit("gaus","","",0.5,2);
TVirtualFitter *fitter = TVirtualFitter::GetFitter();
m_800 = fitter->GetParameter(1);
s_800 = fitter->GetParameter(2);
hist1000->Fit("gaus","","",0.5,2.5);
TVirtualFitter *fitter = TVirtualFitter::GetFitter();
m_1000 = fitter->GetParameter(1);
s_1000 = fitter->GetParameter(2);
Double_t x[6],y[6],ym[6],yup[6],ydown[6];
x[0]=100; x[1]=200; x[2]=400;x[3]=600; x[4]=800; x[5]=1000;
yup[0]=ratio->Eval(100)+s_100;
yup[1]=ratio->Eval(200)+s_200;
yup[2]=ratio->Eval(400)+s_400;
yup[3]=ratio->Eval(600)+s_600;
yup[4]=ratio->Eval(800)+s_800;
yup[5]=ratio->Eval(1000)+s_1000;
ydown[0]=ratio->Eval(100)-s_100;
ydown[1]=ratio->Eval(200)-s_200;
ydown[2]=ratio->Eval(400)-s_400;
ydown[3]=ratio->Eval(600)-s_600;
ydown[4]=ratio->Eval(800)-s_800;
ydown[5]=ratio->Eval(1000)-s_1000;
y[0]=1+s_100/ratio->Eval(100);
y[1]=1+s_200/ratio->Eval(200);
y[2]=1+s_400/ratio->Eval(400);
y[3]=1+s_600/ratio->Eval(600);
y[4]=1+s_800/ratio->Eval(800);
y[5]=1+s_1000/ratio->Eval(1000);
ym[0]=-s_100/m_100;
ym[1]=-s_200/m_200;
ym[2]=-s_400/m_400;
ym[3]=-s_600/m_600;
ym[4]=-s_800/m_800;
ym[5]=-s_1000/m_1000;
TGraph* g = new TGraph(6,x,y);
TGraph* gm = new TGraph(6,x,ym);
TGraph* gup = new TGraph(6,x,yup);
TGraph* gdown = new TGraph(6,x,ydown);
TCanvas *c3 = new TCanvas("c3","c3",1000,1000);
c3->cd();
//gup->Draw("AC*");
//gdown->Draw("C*");
g->Draw("AC*");
gPad->SetBottomMargin(0.2);
gPad->SetLeftMargin(0.2);
gStyle->SetOptStat(0);
g->GetXaxis()->SetTitle("M_{Zbb}");
g->GetXaxis()->SetRangeUser(50,1100);
g->GetYaxis()->SetLabelSize(0.06);
g->GetYaxis()->SetTitle("Uncertainty");
g->GetYaxis()->SetTitleSize(0.06);
g->GetYaxis()->SetTitleOffset(1.4);
g->GetXaxis()->SetLabelSize(0.06);
g->GetXaxis()->SetTitleSize(0.06);
g->GetXaxis()->SetTitleOffset(1);
g->GetYaxis()->SetNdivisions(5);
TFile f("syst_zxx.root","recreate");
g->Write();
f.Close();
//gm->Draw("C*");
//g->SetMaximum(1);
//g->SetMinimum(-1);
//h2c->Draw("same");
TH1D *h22=h2->Clone();
TCanvas *c5 = new TCanvas("c5","c5",1000,1000);
gPad->SetBottomMargin(0.2);
gPad->SetLeftMargin(0.2);
gStyle->SetOptStat(0);
h22->Draw();
h22->GetXaxis()->SetRangeUser(50,1100);
h22->GetYaxis()->SetLabelSize(0.06);
h22->GetYaxis()->SetTitleSize(0.06);
h22->GetYaxis()->SetTitleOffset(1.4);
h22->GetXaxis()->SetLabelSize(0.06);
h22->GetXaxis()->SetTitleSize(0.06);
h22->GetXaxis()->SetTitleOffset(1);
ratio->SetLineColor(kRed);
ratio->Draw("same");
gup->Draw("C");
gdown->Draw("C");
TLegend *leg = new TLegend(0.6,0.7,0.89,0.89);
leg->SetLineColor(0);
leg->SetFillColor(0);
leg->AddEntry(h22,"aMC@NLO / MG5","lep");
leg->AddEntry(ratio,"best fit","l");
leg->AddEntry(gup,"Syst Error (#pm 1 #sigma)","l");
leg->Draw();
TCanvas *c4 = new TCanvas("c4","c4",1000,1000);
c4->Divide(2,2);
c4->cd(1);
histp0->Draw();
c4->cd(2);
histp1->Draw();
c4->cd(3);
histp2->Draw();
c4->cd(4);
histp3->Draw();
}
