Exemplo n.º 1
0
void ThreeDFit() {
     
  const int n = 1000; 
  double x[n], y[n], z[n], v[n]; 
  double ev = 0.1;

  // generate the data
  TRandom2 r; 
  for (int i = 0; i < n; ++i) { 
     x[i] = r.Uniform(0,10);
     y[i] = r.Uniform(0,10);
     z[i] = r.Uniform(0,10); 
     v[i] = sin(x[i] ) + cos(y[i]) + z[i] + r.Gaus(0,ev);         
  }

  // create a 3d binned data structure
  ROOT::Fit::BinData data(n,3); 
  double xx[3];
  for(int i = 0; i < n; ++i) {
     xx[0] = x[i]; 
     xx[1] = y[i]; 
     xx[2] = z[i]; 
     // add the 3d-data coordinate, the predictor value (v[i])  and its errors
     data.Add(xx, v[i], ev); 
  }

  TF3 * f3 = new TF3("f3","[0] * sin(x) + [1] * cos(y) + [2] * z",0,10,0,10,0,10);
  f3->SetParameters(2,2,2);
  ROOT::Fit::Fitter fitter;
  // wrapped the TF1 in a IParamMultiFunction interface for teh Fitter class
  ROOT::Math::WrappedMultiTF1 wf(*f3,3);
  fitter.SetFunction(wf); 
  //
  bool ret = fitter.Fit(data); 
  if (ret) { 
     const ROOT::Fit::FitResult & res = fitter.Result(); 
     // print result (should be around 1) 
     res.Print(std::cout);
     // copy all fit result info (values, chi2, etc..) in TF3
     f3->SetFitResult(res);
     // test fit p-value (chi2 probability)
     double prob = res.Prob();
     if (prob < 1.E-2) 
        Error("exampleFit3D","Bad data fit - fit p-value is %f",prob);
     else
        std::cout << "Good fit : p-value  = " << prob << std::endl;

  }
  else 
     Error("exampleFit3D","3D fit failed");
}
Exemplo n.º 2
0
Arquivo: fitCircle.C Projeto: Y--/root
//____________________________________________________________________
void fitCircle(Int_t n=10000) {
   //generates n points around a circle and fit them
   TCanvas *c1 = new TCanvas("c1","c1",600,600);
   c1->SetGrid();
   gr = new TGraph(n);
   if (n> 999) gr->SetMarkerStyle(1);
   else        gr->SetMarkerStyle(3);
   TRandom3 r;
   Double_t x,y;
   for (Int_t i=0;i<n;i++) {
      r.Circle(x,y,r.Gaus(4,0.3));
      gr->SetPoint(i,x,y);
   }
   c1->DrawFrame(-5,-5,5,5);
   gr->Draw("p");


   auto chi2Function = [&](const Double_t *par) {
      //minimisation function computing the sum of squares of residuals
      // looping at the graph points
      Int_t np = gr->GetN();
      Double_t f = 0;
      Double_t *x = gr->GetX();
      Double_t *y = gr->GetY();
      for (Int_t i=0;i<np;i++) {
         Double_t u = x[i] - par[0];
         Double_t v = y[i] - par[1];
         Double_t dr = par[2] - std::sqrt(u*u+v*v);
         f += dr*dr;
      }
      return f;
   };

   // wrap chi2 funciton in a function object for the fit
   // 3 is the number of fit parameters (size of array par)
   ROOT::Math::Functor fcn(chi2Function,3);
   ROOT::Fit::Fitter  fitter;


   double pStart[3] = {0,0,1};
   fitter.SetFCN(fcn, pStart);
   fitter.Config().ParSettings(0).SetName("x0");
   fitter.Config().ParSettings(1).SetName("y0");
   fitter.Config().ParSettings(2).SetName("R");

   // do the fit 
   bool ok = fitter.FitFCN();
   if (!ok) {
      Error("line3Dfit","Line3D Fit failed");
   }   

   const ROOT::Fit::FitResult & result = fitter.Result();
   result.Print(std::cout);

   //Draw the circle on top of the points
   TArc *arc = new TArc(result.Parameter(0),result.Parameter(1),result.Parameter(2));
   arc->SetLineColor(kRed);
   arc->SetLineWidth(4);
   arc->Draw();
}
Exemplo n.º 3
0
void massfitvn_Jpsi()
{
    double fit_range_low = 2.6;
    double fit_range_high = 3.5;
    double JPsi_mass = 3.097;
    int npt = 7;
    TFile* file1 = TFile::Open("HM185_JpsivnHist_etagap1p5_v30_eff_extdeta.root");
    
    TFile ofile("v2vspt_fromfit_jpsi_HM185_250_deta1p5_doubleCB_v30_eff_exp_extdeta.root","RECREATE");
    
    //v12
    double alpha_fit[14] = {4.30986,3.50841,3.03436,2.73741,2.37934,2.10685,2.03615};
    double n_fit[14] = {1.88853,1.9839,2.03198,2.07295,2.11001,2.15234,2.10154};
    
    TF1* fmasssig[9];
    TF1* fmassbkg[9];
    TF1* fmasstotal[9];
    TF1* fvn[9];
    
    double pt[13];
    double KET_ncq[13];
    double v2[13];
    double v2e[13];
    double v2_bkg[13];
    double v2_ncq[13];
    double v2e_ncq[13];
    double ptbin[14] = {0.2, 1.8, 3.0, 4.5, 6.0, 8.0, 10, 20};
    double a[13];
    double b[13];
    double sigfrac[13];
    
    TCanvas* c[10];
    for(int i=0;i<npt;i++)
    {
        c[i] = new TCanvas(Form("c_%d",i),Form("c_%d",i),800,400);
        c[i]->Divide(2,1);
    }
    
    for(int i=0;i<npt;i++)
    {
        c[i]->cd(1)->SetTopMargin(0.06);
        c[i]->cd(1)->SetLeftMargin(0.18);
        c[i]->cd(1)->SetRightMargin(0.043);
        c[i]->cd(1)->SetBottomMargin(0.145);
        c[i]->cd(2)->SetTopMargin(0.06);
        c[i]->cd(2)->SetLeftMargin(0.18);
        c[i]->cd(2)->SetRightMargin(0.043);
        c[i]->cd(2)->SetBottomMargin(0.145);

    }
    
    TCanvas* c2 = new TCanvas("c2","c2",100,100);
    
    TLatex* tex = new TLatex;
    tex->SetNDC();
    tex->SetTextFont(42);
    tex->SetTextSize(0.045);
    tex->SetLineWidth(2);
 
    TLatex* texCMS = new TLatex;
    texCMS->SetNDC();
    texCMS->SetTextFont(42);
    texCMS->SetTextSize(0.05);
    texCMS->SetTextAlign(12);
    
    TH1D* hist = new TH1D("hist","",10,2.6,3.5);
    hist->SetLineWidth(0);
    //hist->GetYaxis()->SetRangeUser(0,0.3);
    hist->GetXaxis()->SetTitle("#it{m}_{#mu#mu} (GeV)");
    hist->GetYaxis()->SetTitle("v_{2}^{S+B}");
    hist->GetXaxis()->CenterTitle();
    hist->GetYaxis()->CenterTitle();
    hist->GetXaxis()->SetTitleOffset(1.3);
    hist->GetYaxis()->SetTitleOffset(2);
    hist->GetXaxis()->SetLabelOffset(0.007);
    hist->GetYaxis()->SetLabelOffset(0.007);
    hist->GetXaxis()->SetTitleSize(0.045);
    hist->GetYaxis()->SetTitleSize(0.045);
    hist->GetXaxis()->SetTitleFont(42);
    hist->GetYaxis()->SetTitleFont(42);
    hist->GetXaxis()->SetLabelFont(42);
    hist->GetYaxis()->SetLabelFont(42);
    hist->GetXaxis()->SetLabelSize(0.04);
    hist->GetYaxis()->SetLabelSize(0.04);
    hist->SetMinimum(0.01);
    hist->SetMaximum(0.33);
    
    c2->cd();
    hist->Draw();
    
    for(int i=0;i<npt;i++)
    {
        TH1D* h_data = (TH1D*)file1->Get(Form("massjpsi_pt%d",i));
        h_data->SetMinimum(0);
        h_data->SetMarkerSize(0.8);
        h_data->SetMarkerStyle(20);
        h_data->SetLineWidth(1);
        h_data->SetOption("e");
        
        h_data->Rebin(2);

        h_data->GetXaxis()->SetRangeUser(2.6,3.5);
        h_data->GetXaxis()->SetTitle("#it{m}_{#mu#mu} (GeV)");
        h_data->GetYaxis()->SetTitle("Entries / 10 MeV");
        h_data->GetXaxis()->CenterTitle();
        h_data->GetYaxis()->CenterTitle();
        h_data->GetXaxis()->SetTitleOffset(1.3);
        h_data->GetYaxis()->SetTitleOffset(2);
        h_data->GetXaxis()->SetLabelOffset(0.007);
        h_data->GetYaxis()->SetLabelOffset(0.007);
        h_data->GetXaxis()->SetTitleSize(0.045);
        h_data->GetYaxis()->SetTitleSize(0.045);
        h_data->GetXaxis()->SetTitleFont(42);
        h_data->GetYaxis()->SetTitleFont(42);
        h_data->GetXaxis()->SetLabelFont(42);
        h_data->GetYaxis()->SetLabelFont(42);
        h_data->GetXaxis()->SetLabelSize(0.04);
        h_data->GetYaxis()->SetLabelSize(0.04);
        
        h_data->GetXaxis()->SetNoExponent(true);
        ((TGaxis*)h_data->GetXaxis())->SetMaxDigits(7);
        
        h_data->SetMaximum(h_data->GetMaximum()*1.5);
        
        TH1D* h_pt = (TH1D*)file1->Get(Form("Ptjpsi_eff_pt%d",i));
        TH1D* h_KET = (TH1D*)file1->Get(Form("KETjpsi_eff_pt%d",i));
        pt[i] = h_pt->GetMean();
        KET_ncq[i] = h_KET->GetMean()/2.0;

        c[i]->cd(1);
        
