void VFH::loadFeatureModels (const boost::filesystem::path &base_dir, const std::string &extension,
std::vector<vfh_model> &models)
{
if (!boost::filesystem::exists (base_dir) && !boost::filesystem::is_directory (base_dir))
return;
for (boost::filesystem::directory_iterator it (base_dir); it != boost::filesystem::directory_iterator (); ++it)
{
if (boost::filesystem::is_directory (it->status ()))
{
std::stringstream ss;
ss << it->path ();
pcl::console::print_highlight ("Loading %s (%lu models loaded so far).\n", ss.str ().c_str (), (unsigned long)models.size ());
loadFeatureModels (it->path (), extension, models);
}
if(boost::filesystem::is_regular_file (it->status ()))
std::cout<<boost::filesystem::extension (it->path ())<<" "<<extension<<std::endl;
if(boost::filesystem::extension (it->path ()) == extension)
std::cout<<"YES"<<std::endl;
if (boost::filesystem::is_regular_file (it->status ()) && boost::filesystem::extension (it->path ()) == extension)
{
std::cout<<"in"<<std::endl;
vfh_model m;
if (loadHist (base_dir / it->path ().filename (), m))
models.push_back (m);
}
}
}
void qcd_study1( bool fillHists=false, bool savePlots=false, bool interactive=true, const char* datfile = "null" ) {
TLine* line = new TLine() ;
gStyle->SetPalette(1) ;
gStyle->SetPadBottomMargin(0.20) ;
gDirectory->Delete("h*") ;
int nBinsBjets = 3 ;
//-- met3-ht3-v5
const int nBinsMET = 3 ;
const int nBinsHT = 3 ;
// const int version = 5;
float Mbins[nBinsMET+1] = {125, 200.,350.,99999.};
float Hbins[nBinsHT+1] = {400, 600.,1000.,99999.};
// ////-- met4-ht3-v3
// const int nBinsMET = 4 ;
// const int nBinsHT = 3 ;
// const int version = 3;
// float Mbins[nBinsMET+1] = {125, 150.,250.,350.,99999.};
// float Hbins[nBinsHT+1] = {400, 600.,1000.,99999.};
////-- met4-ht4-v15
//const int nBinsMET = 4 ;
//const int nBinsHT = 4 ;
// const int version = 15;
//float Mbins[nBinsMET+1] = {125, 150.,250.,350.,99999.};
//float Hbins[nBinsHT+1] = {400, 500.,800.,1000.,99999.};
TH2F* hdummy = new TH2F("hdummy","",2, Mbins[0], 1500., 2, Hbins[0], 1500. ) ;
const int nQcdSamples(9) ;
char inputfile[9][1000] = {
"files15fb_8TeV/QCD-120to170.root"
,"files15fb_8TeV/QCD-170to300.root"
,"files15fb_8TeV/QCD-300to470.root"
,"files15fb_8TeV/QCD-470to600.root"
,"files15fb_8TeV/QCD-600to800.root"
,"files15fb_8TeV/QCD-800to1000.root"
,"files15fb_8TeV/QCD-1000to1400.root"
,"files15fb_8TeV/QCD-1400to1800.root"
,"files15fb_8TeV/QCD-1800.root"
} ;
char samplename[9][100] = {
"qcd_0120_to_0170"
,"qcd_0170_to_0300"
,"qcd_0300_to_0470"
,"qcd_0470_to_0600"
,"qcd_0600_to_0800"
,"qcd_0800_to_1000"
,"qcd_1000_to_1400"
,"qcd_1400_to_1800"
,"qcd_1800_to_9999"
} ;
// int samplecolor[9] = {
// kOrange+8,
// kRed,
// KMagenta+2,
// KBlue+1,
// KAzure+2,
// KGreen+2,
// kPink-2,
// kViolet+2,
// kOrange+2
// } ;
int samplecolor[9] = {
800+8,
632,
616+2,
600+1,
860+2,
416+2,
900-2,
880+2,
800+2
} ;
TH2F* h0lep[nQcdSamples][nBinsBjets] ;
TH2F* hldp [nQcdSamples][nBinsBjets] ;
TCanvas* cqcd = (TCanvas*) gDirectory->FindObject("cqcd") ;
if ( cqcd == 0x0 ) {
cqcd = new TCanvas("cqcd", "qcd study", 700, 900 ) ;
}
char hname[1000] ;
char htitle[1000] ;
if ( fillHists ) {
TChain* qcdch[nQcdSamples] ;
printf("\n\n") ;
for ( int si=0; si<nQcdSamples; si++ ) {
qcdch[si] = new TChain("tree") ;
printf(" %2d : connecting to %s\n", si, inputfile[si] ) ;
qcdch[si] -> Add( inputfile[si] ) ;
for ( int bbi=0; bbi<nBinsBjets; bbi++ ) {
sprintf( hname, "h_0lep_%db_%s", bbi+1, samplename[si] ) ;
sprintf( htitle, "QCD 0lep yield, nb=%d, %s", bbi+1, samplename[si] ) ;
printf(" booking hist %s : %s\n", hname, htitle ) ;
h0lep[si][bbi] = new TH2F( hname, htitle, nBinsMET, Mbins, nBinsHT, Hbins ) ;
h0lep[si][bbi] -> Sumw2() ;
sprintf( hname, "h_ldp_%db_%s", bbi+1, samplename[si] ) ;
sprintf( htitle, "QCD LDP yield, nb=%d, %s", bbi+1, samplename[si] ) ;
printf(" booking hist %s : %s\n", hname, htitle ) ;
hldp [si][bbi] = new TH2F( hname, htitle, nBinsMET, Mbins, nBinsHT, Hbins ) ;
hldp [si][bbi] -> Sumw2() ;
} // bbi.
} // si.
printf("\n\n") ;
char basecuts[10000] ;
sprintf( basecuts, "pt_1st_leadJet>50&&pt_2nd_leadJet>50&&pt_3rd_leadJet>50&&HT>400&&MET>125&&nMu==0&&nEl==0&&nB>=1&&nJets>=3" ) ;
char bcut[3][100] = { "nB==1", "nB==2", "nB>=3" } ;
for ( int si=0; si<nQcdSamples; si++ ) {
printf(" %2d : %s : 0lep\n", si, samplename[si] ) ; cout << flush ;
for ( int bbi=0; bbi<nBinsBjets; bbi++ ) {
char arg1[1000] ;
char cuts0lep[10000] ;
sprintf( cuts0lep, "(%s)&&(minDelPhiN>4&&%s)", basecuts, bcut[bbi] ) ;
printf(" %db, 0lep cuts : %s\n", bbi+1, cuts0lep ) ;
sprintf( arg1, "HT:MET>>h_0lep_%db_%s", bbi+1, samplename[si] ) ;
qcdch[si] -> Draw( arg1, cuts0lep ) ;
hdummy->Draw() ;
h0lep[si][bbi]->Draw("samecolz") ;
cqcd->Update() ; cqcd->Draw() ;
char cutsldp[10000] ;
sprintf( cutsldp, "(%s)&&(minDelPhiN<=4&&%s)", basecuts, bcut[bbi] ) ;
printf(" %db, ldp cuts : %s\n", bbi+1, cutsldp ) ;
sprintf( arg1, "HT:MET>>h_ldp_%db_%s", bbi+1, samplename[si] ) ;
qcdch[si] -> Draw( arg1, cutsldp, "colz" ) ;
hdummy->Draw() ;
hldp[si][bbi]->Draw("samecolz") ;
cqcd->Update() ; cqcd->Draw() ;
} // bbi.
} // si.
saveHist( "rootfiles/qcd-study1.root", "h*" ) ;
}
//--------
gStyle->SetOptStat(0) ;
gDirectory->Delete("h*") ;
loadHist( "rootfiles/qcd-study1.root" ) ;
for ( int si=0; si<nQcdSamples; si++ ) {
for ( int bbi=0; bbi<nBinsBjets; bbi++ ) {
sprintf( hname, "h_0lep_%db_%s", bbi+1, samplename[si] ) ;
printf(" loading %s\n", hname ) ;
h0lep[si][bbi] = (TH2F*) gDirectory->FindObject( hname ) ;
if ( h0lep[si][bbi] == 0x0 ) { printf("\n\n *** %s missing.\n\n", hname ) ; return ; }
sprintf( hname, "h_ldp_%db_%s", bbi+1, samplename[si] ) ;
printf(" loading %s\n", hname ) ;
hldp [si][bbi] = (TH2F*) gDirectory->FindObject( hname ) ;
if ( hldp [si][bbi] == 0x0 ) { printf("\n\n *** %s missing.\n\n", hname ) ; return ; }
} // bbi.
} // si.
//--- Flatten 2D histos and compute 0lep/LDP ratios for each sample.
int nbins = nBinsMET*(nBinsHT+1) + 1 ;
TH1F* hflat_0lep[nQcdSamples][nBinsBjets] ;
TH1F* hflat_ldp [nQcdSamples][nBinsBjets] ;
TH1F* hflat_0lepldp_ratio[nQcdSamples][nBinsBjets] ;
sprintf( hname, "hflat_0lep_all" ) ;
sprintf( htitle, "All QCD 0lep events" ) ;
TH1F* hflat_0lep_all = bookHist( hname, htitle, nBinsMET, nBinsHT, 5 ) ;
sprintf( hname, "hflat_ldp_all" ) ;
sprintf( htitle, "All QCD ldp events" ) ;
TH1F* hflat_ldp_all = bookHist( hname, htitle, nBinsMET, nBinsHT, 5 ) ;
for ( int bbi=0; bbi<nBinsBjets; bbi++ ) {
for ( int si=0; si<nQcdSamples; si++ ) {
sprintf( hname, "hflat_0lep_%db_%s", bbi+1, samplename[si] ) ;
sprintf( htitle, "QCD 0lep events, nb=%d, %s", bbi+1, samplename[si] ) ;
hflat_0lep[si][bbi] = bookHist( hname, htitle, nBinsMET, nBinsHT, si ) ;
hflat_0lep[si][bbi]->SetFillColor(11) ;
hldp[si][bbi]->Print("all") ;
sprintf( hname, "hflat_ldp_%db_%s", bbi+1, samplename[si] ) ;
sprintf( htitle, "QCD LDP events, nb=%d, %s", bbi+1, samplename[si] ) ;
hflat_ldp[si][bbi] = bookHist( hname, htitle, nBinsMET, nBinsHT, si ) ;
hflat_ldp[si][bbi]->SetFillColor(11) ;
sprintf( hname, "hflat_0lepldp_ratio_%db_%s", bbi+1, samplename[si] ) ;
sprintf( htitle, "QCD 0lep/LDP ratio, nb=%d, %s", bbi+1, samplename[si] ) ;
hflat_0lepldp_ratio[si][bbi] = bookHist( hname, htitle, nBinsMET, nBinsHT, si ) ;
for ( int mbi=0; mbi<nBinsMET; mbi++ ) {
for ( int hbi=0; hbi<nBinsHT; hbi++ ) {
int histbin = 1 + (nBinsHT+1)*mbi + hbi + 1 ;
float n0lep = h0lep[si][bbi] -> GetBinContent( mbi+1, hbi+1 ) ;
float n0lep_err = h0lep[si][bbi] -> GetBinError( mbi+1, hbi+1 ) ;
float nldp = hldp [si][bbi] -> GetBinContent( mbi+1, hbi+1 ) ;
float nldp_err = hldp [si][bbi] -> GetBinError( mbi+1, hbi+1 ) ;
hflat_0lep[si][bbi] -> SetBinContent( histbin, n0lep ) ;
hflat_0lep[si][bbi] -> SetBinError( histbin, n0lep_err ) ;
hflat_ldp[si][bbi] -> SetBinContent( histbin, nldp ) ;
hflat_ldp[si][bbi] -> SetBinError( histbin, nldp_err ) ;
double ratio(0.) ;
if ( nldp > 0 ) { ratio = n0lep / nldp ; }
double ratio_err(0.) ;
if ( n0lep_err > 0. && nldp_err > 0. ) {
ratio_err = ratio * sqrt( pow(n0lep_err/n0lep,2) + pow(nldp_err/nldp,2) ) ;
}
hflat_0lepldp_ratio[si][bbi] -> SetBinContent( histbin, ratio ) ;
hflat_0lepldp_ratio[si][bbi] -> SetBinError( histbin, ratio_err ) ;
} // hbi.
