/*============================================================================*/
void gaus1peakfit(Char_t *s, Float_t x1, Float_t x2, Float_t x3, Float_t x4)
{
Double_t par[5],epar[5],x[4],y[4];
TH1 *hist;
hist = (TH1 *) gROOT->FindObject(s);
setcanvas(1);
TCanvas *c1=(TCanvas*) gROOT->FindObject("c1");
if(c1==NULL)setcanvas(1);
c1->Clear();
hist->SetAxisRange(x1-30,x4+30);
hist->Draw();
//--**-- Linear background estimation --**--//
x[0] = x1;
x[1] = x2;
x[2] = x3;
x[3] = x4;
Int_t bin1 = hist->FindBin(x1);
y[0] = hist->GetBinContent(bin1);
Int_t bin2 = hist->FindBin(x2);
y[1] = hist->GetBinContent(bin2);
Int_t bin3 = hist->FindBin(x3);
y[2] = hist->GetBinContent(bin3);
Int_t bin4 = hist->FindBin(x4);
y[3] = hist->GetBinContent(bin4);
TGraph *g = new TGraph(4,x,y);
TF1 *fpol1 = new TF1("POL1","pol1",x1,x4);
g->Fit(fpol1,"RQN");
par[3]=fpol1->GetParameter(0);
par[4]=fpol1->GetParameter(1);
//--**-- Gaussian Peak estimation without background --**--//
TF1 *fgaus = new TF1("GAUS","gaus",x2,x3);
hist->Fit(fgaus,"RQN");
fgaus->GetParameters(&par[0]);
//--**-- Final Peak Fit with Background --**--//
TF1 *func = new TF1("FGAUS","gaus(0)+pol1(3)",x1,x4);
func->SetParameters(par);
hist->Fit(func,"R+QN");
func->GetParameters(par);
epar[0]=func->GetParError(0);
epar[1]=func->GetParError(1);
epar[2]=func->GetParError(2);
Double_t fwhm = par[2]*TMath::Sqrt(8*TMath::Log(2));
Double_t efwhm = epar[2]*TMath::Sqrt(8*TMath::Log(2));
Double_t N0 = par[0]*(TMath::Sqrt(TMath::TwoPi())*par[2]);
Double_t r0 = epar[0]/par[0];
Double_t r2 = epar[2]/par[2];
Double_t eN0= N0*TMath::Sqrt(r0*r0+r2*r2);
printf("Peak = %f +- %f; FFHM = %f +- %f; Area = %f +- %f\n",
par[1],epar[1],fwhm,efwhm,N0,eN0);
//printf("%11.4f %11.4f %11.0f %11.0f\n",
// par[1],epar[1],N0,eN0);
func->SetLineWidth(0.5);
func->SetLineStyle(1);
func->SetLineColor(4);
func->SetFillColor(4);
func->Draw("same");
}
/*=========================================================*/
void d2d(Char_t *matn)
{
TH2F *hist;
Axis_t axmax=axmin+numchx;
Axis_t aymax=aymin+numchy;
setcanvas(1);
gStyle->SetPalette(1);
gPad->SetLogz(1);
hist=(TH2F*)f1->Get(matn);
hist->SetAxisRange(axmin,axmax,"X");
hist->SetAxisRange(aymin,aymax,"Y");
hist->Draw("COLZ");
return;
}
/*=========================================================*/
Float_t AGY(Char_t *matn,Float_t peak,Float_t width=0.0)
{
Axis_t axmax=axmin+numchx;
setcanvas(2);
TH1D *hist;
hist=(TH1D*)gROOT->FindObject("xtemp");
if(hist!=NULL)hist->Delete();
hist=new TH1D("xtemp","xtemp",NCHX,0,DIMX);
hist->Add(histx,1.0);
Float_t a=GY(matn,peak,width);
histx->Add(hist,1.0);
c1->cd(2);
histx->SetAxisRange(axmin,axmax);
histx->SetLineColor(3);
histx->Draw();
return a;
}
/*=========================================================*/
Float_t AGX(Char_t *matn,Float_t peak,Float_t width=0.0)
{
Axis_t aymax=aymin+numchy;
setcanvas(2);
TH1D *hist;
hist=(TH1D*)gROOT->FindObject("ytemp");
if(hist!=NULL)hist->Delete();
hist=new TH1D("ytemp","ytemp",NCHY,0,DIMY);
hist->Add(histy,1.0);
Float_t a=GX(matn,peak,width);
histy->Add(hist,1.0);
c1->cd(2);
histy->SetAxisRange(aymin,aymax);
histy->SetLineColor(3);
histy->Draw();
return a;
}
void plotdjr(const TString & infile, const TString & outfile) {