        /*p definitions
         [0] CB1 yield;
         [1] Common mean of CB and Gaus;
         [2] CB1 sigma;
         [3] CB n;
         [4] CB alpha;
         [5] CB2 yield;
         [6] CB2 sigma;
         [7-10] poly 3;
         [11] v2 signal;
         [12-13] v2 bkg;
         */
        TF1* f = new TF1(Form("f_%d",i), crystalball_function_total, fit_range_low, fit_range_high, 11);
        f->SetLineColor(2);
        f->SetLineWidth(1);
        f->SetParNames("CB1_Yield","common_mean","CB1_sigma","CB_N","CB_Alpha","CB2_Yield","CB2_Sigma","Pol0","Pol1","Pol2","Pol3");

        //first fit data mass signal + bkg
        
        f->SetParameter(0,10000.);
        f->SetParameter(1,JPsi_mass);
        f->SetParameter(2,0.03);
        f->SetParameter(3,1.0);
        f->SetParameter(4,1.0);
        f->SetParameter(5,10000);
        f->SetParameter(6,0.03);
        
        f->SetParLimits(2,0.01,0.1);
        f->SetParLimits(6,0.01,0.1);
        
        //fix alpha & n from MC
        f->FixParameter(4,alpha_fit[i]);
        f->FixParameter(3,n_fit[i]);
        
        f->FixParameter(1,JPsi_mass); //for first few attempt fix mean of gaussian to get reasonable estimation of other pars; later open it up
        h_data->Fit(Form("f_%d",i),"q","",fit_range_low,fit_range_high);
        h_data->Fit(Form("f_%d",i),"q","",fit_range_low,fit_range_high);
        f->ReleaseParameter(1); //now let gaussian mean float
        h_data->Fit(Form("f_%d",i),"L q","",fit_range_low,fit_range_high);
        h_data->Fit(Form("f_%d",i),"L q","",fit_range_low,fit_range_high);
        h_data->Fit(Form("f_%d",i),"L m","",fit_range_low,fit_range_high);
        
        
        //draw D0 signal separately
        TF1* f1 = new TF1(Form("f_sig_%d",i), crystalball_function_signal, fit_range_low, fit_range_high, 7);
        f1->SetLineColor(kOrange-3);
        f1->SetLineWidth(1);
        f1->SetLineStyle(2);
        f1->SetFillColorAlpha(kOrange-3,0.3);
        f1->SetFillStyle(1001);
        f1->FixParameter(0,f->GetParameter(0));
        f1->FixParameter(1,f->GetParameter(1));
        f1->FixParameter(2,f->GetParameter(2));
        f1->FixParameter(3,f->GetParameter(3));
        f1->FixParameter(4,f->GetParameter(4));
        f1->FixParameter(5,f->GetParameter(5));
        f1->FixParameter(6,f->GetParameter(6));
        
        fmasssig[i] = (TF1*)f1->Clone();
        fmasssig[i]->SetName(Form("masssigfcn_pt%d",i));
        fmasssig[i]->Write();
        
        f1->Draw("LSAME");
        
        //draw poly bkg separately
        TF1* f3 = new TF1(Form("f_bkg_%d",i),"[7] + [8]*x + [9]*x*x + [10]*x*x*x", fit_range_low, fit_range_high);
        f3->SetLineColor(4);
        f3->SetLineWidth(1);
        f3->SetLineStyle(2);
        f3->FixParameter(7,f->GetParameter(7));
        f3->FixParameter(8,f->GetParameter(8));
        f3->FixParameter(9,f->GetParameter(9));
        f3->FixParameter(10,f->GetParameter(10));
        
        fmassbkg[i] = (TF1*)f3->Clone();
        fmassbkg[i]->SetName(Form("massbkgfcn_pt%d",i));
        fmassbkg[i]->Write();
        
        f3->Draw("LSAME");
        
        tex->DrawLatex(0.22,0.86,"185 #leq N_{trk}^{offline} < 250");
        tex->DrawLatex(0.22,0.80,Form("%.1f < p_{T} < %.1f GeV",ptbin[i],ptbin[i+1]));
        tex->DrawLatex(0.22,0.74,"-2.86 < y_{cm} < -1.86 or 0.94 < y_{cm} < 1.94");
        
        texCMS->DrawLatex(.18,.97,"#font[61]{CMS} #it{Preliminary}");
        //texCMS->DrawLatex(.18,.97,"#font[61]{CMS}");
        texCMS->DrawLatex(0.73,0.97, "#scale[0.8]{pPb 8.16 TeV}");
        
        TLegend* leg = new TLegend(0.21,0.4,0.5,0.65,NULL,"brNDC");
        leg->SetBorderSize(0);
        leg->SetTextSize(0.045);
        leg->SetTextFont(42);
        leg->SetFillStyle(0);
        leg->AddEntry(h_data,"data","p");
        leg->AddEntry(f,"Fit","L");
        leg->AddEntry(f1,"J/#psi Signal","f");
        leg->AddEntry(f3,"Combinatorial","l");
        leg->Draw("SAME");
        
        sigfrac[i] = f1->Integral(2.94,3.24)/f->Integral(2.94,3.24);
        
        //c->Print(Form("plots/massfit_pt%d.pdf",i));
        
        //fit vn
        //[9] is vn_sig
        //[10-11] is vn bkg, const + linear vn(pT)
        TGraphErrors* vn_data = (TGraphErrors*)file1->Get(Form("v2_mass_pt%d",i));
        
        c[i]->cd(2);
        
        hist->Draw();
        
        TF1* fmass_combinemassvnfit = new TF1(Form("fmass_combinemassvnfit_%d",i),crystalball_function_total, fit_range_low, fit_range_high, 11);
        
        TF1* fvn_combinemassvnfit = new TF1(Form("fvn_combinemassvnfit_%d",i), crystalball_function_v2, fit_range_low, fit_range_high, 15);
        
        fmass_combinemassvnfit->SetLineColor(2);
        fmass_combinemassvnfit->SetLineWidth(1);
        
        fvn_combinemassvnfit->SetLineColor(2);
        fvn_combinemassvnfit->SetLineWidth(1);

        ROOT::Math::WrappedMultiTF1 wfmass_combinemassvnfit(*fmass_combinemassvnfit,1);
        ROOT::Math::WrappedMultiTF1 wfvn_combinemassvnfit(*fvn_combinemassvnfit,1);
        
        ROOT::Fit::DataOptions opt;
        ROOT::Fit::DataRange range_massfit;

        range_massfit.SetRange(fit_range_low,fit_range_high);
        ROOT::Fit::BinData datamass(opt,range_massfit);
        ROOT::Fit::FillData(datamass, h_data);
        
        ROOT::Fit::DataRange range_vnfit;
        range_vnfit.SetRange(fit_range_low,fit_range_high);
        ROOT::Fit::BinData datavn(opt,range_vnfit);
        ROOT::Fit::FillData(datavn, vn_data);
        
        ROOT::Fit::Chi2Function chi2_B(datamass, wfmass_combinemassvnfit);
        ROOT::Fit::Chi2Function chi2_SB(datavn, wfvn_combinemassvnfit);
        
        GlobalChi2_poly3bkg_floatwidth globalChi2(chi2_B, chi2_SB);

        ROOT::Fit::Fitter fitter;
        
        const int Npar = 15;
        double par0[Npar];
        for( int ipar = 0; ipar < f->GetNpar(); ipar++ ) par0[ipar] = f->GetParameter(ipar);
        par0[11] = 0.01;
        par0[12] = 0.10;
        par0[13] = 0.05;
        par0[14] = 0.01;

        
        fitter.Config().SetParamsSettings(Npar,par0);
        // fix parameter
        fitter.Config().ParSettings(0).Fix();
        fitter.Config().ParSettings(1).Fix();
        fitter.Config().ParSettings(2).Fix();
        fitter.Config().ParSettings(3).Fix();
        fitter.Config().ParSettings(4).Fix();
        fitter.Config().ParSettings(5).Fix();
        fitter.Config().ParSettings(6).Fix();
        fitter.Config().ParSettings(7).Fix();
        fitter.Config().ParSettings(8).Fix();
        fitter.Config().ParSettings(9).Fix();
        fitter.Config().ParSettings(10).Fix();
        
        fitter.Config().MinimizerOptions().SetPrintLevel(0);
        fitter.Config().SetMinimizer("Minuit2","Migrad");

        fitter.FitFCN(Npar,globalChi2,0,datamass.Size()+datavn.Size(),true);
        ROOT::Fit::FitResult result = fitter.Result();
        result.Print(std::cout);
        
        fmass_combinemassvnfit->SetFitResult( result, iparmassfit_poly3bkg_floatwidth);
        fmass_combinemassvnfit->SetRange(range_massfit().first, range_massfit().second);
        fmass_combinemassvnfit->SetLineColor(kRed);
        h_data->GetListOfFunctions()->Add(fmass_combinemassvnfit);
        //c->cd();
        //h_data->Draw();
        
        fvn_combinemassvnfit->SetFitResult( result, iparvnfit_poly3bkg_floatwidth);
        fvn_combinemassvnfit->SetRange(range_vnfit().first, range_vnfit().second);
        fvn_combinemassvnfit->SetLineColor(2);
        //fvn_combinemassvnfit->SetLineStyle(2);
        vn_data->GetListOfFunctions()->Add(fvn_combinemassvnfit);
        vn_data->SetTitle("");
        vn_data->SetMarkerSize(0.8);
        vn_data->SetLineWidth(1);
        //c1->cd();
        vn_data->Draw("PESAME");
        
        fvn[i] = (TF1*)fvn_combinemassvnfit->Clone();
        fvn[i]->SetName(Form("vnfit_pt%d",i));
        fvn[i]->Write();
        
        fmasstotal[i] = (TF1*)fmass_combinemassvnfit->Clone();
        fmasstotal[i]->SetName(Form("masstotalfcn_pt%d",i));
        fmasstotal[i]->Write();
        
        tex->DrawLatex(0.22,0.86,"185 #leq N_{trk}^{offline} < 250");
        tex->DrawLatex(0.22,0.80,Form("%.1f < p_{T} < %.1f GeV",ptbin[i],ptbin[i+1]));
        //tex->DrawLatex(0.22,0.74,"1.4 < |y_{cm}+0.46| < 2.4");
        tex->DrawLatex(0.22,0.74,"-2.86 < y_{cm} < -1.86 or 0.94 < y_{cm} < 1.94");
        //tex->DrawLatex(0.22,0.68,"|#Delta#eta| > 2");