} // mbi.
hflat_0lep_all -> Add( hflat_0lep[si][bbi] ) ;
hflat_ldp_all -> Add( hflat_ldp [si][bbi] ) ;
cqcd->Clear() ;
cqcd->Divide(1,3) ;
cqcd->cd(1) ;
hflat_0lep[si][bbi] -> DrawCopy("histe") ;
hflat_0lep[si][bbi] -> DrawCopy("samee") ;
cqcd->cd(2) ;
hflat_ldp[si][bbi] -> DrawCopy("histe") ;
hflat_ldp[si][bbi] -> DrawCopy("samee") ;
cqcd->cd(3) ;
hflat_0lepldp_ratio[si][bbi]->SetMinimum(-0.1) ;
hflat_0lepldp_ratio[si][bbi]->SetMaximum(0.6) ;
hflat_0lepldp_ratio[si][bbi]->SetMarkerStyle(20) ;
hflat_0lepldp_ratio[si][bbi]->SetLineWidth(2) ;
hflat_0lepldp_ratio[si][bbi]->DrawCopy() ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
line->DrawLine(0.5,0,nbins+0.5,0) ;
cqcd->Update() ; cqcd->Draw() ;
} // si.
} // bbi.
TH1F* hflat_0lep_all_sqrtNerrs = (TH1F*) hflat_0lep_all->Clone("hflat_0lep_all_sqrtNerrs") ;
TH1F* hflat_ldp_all_sqrtNerrs = (TH1F*) hflat_ldp_all ->Clone("hflat_ldp_all_sqrtNerrs") ;
for ( int bi=1; bi<=nbins; bi++ ) {
double val ;
val = hflat_0lep_all_sqrtNerrs->GetBinContent( bi ) ;
hflat_0lep_all_sqrtNerrs -> SetBinError( bi, sqrt(val) ) ;
val = hflat_ldp_all_sqrtNerrs->GetBinContent( bi ) ;
hflat_ldp_all_sqrtNerrs -> SetBinError( bi, sqrt(val) ) ;
}
//--- Compute sample average of 0lep/LDP ratio
TH1F* hflat_0lepldp_ratio_ave[nBinsBjets] ;
for ( int bbi=0; bbi<nBinsBjets; bbi++ ) {
sprintf( hname, "hflat_0lepldp_ratio_ave_%db", bbi+1 ) ;
sprintf( htitle, "QCD 0lep/LDP average ratio, nb=%d", bbi+1 ) ;
hflat_0lepldp_ratio_ave[bbi] = bookHist( hname, htitle, nBinsMET, nBinsHT, 5 ) ;
hflat_0lepldp_ratio_ave[bbi] -> SetMarkerStyle(24) ;
hflat_0lepldp_ratio_ave[bbi] -> SetMarkerSize(2.0) ;
hflat_0lepldp_ratio_ave[bbi] -> SetLineWidth(3) ;
for ( int binind=1; binind<=nbins; binind++ ) {
double wvsum(0.) ;
double wsum(0.) ;
for ( int si=0; si<nQcdSamples; si++ ) {
double val = hflat_0lepldp_ratio[si][bbi] -> GetBinContent( binind ) ;
double err = hflat_0lepldp_ratio[si][bbi] -> GetBinError( binind ) ;
if ( err > 0 ) {
double weight = 1./(err*err) ;
wvsum += val*weight ;
wsum += weight ;
}
} // si.
if ( wsum > 0. ) {
hflat_0lepldp_ratio_ave[bbi] -> SetBinContent( binind, wvsum/wsum ) ;
hflat_0lepldp_ratio_ave[bbi] -> SetBinError( binind, 1./sqrt(wsum) ) ;
}
} // binind
} // bbi.
//--- Compute RMS spread of samples and total uncertainty
TH1F* hflat_0lepldp_ratio_ave_withRMSerror[nBinsBjets] ;
printf("\n\n") ;
for ( int bbi=0; bbi<nBinsBjets; bbi++ ) {
sprintf( hname, "hflat_0lepldp_ratio_ave_%db_withRMSerror", bbi+1 ) ;
sprintf( htitle, "QCD 0lep/LDP average ratio, RMS included in error, nb=%d", bbi+1 ) ;
hflat_0lepldp_ratio_ave_withRMSerror[bbi] = bookHist( hname, htitle, nBinsMET, nBinsHT, 5 ) ;
hflat_0lepldp_ratio_ave_withRMSerror[bbi] -> SetMarkerStyle(24) ;
hflat_0lepldp_ratio_ave_withRMSerror[bbi] -> SetMarkerSize(2.0) ;
hflat_0lepldp_ratio_ave_withRMSerror[bbi] -> SetLineWidth(3) ;
for ( int binind=1; binind<=nbins; binind++ ) {
double sumsquare(0.) ;
int nsum(0) ;
double ave = hflat_0lepldp_ratio_ave[bbi] -> GetBinContent( binind ) ;
double ave_err = hflat_0lepldp_ratio_ave[bbi] -> GetBinError( binind ) ;
for ( int si=0; si<nQcdSamples; si++ ) {
double val = hflat_0lepldp_ratio[si][bbi] -> GetBinContent( binind ) ;
double err = hflat_0lepldp_ratio[si][bbi] -> GetBinError( binind ) ;
if ( err <= 0 ) { continue ; }
if ( val <= 0 ) { continue ; }
if ( err/val > 0.5 ) { continue ; } //-- do not include points with very large errors.
double diff = val - ave ;
sumsquare += diff*diff ;
nsum ++ ;
} // si.
if ( nsum > 1 ) {
double rms = sqrt(sumsquare/nsum) ;
double totalerr = sqrt( ave_err*ave_err + rms*rms ) ;
const char* binlabel = hflat_0lepldp_ratio_ave_withRMSerror[bbi] -> GetXaxis() -> GetBinLabel( binind ) ;
printf(" %s : %s : ratio = %5.3f, stat err = %5.3f, RMS = %5.3f, total err = %5.3f\n",
hname, binlabel, ave, ave_err, rms, totalerr ) ;
hflat_0lepldp_ratio_ave_withRMSerror[bbi] -> SetBinContent( binind, ave ) ;
hflat_0lepldp_ratio_ave_withRMSerror[bbi] -> SetBinError( binind, totalerr ) ;
} else {
hflat_0lepldp_ratio_ave_withRMSerror[bbi] -> SetBinContent( binind, ave ) ;
hflat_0lepldp_ratio_ave_withRMSerror[bbi] -> SetBinError( binind, ave_err ) ;
}
} // binind
printf("\n") ;
} // bbi.
printf("\n\n") ;
//--- compute global average 0lep/LDP ratio.
double all0lep(0.) ;
double allldp(0.) ;
printf("\n\n") ;
for ( int bbi=0; bbi<nBinsBjets; bbi++ ) {
for ( int si=0; si<nQcdSamples; si++ ) {
double sample_all0lep = h0lep[si][bbi] -> Integral() ;
double sample_allldp = hldp [si][bbi] -> Integral() ;
double sample_ratio(0.) ;
if ( sample_allldp > 0 ) { sample_ratio = sample_all0lep / sample_allldp ; }
printf( "%s, nb=%d : 0lep = %8.1f, LDP = %8.1f, ratio = %5.3f\n", samplename[si], bbi+1, sample_all0lep, sample_allldp, sample_ratio ) ;
all0lep += sample_all0lep ;
allldp += sample_allldp ;
} // si.
printf("\n") ;
} // bbi.
printf("\n\n") ;
double global_0lepldp_ratio(0.) ;
if ( allldp > 0.) {
global_0lepldp_ratio = all0lep / allldp ;
} else {
printf("\n\n *** You screwed up.\n\n") ; return ;
}
printf(" overall : 0lep = %9.1f, LDP = %9.1f, ratio = %5.3f\n", all0lep, allldp, global_0lepldp_ratio ) ;
//--- Compute scale factors. SF_i = (0lep/LDP)_i / global_(0lep/LDP)
TH1F* hflat_scale_factor[nBinsBjets] ;
TH1F* hflat_scale_factor_withRMSerror[nBinsBjets] ;
for ( int bbi=0; bbi<nBinsBjets; bbi++ ) {
sprintf( hname, "hflat_scale_factor_%db", bbi+1 ) ;
sprintf( htitle, "QCD scale factor, nb=%d", bbi+1 ) ;
hflat_scale_factor[bbi] = (TH1F*) hflat_0lepldp_ratio_ave[bbi]->Clone( hname ) ;
hflat_scale_factor[bbi] -> SetTitle( htitle ) ;
hflat_scale_factor[bbi] -> Scale( 1./ global_0lepldp_ratio ) ;
sprintf( hname, "hflat_scale_factor_%db_withRMSerror", bbi+1 ) ;
sprintf( htitle, "QCD scale factor, nb=%d, RMS error included ", bbi+1 ) ;
hflat_scale_factor_withRMSerror[bbi] = (TH1F*) hflat_0lepldp_ratio_ave_withRMSerror[bbi]->Clone( hname ) ;
hflat_scale_factor_withRMSerror[bbi] -> SetTitle( htitle ) ;
hflat_scale_factor_withRMSerror[bbi] -> Scale( 1./ global_0lepldp_ratio ) ;
} // bbi.
