void plot_signif2(void)
{
// plot significance results obtained using gen_phithe.C
// data at constant phi_norm

#include <TMath.h>
#include <TRandom.h>

gROOT->Reset();
//TTree *Bfield = (TTree *) gROOT->FindObject("Bfield");
gStyle->SetPalette(1,0);
gStyle->SetOptStat(kFALSE);
gStyle->SetPadRightMargin(0.15);
gStyle->SetPadLeftMargin(0.15);
gStyle->SetPadBottomMargin(0.15);
//

   char string[256];
   char filename[80];
   Int_t j,jj;

   // input data 
 
   #define npts 7;

   // add dummy point on end to be able to plot beyond last data

   Float_t phi_norm1[npts]={0,1,1,1,1,1,10};
   Float_t theta_norm1[npts]={0,1.5,1.25,1.0,0.75,0.5,10};
   Float_t nevents1[npts]={0,6090,6045,6000,5954,5909,100000};
   Float_t gensb1[npts]={-1,0.562,0.469,0.375,0.281,0.187,10};
   Float_t logsig1[npts]={-1,12.2,10.1,8.2,6.5,4.7,100};
   Float_t gensig1[npts]={-1,12.07,10.06,8.05,6.03,4.02,100};
   Float_t fitsig1[npts]={-1,12.84,10.51,8.48,6.69,4.73,100};


   // write data to file

   FILE *out;
   sprintf(filename,"plot_signif2.dat");
   out = fopen(filename,"w+");
   for (j=1;j<npts-1;j++) {
      fprintf (out,"%d & %.2f & %.2f & %.3f & %.2f & %.2f & %.2f\n",nevents1[j],phi_norm1[j],theta_norm1[j],gensb1[j],logsig1[j],gensig1[j],fitsig1[j]);
      }
   fclose(out);


   // rescale parameters
   Float_t phi_norm[npts];
   Float_t theta_norm[npts];
   Float_t scale=10;
   for (j=0;j<npts;j++) {
      phi_norm[j] = phi_norm1[j]*scale;
      theta_norm[j] = theta_norm1[j]*scale;
      }
     
   //
   TCanvas *c1 = new TCanvas("c1","c1 plot_signif2",200,10,700,500);
   Float_t xmin = 0.1;
   Float_t xmax = 0.7;
   Float_t ymin = 0;
   Float_t ymax = 20;
   c1->SetGridx();
   c1->SetGridy();
   c1->SetBorderMode(0);
   c1->SetFillColor(0);

   TGraph *glogsig0 = new TGraph (npts,gensb1,logsig1);
   TGraph *gphi_norm1 = new TGraph (npts,gensb1,phi_norm);
   TGraph *gtheta_norm1 = new TGraph (npts,gensb1,theta_norm);
   TGraph *ggensig1 = new TGraph (npts,gensb1,gensig1);
   glogsig0->GetXaxis()->SetRangeUser(xmin,xmax);
   glogsig0->GetYaxis()->SetRangeUser(ymin,ymax);
   glogsig0->GetXaxis()->SetTitleSize(0.05);
   glogsig0->GetYaxis()->SetTitleSize(0.05);
   glogsig0->GetXaxis()->SetTitle("Generated Signal/Background");
   glogsig0->GetYaxis()->SetTitle("");
   glogsig0->SetTitle("");

   glogsig0->SetMarkerColor(2);
   glogsig0->SetMarkerStyle(20);
   ggensig1->SetMarkerColor(2);
   ggensig1->SetMarkerStyle(21);
   gphi_norm1->SetMarkerColor(1);
   gphi_norm1->SetMarkerStyle(25);
   gtheta_norm1->SetMarkerColor(1);
   gtheta_norm1->SetMarkerStyle(24);

   TLegend *leg = new TLegend(0.45,0.70,0.85,0.9);
   leg->AddEntry(glogsig0,"Log Likelihood","p");
   leg->AddEntry(ggensig1,"Gen S/sqrt(B)","p");
   leg->AddEntry(gphi_norm1,"#phi parameter #times 10","p");
   leg->AddEntry(gtheta_norm1,"#theta parameter #times 10","p");

   glogsig0->Draw("AP");
   leg->Draw();
   gphi_norm1->Draw("sameP");
   gtheta_norm1->Draw("sameP");
   ggensig1->Draw("sameP");

   sprintf (string,"Fit function = %.1f + %.2f B\n");
   // printf("string=%s",string);
   t1 = new TLatex(0.2,0.85,string);
   t1->SetNDC();
   t1->SetTextSize(0.04);
   // t1->Draw();

   //
   TCanvas *c2 = new TCanvas("c2","c2 plot_signif2",200,10,700,500);

   TGraph *glogsig1 = new TGraph (npts,gensb1,logsig1);

   for (j=0;j<npts;j++) {
      printf("j=%d, gensb1=%f, logsig1=%f\n",j,gensb1[j],logsig1[j]);
      }