        
        //texCMS->DrawLatex(.18,.97,"#font[61]{CMS}");
        texCMS->DrawLatex(.18,.97,"#font[61]{CMS} #it{Preliminary}");
        texCMS->DrawLatex(0.73,0.97, "#scale[0.8]{pPb 8.16 TeV}");
        
        v2[i] = fvn_combinemassvnfit->GetParameter(11);
        v2e[i] = fvn_combinemassvnfit->GetParError(11);
        v2_bkg[i] = fvn_combinemassvnfit->GetParameter(12) + fvn_combinemassvnfit->GetParameter(13) * JPsi_mass;
        v2_ncq[i] = v2[i]/2.0;
        v2e_ncq[i] = v2e[i]/2.0;
        a[i] = fvn_combinemassvnfit->GetParameter(12);
        b[i] = fvn_combinemassvnfit->GetParameter(13);
        
        TF1* fvnbkg = new TF1(Form("fvnbkg_%d",1),"( [0] + [1] * x)", fit_range_low, fit_range_high);
        fvnbkg->FixParameter(0,fvn_combinemassvnfit->GetParameter(12));
        fvnbkg->FixParameter(1,fvn_combinemassvnfit->GetParameter(13));
        
        fvnbkg->SetName(Form("fvnbkg_fcn_pt%d",i));
        fvnbkg->Write();
        
        fvnbkg->SetLineStyle(7);
        //fvnbkg->Draw("LSAME");
        
        TF1* fvnsig = new TF1(Form("fvnsig_%d",i),function_v2_sig,fit_range_low,fit_range_high,12);
        for(int k=0;k<12;k++)
        {
            fvnsig->FixParameter(k,fvn_combinemassvnfit->GetParameter(k));
            
        }
        
        fvnsig->SetLineColor(kOrange-3);
        fvnsig->SetLineWidth(1);
        fvnsig->SetLineStyle(2);
        fvnsig->SetFillColorAlpha(kOrange-3,0.3);
        fvnsig->SetFillStyle(1001);
        
        //fvnsig->Draw("LSAME");
        
        TLegend* leg1 = new TLegend(0.72,0.525,0.91,0.65,NULL,"brNDC");
        leg1->SetBorderSize(0);
        leg1->SetTextSize(0.045);
        leg1->SetTextFont(42);
        leg1->SetFillStyle(0);
        leg1->AddEntry(h_data,"data","p");
        leg1->AddEntry(fvn_combinemassvnfit,"Fit","l");
        //leg1->AddEntry(fvnsig,"#alpha(#it{m}_{#mu#mu})v_{2}^{S}","f");
        leg1->Draw("SAME");

        double xmass[200];
        double pullmass[200];
        
        float Chi2=0;
        int ndf = (fit_range_high - fit_range_low)/0.01 - 8;
        
        for(int k=0;k<h_data->GetNbinsX();k++)
        {
            xmass[k] = h_data->GetBinCenter(k);
            pullmass[k] = (h_data->GetBinContent(k) - fmass_combinemassvnfit->Eval(xmass[k]))/h_data->GetBinError(k);
            if(fabs(pullmass[k])<5)
            {
                //cout<<pullmass[k]<<endl;
                Chi2 += pullmass[k]*pullmass[k];
            }
        }

        c[i]->cd(1);
        tex->DrawLatex(0.22,0.67,Form("#chi^{2}/ndf = %.0f/%d",Chi2,ndf));
        
        double xv2[200];
        double pullv2[200];
        double v2y[200];
        
        float Chi2v2=0;
        int ndfv2 = 8 - 4; //Nbin - Npar
        
        for(int k=0;k<vn_data->GetN()-1;k++)
        {
            vn_data->GetPoint(k,xv2[k],v2y[k]);
            //xv2[k] = vn_dara->GetBinCenter(k);
            pullv2[k] = (v2y[k] - fvn_combinemassvnfit->Eval(xv2[k]))/vn_data->GetErrorY(k);
            cout<<k<<": "<<pullv2[k]<<endl;
            if(fabs(pullv2[k])<1000)
            {
                //cout<<pullmass[k]<<endl;
                Chi2v2 += pullv2[k]*pullv2[k];
            }
            cout<<"fcn: "<<fvn_combinemassvnfit->Eval(xv2[k])<<endl;
            cout<<"data: "<<v2y[k]<<endl;
        }

        c[i]->cd(2);
        tex->DrawLatex(0.22,0.67,Form("#chi^{2}/ndf = %.1f/%d",Chi2v2,ndfv2));
        
    }
    
    for(int i=0;i<npt;i++)
    {
        c[i]->Print(Form("plots/v30/eff/exp/JPsi_mass_vnfit_combine_pt%d.pdf",i));
        c[i]->Print(Form("plots/v30/eff/exp/JPsi_mass_vnfit_combine_pt%d.gif",i));
    }
    
    TGraphErrors* v2plot = new TGraphErrors(npt,pt,v2,0,v2e);
    TGraphErrors* v2ncqplot = new TGraphErrors(npt,KET_ncq,v2_ncq,0,v2e_ncq);
    TGraphErrors* v2bkgplot = new TGraphErrors(npt,pt,v2_bkg,0,0);
    
    v2plot->SetName("v2vspt");
    v2ncqplot->SetName("v2vsKET_ncq");
    v2bkgplot->SetName("v2bkgvspt");
    
    v2plot->Write();
    v2ncqplot->Write();
    v2bkgplot->Write();
}
Exemplo n.º 4
0
void combinedFit() {

  TH1D * hB = new TH1D("hB","histo B",100,0,100);
  TH1D * hSB = new TH1D("hSB","histo S+B",100, 0,100);

  TF1 * fB = new TF1("fB","expo",0,100);
  fB->SetParameters(1,-0.05);
  hB->FillRandom("fB");

  TF1 * fS = new TF1("fS","gaus",0,100);
  fS->SetParameters(1,30,5);

  hSB->FillRandom("fB",2000);
  hSB->FillRandom("fS",1000);

  // perform now global fit

  TF1 * fSB = new TF1("fSB","expo + gaus(2)",0,100);

  ROOT::Math::WrappedMultiTF1 wfB(*fB,1);
  ROOT::Math::WrappedMultiTF1 wfSB(*fSB,1);

  ROOT::Fit::DataOptions opt;
  ROOT::Fit::DataRange rangeB;
  // set the data range
  rangeB.SetRange(10,90);
  ROOT::Fit::BinData dataB(opt,rangeB);
  ROOT::Fit::FillData(dataB, hB);

  ROOT::Fit::DataRange rangeSB;
  rangeSB.SetRange(10,50);
  ROOT::Fit::BinData dataSB(opt,rangeSB);
  ROOT::Fit::FillData(dataSB, hSB);

  ROOT::Fit::Chi2Function chi2_B(dataB, wfB);
  ROOT::Fit::Chi2Function chi2_SB(dataSB, wfSB);

  GlobalChi2 globalChi2(chi2_B, chi2_SB);

  ROOT::Fit::Fitter fitter;

  const int Npar = 6;
  double par0[Npar] = { 5,5,-0.1,100, 30,10};

  // create before the parameter settings in order to fix or set range on them
  fitter.Config().SetParamsSettings(6,par0);
  // fix 5-th parameter
  fitter.Config().ParSettings(4).Fix();
  // set limits on the third and 4-th parameter
  fitter.Config().ParSettings(2).SetLimits(-10,-1.E-4);
  fitter.Config().ParSettings(3).SetLimits(0,10000);
  fitter.Config().ParSettings(3).SetStepSize(5);

  fitter.Config().MinimizerOptions().SetPrintLevel(0);
  fitter.Config().SetMinimizer("Minuit2","Migrad");

  // fit FCN function directly
  // (specify optionally data size and flag to indicate that is a chi2 fit)
  fitter.FitFCN(6,globalChi2,0,dataB.Size()+dataSB.Size(),true);
  ROOT::Fit::FitResult result = fitter.Result();
  result.Print(std::cout);

  TCanvas * c1 = new TCanvas("Simfit","Simultaneous fit of two histograms",
                             10,10,700,700);
  c1->Divide(1,2);
  c1->cd(1);
  gStyle->SetOptFit(1111);

  fB->SetFitResult( result, iparB);
  fB->SetRange(rangeB().first, rangeB().second);
  fB->SetLineColor(kBlue);
  hB->GetListOfFunctions()->Add(fB);
  hB->Draw();

  c1->cd(2);
  fSB->SetFitResult( result, iparSB);
  fSB->SetRange(rangeSB().first, rangeSB().second);
  fSB->SetLineColor(kRed);
  hSB->GetListOfFunctions()->Add(fSB);
  hSB->Draw();


}
Int_t line3Dfit()
{
   gStyle->SetOptStat(0);
   gStyle->SetOptFit();


   //double e = 0.1;
   Int_t nd = 10000;


//    double xmin = 0; double ymin = 0;
//    double xmax = 10; double ymax = 10;

   TGraph2D * gr = new TGraph2D();

   // Fill the 2D graph
   double p0[4] = {10,20,1,2};