//--- set Scale Factor values in dat file if one is provided.
if ( strcmp( datfile, "null" ) != 0 ) {
printf("\n\n\n Setting QCD scale factors in %s\n\n", datfile ) ;
for ( int mbi=0; mbi<nBinsMET; mbi++ ) {
for ( int hbi=0; hbi<nBinsHT; hbi++ ) {
for ( int bbi=0; bbi<nBinsBjets; bbi++ ) {
char parname[1000] ;
int histbin = 1 + (nBinsHT+1)*mbi + hbi + 1 ;
double val = hflat_scale_factor_withRMSerror[bbi]->GetBinContent( histbin ) ;
double err = hflat_scale_factor_withRMSerror[bbi]->GetBinError( histbin ) ;
if ( err <= 0 ) {
val = 1.0 ;
err = 3.0 ;
}
sprintf( parname, "sf_qcd_M%d_H%d_%db", mbi+1, hbi+1, bbi+1 ) ;
updateFileValue( datfile, parname, val ) ;
sprintf( parname, "sf_qcd_M%d_H%d_%db_err", mbi+1, hbi+1, bbi+1 ) ;
updateFileValue( datfile, parname, err ) ;
} // bbi.
} // hbi.
} // mbi.
}
//=========== End calculations. Plots and other output below here. ===================================
//--- Plot all samples together
TCanvas* cqcd2 = (TCanvas*) gDirectory->FindObject("cqcd2") ;
if ( cqcd2 == 0x0 ) {
cqcd2 = new TCanvas("cqcd2", "qcd study", 1700, 600 ) ;
}
TLegend* l2 = new TLegend( 0.79, 0.70, 0.99, 0.99 ) ;
l2->AddEntry( hflat_0lepldp_ratio[0][0], "120 to 170" ) ;
l2->AddEntry( hflat_0lepldp_ratio[1][0], "170 to 300" ) ;
l2->AddEntry( hflat_0lepldp_ratio[2][0], "300 to 470" ) ;
l2->AddEntry( hflat_0lepldp_ratio[3][0], "470 to 600" ) ;
l2->AddEntry( hflat_0lepldp_ratio[4][0], "600 to 800" ) ;
l2->AddEntry( hflat_0lepldp_ratio[5][0], "800 to 1000" ) ;
l2->AddEntry( hflat_0lepldp_ratio[6][0], "1000 to 1400" ) ;
l2->AddEntry( hflat_0lepldp_ratio[7][0], "1400 to 1800" ) ;
l2->AddEntry( hflat_0lepldp_ratio[8][0], "> 1800" ) ;
l2->AddEntry( hflat_0lepldp_ratio_ave[0], "Average ratio" ) ;
cqcd2 -> Clear() ;
cqcd2 -> Divide(3,1) ;
cqcd2 -> cd(1) ;
hflat_0lepldp_ratio[0][0] -> SetTitle("QCD 0lep/LDP ratio, nb=1") ;
for ( int si=0; si<nQcdSamples; si++ ) {
hflat_0lepldp_ratio[si][0] -> SetMarkerStyle(20+si) ;
hflat_0lepldp_ratio[si][0] -> SetLineColor(samplecolor[si]) ;
hflat_0lepldp_ratio[si][0] -> SetMarkerColor(samplecolor[si]) ;
if ( si == 0 ) { hflat_0lepldp_ratio[si][0] -> DrawCopy() ; } else { hflat_0lepldp_ratio[si][0] -> DrawCopy("same") ; }
}
hflat_0lepldp_ratio_ave[0]->DrawCopy("same") ;
line->DrawLine(0.5,0,nbins+0.5,0) ;
l2->Draw() ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
cqcd2 -> cd(2) ;
hflat_0lepldp_ratio[0][1] -> SetTitle("QCD 0lep/LDP ratio, nb=2") ;
for ( int si=0; si<nQcdSamples; si++ ) {
hflat_0lepldp_ratio[si][1] -> SetMarkerStyle(20+si) ;
hflat_0lepldp_ratio[si][1] -> SetLineColor(samplecolor[si]) ;
hflat_0lepldp_ratio[si][1] -> SetMarkerColor(samplecolor[si]) ;
if ( si == 0 ) { hflat_0lepldp_ratio[si][1] -> DrawCopy() ; } else { hflat_0lepldp_ratio[si][1] -> DrawCopy("same") ; }
}
hflat_0lepldp_ratio_ave[1]->DrawCopy("same") ;
line->DrawLine(0.5,0,nbins+0.5,0) ;
l2->Draw() ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
cqcd2 -> cd(3) ;
hflat_0lepldp_ratio[0][2] -> SetTitle("QCD 0lep/LDP ratio, nb>=3") ;
for ( int si=0; si<nQcdSamples; si++ ) {
hflat_0lepldp_ratio[si][2] -> SetMarkerStyle(20+si) ;
hflat_0lepldp_ratio[si][2] -> SetLineColor(samplecolor[si]) ;
hflat_0lepldp_ratio[si][2] -> SetMarkerColor(samplecolor[si]) ;
if ( si == 0 ) { hflat_0lepldp_ratio[si][2] -> DrawCopy() ; } else { hflat_0lepldp_ratio[si][2] -> DrawCopy("same") ; }
}
hflat_0lepldp_ratio_ave[2]->DrawCopy("same") ;
line->DrawLine(0.5,0,nbins+0.5,0) ;
l2->Draw() ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
cqcd2->Update() ; cqcd2->Draw() ;
if ( savePlots ) {
cqcd2 -> SaveAs("outputfiles/qcd-study1-allonone.png") ;
cqcd2 -> SaveAs("outputfiles/qcd-study1-allonone.pdf") ;
}
//--- Go through the samples, 1 by 1, and draw numerator, denominator, and ratio
TCanvas* cqcd3 = (TCanvas*) gDirectory->FindObject("cqcd3") ;
if ( cqcd3 == 0x0 ) {
cqcd3 = new TCanvas("cqcd3", "qcd study", 1200, 900 ) ;
}
char oldtitle[1000] ;
sprintf( oldtitle, "QCD 0lep/LDP ratio, nb=1, %s", samplename[0] ) ;
hflat_0lepldp_ratio[0][0] -> SetTitle(oldtitle) ;
sprintf( oldtitle, "QCD 0lep/LDP ratio, nb=2, %s", samplename[0] ) ;
hflat_0lepldp_ratio[0][1] -> SetTitle(oldtitle) ;
sprintf( oldtitle, "QCD 0lep/LDP ratio, nb>=3, %s", samplename[0] ) ;
hflat_0lepldp_ratio[0][2] -> SetTitle(oldtitle) ;
cqcd3->Clear() ;
cqcd3->Divide(3,3) ;
for ( int si=0; si<nQcdSamples; si++ ) {
TLegend* l3 = new TLegend( 0.65, 0.78, 0.99, 0.92) ;
l3->AddEntry( hflat_0lepldp_ratio[si][0], samplename[si] ) ;
l3->AddEntry( hflat_0lepldp_ratio_ave[0], "Average") ;
for ( int bbi=0; bbi<nBinsBjets; bbi++ ) {
cqcd3->cd(1+bbi) ;
hflat_0lep[si][bbi] -> DrawCopy("histe") ;
hflat_0lep[si][bbi] -> DrawCopy("samee") ;
cqcd3->cd(4+bbi) ;
hflat_ldp[si][bbi] -> DrawCopy("histe") ;
hflat_ldp[si][bbi] -> DrawCopy("samee") ;
cqcd3->cd(7+bbi) ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
hflat_0lepldp_ratio[si][bbi]->DrawCopy() ;
hflat_0lepldp_ratio_ave[bbi]->DrawCopy("same") ;
line->DrawLine(0.5,0,nbins+0.5,0) ;
l3->Draw() ;
} // bbi.
cqcd3->Update() ; cqcd3->Draw() ;
if ( savePlots ) {
char filename[1000] ;
sprintf( filename, "outputfiles/qcd-study1-%s.pdf", samplename[si] ) ;
cqcd3 -> SaveAs( filename ) ;
sprintf( filename, "outputfiles/qcd-study1-%s.png", samplename[si] ) ;
cqcd3 -> SaveAs( filename ) ;
}
if ( interactive ) {
char a = getchar() ;
if ( a == 'q') { return ; }
}
} // si.
//--- Draw the average 0lep/LDP ratio with MC stat error and total error.