gSystem->Load("libFWCoreFWLite.so");
AutoLibraryLoader::enable();
TH1::SetDefaultSumw2();
TChain *tree = new TChain("Events");
tree->Add(infile);
tree->SetAlias("GenEvent","GenEventInfoProduct_generator__GEN.obj");
tree->SetAlias("LHEEvent","LHEEventProduct_externalLHEProducer__LHE.obj");
TCut weight = "GenEvent.weight()";
int nbins = 50.;
double djrmin = -0.5;
double djrmax = 3.;
//typeMC sets the kind of sample we are looking at:
//0 is for NLO with FXFX merging;
//1 is for LO with MLM;
//2 is for LO with MLM (plotting partons after excluding non-matched partons in wbb/vbf type processes)
int typeMC = 2;
TCanvas *c1 = new TCanvas("c1", "c1", 800, 600);
TPad *pad[5];
setcanvas(c1,pad);
pad[0]->cd();
makeplot("djr0",tree,weight,"log10(GenEvent.DJRValues_[0])","DJR 0->1",nbins,djrmin,djrmax,typeMC);
pad[1]->cd();
makeplot("djr1",tree,weight,"log10(GenEvent.DJRValues_[1])","DJR 1->2",nbins,djrmin,djrmax,typeMC);
pad[2]->cd();
makeplot("djr2",tree,weight,"log10(GenEvent.DJRValues_[2])","DJR 2->3",nbins,djrmin,djrmax,typeMC);
pad[3]->cd();
makeplot("djr3",tree,weight,"log10(GenEvent.DJRValues_[3])","DJR 3->4",nbins,djrmin,djrmax,typeMC);
pad[4]->cd();
makeplot("djr4",tree,weight,"log10(GenEvent.DJRValues_[4])","DJR 4->5",nbins,djrmin,djrmax,typeMC);
c1->Print(outfile);
return;
}
/*=========================================================*/
void dy(Char_t *matn)
{
TH1D *hist[3];
Axis_t aymax=aymin+numchy;
Char_t str[255];
setcanvas(1);
sprintf(str,"%sy",matn);
hist[2]=(TH1D*)gROOT->FindObject(str);
if(hist[2]==NULL){
hist[2]=new TH1D(str,str,NCHY,0,DIMY);
pjy(matn);
sprintf(str,"%s_py",matn);
hist[0]=(TH1D*)gROOT->FindObject(str);
sprintf(str,"%s_bgy",matn);
hist[1]=(TH1D*)gROOT->FindObject(str);
hist[2]->Add(hist[0],hist[1],1.0,-1.0);
hist[2]->SetLineColor(2);
}
hist[2]->SetAxisRange(aymin,aymax);
hist[2]->Draw();
return;
}
/*=========================================================*/
void dx(Char_t *matn)
{
TH1D *hist[3];
Axis_t axmax=axmin+numchx;
Char_t str[255];
setcanvas(1);
sprintf(str,"%sx",matn);
hist[2]=(TH1D*)gROOT->FindObject(str);
if(hist[2]==NULL){
hist[2]=new TH1D(str,str,NCHX,0,DIMX);
pjx(matn);
sprintf(str,"%s_px",matn);
hist[0]=(TH1D*)gROOT->FindObject(str);
sprintf(str,"%s_bgx",matn);
hist[1]=(TH1D*)gROOT->FindObject(str);
hist[2]->Add(hist[0],hist[1],1.0,-1.0);
hist[2]->SetLineColor(2);
}
hist[2]->SetAxisRange(axmin,axmax);
hist[2]->Draw();
return;
}
/*============================================================================*/
void gaus2peakfit(Char_t *s, Float_t x1, Float_t x2, Float_t x3, Float_t x4)
{
Double_t par[8],epar[8],x[2],y[2];
TH1 *hist;
hist = (TH1 *) gROOT->FindObject(s);
TCanvas *c1=(TCanvas*) gROOT->FindObject("c1");
if(c1==NULL)setcanvas(1);
c1->Clear();
hist->SetAxisRange(x1-30,x4+30);
hist->Draw();
//--**-- Linear background estimation --**--//
x[0] = x1;
x[1] = x4;
Int_t bin1 = hist->FindBin(x1);
y[0] = hist->GetBinContent(bin1);
Int_t bin2 = hist->FindBin(x4);
y[1] = hist->GetBinContent(bin2);
TGraph *g = new TGraph(2,x,y);
TF1 *fpol1 = new TF1("POL1","pol1",x1,x4);
g->Fit(fpol1,"RQN");
par[6]=fpol1->GetParameter(0);
par[7]=fpol1->GetParameter(1);
//--**-- Two Gaussian Peak estimation without background --**--//