   // generate graph with the 3d points
   for (Int_t N=0; N<nd; N++) {
      double x,y,z = 0;
      // Generate a random number 
      double t = gRandom->Uniform(0,10);
      line(t,p0,x,y,z);
      double err = 1;
    // do a gaussian smearing around the points in all coordinates
      x += gRandom->Gaus(0,err);  
      y += gRandom->Gaus(0,err);  
      z += gRandom->Gaus(0,err);  
      gr->SetPoint(N,x,y,z);
      //dt->SetPointError(N,0,0,err);
   }
   // fit the graph now 
   
   ROOT::Fit::Fitter  fitter;
   
   
   // make the functor objet
   SumDistance2 sdist(gr);
#ifdef __CINT__
   ROOT::Math::Functor fcn(&sdist,4,"SumDistance2");
#else
   ROOT::Math::Functor fcn(sdist,4);
#endif
   // set the function and the initial parameter values
   double pStart[4] = {1,1,1,1};
   fitter.SetFCN(fcn,pStart);
   // set step sizes different than default ones (0.3 times parameter values)
   for (int i = 0; i < 4; ++i) fitter.Config().ParSettings(i).SetStepSize(0.01);
  
   bool ok = fitter.FitFCN();
   if (!ok) {
      Error("line3Dfit","Line3D Fit failed");
      return 1;
   }
   
   const ROOT::Fit::FitResult & result = fitter.Result();
   
   std::cout << "Total final distance square " << result.MinFcnValue() << std::endl;
   result.Print(std::cout);
   

   gr->Draw("p0");

   // get fit parameters
   const double * parFit = result.GetParams();

   
   // draw the fitted line
   int n = 1000;
   double t0 = 0;
   double dt = 10;
   TPolyLine3D *l = new TPolyLine3D(n);
   for (int i = 0; i <n;++i) {
      double t = t0+ dt*i/n;
      double x,y,z;
      line(t,parFit,x,y,z);
      l->SetPoint(i,x,y,z);
   }
   l->SetLineColor(kRed);
   l->Draw("same");
   
   // draw original line
   TPolyLine3D *l0 = new TPolyLine3D(n);
   for (int i = 0; i <n;++i) {
      double t = t0+ dt*i/n;
      double x,y,z;
      line(t,p0,x,y,z);
      l0->SetPoint(i,x,y,z);
   }
   l0->SetLineColor(kBlue);
   l0->Draw("same");
   return 0;
}
void view_SMEvents_3D_from_Hits() {
	/*** Displays an 3D occupancy plot for each SM Event. (stop mode event)

	Can choose which SM event to start at. (find "CHOOSE THIS" in this script)
	Input file must be a Hits file (_interpreted_Hits.root file).
	***/
	gROOT->Reset();

	// Setting up file, treereader, histogram
	TFile *f = new TFile("/home/pixel/pybar/tags/2.0.2_new/pyBAR-master/pybar/module_202_new/101_module_202_new_stop_mode_ext_trigger_scan_interpreted_Hits.root");


	if (!f) { // if we cannot open the file, print an error message and return immediately
		cout << "Error: cannot open the root file!\n";
		//return;
	}

	TTreeReader *reader = new TTreeReader("Table", f);

	TTreeReaderValue<UInt_t> h5_file_num(*reader, "h5_file_num");
	TTreeReaderValue<Long64_t> event_number(*reader, "event_number");
	TTreeReaderValue<UChar_t> tot(*reader, "tot");
	TTreeReaderValue<UChar_t> relative_BCID(*reader, "relative_BCID");
	TTreeReaderValue<Long64_t> SM_event_num(*reader, "SM_event_num");
	TTreeReaderValue<Double_t> x(*reader, "x");
	TTreeReaderValue<Double_t> y(*reader, "y");
	TTreeReaderValue<Double_t> z(*reader, "z");

	// Initialize the canvas and graph
	TCanvas *c1 = new TCanvas("c1","3D Occupancy for Specified SM Event", 1000, 10, 900, 550);
	c1->SetRightMargin(0.25);
	TGraph2D *graph = new TGraph2D();

	// Variables used to loop the main loop
	bool endOfReader = false; // if reached end of the reader
	bool quit = false; // if pressed q
	int smEventNum = 1; // the current SM-event CHOOSE THIS to start at desired SM event number
	
	// Main Loop (loops for every smEventNum)
	while (!endOfReader && !quit) {
		// Variables used in this main loop
		int startEntryNum = 0;
		int endEntryNum = 0;
		string histTitle = "3D Occupancy for SM Event ";
		string inString = "";
		bool fitFailed = false; // true if the 3D fit failed
		bool lastEvent = false;

		// Declaring some important output values for the current graph and/or line fit
		int numEntries = 0;
		double sumSquares = 0;

		// Get startEntryNum and endEntryNum
		startEntryNum = getEntryNumWithSMEventNum(reader, smEventNum);
		endEntryNum = getEntryNumWithSMEventNum(reader, smEventNum + 1);

		if (startEntryNum == -2) { // can't find the smEventNum
			cout << "Error: There should not be any SM event numbers that are missing." << "\n";
		} else if (startEntryNum == -3) { 
			endOfReader = true;
			break;
		} else if (endEntryNum == -3) { // assuming no SM event nums are skipped
			endEntryNum = reader->GetEntries(false);
			lastEvent = true;
		}

		// Fill TGraph with points and set title and axes
		graph = new TGraph2D(); // create a new TGraph to refresh

		reader->SetEntry(startEntryNum);
		for (int i = 0; i < endEntryNum - startEntryNum; i++) {
			graph->SetPoint(i, (*x - 0.001), (*y + 0.001), (*z - 0.001));
			endOfReader = !(reader->Next());
		}

		histTitle.append(to_string(smEventNum));
		graph->SetTitle(histTitle.c_str());
		graph->GetXaxis()->SetTitle("x (mm)");
		graph->GetYaxis()->SetTitle("y (mm)");
		graph->GetZaxis()->SetTitle("z (mm)");

		graph->GetXaxis()->SetLimits(0, 20); // ROOT is buggy, x and y use setlimits()
		graph->GetYaxis()->SetLimits(-16.8, 0); // but z uses setrangeuser()
		graph->GetZaxis()->SetRangeUser(0, 40.96);
		c1->SetTitle(histTitle.c_str());

		// 3D Fit, display results, draw graph and line fit, only accept "good" events, get input
		if (!endOfReader || lastEvent) {
			// Display some results
			numEntries = graph->GetN();
			cout << "Current SM Event Number: " << smEventNum << "\n";
			cout << "Number of entries:       " << numEntries << "\n";

			// Starting the fit. First, get decent starting parameters for the fit - do two 2D fits (one for x vs z, one for y vs z)
			TGraph *graphZX = new TGraph();
			TGraph *graphZY = new TGraph();
			reader->SetEntry(startEntryNum);
			for (int i = 0; i < endEntryNum - startEntryNum; i++) {
				graphZX->SetPoint(i, (*z - 0.001), (*x + 0.001));
				graphZY->SetPoint(i, (*z - 0.001), (*y + 0.001));
				reader->Next();
			}
			TFitResultPtr fitZX = graphZX->Fit("pol1", "WQS"); // w for ignore error of each pt, q for quiet (suppress results output), s for return a tfitresultptr
			TFitResultPtr fitZY = graphZY->Fit("pol1", "WQS");
			Double_t param0 = fitZX->GetParams()[0];
			Double_t param1 = fitZX->GetParams()[1];
			Double_t param2 = fitZY->GetParams()[0];
			Double_t param3 = fitZY->GetParams()[1];

			// // Draw the lines for the two 2D fits
			// int n = 2;
			// TPolyLine3D *lineZX = new TPolyLine3D(n);
			// TPolyLine3D *lineZY = new TPolyLine3D(n);
			// lineZX->SetPoint(0, param0, 0, 0);
			// lineZX->SetPoint(1, param0 + param1 * 40.96, 0, 40.96);
			// lineZX->SetLineColor(kBlue);
			// lineZX->Draw("same");
			// lineZY->SetPoint(0, 0, param2, 0);
			// lineZY->SetPoint(1, 0, param2 + param3 * 40.96, 40.96);
			// lineZY->SetLineColor(kGreen);
			// lineZY->Draw("same");


			// 3D FITTING CODE (based on line3Dfit.C), draw graph and line fit
			ROOT::Fit::Fitter  fitter;
		   	SumDistance2 sdist(graph);
#ifdef __CINT__
		   	ROOT::Math::Functor fcn(&sdist,4,"SumDistance2");
#else
		   	ROOT::Math::Functor fcn(sdist,4);
#endif
			// set the function and the initial parameter values
			double pStart[4] = {param0,param1,param2,param3};
			fitter.SetFCN(fcn,pStart);
			// set step sizes different than default ones (0.3 times parameter values)
			for (int i = 0; i < 4; ++i) fitter.Config().ParSettings(i).SetStepSize(0.01);

			bool ok = fitter.FitFCN();
			if (!ok) {
			  Error("line3Dfit","Line3D Fit failed");
			  fitFailed = true;
			} else {
				const ROOT::Fit::FitResult & result = fitter.Result();
				const double * fitParams = result.GetParams();

				sumSquares = result.MinFcnValue();
				std::cout << "Sum of distance squares:  " << sumSquares << std::endl;
				std::cout << "Sum of distance squares divided by numEntries: " << sumSquares/numEntries << std::endl;
				std::cout << "Theta : " << TMath::ATan(sqrt(pow(fitParams[1], 2) + pow(fitParams[3], 2))) << std::endl;
				// result.Print(std::cout); // (un)suppress results output

				// Draw the graph
				graph->SetMarkerStyle(8);
				graph->SetMarkerSize(0.5);
				graph->Draw("pcol");

				// Draw the fitted line
				int n = 1000;
				double t0 = 0; // t is the z coordinate
				double dt = 40.96;
				TPolyLine3D *l = new TPolyLine3D(n);
				for (int i = 0; i <n;++i) {
				  double t = t0+ dt*i/n;
				  double x,y,z;
				  line(t,fitParams,x,y,z);
				  l->SetPoint(i,x,y,z);
				}
				l->SetLineColor(kRed);
				l->Draw("same");