TCanvas* cqcd4 = (TCanvas*) gDirectory->FindObject("cqcd4") ;
if ( cqcd4 == 0x0 ) {
cqcd4 = new TCanvas("cqcd4", "qcd study", 1700, 600 ) ;
}
gStyle->SetEndErrorSize(5) ;
cqcd4->Clear() ;
cqcd4->Divide(3,1) ;
cqcd4 -> cd(1) ;
hflat_0lepldp_ratio_ave[0] -> SetTitle("Average QCD 0lep/LDP ratio, nb=1") ;
hflat_0lepldp_ratio_ave[0] -> SetMarkerSize(1.2) ;
hflat_0lepldp_ratio_ave[0] -> SetMarkerStyle(20) ;
hflat_0lepldp_ratio_ave[0] -> SetMaximum(0.6) ;
hflat_0lepldp_ratio_ave[0] -> SetMinimum(-0.1) ;
hflat_0lepldp_ratio_ave[0]->DrawCopy("e1") ;
hflat_0lepldp_ratio_ave_withRMSerror[0]->SetMarkerStyle() ;
hflat_0lepldp_ratio_ave_withRMSerror[0]->SetLineColor(4) ;
hflat_0lepldp_ratio_ave_withRMSerror[0]->DrawCopy("samee1") ;
hflat_0lepldp_ratio_ave[0]->DrawCopy("samee1") ;
line->DrawLine(0.5,0,nbins+0.5,0) ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
cqcd4 -> cd(2) ;
hflat_0lepldp_ratio_ave[1] -> SetTitle("Average QCD 0lep/LDP ratio, nb=2") ;
hflat_0lepldp_ratio_ave[1] -> SetMarkerSize(1.2) ;
hflat_0lepldp_ratio_ave[1] -> SetMarkerStyle(20) ;
hflat_0lepldp_ratio_ave[1] -> SetMaximum(0.6) ;
hflat_0lepldp_ratio_ave[1] -> SetMinimum(-0.1) ;
hflat_0lepldp_ratio_ave[1]->DrawCopy("e1") ;
hflat_0lepldp_ratio_ave_withRMSerror[1]->SetMarkerStyle() ;
hflat_0lepldp_ratio_ave_withRMSerror[1]->SetLineColor(4) ;
hflat_0lepldp_ratio_ave_withRMSerror[1]->DrawCopy("samee1") ;
hflat_0lepldp_ratio_ave[1]->DrawCopy("samee1") ;
line->DrawLine(0.5,0,nbins+0.5,0) ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
cqcd4 -> cd(3) ;
hflat_0lepldp_ratio_ave[2] -> SetTitle("Average QCD 0lep/LDP ratio, nb>=3") ;
hflat_0lepldp_ratio_ave[2] -> SetMarkerSize(1.2) ;
hflat_0lepldp_ratio_ave[2] -> SetMarkerStyle(20) ;
hflat_0lepldp_ratio_ave[2] -> SetMaximum(0.6) ;
hflat_0lepldp_ratio_ave[2] -> SetMinimum(-0.1) ;
hflat_0lepldp_ratio_ave[2]->DrawCopy("e1") ;
hflat_0lepldp_ratio_ave_withRMSerror[2]->SetMarkerStyle() ;
hflat_0lepldp_ratio_ave_withRMSerror[2]->SetLineColor(4) ;
hflat_0lepldp_ratio_ave_withRMSerror[2]->DrawCopy("samee1") ;
hflat_0lepldp_ratio_ave[2]->DrawCopy("samee1") ;
line->DrawLine(0.5,0,nbins+0.5,0) ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
cqcd4->Update() ; cqcd4->Draw() ;
if ( savePlots ) {
cqcd4 -> SaveAs("outputfiles/qcd-study1-averatio.png") ;
cqcd4 -> SaveAs("outputfiles/qcd-study1-averatio.pdf") ;
}
//--- Draw the QCD scale factor with MC stat error and total error.
TCanvas* cqcd5 = (TCanvas*) gDirectory->FindObject("cqcd5") ;
if ( cqcd5 == 0x0 ) {
cqcd5 = new TCanvas("cqcd5", "qcd study", 1700, 600 ) ;
}
gStyle->SetEndErrorSize(5) ;
cqcd5->Clear() ;
cqcd5->Divide(3,1) ;
cqcd5 -> cd(1) ;
hflat_scale_factor[0] -> SetTitle("QCD Scale Factor, nb=1") ;
hflat_scale_factor[0] -> SetMarkerSize(1.2) ;
hflat_scale_factor[0] -> SetMarkerStyle(20) ;
hflat_scale_factor[0] -> SetMaximum(2.6) ;
hflat_scale_factor[0] -> SetMinimum(-0.1) ;
hflat_scale_factor[0]->DrawCopy("e1") ;
hflat_scale_factor_withRMSerror[0]->SetMarkerStyle() ;
hflat_scale_factor_withRMSerror[0]->SetLineColor(4) ;
hflat_scale_factor_withRMSerror[0]->DrawCopy("samee1") ;
hflat_scale_factor[0]->DrawCopy("samee1") ;
line->DrawLine(0.5,0,nbins+0.5,0) ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
cqcd5 -> cd(2) ;
hflat_scale_factor[1] -> SetTitle("QCD Scale Factor, nb=2") ;
hflat_scale_factor[1] -> SetMarkerSize(1.2) ;
hflat_scale_factor[1] -> SetMarkerStyle(20) ;
hflat_scale_factor[1] -> SetMaximum(2.6) ;
hflat_scale_factor[1] -> SetMinimum(-0.1) ;
hflat_scale_factor[1]->DrawCopy("e1") ;
hflat_scale_factor_withRMSerror[1]->SetMarkerStyle() ;
hflat_scale_factor_withRMSerror[1]->SetLineColor(4) ;
hflat_scale_factor_withRMSerror[1]->DrawCopy("samee1") ;
hflat_scale_factor[1]->DrawCopy("samee1") ;
line->DrawLine(0.5,0,nbins+0.5,0) ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
cqcd5 -> cd(3) ;
hflat_scale_factor[2] -> SetTitle("QCD Scale Factor, nb>=3") ;
hflat_scale_factor[2] -> SetMarkerSize(1.2) ;
hflat_scale_factor[2] -> SetMarkerStyle(20) ;
hflat_scale_factor[2] -> SetMaximum(2.6) ;
hflat_scale_factor[2] -> SetMinimum(-0.1) ;
hflat_scale_factor[2]->DrawCopy("e1") ;
hflat_scale_factor_withRMSerror[2]->SetMarkerStyle() ;
hflat_scale_factor_withRMSerror[2]->SetLineColor(4) ;
hflat_scale_factor_withRMSerror[2]->DrawCopy("samee1") ;
hflat_scale_factor[2]->DrawCopy("samee1") ;
line->DrawLine(0.5,0,nbins+0.5,0) ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
cqcd5->Update() ; cqcd5->Draw() ;
if ( savePlots ) {
cqcd5 -> SaveAs("outputfiles/qcd-study1-scalefactor.png") ;
cqcd5 -> SaveAs("outputfiles/qcd-study1-scalefactor.pdf") ;
}
} // qcd_study.
void draw_closure_sums4( const char* plotname = "njet", const char* infile = "outputfiles/closure-sums4.root" ) {
char hname[100] ;
gStyle -> SetOptStat(0) ;
gStyle -> SetPadLeftMargin(0.13) ;
gDirectory -> Delete( "h*" ) ;
loadHist( infile ) ;
gDirectory -> ls() ;
sprintf( hname, "h_closure_%s_model_fit", plotname ) ;
TH1F* h_model_fit = get_hist( hname ) ;
TString tsn( hname ) ;
tsn.ReplaceAll( "fit", "zero_err" ) ;
TH1F* h_model_zero_err = (TH1F*) h_model_fit -> Clone( tsn.Data() ) ;
for ( int bi=1; bi<= h_model_zero_err->GetNbinsX(); bi++ ) {
h_model_zero_err -> SetBinError( bi, 0.0000001 ) ;
}
sprintf( hname, "h_closure_%s_model_fit_and_syst", plotname ) ;
TH1F* h_model_fit_and_syst = get_hist( hname ) ;
sprintf( hname, "h_closure_%s_model_total", plotname ) ;
TH1F* h_model_total = get_hist( hname ) ;
sprintf( hname, "h_closure_%s_qcdmc", plotname ) ;
TH1F* h_model_qcdmc = get_hist( hname ) ;
h_model_qcdmc -> SetMarkerStyle(20) ;
h_model_qcdmc -> SetMarkerSize(1.5) ;
h_model_qcdmc -> SetLineWidth(2) ;
TCanvas* can = (TCanvas*) gDirectory -> FindObject( "can_dcs" ) ;
if ( can == 0x0 ) {
can = new TCanvas( "can_dcs", "", 700, 800 ) ;
}
can -> Clear() ;
if ( strcmp( plotname, "10boxes" ) == 0 ) {
gPad -> SetBottomMargin( 0.20 ) ;
h_model_total -> GetXaxis() -> LabelsOption("v") ;
} else {
gPad -> SetBottomMargin( 0.10 ) ;
}
TLegend* legend(0x0) ;
if ( strcmp( plotname, "ht" ) == 0 ) {
legend = new TLegend( 0.60, 0.15, 0.98, 0.40 ) ;
} else {
legend = new TLegend( 0.60, 0.70, 0.98, 0.95 ) ;
}
legend -> AddEntry( h_model_fit, "Model, Fit" ) ;
legend -> AddEntry( h_model_fit_and_syst, "Model, Fit + MHT" ) ;
legend -> AddEntry( h_model_total, "Model, Fit + MHT + MC" ) ;
legend -> AddEntry( h_model_qcdmc, "QCD Monte Carlo" ) ;
h_model_fit -> SetFillColor( kRed-7 ) ;
h_model_fit_and_syst -> SetFillColor( kRed-9 ) ;
h_model_total -> SetFillColor( kRed-10 ) ;
h_model_zero_err -> SetLineColor( 4 ) ;
h_model_total -> SetYTitle( "QCD BG events" ) ;
h_model_total -> SetTitleSize( 0.05, "y" ) ;
if ( strcmp( plotname, "njet" ) == 0 ) { h_model_total -> SetTitle( "Njet bins" ) ; }
if ( strcmp( plotname, "nb" ) == 0 ) { h_model_total -> SetTitle( "Nb bins" ) ; }
if ( strcmp( plotname, "mht" ) == 0 ) { h_model_total -> SetTitle( "MHT bins" ) ; }
if ( strcmp( plotname, "ht" ) == 0 ) { h_model_total -> SetTitle( "HT bins" ) ; }
if ( strcmp( plotname, "10boxes" ) == 0 ) { h_model_total -> SetTitle( "MHT-HT bins" ) ; }
h_model_total -> Draw( "e2" ) ;
h_model_fit_and_syst -> Draw( "e2 same" ) ;
h_model_fit -> Draw("e2 same" ) ;
h_model_zero_err -> Draw( "same" ) ;
gPad -> SetGridy(1) ;
h_model_qcdmc -> Draw( "same" ) ;
h_model_total -> Draw( "axig same" ) ;
h_model_total -> Draw( "axis same" ) ;
legend -> Draw() ;
char fname[1000] ;
sprintf( fname, "outputfiles/closure-sum-%s.pdf", plotname ) ;
can -> SaveAs( fname ) ;
} // draw_closure_sums4
void draw_analysis_mht_plots3( const char* infile = "outputfiles/analysis-output3-default.root", bool with_numbers = true, const char* save_file_base = "plot-dtt-analysis3" ) {
gDirectory -> Delete( "h*" ) ;
gStyle -> SetOptStat(0) ;
loadHist( infile ) ;
int wx(50), wy(50) ;
//--- Canvas by Nb, 3x3 Njet vs HT grid
for ( int nbi=0; nbi<=3; nbi++ ) {
char cname[100] ;
char ctitle[100] ;
sprintf( cname, "can_draw_dtt_analysis1_nb%d", nbi ) ;
sprintf( ctitle, "MHT distributions, Nb%d", nbi ) ;
TCanvas* can = new TCanvas( cname, ctitle, 900, 900 ) ;
can -> Divide( 3, 3 ) ;
can -> SetWindowPosition( wx, wy ) ;
wx += 50 ;
wy += 20 ;
int ci(1) ;
for ( int hti=1; hti<4; hti++ ) {
for ( int nji=1; nji<4; nji++ ) {
can -> cd( ci++ ) ;
char hname[100] ;
sprintf( hname, "h_lostlep_mht_cdtt_nb%d_nj%d_ht%d_80bin", nbi, nji, hti ) ;
TH1F* hpll_cdtt = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hpll_cdtt == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_lostlep_mht_mc_nb%d_nj%d_ht%d_80bin", nbi, nji, hti ) ;
TH1F* hpll_mc = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hpll_mc == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
do_plots( hpll_cdtt, hpll_mc ) ;
if ( with_numbers) do_numbers( hpll_cdtt, hpll_mc ) ;
} // nji
} // hti
char savefile[10000] ;
sprintf( savefile, "outputfiles/%s-mht-nb%d.pdf", save_file_base, nbi ) ;
can -> SaveAs( savefile ) ;
} // nbi.