   Float_t xmin = 0;
   Float_t xmax = 1;
   Float_t ymin = 0;
   Float_t ymax = 20;
   glogsig1->GetXaxis()->SetRangeUser(xmin,xmax);
   glogsig1->GetYaxis()->SetRangeUser(ymin,ymax);
   glogsig1->GetXaxis()->SetTitleSize(0.05);
   glogsig1->GetYaxis()->SetTitleSize(0.05);
   glogsig1->GetXaxis()->SetTitle("Generated Signal/Background");
   glogsig1->GetYaxis()->SetTitle("Estimated Significance");
   glogsig1->SetTitle("");
   glogsig1->SetMarkerColor(2);
   glogsig1->SetMarkerStyle(20);
   c2->SetGridx();
   c2->SetGridy();
   c2->SetBorderMode(0);
   c2->SetFillColor(0);
   c2->Divide(2,2);

   c2->cd(1);
   c2_1->SetGridx();
   c2_1->SetGridy();
   c2_1->SetBorderMode(0);
   c2_1->SetFillColor(0);
   TLegend *leg1 = new TLegend(0.45,0.75,0.85,0.9);
   leg1->AddEntry(glogsig1,"Log Likelihood","p");
   glogsig1->Draw("AP");
   leg1->Draw();

   TGraph *glogsig2 = new TGraph (npts,phi_norm1,logsig1);
   Float_t xmin = 0;
   Float_t xmax = 2;
   Float_t ymin = 0;
   Float_t ymax = 20;
   glogsig2->GetXaxis()->SetRangeUser(xmin,xmax);
   glogsig2->GetYaxis()->SetRangeUser(ymin,ymax);
   glogsig2->GetXaxis()->SetTitleSize(0.05);
   glogsig2->GetYaxis()->SetTitleSize(0.05);
   glogsig2->GetXaxis()->SetTitle("#phi parameter");
   glogsig2->GetYaxis()->SetTitle("Estimated Significance");
   glogsig2->SetTitle("");
   glogsig2->SetMarkerColor(2);
   glogsig2->SetMarkerStyle(20);

   c2->cd(2);
   c2_2->SetGridx();
   c2_2->SetGridy();
   c2_2->SetBorderMode(0);
   c2_2->SetFillColor(0);
   TLegend *leg2 = new TLegend(0.45,0.75,0.85,0.9);
   leg2->AddEntry(glogsig2,"Log Likelihood","p");
   glogsig2->Draw("AP");
   leg2->Draw();

   TGraph *glogsig3 = new TGraph (npts,theta_norm1,logsig1);
   Float_t xmin = 0;
   Float_t xmax = 2;
   Float_t ymin = 0;
   Float_t ymax = 20;
   glogsig3->GetXaxis()->SetRangeUser(xmin,xmax);
   glogsig3->GetYaxis()->SetRangeUser(ymin,ymax);
   glogsig3->GetXaxis()->SetTitleSize(0.05);
   glogsig3->GetYaxis()->SetTitleSize(0.05);
   glogsig3->GetXaxis()->SetTitle("#theta parameter");
   glogsig3->GetYaxis()->SetTitle("Estimated Significance");
   glogsig3->SetTitle("");
   glogsig3->SetMarkerColor(2);
   glogsig3->SetMarkerStyle(20);

   c2->cd(3);
   c2_3->SetGridx();
   c2_3->SetGridy();
   c2_3->SetBorderMode(0);
   c2_3->SetFillColor(0);
   TLegend *leg3 = new TLegend(0.45,0.75,0.85,0.9);
   leg3->AddEntry(glogsig3,"Log Likelihood","p");
   glogsig3->Draw("AP");
   leg3->Draw();

   TGraph *glogsig4 = new TGraph (npts,fitsig1,logsig1);
   Float_t xmin = 4;
   Float_t xmax = 14;
   Float_t ymin = 0;
   Float_t ymax = 20;
   glogsig4->GetXaxis()->SetRangeUser(xmin,xmax);
   glogsig4->GetYaxis()->SetRangeUser(ymin,ymax);
   glogsig4->GetXaxis()->SetTitleSize(0.05);
   glogsig4->GetYaxis()->SetTitleSize(0.05);
   glogsig4->GetXaxis()->SetTitle("Fit  S/sqrt(B)");
   glogsig4->GetYaxis()->SetTitle("Estimated Significance");
   glogsig4->SetTitle("");
   glogsig4->SetMarkerColor(2);
   glogsig4->SetMarkerStyle(20);

   c2->cd(4);
   c2_4->SetGridx();
   c2_4->SetGridy();
   c2_4->SetBorderMode(0);
   c2_4->SetFillColor(0);
   TLegend *leg4 = new TLegend(0.45,0.75,0.85,0.9);
   leg4->AddEntry(glogsig4,"Log Likelihood","p");
   glogsig4->Draw("AP");
   leg4->Draw();

   //
   c1->SaveAs("plot_c1_signif2.eps");
   c1->SaveAs("plot_c1_signif2.gif");
   c2->SaveAs("plot_c2_signif2.eps");
   c2->SaveAs("plot_c2_signif2.gif");
}