				// Access fit params and minfcnvalue
				// cout << "FIT1: " << fitParams[1] << "\n";
				// cout << "FIT2: " << result.MinFcnValue() << "\n";
			}

			// Criteria to be a good event (if not good entry, then don't show)
			bool isGoodEvent = false;

				// the following block of code finds the mean X, Y ans Z values
				double meanX = 0;
				double meanY = 0;
				double meanZ = 0;
				reader->SetEntry(startEntryNum);
				for (int i = 0; i < endEntryNum - startEntryNum; i++) {
					meanX += graph->GetX()[i];
					meanY += graph->GetY()[i];
					meanZ += graph->GetZ()[i];
					reader->Next();
				}
				meanX /= endEntryNum - startEntryNum;
				meanY /= endEntryNum - startEntryNum;
				meanZ /= endEntryNum - startEntryNum;

				// the following code block calculates the fraction of the hits in the smEvent that are inside a sphere, centered at the mean XYZ, of radius 'radius' (larger fraction means the track is less like a long streak and more like a dense blob)
				double radius = 1; // length in mm 
				double fractionInsideSphere = 0;
				reader->SetEntry(startEntryNum);
				for (int i = 0; i < endEntryNum - startEntryNum; i++) {
					double distanceFromMeanXYZ = sqrt(pow(graph->GetX()[i] - meanX, 2) + pow(graph->GetY()[i] - meanY, 2) + pow(graph->GetZ()[i] - meanZ, 2));
					if (distanceFromMeanXYZ <= 2) {
						fractionInsideSphere += 1;
					}
					reader->Next();
				}
				fractionInsideSphere /= endEntryNum - startEntryNum;

				cout << "fraction inside sphere: " << fractionInsideSphere << "\n";

			// if (numEntries >= 50 
			// 	&& sumSquares/numEntries < 2.0 
			// 	&& fractionInsideSphere < 0.8) {

			// 	isGoodEvent = true;
			// }

			isGoodEvent = true;

			if (isGoodEvent) { // won't show drawings or ask for input unless its a good event
				c1->Update(); // show all the drawings
				// handle input
				bool inStringValid = false;
	            do {
		            cout << "<Enter>: next event; 'b': previous SM event; [number]: specific SM event number; 'q': quit.\n";
		            getline(cin, inString);

		            // Handles behavior according to input
		            if (inString.empty()) { // <Enter>
		            	// leave things be
						inStringValid = true;
		            } else if (inString.compare("b") == 0) {
						smEventNum -= 2; // because it gets incremented once at the end of this do while loop
						inStringValid = true;
					} else if (inString.compare("q") == 0 || inString.compare(".q") == 0) {
						quit = true;
						inStringValid = true;
					} else if (canConvertStringToPosInt(inString)) {
						smEventNum = convertStringToPosInt(inString) - 1; // -1 because it gets incremented once at the end of this do while loop
						inStringValid = true;
					} // else, leave inStringValid as false, so that it asks for input again
				} while (!inStringValid);
			} else {
				cout << "\n";
			}

		}
		smEventNum++;
	}

	cout << "Exiting program.\n";
}
TF1* fit_histo_poly3bkg_floatwidth_poly2bkg_combinemassvnfit( bool isPbPb, int centlow, int centhigh, TH1D * histo, TH1D * h_mc_matched_signal, TH1D * h_mc_matched_kpiswapped, int ipt, TString cfgname, bool get_sig_bkg_ratio = false, TH1D * Ratio_signal_foreground = NULL, TH1D * h_vnvsmass = NULL, TH1D * h_vnvspt = NULL, TString vnorder = "v2", TString EPorSP = "SP", TH1D * h_vnvspt_bkg = NULL)
{
	Double_t setparam0=100.;
	Double_t setparam1=1.8648;
	Double_t setparam2=0.03;
	Double_t setparam3=0.005;
	Double_t setparam4=0.1;
	Double_t setparam7=0.1;
	Double_t fixparam1=1.8648;

	double fit_range_low = generalfitrange_masslow;
	double fit_range_high = generalfitrange_masshigh;
	double histomassbinsize = histo->GetBinWidth(10);

	float ptmin = ptbins[ipt];
	float ptmax = ptbins[ipt+1];

	//remove the fit function from v2 fit when perform v3 fit
	if( histo->GetListOfFunctions()->FindObject(Form("fmass_combinemassvnfit_%s_%d",cfgname.Data(),ipt)) )
		histo->GetListOfFunctions()->Remove( histo->GetListOfFunctions()->FindObject(Form("fmass_combinemassvnfit_%s_%d",cfgname.Data(),ipt)) );

	TH1F* histo_copy_nofitfun = ( TH1F * ) histo->Clone("histo_copy_nofitfun");
	TH1F* histo_massfit = ( TH1F * ) histo->Clone("histo_massfit");

	TCanvas* cfg= new TCanvas(Form("cfg_poly3bkg_floatwidth_poly2bkg_combinemassvnfit_%s_%d",cfgname.Data(),ipt),Form("cfg_poly3bkg_floatwidth_poly2bkg_combinemassvnfit_%s_%d",cfgname.Data(),ipt),600,600);

    gPad->SetRightMargin(0.043);
    gPad->SetLeftMargin(0.18);
    gPad->SetTopMargin(0.1);
    gPad->SetBottomMargin(0.145);

    TF1* f = new TF1(Form("f_%s_%d",cfgname.Data(),ipt),"[0]*([5]*([4]*TMath::Gaus(x,[1],[2]*(1.0 +[6]))/(sqrt(2*3.14159)*[2]*(1.0 +[6]))+(1-[4])*TMath::Gaus(x,[1],[3]*(1.0 +[6]))/(sqrt(2*3.14159)*[3]*(1.0 +[6])))+(1-[5])*TMath::Gaus(x,[8],[7]*(1.0 +[6]))/(sqrt(2*3.14159)*[7]*(1.0 +[6]))) + [9] + [10]*x + [11]*x*x + [12]*x*x*x", fit_range_low, fit_range_high);

	f->SetParLimits(10,-1000,1000);
	f->SetParLimits(3,0.001,0.05);
	f->SetParLimits(2,0.01,0.1);
	f->SetParLimits(7,0.02,0.2);
	f->SetParLimits(5,0,1);
	f->SetParLimits(4,0,1);

	f->SetParameter(0,setparam0);
	f->SetParameter(1,setparam1);
	f->SetParameter(2,setparam2);
	f->SetParameter(3,setparam3);
	f->SetParameter(4,setparam4);

	f->FixParameter(7,setparam7);
	f->FixParameter(8,setparam1);
	f->FixParameter(5,1);
	f->FixParameter(1,fixparam1);
	f->FixParameter(9,0);
	f->FixParameter(10,0);
	f->FixParameter(11,0);
	f->FixParameter(12,0);
	f->FixParameter(6,0);

	h_mc_matched_signal->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"q","",fit_range_low,fit_range_high);
	h_mc_matched_signal->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"q","",fit_range_low,fit_range_high);
	f->ReleaseParameter(1);
	h_mc_matched_signal->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"L q","",fit_range_low,fit_range_high);
	h_mc_matched_signal->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"L q","",fit_range_low,fit_range_high);
	h_mc_matched_signal->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"L m","",fit_range_low,fit_range_high);

	f->FixParameter(1,f->GetParameter(1));
	f->FixParameter(2,f->GetParameter(2));
	f->FixParameter(3,f->GetParameter(3));
	f->FixParameter(4,f->GetParameter(4));
	f->FixParameter(5,0);
	f->ReleaseParameter(7);
	f->ReleaseParameter(8);
	f->SetParameter(7,setparam7);
    f->SetParameter(8,setparam1);//mean for swapped candidates
    //if want to fix parameter 8 to parameter 1
    //f->FixParameter(8,f->GetParameter(1));

	h_mc_matched_kpiswapped->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"L q","",fit_range_low,fit_range_high);
	h_mc_matched_kpiswapped->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"L q","",fit_range_low,fit_range_high);
	h_mc_matched_kpiswapped->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"L q","",fit_range_low,fit_range_high);
	h_mc_matched_kpiswapped->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"L m","",fit_range_low,fit_range_high);

	f->FixParameter(5,h_mc_matched_signal->Integral(0,1000)/(h_mc_matched_kpiswapped->Integral(0,1000)+h_mc_matched_signal->Integral(0,1000)));
	f->FixParameter(7,f->GetParameter(7));
	f->FixParameter(8,f->GetParameter(8));
	f->ReleaseParameter(9);
	f->ReleaseParameter(10);
	f->ReleaseParameter(11);
	f->ReleaseParameter(12);

	f->SetLineColor(kRed);

	histo_massfit->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"q","",fit_range_low,fit_range_high);
	histo_massfit->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"q","",fit_range_low,fit_range_high);
	f->ReleaseParameter(1);
	////Release Parameter 6 to float signal width
	f->ReleaseParameter(6);
	f->SetParameter(6,0);
	f->SetParLimits(6,-1.0,1.0);
	histo_massfit->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"L q","",fit_range_low,fit_range_high);
	histo_massfit->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"L q","",fit_range_low,fit_range_high);
	histo_massfit->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"L q","",fit_range_low,fit_range_high);
	histo_massfit->Fit(Form("f_%s_%d",cfgname.Data(),ipt),"L m","",fit_range_low,fit_range_high);

	//begin combine fit
    TF1* fmass_combinemassvnfit = new TF1(Form("fmass_combinemassvnfit_%s_%d",cfgname.Data(),ipt),"[0]*([5]*([4]*TMath::Gaus(x,[1],[2]*(1.0 +[6]))/(sqrt(2*3.14159)*[2]*(1.0 +[6]))+(1-[4])*TMath::Gaus(x,[1],[3]*(1.0 +[6]))/(sqrt(2*3.14159)*[3]*(1.0 +[6])))+(1-[5])*TMath::Gaus(x,[8],[7]*(1.0 +[6]))/(sqrt(2*3.14159)*[7]*(1.0 +[6]))) + [9] + [10]*x + [11]*x*x + [12]*x*x*x", fit_range_low, fit_range_high);