//--- Canvas for sum over Nb, 3x3 Njet vs HT grid
{ // sum over Nb
char cname[100] ;
char ctitle[100] ;
sprintf( cname, "can_draw_dtt_analysis1_nball" ) ;
sprintf( ctitle, "MHT distributions, all Nb" ) ;
TCanvas* can = new TCanvas( cname, ctitle, 900, 900 ) ;
can -> Divide( 3, 3 ) ;
can -> SetWindowPosition( wx, wy ) ;
wx += 50 ;
wy += 20 ;
int ci(1) ;
for ( int hti=1; hti<4; hti++ ) {
for ( int nji=1; nji<4; nji++ ) {
can -> cd( ci++ ) ;
char hname[1000] ;
char htitle[1000] ;
sprintf( hname, "h_lostlep_mht_cdtt_nb1_nj1_ht1_80bin" ) ;
TH1F* hp_toclone = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp_toclone == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_mht_cdtt_nj%d_ht%d", nji, hti ) ;
sprintf( htitle, "MHT, from cdtt, Njet%d, HT%d", nji, hti ) ;
TH1F* hp_cdtt = (TH1F*) hp_toclone -> Clone( hname ) ;
hp_cdtt -> Reset() ;
hp_cdtt -> SetTitle( htitle ) ;
sprintf( hname, "h_mht_mc_nj%d_ht%d", nji, hti ) ;
sprintf( htitle, "MHT, from MC, Njet%d, HT%d", nji, hti ) ;
TH1F* hp_mc = (TH1F*) hp_toclone -> Clone( hname ) ;
hp_mc -> Reset() ;
hp_mc -> SetTitle( htitle ) ;
for ( int nbi=0; nbi<=3; nbi++ ) {
char hname[100] ;
sprintf( hname, "h_lostlep_mht_cdtt_nb%d_nj%d_ht%d_80bin", nbi, nji, hti ) ;
TH1F* hpll_cdtt = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hpll_cdtt == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_lostlep_mht_mc_nb%d_nj%d_ht%d_80bin", nbi, nji, hti ) ;
TH1F* hpll_mc = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hpll_mc == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
hp_cdtt -> Add( hpll_cdtt ) ;
hp_mc -> Add( hpll_mc ) ;
} // nbi.
do_plots( hp_cdtt, hp_mc ) ;
if ( with_numbers) do_numbers( hp_cdtt, hp_mc ) ;
} // nji
} // hti
char savefile[10000] ;
sprintf( savefile, "outputfiles/%s-mht-nball.pdf", save_file_base ) ;
can -> SaveAs( savefile ) ;
} // sum over Nb
//--- Canvas for HT bins --------------------------------------------------------------------
{ // HT bins canvas
char cname[100] ;
char ctitle[100] ;
sprintf( cname, "can_draw_dtt_analysis1_ht_bins" ) ;
sprintf( ctitle, "MHT distributions, HT bins" ) ;
TCanvas* can = new TCanvas( cname, ctitle, 400, 1100 ) ;
can -> Divide( 1, 3 ) ;
can -> SetWindowPosition( wx, wy ) ;
wx += 50 ;
wy += 20 ;
int ci(1) ;
for ( int hti=1; hti<4; hti++ ) {
can -> cd( ci++ ) ;
char hname[1000] ;
char htitle[1000] ;
sprintf( hname, "h_lostlep_mht_cdtt_nb1_nj1_ht%d_80bin", hti ) ;
TH1F* hp_toclone = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp_toclone == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_mht_cdtt_ht%d", hti ) ;
sprintf( htitle, "MHT, from cdtt, HT%d", hti ) ;
TH1F* hp_cdtt = (TH1F*) hp_toclone -> Clone( hname ) ;
hp_cdtt -> Reset() ;
hp_cdtt -> SetTitle( htitle ) ;
sprintf( hname, "h_mht_mc_ht%d", hti ) ;
sprintf( htitle, "MHT, from MC, HT%d", hti ) ;
TH1F* hp_mc = (TH1F*) hp_toclone -> Clone( hname ) ;
hp_mc -> Reset() ;
hp_mc -> SetTitle( htitle ) ;
for ( int nji=1; nji<4; nji++ ) {
for ( int nbi=0; nbi<4; nbi++ ) {
sprintf( hname, "h_lostlep_mht_cdtt_nb%d_nj%d_ht%d_80bin", nbi, nji, hti ) ;
TH1F* hpll_cdtt = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hpll_cdtt == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_lostlep_mht_mc_nb%d_nj%d_ht%d_80bin", nbi, nji, hti ) ;
TH1F* hpll_mc = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hpll_mc == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
hp_cdtt -> Add( hpll_cdtt ) ;
hp_mc -> Add( hpll_mc ) ;
} // nbi
} // nji
do_plots( hp_cdtt, hp_mc ) ;
if ( with_numbers) do_numbers( hp_cdtt, hp_mc ) ;
} // hti
char savefile[10000] ;
sprintf( savefile, "outputfiles/%s-mht-ht.pdf", save_file_base ) ;
can -> SaveAs( savefile ) ;
} // HT bins canvas
//--- Canvas for Njet bins --------------------------------------------------------------------
{ // Njet bins canvas
char cname[100] ;
char ctitle[100] ;
sprintf( cname, "can_draw_dtt_analysis1_njet_bins" ) ;
sprintf( ctitle, "MHT distributions, Njet bins" ) ;
TCanvas* can = new TCanvas( cname, ctitle, 400, 1100 ) ;
can -> Divide( 1, 3 ) ;
can -> SetWindowPosition( wx, wy ) ;
wx += 50 ;
wy += 20 ;
int ci(1) ;
for ( int nji=1; nji<4; nji++ ) {
can -> cd( ci++ ) ;
char hname[1000] ;
char htitle[1000] ;
sprintf( hname, "h_lostlep_mht_cdtt_nb1_nj1_ht1_80bin" ) ;
TH1F* hp_toclone = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp_toclone == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_mht_cdtt_njet%d", nji ) ;
sprintf( htitle, "MHT, from cdtt, Njet%d", nji ) ;
TH1F* hp_cdtt = (TH1F*) hp_toclone -> Clone( hname ) ;
hp_cdtt -> Reset() ;
hp_cdtt -> SetTitle( htitle ) ;
sprintf( hname, "h_mht_mc_njet%d", nji ) ;
sprintf( htitle, "MHT, from MC, Njet%d", nji ) ;
TH1F* hp_mc = (TH1F*) hp_toclone -> Clone( hname ) ;
hp_mc -> Reset() ;
hp_mc -> SetTitle( htitle ) ;
for ( int hti=1; hti<4; hti++ ) {
for ( int nbi=0; nbi<4; nbi++ ) {
sprintf( hname, "h_lostlep_mht_cdtt_nb%d_nj%d_ht%d_80bin", nbi, nji, hti ) ;
TH1F* hpll_cdtt = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hpll_cdtt == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_lostlep_mht_mc_nb%d_nj%d_ht%d_80bin", nbi, nji, hti ) ;
TH1F* hpll_mc = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hpll_mc == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
hp_cdtt -> Add( hpll_cdtt ) ;
hp_mc -> Add( hpll_mc ) ;
} // nbi
} // hti
do_plots( hp_cdtt, hp_mc ) ;
if ( with_numbers) do_numbers( hp_cdtt, hp_mc ) ;
} // hti
char savefile[10000] ;
sprintf( savefile, "outputfiles/%s-mht-njet.pdf", save_file_base ) ;
can -> SaveAs( savefile ) ;
} // Njet bins canvas
//--- Canvas for Nb bins --------------------------------------------------------------------
{ // Nb bins canvas
char cname[100] ;
char ctitle[100] ;
sprintf( cname, "can_draw_dtt_analysis1_nb_bins" ) ;
sprintf( ctitle, "MHT distributions, Nb bins" ) ;
TCanvas* can = new TCanvas( cname, ctitle, 400, 1100 ) ;
can -> Divide( 1, 4 ) ;
can -> SetWindowPosition( wx, wy ) ;
wx += 50 ;
wy += 20 ;
int ci(1) ;
for ( int nbi=0; nbi<4; nbi++ ) {
can -> cd( ci++ ) ;
char hname[1000] ;
char htitle[1000] ;
sprintf( hname, "h_lostlep_mht_cdtt_nb1_nj1_ht1_80bin" ) ;
TH1F* hp_toclone = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp_toclone == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_mht_cdtt_nb%d", nbi ) ;
sprintf( htitle, "MHT, from cdtt, Nb%d", nbi ) ;
TH1F* hp_cdtt = (TH1F*) hp_toclone -> Clone( hname ) ;
hp_cdtt -> Reset() ;
hp_cdtt -> SetTitle( htitle ) ;
sprintf( hname, "h_mht_mc_nb%d", nbi ) ;
sprintf( htitle, "MHT, from MC, Nb%d", nbi ) ;
TH1F* hp_mc = (TH1F*) hp_toclone -> Clone( hname ) ;
hp_mc -> Reset() ;
hp_mc -> SetTitle( htitle ) ;
for ( int hti=1; hti<4; hti++ ) {
for ( int nji=1; nji<4; nji++ ) {
sprintf( hname, "h_lostlep_mht_cdtt_nb%d_nj%d_ht%d_80bin", nbi, nji, hti ) ;
TH1F* hpll_cdtt = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hpll_cdtt == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_lostlep_mht_mc_nb%d_nj%d_ht%d_80bin", nbi, nji, hti ) ;
TH1F* hpll_mc = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hpll_mc == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
hp_cdtt -> Add( hpll_cdtt ) ;
hp_mc -> Add( hpll_mc ) ;
} // nji
} // hti
do_plots( hp_cdtt, hp_mc ) ;
if ( with_numbers) do_numbers( hp_cdtt, hp_mc ) ;
} // hti
char savefile[10000] ;
sprintf( savefile, "outputfiles/%s-mht-nb.pdf", save_file_base ) ;
can -> SaveAs( savefile ) ;
} // Nb bins canvas
//--- Canvas for sum over all --------------------------------------------------------------------
{ // sum over all
char cname[100] ;
char ctitle[100] ;
sprintf( cname, "can_draw_dtt_analysis1_all" ) ;
sprintf( ctitle, "MHT distributions, all" ) ;
TCanvas* can = new TCanvas( cname, ctitle, 700, 600 ) ;
can -> SetWindowPosition( wx, wy ) ;
wx += 50 ;
wy += 20 ;
char hname[1000] ;
char htitle[1000] ;
sprintf( hname, "h_lostlep_mht_cdtt_nb1_nj1_ht1_80bin" ) ;
TH1F* hp_toclone = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp_toclone == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_mht_cdtt_all" ) ;
sprintf( htitle, "MHT, from cdtt, all" ) ;
TH1F* hp_cdtt = (TH1F*) hp_toclone -> Clone( hname ) ;
hp_cdtt -> Reset() ;
hp_cdtt -> SetTitle( htitle ) ;
sprintf( hname, "h_mht_mc_all" ) ;
sprintf( htitle, "MHT, from MC, all" ) ;
TH1F* hp_mc = (TH1F*) hp_toclone -> Clone( hname ) ;
hp_mc -> Reset() ;
hp_mc -> SetTitle( htitle ) ;
for ( int nbi=0; nbi<4; nbi++ ) {