fgaus1 = new TF1("m1","gaus",x1,x2);
fgaus2 = new TF1("m2","gaus",x3,x4);
hist->Fit(fgaus1,"R+QN");
hist->Fit(fgaus2,"R+QN");
fgaus1->GetParameters(&par[0]);
fgaus2->GetParameters(&par[3]);
//--**-- Final Peak Fit with Background --**--//
func = new TF1("m","gaus(0)+gaus(3)+pol1(6)",x1,x4);
func->SetParameters(par);
hist->Fit(func,"R+QN");
func->SetLineWidth(0.5);
func->SetLineStyle(1);
func->SetLineColor(4);
func->SetFillColor(4);
func->Draw("same");
func->GetParameters(par);
epar[0]=func->GetParError(0);
epar[1]=func->GetParError(1);
epar[2]=func->GetParError(2);
epar[3]=func->GetParError(3);
epar[4]=func->GetParError(4);
epar[5]=func->GetParError(5);
Double_t fwhm1 = par[2]*TMath::Sqrt(8*TMath::Log(2));
Double_t efwhm1 = epar[2]*TMath::Sqrt(8*TMath::Log(2));
Double_t N10 = par[0]*(TMath::Sqrt(TMath::TwoPi())*par[2]);
Double_t r10 = epar[0]/par[0];
Double_t r12 = epar[2]/par[2];
Double_t eN10= N10*TMath::Sqrt(r10*r10+r12*r12);
Double_t fwhm2 = par[5]*TMath::Sqrt(8*TMath::Log(2));
Double_t efwhm2 = epar[5]*TMath::Sqrt(8*TMath::Log(2));
Double_t N20 = par[3]*(TMath::Sqrt(TMath::TwoPi())*par[5]);
Double_t r20 = epar[3]/par[3];
Double_t r22 = epar[5]/par[5];
Double_t eN20= N20*TMath::Sqrt(r20*r20+r22*r22);
//printf("Peak = %f +- %f; FFHM = %f +- %f; Area = %f +- %f\n",
// par[1],epar[1],fwhm1,efwhm1,N10,eN10);
//printf("Peak = %f +- %f; FFHM = %f +- %f; Area = %f +- %f\n",
// par[4],epar[4],fwhm2,efwhm2,N20,eN20);
printf("%11.4f %11.4f %11.0f %11.0f\n",
par[1],epar[1],N10,eN10);
printf("%11.4f %11.4f %11.0f %11.0f\n",
par[4],epar[4],N20,eN20);
}
/*=========================================================*/
Float_t GX(Char_t *matn,Float_t peak,Float_t width=0.0,Int_t cy=0)
{
TH2 *hist2;
TH1 *hist[5];
Char_t str[255];
Int_t nxmin,nxmax;
Float_t ratio,a,b;
Float_t xmin,xmax;
Axis_t aymax=aymin+numchy;
s1=new TSpectrum();
hist2 = (TH2*)f1->Get(matn);
if(hist2==NULL){
printf("Couldn't find %s\n",matn);
return -1.0;
}
hist2->SetAxisRange(0,DIMX,"X");
hist2->SetAxisRange(0,DIMY,"Y");
sprintf(str,"%s_px",matn);
hist[0]=(TH1*)gROOT->FindObject(str);
if(hist[0]==NULL){
pjx(matn);
hist[0]=(TH1*)gROOT->FindObject(str);
}
hist[0]->SetAxisRange(0,DIMX);
sprintf(str,"%s_py",matn);
hist[1]=(TH1*)gROOT->FindObject(str);
if(hist[1]==NULL){
pjy(matn);
hist[1]=(TH1*)gROOT->FindObject(str);
}
hist[1]->SetAxisRange(0,DIMY);
sprintf(str,"%s_bgx",matn);
hist[2]=(TH1*)gROOT->FindObject(str);
hist[2]->SetAxisRange(0,DIMX);
if(width==0.0){
width = (Float_t)f2x->Eval(peak/1000.);
width=sqrt(width);
}
printf("width=%f\n",width);
xmin=peak-width;
xmax=peak+width;
nxmin=hist[0]->FindBin(xmin);
nxmax=hist[0]->FindBin(xmax);
a=hist[2]->Integral(nxmin,nxmax);
b=hist[0]->Integral();
sprintf(str,"%sg%4.4iy",matn,(Int_t)peak);
hist[3]=(TH1*)gROOT->FindObject(str);
if(hist[3]!=NULL)hist[3]->Delete();
hist[3]=hist2->ProjectionY(str, nxmin, nxmax);
ratio=a/b;
hist[3]->Add(hist[1],-ratio);
hist[4]=s1->Background(hist[3],30);
hist[3]->Add(hist[4],-1);
hist[3]->SetLineColor(2);
hist[3]->SetAxisRange(aymin,aymax);
histy->Add(histy,hist[3],0.0,1.0);
if(cy>=1){
c1=(TCanvas *)gROOT->FindObject("c1");
if(c1==NULL)setcanvas(cy);
c1->cd(cy);
c1->SetCrosshair(1);
hist[3]->Draw();
}
return ratio;
}