	TF1* fvn_combinemassvnfit = new TF1(Form("fvn_combinemassvnfit_%s_%d",cfgname.Data(),ipt), "( ( [0]*([5]*([4]*TMath::Gaus(x,[1],[2]*(1.0 +[6]))/(sqrt(2*3.14159)*[2]*(1.0 +[6]))+(1-[4])*TMath::Gaus(x,[1],[3]*(1.0 +[6]))/(sqrt(2*3.14159)*[3]*(1.0 +[6])))+(1-[5])*TMath::Gaus(x,[8],[7]*(1.0 +[6]))/(sqrt(2*3.14159)*[7]*(1.0 +[6]))) ) / ( [0]*([5]*([4]*TMath::Gaus(x,[1],[2]*(1.0 +[6]))/(sqrt(2*3.14159)*[2]*(1.0 +[6]))+(1-[4])*TMath::Gaus(x,[1],[3]*(1.0 +[6]))/(sqrt(2*3.14159)*[3]*(1.0 +[6])))+(1-[5])*TMath::Gaus(x,[8],[7]*(1.0 +[6]))/(sqrt(2*3.14159)*[7]*(1.0 +[6]))) + [9] + [10]*x + [11]*x*x + [12]*x*x*x ) ) * [13] + ( 1.0 - ( ( [0]*([5]*([4]*TMath::Gaus(x,[1],[2]*(1.0 +[6]))/(sqrt(2*3.14159)*[2]*(1.0 +[6]))+(1-[4])*TMath::Gaus(x,[1],[3]*(1.0 +[6]))/(sqrt(2*3.14159)*[3]*(1.0 +[6])))+(1-[5])*TMath::Gaus(x,[8],[7]*(1.0 +[6]))/(sqrt(2*3.14159)*[7]*(1.0 +[6]))) ) / ( [0]*([5]*([4]*TMath::Gaus(x,[1],[2]*(1.0 +[6]))/(sqrt(2*3.14159)*[2]*(1.0 +[6]))+(1-[4])*TMath::Gaus(x,[1],[3]*(1.0 +[6]))/(sqrt(2*3.14159)*[3]*(1.0 +[6])))+(1-[5])*TMath::Gaus(x,[8],[7]*(1.0 +[6]))/(sqrt(2*3.14159)*[7]*(1.0 +[6]))) + [9] + [10]*x + [11]*x*x + [12]*x*x*x ) ) ) * ( [14] + [15] * x + [16] * x * x)", fit_range_low, fit_range_high);

	ROOT::Math::WrappedMultiTF1 wfmass_combinemassvnfit(*fmass_combinemassvnfit,1);
	ROOT::Math::WrappedMultiTF1 wfvn_combinemassvnfit(*fvn_combinemassvnfit,1);

	ROOT::Fit::DataOptions opt;
	ROOT::Fit::DataRange range_massfit;
	// set the data range
	range_massfit.SetRange(fit_range_low,fit_range_high);
	ROOT::Fit::BinData datamass(opt,range_massfit);
	ROOT::Fit::FillData(datamass, histo);

	ROOT::Fit::DataRange range_vnfit;
	range_vnfit.SetRange(fit_range_low,fit_range_high);
	ROOT::Fit::BinData datavn(opt,range_vnfit);
	ROOT::Fit::FillData(datavn, h_vnvsmass);

	ROOT::Fit::Chi2Function chi2_B(datamass, wfmass_combinemassvnfit);
	ROOT::Fit::Chi2Function chi2_SB(datavn, wfvn_combinemassvnfit);

	GlobalChi2_poly3bkg_floatwidth_poly2bkg globalChi2(chi2_B, chi2_SB);

	ROOT::Fit::Fitter fitter;

	const int Npar = 17;
	double par0[Npar];
	for( int ipar = 0; ipar < f->GetNpar(); ipar++ )
		par0[ipar] = f->GetParameter(ipar);
	par0[13] = 0.01;
	par0[14] = 0.10;
	par0[15] = 0.05;
	par0[16] = 0.05;

	// create before the parameter settings in order to fix or set range on them
	fitter.Config().SetParamsSettings(Npar,par0);
	// fix parameter
	fitter.Config().ParSettings(2).Fix();
	fitter.Config().ParSettings(3).Fix();
	fitter.Config().ParSettings(4).Fix();
	fitter.Config().ParSettings(5).Fix();
	fitter.Config().ParSettings(7).Fix();
	fitter.Config().ParSettings(8).Fix();
	// set limits on the third and 4-th parameter
	fitter.Config().ParSettings(1).SetLimits(1.7, 2.0);
	//fitter.Config().ParSettings(12).SetStepSize(0.005);
	//fitter.Config().UseWeightCorrection();

	fitter.Config().MinimizerOptions().SetPrintLevel(0);
	fitter.Config().SetMinimizer("Minuit2","Migrad");

	// fit FCN function directly
	// (specify optionally data size and flag to indicate that is a chi2 fit)
	//fitter.FitFCN(Npar,globalChi2,0,datamass.Size()+datavn.Size(),false);
	fitter.FitFCN(Npar,globalChi2,0,datamass.Size()+datavn.Size(),true);
	ROOT::Fit::FitResult result = fitter.Result();
	result.Print(std::cout);

	fmass_combinemassvnfit->SetFitResult( result, iparmassfit_poly3bkg_floatwidth_poly2bkg);
	fmass_combinemassvnfit->SetRange(range_massfit().first, range_massfit().second);
	fmass_combinemassvnfit->SetLineColor(kRed);
	histo->GetListOfFunctions()->Add(fmass_combinemassvnfit);

	fvn_combinemassvnfit->SetFitResult( result, iparvnfit_poly3bkg_floatwidth_poly2bkg);
	fvn_combinemassvnfit->SetRange(range_vnfit().first, range_vnfit().second);
	fvn_combinemassvnfit->SetLineColor(4.0);
	fvn_combinemassvnfit->SetLineStyle(2);
	h_vnvsmass->GetListOfFunctions()->Add(fvn_combinemassvnfit);

	h_vnvspt->SetBinContent( ipt+1, fvn_combinemassvnfit->GetParameter(13));
	h_vnvspt->SetBinError( ipt+1, fvn_combinemassvnfit->GetParError(13));

	//double x[2] = {1.73, 1.864};
	//double error[2];
	//does not work
	//result.GetConfidenceIntervals(2, 1, 1, x, error, 0.683, false);

	//h_vnvspt_bkg->SetBinContent( ipt+1, fvn_combinemassvnfit->GetParameter(13) + fvn_combinemassvnfit->GetParameter(14) * 1.864);
	//h_vnvspt_bkg->SetBinError( ipt+1, error[0]);
	h_vnvspt_bkg->SetBinContent( ipt+1, fvn_combinemassvnfit->GetParameter(14) + fvn_combinemassvnfit->GetParameter(15) * 1.864 + fvn_combinemassvnfit->GetParameter(16) * 1.864 * 1.864);
	h_vnvspt_bkg->SetBinError( ipt+1, 0. );

	TCanvas* cfg_massfit_combinemassvn = new TCanvas(Form("cfg_poly3bkg_floatwidth_poly2bkg_combinemassvnfit_massfit_combinemassvn_%s_%d_%s_%s",cfgname.Data(),ipt,vnorder.Data(),EPorSP.Data()),Form("cfg_poly3bkg_floatwidth_poly2bkg_combinemassvnfit_massfit_combinemassvn_%s_%d_%s_%s",cfgname.Data(),ipt,vnorder.Data(),EPorSP.Data()),600,600);

    gPad->SetRightMargin(0.043);
    gPad->SetLeftMargin(0.18);
//    gPad->SetTopMargin(0.1);
    gPad->SetBottomMargin(0.145);

	histo->SetXTitle("m_{#piK} (GeV/c^{2})");
	histo->SetYTitle("Entries / (5 MeV/c^{2})");
	histo->GetXaxis()->CenterTitle();
	histo->GetYaxis()->CenterTitle();
	//histo->SetAxisRange(0,histo->GetMaximum()*1.4*1.2,"Y");
	histo->GetXaxis()->SetRangeUser(fit_range_low+0.0001,fit_range_high-0.0001);
	histo->GetXaxis()->SetTitleOffset(1.3);
	histo->GetYaxis()->SetTitleOffset(1.8);
	histo->GetXaxis()->SetLabelOffset(0.007);
	histo->GetYaxis()->SetLabelOffset(0.007);
	histo->GetXaxis()->SetTitleSize(0.045);
	histo->GetYaxis()->SetTitleSize(0.045);
	histo->GetXaxis()->SetTitleFont(42);
	histo->GetYaxis()->SetTitleFont(42);
	histo->GetXaxis()->SetLabelFont(42);
	histo->GetYaxis()->SetLabelFont(42);
	histo->GetXaxis()->SetLabelSize(0.04);
	histo->GetYaxis()->SetLabelSize(0.04);
	histo->SetMarkerSize(0.8);
	histo->SetMarkerStyle(20);
	histo->SetStats(0);
	histo->Draw("e");
	
	TF1* background = new TF1(Form("background_%s_%d",cfgname.Data(),ipt),"[0]+[1]*x+[2]*x*x+[3]*x*x*x");
	background->SetParameter(0,fmass_combinemassvnfit->GetParameter(9));
	background->SetParameter(1,fmass_combinemassvnfit->GetParameter(10));
	background->SetParameter(2,fmass_combinemassvnfit->GetParameter(11));
	background->SetParameter(3,fmass_combinemassvnfit->GetParameter(12));
	background->SetLineColor(4);
	background->SetRange(fit_range_low,fit_range_high);
	background->SetLineStyle(2);