for ( int hti=1; hti<4; hti++ ) {
for ( int nji=1; nji<4; nji++ ) {
sprintf( hname, "h_lostlep_mht_cdtt_nb%d_nj%d_ht%d_80bin", nbi, nji, hti ) ;
TH1F* hpll_cdtt = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hpll_cdtt == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_lostlep_mht_mc_nb%d_nj%d_ht%d_80bin", nbi, nji, hti ) ;
TH1F* hpll_mc = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hpll_mc == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
hp_cdtt -> Add( hpll_cdtt ) ;
hp_mc -> Add( hpll_mc ) ;
} // nji
} // hti
} // nbi
do_plots( hp_cdtt, hp_mc ) ;
if ( with_numbers) do_numbers( hp_cdtt, hp_mc ) ;
char savefile[10000] ;
sprintf( savefile, "outputfiles/%s-mht-all.pdf", save_file_base ) ;
can -> SaveAs( savefile ) ;
} // sum over all
//--- Canvas for superbins for MHT2, HT12 --------------------------------------------------------------------
{
char cname[100] ;
char ctitle[100] ;
sprintf( cname, "can_draw_dtt_analysis1_superbins_mht2_ht12" ) ;
sprintf( ctitle, "MHT distributions for mht2 superbins, HT12 " ) ;
TCanvas* can = new TCanvas( cname, ctitle, 1400, 700 ) ;
can -> Divide(4,2) ;
can -> SetWindowPosition( wx, wy ) ;
wx += 50 ;
wy += 20 ;
char hname[1000] ;
char htitle[1000] ;
int ci(1) ;
for ( int sbi=0; sbi<3; sbi++ ) {
can -> cd(ci++ ) ;
sprintf( hname, "h_lostlep_mht_cdtt_mht2_superbin%02d", sbi ) ;
TH1F* hp_cdtt = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp_cdtt == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_lostlep_mht_mc_mht2_superbin%02d", sbi ) ;
TH1F* hp_mc = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp_mc == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
do_plots( hp_cdtt, hp_mc ) ;
if ( with_numbers) do_numbers( hp_cdtt, hp_mc ) ;
} // sbi
char savefile[10000] ;
sprintf( savefile, "outputfiles/%s-superbins-mht2-ht12.pdf", save_file_base ) ;
can -> SaveAs( savefile ) ;
} // superbins for mht2, ht12
//--- Canvas for superbins for MHT2, HT3 --------------------------------------------------------------------
{
char cname[100] ;
char ctitle[100] ;
sprintf( cname, "can_draw_dtt_analysis1_superbins_mht2_ht3" ) ;
sprintf( ctitle, "MHT distributions for mht2 superbins, HT3 " ) ;
TCanvas* can = new TCanvas( cname, ctitle, 1400, 700 ) ;
can -> Divide(4,2) ;
can -> SetWindowPosition( wx, wy ) ;
wx += 50 ;
wy += 20 ;
char hname[1000] ;
char htitle[1000] ;
int ci(1) ;
for ( int sbi=3; sbi<6; sbi++ ) {
can -> cd(ci++ ) ;
sprintf( hname, "h_lostlep_mht_cdtt_mht2_superbin%02d", sbi ) ;
TH1F* hp_cdtt = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp_cdtt == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_lostlep_mht_mc_mht2_superbin%02d", sbi ) ;
TH1F* hp_mc = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp_mc == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
do_plots( hp_cdtt, hp_mc ) ;
if ( with_numbers) do_numbers( hp_cdtt, hp_mc ) ;
} // sbi
char savefile[10000] ;
sprintf( savefile, "outputfiles/%s-superbins-mht2-ht3.pdf", save_file_base ) ;
can -> SaveAs( savefile ) ;
} // superbins for mht2, ht3
//--- Canvas for superbins for MHT3 --------------------------------------------------------------------
{
char cname[100] ;
char ctitle[100] ;
sprintf( cname, "can_draw_dtt_analysis1_superbins_mht3" ) ;
sprintf( ctitle, "MHT distributions for mht3 superbins" ) ;
TCanvas* can = new TCanvas( cname, ctitle, 600, 900 ) ;
can -> Divide(1,2) ;
can -> SetWindowPosition( wx, wy ) ;
wx += 50 ;
wy += 20 ;
char hname[1000] ;
char htitle[1000] ;
int ci(1) ;
for ( int sbi=0; sbi<1; sbi++ ) {
can -> cd(ci++ ) ;
sprintf( hname, "h_lostlep_mht_cdtt_mht3_superbin%02d", sbi ) ;
TH1F* hp_cdtt = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp_cdtt == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
sprintf( hname, "h_lostlep_mht_mc_mht3_superbin%02d", sbi ) ;
TH1F* hp_mc = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp_mc == 0x0 ) {
printf("\n\n *** Missing hist %s\n\n", hname ) ;
return ;
}
do_plots( hp_cdtt, hp_mc ) ;
if ( with_numbers) do_numbers( hp_cdtt, hp_mc ) ;
} // sbi
char savefile[10000] ;
sprintf( savefile, "outputfiles/%s-superbins-mht3.pdf", save_file_base ) ;
can -> SaveAs( savefile ) ;
} // superbins for mht3
} // draw_analysis_mht_plots3
void draw_qcd_ratio_v3( const char* infile = "outputfiles/hists-v2d-qcd.root", const char* outputdir = "outputfiles/" ) {
setup_bins();
TLine* line0 = new TLine() ;
line0 -> SetLineColor(4) ;
TString tstring ;
TLine* rline = new TLine() ;
rline -> SetLineColor(2) ;
double ratio_max = 1.0 ;
char command[10000] ;
sprintf( command, "mkdir -p %s", outputdir ) ;
gSystem -> Exec( command ) ;
gStyle -> SetOptStat(0) ;
gDirectory -> Delete( "h*" ) ;
loadHist( infile ) ;
char hname[1000] ;
char label[100] ;
TH1F* h_ldp = get_hist( "h_ldp" ) ;
TH1F* h_hdp = get_hist( "h_hdp" ) ;
TH1F* h_max_ldp_weight = get_hist( "h_max_ldp_weight" ) ;
TH1F* h_ratio = new TH1F( "h_ratio", "QCD H/L ratio", nb_global_after_exclusion, 0.5, nb_global_after_exclusion + 0.5 ) ;
TH1F* h_max_ldp_weight_search_bins = new TH1F( "h_max_ldp_weight_search_bins", "max LDP weight", nb_global_after_exclusion, 0.5, nb_global_after_exclusion + 0.5 ) ;
TH1F* h_ldp_search_bins = new TH1F( "h_ldp_search_bins", "LDP counts, search bins", nb_global_after_exclusion, 0.5, nb_global_after_exclusion + 0.5 ) ;
TH1F* h_hdp_search_bins = new TH1F( "h_hdp_search_bins", "HDP counts, search bins", nb_global_after_exclusion, 0.5, nb_global_after_exclusion + 0.5 ) ;
TH1F * h_ratio_nb[10], * h_ratio_nj[10];
for ( int nb_count = 0; nb_count < nb_nb; nb_count++)
{
TString nb_str; nb_str.Form("%d",nb_count);
h_ratio_nb[nb_count] = new TH1F( "h_ratio_nb"+nb_str, "QCD H/L ratio, Nb"+nb_str, no_bin_bjet[nb_count], 0.5, no_bin_bjet[nb_count]+0.5 ) ;
}
for ( int nj_count = 1; nj_count <= nb_nj; nj_count++)
{
TString nj_str; nj_str.Form("%d",nj_count);
h_ratio_nj[nj_count] = new TH1F( "h_ratio_nj"+nj_str, "QCD H/L ratio, Nj"+nj_str, no_bin_njet[nj_count-1], 0.5, no_bin_njet[nj_count-1]+0.5 ) ;
}
int bi_hist(0) ;
int bi_search_hist(0) ;
int bi_nb_hist[10] = {};
int bi_nj_hist[10] = {};
for ( int bi_nj=1; bi_nj<=nb_nj; bi_nj++ ) {
for ( int bi_nb=1; bi_nb<=nb_nb; bi_nb++ ) {
for ( int bi_htmht=1; bi_htmht<=nb_htmht; bi_htmht++ ) {
bi_hist++ ; // this line should be reviewd when updating the code that produces h_ldp and h_hdp
if ( is_this_bin_excluded(bi_nj-1, bi_nb-1, bi_htmht-1) ) continue;
sprintf( label, "%s", h_ldp -> GetXaxis() -> GetBinLabel( bi_hist ) ) ;
//printf( " %3d : Nj%d Nb%d HTMHT%d : %30s\n", bi_hist, bi_nj, bi_nb-1, bi_htmht, label ) ;
if ( bi_htmht > 3 ) {
bi_search_hist ++ ;
double ldp_val = h_ldp -> GetBinContent( bi_hist ) ;
double ldp_err = h_ldp -> GetBinError( bi_hist ) ;
double hdp_val = h_hdp -> GetBinContent( bi_hist ) ;
double hdp_err = h_hdp -> GetBinError( bi_hist ) ;
double ratio_val(0.) ;
double ratio_err(0.) ;
if ( ldp_val > 0. && hdp_val > 0. ) {
ratio_val = hdp_val / ldp_val ;
ratio_err = ratio_val * sqrt( pow( ldp_err/ldp_val, 2. ) + pow( hdp_err/hdp_val, 2. ) ) ;
}
h_ratio -> SetBinContent( bi_search_hist, ratio_val ) ;
h_ratio -> SetBinError( bi_search_hist, ratio_err ) ;
h_ratio -> GetXaxis() -> SetBinLabel( bi_search_hist, label ) ;
h_max_ldp_weight_search_bins -> SetBinContent( bi_search_hist, h_max_ldp_weight->GetBinContent( bi_hist ) ) ;
h_max_ldp_weight_search_bins -> GetXaxis() -> SetBinLabel( bi_search_hist, label ) ;
h_ldp_search_bins -> SetBinContent( bi_search_hist, ldp_val ) ;
h_ldp_search_bins -> SetBinError( bi_search_hist, ldp_err ) ;
h_ldp_search_bins -> GetXaxis() -> SetBinLabel( bi_search_hist, label ) ;
h_hdp_search_bins -> SetBinContent( bi_search_hist, hdp_val ) ;
h_hdp_search_bins -> SetBinError( bi_search_hist, hdp_err ) ;
h_hdp_search_bins -> GetXaxis() -> SetBinLabel( bi_search_hist, label ) ;
printf( " search %3d : %30s : R= %6.4f +/- %6.4f\n", bi_search_hist, label, ratio_val, ratio_err ) ;
TH1F* hp_nb(0x0) ;
hp_nb = h_ratio_nb[bi_nb-1] ;
bi_nb_hist[bi_nb-1]++;
hp_nb -> SetBinContent( bi_nb_hist[bi_nb-1], ratio_val ) ;
hp_nb -> SetBinError( bi_nb_hist[bi_nb-1], ratio_err ) ;
hp_nb -> GetXaxis() -> SetBinLabel( bi_nb_hist[bi_nb-1], label ) ;
TH1F* hp_nj(0x0) ;
hp_nj = h_ratio_nj[bi_nj] ;
bi_nj_hist[bi_nj-1]++;
hp_nj -> SetBinContent( bi_nj_hist[bi_nj-1], ratio_val ) ;
hp_nj -> SetBinError ( bi_nj_hist[bi_nj-1], ratio_err ) ;
hp_nj -> GetXaxis() -> SetBinLabel( bi_nj_hist[bi_nj-1], label ) ;
} // not control bin.