    TF1* mass = new TF1(Form("fmass_%s_%d",cfgname.Data(),ipt),"[0]*([5]*([4]*Gaus(x,[1],[2]*(1.0 +[6]))/(sqrt(2*3.14159)*[2]*(1.0 +[6]))+(1-[4])*Gaus(x,[1],[3]*(1.0 +[6]))/(sqrt(2*3.14159)*[3]*(1.0 +[6]))))");
    mass->SetParameters(f->GetParameter(0),f->GetParameter(1),f->GetParameter(2),f->GetParameter(3),f->GetParameter(4),f->GetParameter(5),f->GetParameter(6));
    mass->SetParError(0,f->GetParError(0));
    mass->SetParError(1,f->GetParError(1));
    mass->SetParError(2,f->GetParError(2));
    mass->SetParError(3,f->GetParError(3));
    mass->SetParError(4,f->GetParError(4));
    mass->SetParError(5,f->GetParError(5));
    mass->SetParError(6,f->GetParError(6));
    mass->SetFillColor(kOrange-3);
    mass->SetFillStyle(3002);
    mass->SetLineColor(kOrange-3);
    mass->SetLineWidth(3);
    mass->SetLineStyle(2);

	TF1* massSwap = new TF1(Form("fmassSwap_%s_%d",cfgname.Data(),ipt),"[0]*(1-[2])*Gaus(x,[1],[3]*(1.0 +[4]))/(sqrt(2*3.14159)*[3]*(1.0 +[4]))");
	massSwap->SetParameters(fmass_combinemassvnfit->GetParameter(0),fmass_combinemassvnfit->GetParameter(8),fmass_combinemassvnfit->GetParameter(5),fmass_combinemassvnfit->GetParameter(7),fmass_combinemassvnfit->GetParameter(6));
	massSwap->SetParError(0,fmass_combinemassvnfit->GetParError(0));
	massSwap->SetParError(1,fmass_combinemassvnfit->GetParError(8));
	massSwap->SetParError(2,fmass_combinemassvnfit->GetParError(5));
	massSwap->SetParError(3,fmass_combinemassvnfit->GetParError(7));
	massSwap->SetParError(4,fmass_combinemassvnfit->GetParError(6));
	massSwap->SetFillColor(kGreen+4);
	massSwap->SetFillStyle(3005);
	massSwap->SetLineColor(kGreen+4);
	massSwap->SetLineWidth(3);
	massSwap->SetLineStyle(1);

	background->Draw("same");   
	mass->SetRange(fit_range_low,fit_range_high);	
	mass->Draw("same");
	massSwap->SetRange(fit_range_low,fit_range_high);
	massSwap->Draw("same");

	Double_t yield = mass->Integral(fit_range_low,fit_range_high)/histomassbinsize;
	Double_t yieldErr = mass->Integral(fit_range_low,fit_range_high)/histomassbinsize*mass->GetParError(0)/mass->GetParameter(0);

	TLegend* leg = new TLegend(0.65,0.58,0.82,0.88,NULL,"brNDC");
	leg->SetBorderSize(0);
	leg->SetTextSize(0.04);
	leg->SetTextFont(42);
	leg->SetFillStyle(0);
	leg->AddEntry(histo,"Data","pl");
	leg->AddEntry(fmass_combinemassvnfit,"Fit","l");
	leg->AddEntry(mass,"D^{0}+#bar{D^{#lower[0.2]{0}}} Signal","f");
	leg->AddEntry(massSwap,"K-#pi swapped","f");
	leg->AddEntry(background,"Combinatorial","l");
	leg->Draw("same");

	TLatex Tl;
	Tl.SetNDC();
	Tl.SetTextAlign(12);
	Tl.SetTextSize(0.05);
	Tl.SetTextFont(42);
	Tl.DrawLatex(0.18,0.965, "#font[61]{CMS}");
	if( isPbPb )
		Tl.DrawLatex(0.61,0.965, "#scale[0.8]{PbPb #sqrt{s_{NN}} = 5.02 TeV}");
	else
		Tl.DrawLatex(0.65,0.965, "#scale[0.8]{pp #sqrt{s_{NN}} = 5.02 TeV}");

	TLatex* tex;

	if( isPbPb )
	{
		tex = new TLatex(0.22,0.83,"|y| < 1.0");
		tex->SetNDC();
		tex->SetTextFont(42);
		tex->SetTextSize(0.04);
		tex->SetLineWidth(2);
		tex->Draw();

		tex = new TLatex(0.22,0.78,Form("Cent. %d-%d%%", centlow, centhigh));
		tex->SetNDC();
		tex->SetTextFont(42);
		tex->SetTextSize(0.04);
		tex->SetLineWidth(2);
		tex->Draw();

		tex = new TLatex(0.22,0.73,Form("%.1f < p_{T} < %.1f GeV/c",ptmin,ptmax));
		tex->SetNDC();
		tex->SetTextFont(42);
		tex->SetTextSize(0.04);
		tex->SetLineWidth(2);
		tex->Draw();

		tex = new TLatex(0.22,0.68,Form("N_{sig}: %d #pm %d",int(yield),int(yieldErr)));
		tex->SetNDC();
		tex->SetTextFont(42);
		tex->SetTextSize(0.04);
		tex->SetLineWidth(2);
		tex->Draw();
	}
	else
	{
		tex = new TLatex(0.22,0.83,"|y| < 1.0");
		tex->SetNDC();
		tex->SetTextFont(42);
		tex->SetTextSize(0.04);
		tex->SetLineWidth(2);
		tex->Draw();

		tex = new TLatex(0.22,0.78,Form("%.1f < p_{T} < %.1f GeV/c",ptmin,ptmax));
		tex->SetNDC();
		tex->SetTextFont(42);
		tex->SetTextSize(0.04);
		tex->SetLineWidth(2);
		tex->Draw();

		tex = new TLatex(0.22,0.73,Form("N_{sig}: %d #pm %d",int(yield),int(yieldErr)));
		tex->SetNDC();
		tex->SetTextFont(42);
		tex->SetTextSize(0.04);
		tex->SetLineWidth(2);
		tex->Draw();
	}

	histo_copy_nofitfun->Draw("esame");

	if( get_sig_bkg_ratio )
	{
		for(int ibin = 0; ibin < histo->GetNbinsX(); ibin++)
		{
			double foreground = 0.;
			double signal = 0.;
			double ratio = 0.;
			double ratioError = 999.;

			double massbinleftedge = massmin + histomassbinsize * ibin;
			double massbinrightedge = massmin + histomassbinsize * (ibin+1);

			if( massbinleftedge > (fit_range_low - 0.0002) && massbinrightedge < (fit_range_high + 0.0002) )
			{
				foreground = f->Integral(massbinleftedge, massbinrightedge)/histomassbinsize;
				//foregroundErr = f->IntegralError(massbinleftedge, massbinrightedge)/histomassbinsize;
				//foreground =  histo->Integral(ibin+1, ibin+1);
				signal = mass->Integral(massbinleftedge, massbinrightedge)/histomassbinsize + massSwap->Integral(massbinleftedge, massbinrightedge)/histomassbinsize;
				//signal = mass->Integral(massbinleftedge, massbinrightedge)/histomassbinsize;
				//signal = foreground - background->Integral(massbinleftedge, massbinrightedge)/histomassbinsize;
				//signalErr = signal * yieldErr/yield;
				if( foreground > 0 )
				{
					ratio = signal/foreground;
					ratioError = TMath::Sqrt( foreground * ratio * (1.0 - ratio) ) / foreground;
				}
				else
				{
					ratio = 0.5;
					ratioError = 0.5;
				}
			}
			else
			{
				ratio = 0.0;
				ratioError = 1.0;
			}

			Ratio_signal_foreground->SetBinContent(ibin+1, ratio);
			Ratio_signal_foreground->SetBinError(ibin+1, ratioError);
		}

		TF1* Func_Ratio_signal_foreground = new TF1(Form("Func_Ratio_signal_foreground_%s_%d",cfgname.Data(),ipt),"([0]*([5]*([4]*TMath::Gaus(x,[1],[2]*(1.0 +[6]))/(sqrt(2*3.14159)*[2]*(1.0 +[6]))+(1-[4])*TMath::Gaus(x,[1],[3]*(1.0 +[6]))/(sqrt(2*3.14159)*[3]*(1.0 +[6])))+(1-[5])*TMath::Gaus(x,[8],[7]*(1.0 +[6]))/(sqrt(2*3.14159)*[7]*(1.0 +[6]))))/([0]*([5]*([4]*TMath::Gaus(x,[1],[2]*(1.0 +[6]))/(sqrt(2*3.14159)*[2]*(1.0 +[6]))+(1-[4])*TMath::Gaus(x,[1],[3]*(1.0 +[6]))/(sqrt(2*3.14159)*[3]*(1.0 +[6])))+(1-[5])*TMath::Gaus(x,[8],[7]*(1.0 +[6]))/(sqrt(2*3.14159)*[7]*(1.0 +[6]))) + [9] + [10]*x + [11]*x*x + [12]*x*x*x)", generalfitrange_masslow, generalfitrange_masshigh);
        for( int ipar = 0; ipar < 13; ipar++ )
        {
            Func_Ratio_signal_foreground->SetParameter( ipar, f->GetParameter(ipar));
            Func_Ratio_signal_foreground->SetParError(ipar, f->GetParError(ipar));
        }
		Func_Ratio_signal_foreground->SetLineColor(2.0);
		Ratio_signal_foreground->GetListOfFunctions()->Add(Func_Ratio_signal_foreground);
	}

	if(isPbPb)
	{
		cfg_massfit_combinemassvn->SaveAs(Form("Plots_vn/combinemassvnfit/DMass_combinemassvnfit_isPbPb%d_%s_cent%dto%d_%d_%s_%s_poly3bkg_floatwidth_poly2bkg_combinemassvnfit.pdf", isPbPb, cfgname.Data(), centlow, centhigh, ipt, vnorder.Data(),EPorSP.Data()));
		cfg_massfit_combinemassvn->SaveAs(Form("Plots_vn/combinemassvnfit/DMass_combinemassvnfit_isPbPb%d_%s_cent%dto%d_%d_%s_%s_poly3bkg_floatwidth_poly2bkg_combinemassvnfit.png", isPbPb, cfgname.Data(), centlow, centhigh, ipt, vnorder.Data(),EPorSP.Data()));
	}