} // bi_htmht
} // bi_nb
} // bi_nj
h_ratio -> GetXaxis() -> LabelsOption( "v" ) ;
h_ratio -> SetMarkerStyle(20) ;
h_max_ldp_weight_search_bins -> GetXaxis() -> LabelsOption( "v" ) ;
h_ldp_search_bins -> GetXaxis() -> LabelsOption( "v" ) ;
h_hdp_search_bins -> GetXaxis() -> LabelsOption( "v" ) ;
for ( int nb_count = 0; nb_count < nb_nb; nb_count++)
{
h_ratio_nb[nb_count] -> GetXaxis() -> LabelsOption( "v" ) ;
h_ratio_nb[nb_count] -> SetMarkerStyle(20) ;
}
for ( int nj_count = 1; nj_count <= nb_nj; nj_count++)
{
h_ratio_nj[nj_count] -> GetXaxis() -> LabelsOption( "v" ) ;
h_ratio_nj[nj_count] -> SetMarkerStyle(20) ;
}
h_ratio -> Draw() ;
gPad -> SetGridy(1) ;
saveHist("outputfiles/qcdmc-ratio-v3.root","h*") ;
} // draw_qcd_ratio_v3
void draw_syst_hists( const char* inwsfile, const char* syst_name, int sig_mass = 0, float max_msig_evts = 8., float max_msb_evts = 16. ) {
gStyle -> SetOptStat(0) ;
gStyle -> SetPadLeftMargin(0.15) ;
gStyle -> SetTitleW( 0.9 ) ;
gDirectory -> Delete( "h*" ) ;
loadHist( inwsfile ) ;
TLine* line = new TLine() ;
line -> SetLineStyle(2) ;
//----
gSystem -> Exec( "mkdir -p outputfiles/syst-plots" ) ;
TString infile_ts( inwsfile ) ;
TObjArray* tokens = infile_ts.Tokenize("/") ;
TObjString* tos = (TObjString*) (tokens -> At( tokens->GetEntries() - 1 ) ) ;
TString fname( tos->GetString() ) ;
printf( "ws file name : %s\n", fname.Data() ) ;
TString pdfbasename = fname.ReplaceAll(".root","") ;
printf(" pdf base name : %s\n", pdfbasename.Data() ) ;
char sigsb_str[2][10] = { "msig", "msb" } ;
for ( int ssbi=0; ssbi<2; ssbi++ ) {
char cname[100] ;
sprintf( cname, "can_evts_%s", sigsb_str[ssbi] ) ;
TCanvas* can_evts = (TCanvas*) gDirectory -> FindObject( cname ) ;
if ( can_evts == 0x0 ) {
if ( ssbi == 0 ) {
can_evts = new TCanvas( cname, "SIG observables", 1100, 300 ) ;
} else {
can_evts = new TCanvas( cname, "SB observables", 1100, 300 ) ;
}
}
sprintf( cname, "can_frac_%s", sigsb_str[ssbi] ) ;
TCanvas* can_frac = (TCanvas*) gDirectory -> FindObject( cname ) ;
if ( can_frac == 0x0 ) {
if ( ssbi == 0 ) {
can_frac = new TCanvas( cname, "SIG observables, syst (%)", 1100, 300 ) ;
} else {
can_frac = new TCanvas( cname, "SB observables, syst (%)", 1100, 300 ) ;
}
}
can_evts -> Clear() ;
can_evts -> Divide(4,1) ;
can_frac -> Clear() ;
can_frac -> Divide(4,1) ;
for ( int ci=1; ci<=4; ci++ ) {
char hname[1000] ;
char hnamev[1000] ;
char hnamenf[1000] ;
sprintf( hname, "h_syst_%s_%s_met%d_nom", syst_name, sigsb_str[ssbi], ci ) ;
TH1F* hist_nom = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hist_nom == 0x0 ) { printf("\n\n *** Can't find %s\n\n", hname ) ; return ; }
sprintf( hnamenf, "%s_nf", hname ) ;
TH1F* hist_nom_nf = (TH1F*) hist_nom -> Clone( hnamenf ) ;
sprintf( hname, "h_syst_%s_%s_met%d_m1s", syst_name, sigsb_str[ssbi], ci ) ;
TH1F* hist_m1s = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hist_m1s == 0x0 ) { printf("\n\n *** Can't find %s\n\n", hname ) ; return ; }
sprintf( hnamev, "%s_var", hname ) ;
TH1F* hist_m1s_var = (TH1F*) hist_m1s -> Clone( hnamev ) ;
sprintf( hname, "h_syst_%s_%s_met%d_p1s", syst_name, sigsb_str[ssbi], ci ) ;
TH1F* hist_p1s = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hist_p1s == 0x0 ) { printf("\n\n *** Can't find %s\n\n", hname ) ; return ; }
sprintf( hnamev, "%s_var", hname ) ;
TH1F* hist_p1s_var = (TH1F*) hist_p1s -> Clone( hnamev ) ;
TString htitle ;
htitle = hist_nom -> GetTitle() ;
if ( sig_mass > 0 ) {
char sigmassstr[1000] ;
sprintf( sigmassstr, ", higgsino mass = %d", sig_mass ) ;
htitle.ReplaceAll( ", nominal", sigmassstr ) ;
} else {
htitle.ReplaceAll( ", nominal", "" ) ;
}
hist_nom -> SetTitle( htitle ) ;
htitle = hist_m1s_var -> GetTitle() ;
if ( sig_mass > 0 ) {
char sigmassstr[1000] ;
sprintf( sigmassstr, ", higgsino mass = %d", sig_mass ) ;
htitle.ReplaceAll( ", -1 sigma", sigmassstr ) ;
} else {
htitle.ReplaceAll( ", -1 sigma", "" ) ;
}
hist_m1s_var -> SetTitle( htitle ) ;
hist_nom -> SetLineWidth( 2 ) ;
hist_nom_nf -> SetLineWidth( 2 ) ;
hist_m1s -> SetLineWidth( 2 ) ;
hist_p1s -> SetLineWidth( 2 ) ;
// hist_m1s -> SetLineColor( 4 ) ;
// hist_p1s -> SetLineColor( 2 ) ;
hist_m1s -> SetLineColor( 2 ) ;
hist_p1s -> SetLineColor( 4 ) ;
hist_nom -> SetFillColor( 18 ) ;
float max_evts(0.) ;
if ( ssbi == 0 ) {
max_evts = max_msig_evts ;
} else {
max_evts = max_msb_evts ;
}
float hmax(0.) ;
if ( max_evts < 0 ) {
if ( 1.2*(hist_nom->GetMaximum()) > hmax ) { hmax = 1.2*(hist_nom->GetMaximum()) ; }
if ( 1.2*(hist_m1s->GetMaximum()) > hmax ) { hmax = 1.2*(hist_m1s->GetMaximum()) ; }
if ( 1.2*(hist_p1s->GetMaximum()) > hmax ) { hmax = 1.2*(hist_p1s->GetMaximum()) ; }
} else {
hmax = max_evts ;
}
hist_nom -> SetMaximum( hmax ) ;
for ( int hbi=1; hbi <= hist_nom -> GetNbinsX(); hbi++ ) {
float nom_val, p1s_val, m1s_val ;
nom_val = hist_nom -> GetBinContent( hbi ) ;
p1s_val = hist_p1s -> GetBinContent( hbi ) ;
m1s_val = hist_m1s -> GetBinContent( hbi ) ;
hist_p1s_var -> SetBinContent( hbi, 0. ) ;
hist_m1s_var -> SetBinContent( hbi, 0. ) ;
if ( nom_val > 0 ) {
hist_p1s_var -> SetBinContent( hbi, (p1s_val - nom_val)/nom_val ) ;
hist_m1s_var -> SetBinContent( hbi, (m1s_val - nom_val)/nom_val ) ;
printf( " hbi=%d : p1s, nom, m1s : %.2f %.2f %.2f\n", hbi, p1s_val, nom_val, m1s_val ) ;
}
} // hbi
hist_m1s_var -> SetMinimum( -0.3 ) ;
hist_m1s_var -> SetMaximum( 0.3 ) ;
// hist_m1s_var -> SetLineColor( 4 ) ;
// hist_p1s_var -> SetLineColor( 2 ) ;
// hist_m1s_var -> SetLineWidth( 2 ) ;
// hist_p1s_var -> SetLineWidth( 2 ) ;
hist_m1s_var -> SetLineColor( 2 ) ;
hist_p1s_var -> SetLineColor( 4 ) ;
hist_m1s_var -> SetLineWidth( 2 ) ;
hist_p1s_var -> SetLineWidth( 2 ) ;
// hist_m1s_var -> SetFillColor( 4 ) ;
hist_m1s_var -> SetFillColor( 2 ) ;
hist_m1s_var -> SetFillStyle( 3354 ) ;
// hist_p1s_var -> SetFillColor( 2 ) ;
hist_p1s_var -> SetFillColor( 4 ) ;
hist_p1s_var -> SetFillStyle( 3345 ) ;
hist_nom -> SetTitleOffset( 1.5, "y" ) ;
hist_m1s_var -> SetTitleOffset( 1.5, "y" ) ;
hist_nom -> SetTitleSize( 0.05, "y" ) ;
hist_m1s_var -> SetTitleSize( 0.05, "y" ) ;
hist_nom -> SetLabelSize( 0.07, "x" ) ;
hist_m1s_var -> SetLabelSize( 0.07, "x" ) ;
hist_nom -> SetLabelSize( 0.05, "y" ) ;
hist_m1s_var -> SetLabelSize( 0.05, "y" ) ;
hist_nom -> SetLabelOffset( 0.01, "x" ) ;
hist_m1s_var -> SetLabelOffset( 0.01, "x" ) ;
hist_nom -> SetLabelOffset( 0.01, "y" ) ;
hist_m1s_var -> SetLabelOffset( 0.01, "y" ) ;
hist_nom -> SetYTitle( "Events at theory Xsec" ) ;
hist_m1s_var -> SetYTitle( "Systematic (var-nom)/nom" ) ;
can_evts -> cd( ci ) ;
hist_nom -> Draw() ;
hist_m1s -> Draw("same" ) ;
hist_p1s -> Draw("same" ) ;
hist_nom_nf -> Draw("same" ) ;
hist_nom -> Draw("same axis" ) ;
can_frac -> cd( ci ) ;
hist_m1s_var -> Draw( ) ;
hist_p1s_var -> Draw("same" ) ;
line -> DrawLine( hist_m1s_var->GetBinLowEdge(1), 0., hist_m1s_var->GetBinLowEdge( hist_nom -> GetNbinsX() + 1 ), 0. ) ;
} // ci
char pdfname[10000] ;
sprintf( pdfname, "outputfiles/syst-plots/%s-syst-%s-events-%s.pdf", pdfbasename.Data(), syst_name, sigsb_str[ssbi] ) ;
can_evts -> SaveAs( pdfname ) ;
sprintf( pdfname, "outputfiles/syst-plots/%s-syst-%s-frac-%s.pdf", pdfbasename.Data(), syst_name, sigsb_str[ssbi] ) ;
can_frac -> SaveAs( pdfname ) ;
} // ssbi.