	TCanvas* cfg_vnfit_combinemassvn = new TCanvas(Form("cfg_poly3bkg_floatwidth_poly2bkg_combinemassvnfit_vnfit_combinemassvn_%s_%d_%s_%s",cfgname.Data(),ipt,vnorder.Data(),EPorSP.Data()),Form("cfg_poly3bkg_floatwidth_poly2bkg_combinemassvnfit_vnfit_combinemassvn_%s_%d_%s_%s",cfgname.Data(),ipt,vnorder.Data(),EPorSP.Data()),600,600);

	h_vnvsmass->GetYaxis()->SetRangeUser(-0.2, 0.6);
	if( vnorder == "v2") h_vnvsmass->GetYaxis()->SetTitle("v_{2}");
	if( vnorder == "v3") h_vnvsmass->GetYaxis()->SetTitle("v_{3}");
	h_vnvsmass->GetXaxis()->SetTitle("m_{#piK} (GeV/c^{2})");
	h_vnvsmass->GetXaxis()->SetTitleSize(0.05);
	h_vnvsmass->GetYaxis()->SetTitleSize(0.05);

	h_vnvsmass->SetMarkerColor(4.0);
	h_vnvsmass->SetLineColor(4.0);
	h_vnvsmass->SetMarkerStyle(21);
	h_vnvsmass->SetMarkerSize(1.3);
	h_vnvsmass->Draw();

    TLatex Tl2; 
    Tl2.SetNDC();
    Tl2.SetTextAlign(12);
    Tl2.SetTextSize(0.05);
    Tl2.SetTextFont(42);
    Tl2.DrawLatex(0.125,0.965, "#font[61]{CMS}");
    Tl2.DrawLatex(0.57,0.965, "#scale[0.8]{PbPb #sqrt{s_{NN}} = 5.02 TeV}");

    tex = new TLatex(0.18,0.83,"|y| < 1.0");
    tex->SetNDC();
    tex->SetTextFont(42);
    tex->SetTextSize(0.04);
    tex->SetLineWidth(2);
    tex->Draw();

    tex = new TLatex(0.18,0.78,Form("Cent. %d-%d%%", centlow, centhigh));
    tex->SetNDC();
    tex->SetTextFont(42);
    tex->SetTextSize(0.04);
    tex->SetLineWidth(2);
    tex->Draw();

    tex = new TLatex(0.18,0.73,Form("%.1f < p_{T} < %.1f GeV/c",ptmin,ptmax));
    tex->SetNDC();
    tex->SetTextFont(42);
    tex->SetTextSize(0.04);
    tex->SetLineWidth(2);
    tex->Draw();

    if( vnorder == "v2" ) 
        tex = new TLatex(0.55,0.83,Form("v_{2}^{sig} = %.3f #pm %.3f",fvn_combinemassvnfit->GetParameter(13), fvn_combinemassvnfit->GetParError(13)));
    else if( vnorder == "v3" )
        tex = new TLatex(0.55,0.83,Form("v_{3}^{sig} = %.3f #pm %.3f",fvn_combinemassvnfit->GetParameter(13), fvn_combinemassvnfit->GetParError(13)));

    tex->SetNDC();
    tex->SetTextFont(42);
    tex->SetTextSize(0.04);
    tex->SetLineWidth(2);
    tex->Draw();
	
	if(isPbPb)
	{
		cfg_vnfit_combinemassvn->SaveAs(Form("Plots_vn/combinemassvnfit/cfg_vnfit_combinemassvn_%s_cent%dto%d_%d_%s_%s_poly3bkg_floatwidth_poly2bkg_combinemassvnfit.pdf",cfgname.Data(),centlow,centhigh,ipt,vnorder.Data(),EPorSP.Data()));
		cfg_vnfit_combinemassvn->SaveAs(Form("Plots_vn/combinemassvnfit/cfg_vnfit_combinemassvn_%s_cent%dto%d_%d_%s_%s_poly3bkg_floatwidth_poly2bkg_combinemassvnfit.png",cfgname.Data(),centlow,centhigh,ipt,vnorder.Data(),EPorSP.Data()));
	}

	return mass;
}
Exemplo n.º 8
0
Int_t line3dfit_copy()
{
   gStyle->SetOptStat(0);
   gStyle->SetOptFit();


   //double e = 0.1;
   // Int_t nd = 5;


//    double xmin = 0; double ymin = 0;
//    double xmax = 10; double ymax = 10;

   TGraph2D * gr = new TGraph2D();

   // Fill the 2D graph
   // double p0[4] = {10,20,1,2};

   // generate graph with the 3d points
   // for (Int_t N=0; N<nd; N++) {
   //    double x,y,z = 0;
   //    // Generate a random number
   //    double t = gRandom->Uniform(0,10);
   //    line(t,p0,x,y,z);
   //    double err = 1;
   //  // do a gaussian smearing around the points in all coordinates
   //    x += gRandom->Gaus(0,err);
   //    y += gRandom->Gaus(0,err);
   //    z += gRandom->Gaus(0,err);
   //    gr->SetPoint(N,x,y,z);
   //    //dt->SetPointError(N,0,0,err);
   // }


   // gr->SetPoint(0, 3, 3, 5);
   // gr->SetPoint(1, 3, 3, 3);
   // gr->SetPoint(2, 4, 3.5, 5);
   // gr->SetPoint(3, 6.2, 7.3, 5.8);
   // gr->SetPoint(4, 9, 8, 7);
   // gr->SetPoint(5, 5, 5, 5);

   gr->SetPoint(0, 19, -4.25, 1.92);
   gr->SetPoint(1, 19, -4.30, 1.92);
   gr->SetPoint(2, 19, -4.35, 1.92);
   gr->SetPoint(3, 19, -4.40, 1.92);
   gr->SetPoint(4, 19, -4.45, 1.92);
   gr->SetPoint(5, 19, -4.50, 1.92);
   gr->SetPoint(6, 19, -4.55, 1.92);
   gr->SetPoint(7, 19, -4.60, 1.92);
   gr->SetPoint(8, 18.75, -4.30, 1.92);
   gr->SetPoint(9, 18.75, -4.35, 1.92);
   gr->SetPoint(10, 18.75, -4.40, 1.92);
   gr->SetPoint(11, 18.75, -4.45, 1.92);
   gr->SetPoint(12, 18.75, -4.50, 1.92);
   gr->SetPoint(13, 18.75, -4.55, 1.92);
   gr->SetPoint(14, 19, -4.20, 2.08);
   gr->SetPoint(15, 19, -4.65, 2.08);
   gr->SetPoint(16, 19, -4.70, 2.08);
   gr->SetPoint(17, 18.75, -4.25, 2.08);
   gr->SetPoint(18, 18.75, -4.60, 2.08);
   // gr->SetPoint(19, 19.001, -4.151, 2.241);
   // gr->SetPoint(20, 18.751, -4.201, 2.241);
   gr->SetPoint(19, 19., -4.15, 2.24);
   gr->SetPoint(20, 18.5723, -4.20, 2.24);

   // gr->SetMarkerStyle(8);
   // gr->Draw("p");
   
   // gr->Draw("p0");
   // TFitResultPtr fit = gr->Fit("pol1", "WS");
   // // fit->Print("V");
   // Double_t p0 = fit->Value(0);
   // Double_t p1 = fit->Value(1);

   // // draw the line
   // TPolyLine3D *l = new TPolyLine3D(2);
   // double dz = 8;
   // l->SetPoint(0,0,0,p0);
   // l->SetPoint(1,dz,0,dz * p1);

   // l->SetLineColor(kRed);
   // l->Draw("same");

   // fit the graph now, and make the functor objet

   ROOT::Fit::Fitter  fitter;

   SumDistance2 sdist(gr);
#ifdef __CINT__
   ROOT::Math::Functor fcn(&sdist,4,"SumDistance2");
#else
   ROOT::Math::Functor fcn(sdist,4);
#endif
   // set the function and the initial parameter values
   double pStart[4] = {1,1,1,1};
   fitter.SetFCN(fcn,pStart);
   // set step sizes different than default ones (0.3 times parameter values)
   for (int i = 0; i < 4; ++i) fitter.Config().ParSettings(i).SetStepSize(0.01);

   bool ok = fitter.FitFCN();
   if (!ok) {
      Error("line3Dfit","Line3D Fit failed");
      return 1;
   }

   const ROOT::Fit::FitResult & result = fitter.Result();

   std::cout << "Total final distance square " << result.MinFcnValue() << std::endl;
   // result.Print(std::cout); // @@@ suppress output


   // get fit parameters
   const double * parFit = result.GetParams();

   // draw the fitted line
   int n = 1000;
   double t0 = 0;
   double dt = 10;
   TPolyLine3D *l = new TPolyLine3D(n);
   for (int i = 0; i <n;++i) {
      double t = t0+ dt*i/n;
      double x,y,z;
      line(t,parFit,x,y,z);
      l->SetPoint(i,x,y,z);
   }
   l->SetLineColor(kRed);
   l->Draw("same");

   // Access to fit params and minfcnvalue
   cout << parFit[1] << "\n";
   cout << result.MinFcnValue() << "\n";


   // // draw original line
   // TPolyLine3D *l0 = new TPolyLine3D(n);
   // for (int i = 0; i <n;++i) {
   //    double t = t0+ dt*i/n;
   //    double x,y,z;
   //    line(t,p0,x,y,z);
   //    l0->SetPoint(i,x,y,z);
   // }
   // l0->SetLineColor(kBlue);
   // l0->Draw("same");
   

   return 0;
}