} // draw_syst_hists
void draw_analysis_ratio_plots3( const char* infile = "outputfiles/cdtt_input.root", const char* save_file_base = "plot-dtt-analysis3" ) {
gDirectory -> Delete( "h*" ) ;
gStyle -> SetOptStat(0) ;
loadHist( infile ) ;
int wx(50), wy(50) ;
char cname[100] ;
char ctitle[100] ;
TCanvas* can ;
int ci ;
char savefile[10000] ;
//--- 3x3 Njet vs HT grid
sprintf( cname, "can_draw_analysis_ratio_plots" ) ;
sprintf( ctitle, "lost/found ratio vs W pT" ) ;
can = new TCanvas( cname, ctitle, 900, 900 ) ;
can -> Divide( 3, 3 ) ;
can -> SetWindowPosition( wx, wy ) ; wx += 50 ; wy += 20 ;
ci = 1 ;
for ( int hti=1; hti<4; hti++ ) {
for ( int nji=1; nji<4; nji++ ) {
can -> cd( ci++ ) ;
char hname[100] ;
sprintf( hname, "h_wpt_lostfound_ratio_nj%d_ht%d", nji, hti ) ;
TH1F* hp = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp == 0x0 ) { printf("\n\n *** Missing hist %s\n\n", hname ) ; return ; }
hp -> SetMarkerStyle(20) ;
hp -> SetMarkerSize(0.5) ;
do_plots( hp ) ;
} // wpti
} // hti
sprintf( savefile, "outputfiles/%s-lostfound-ratio.pdf", save_file_base ) ;
can -> SaveAs( savefile ) ;
//--- 3 Njet plots
sprintf( cname, "can_draw_analysis_ratio_plots_njet" ) ;
sprintf( ctitle, "lost/found ratio vs W pT, Njet bins" ) ;
can = new TCanvas( cname, ctitle, 1300, 600 ) ;
can -> Divide( 3, 1 ) ;
can -> SetWindowPosition( wx, wy ) ; wx += 50 ; wy += 20 ;
ci = 1 ;
for ( int nji=1; nji<4; nji++ ) {
can -> cd( ci++ ) ;
for ( int hti=1; hti<4; hti++ ) {
char hname[100] ;
sprintf( hname, "h_wpt_lostfound_ratio_nj%d_ht%d", nji, hti ) ;
TH1F* hp = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp == 0x0 ) { printf("\n\n *** Missing hist %s\n\n", hname ) ; return ; }
if ( hti==1 ) {
do_plots( hp ) ;
hp -> SetMarkerStyle(20) ;
hp -> SetMarkerSize(0.5) ;
hp -> Draw("same") ;
} else {
if ( hti==2) { hp -> SetLineColor(2) ; hp -> SetMarkerColor(2) ; hp -> SetMarkerStyle(21) ; hp -> SetMarkerSize(0.5) ; }
if ( hti==3) { hp -> SetLineColor(4) ; hp -> SetMarkerColor(4) ; hp -> SetMarkerStyle(22) ; hp -> SetMarkerSize(0.5) ; }
hp->Draw("same") ;
}
} // hti
} // nji
sprintf( savefile, "outputfiles/%s-lostfound-ratio-njet-bins.pdf", save_file_base ) ;
can -> SaveAs( savefile ) ;
//--- 3 HT plots
sprintf( cname, "can_draw_analysis_ratio_plots_ht" ) ;
sprintf( ctitle, "lost/found ratio vs W pT, HT bins" ) ;
can = new TCanvas( cname, ctitle, 1300, 600 ) ;
can -> Divide( 3, 1 ) ;
can -> SetWindowPosition( wx, wy ) ; wx += 50 ; wy += 20 ;
ci = 1 ;
for ( int hti=1; hti<4; hti++ ) {
can -> cd( ci++ ) ;
for ( int nji=1; nji<4; nji++ ) {
char hname[100] ;
sprintf( hname, "h_wpt_lostfound_ratio_nj%d_ht%d", nji, hti ) ;
TH1F* hp = (TH1F*) gDirectory -> FindObject( hname ) ;
if ( hp == 0x0 ) { printf("\n\n *** Missing hist %s\n\n", hname ) ; return ; }
if ( nji==1 ) {
hp -> SetMarkerStyle(20) ;
hp -> SetMarkerSize(0.5) ;
hp -> SetMarkerColor(1) ;
hp -> SetLineColor(1) ;
do_plots( hp ) ;
hp -> Draw("same") ;
} else {
if ( nji==2) { hp -> SetLineColor(2) ; hp -> SetMarkerColor(2) ; hp -> SetMarkerStyle(21) ; hp -> SetMarkerSize(0.5) ; }
if ( nji==3) { hp -> SetLineColor(4) ; hp -> SetMarkerColor(4) ; hp -> SetMarkerStyle(22) ; hp -> SetMarkerSize(0.5) ; }
hp->Draw("same") ;
}
} // nji
} // hti
sprintf( savefile, "outputfiles/%s-lostfound-ratio-ht-bins.pdf", save_file_base ) ;
can -> SaveAs( savefile ) ;
} // draw_analysis_ratio_plots3
void create_model_ratio_hist1( const char* model_pars_file = "outputfiles/model-pars-qcdmc3.txt",
const char* qcd_ratio_file = "outputfiles/qcdmc-ratio-v3.root" ) {
setup_bins();
gDirectory -> Delete( "h*" ) ;
loadHist( qcd_ratio_file, "qcdmc" ) ;
read_pars( model_pars_file ) ;
TH1F* h_ratio_all = new TH1F( "h_ratio_all", "QCD model H/L ratio", nb_global_after_exclusion, 0.5, nb_global_after_exclusion + 0.5 ) ;
TH1F* h_max_ldp_weight_search_bins = get_hist( "h_max_ldp_weight_search_bins_qcdmc" ) ;
TH1F* h_ldp_search_bins = get_hist( "h_ldp_search_bins_qcdmc" ) ;
TH1F* h_hdp_search_bins = get_hist( "h_hdp_search_bins_qcdmc" ) ;
TH1F* h_ratio_qcdmc = get_hist( "h_ratio_qcdmc" ) ;
int bi_hist_with_exclusion(0) ;
for ( int bi_nj=1; bi_nj<=nb_nj; bi_nj++ ) {
for ( int bi_nb=1; bi_nb<=nb_nb; bi_nb++ ) {
for ( int bi_htmht=4; bi_htmht<=nb_htmht; bi_htmht++ ) {
if ( is_this_bin_excluded(bi_nj-1, bi_nb-1, bi_htmht-1) ) continue;
bi_hist_with_exclusion++; // these few lines should be changed when we update the code that produces qcdmc-ratio-v3.root
int bi_ht, bi_mht ;
htmht_bin_to_ht_and_mht_bins( bi_htmht, bi_ht, bi_mht ) ;
char label[100] ;
sprintf( label, " %3d Nj%d-Nb%d-MHT%d-HT%d (%d)", bi_hist_with_exclusion, bi_nj, bi_nb-1, bi_mht-1, bi_ht, bi_htmht-3 ) ;
double model_ratio_val = 0;
double model_ratio_err = 0;
model_ratio_val = par_val_ht[bi_ht] * par_val_njet[bi_nj] * par_val_ht_mht[bi_ht][bi_mht] * par_val_nb[bi_nb] ;
model_ratio_err = model_ratio_val * sqrt(
pow( par_err_ht_fit[bi_ht]/par_val_ht[bi_ht], 2. )
+ pow( par_err_ht_syst[bi_ht]/par_val_ht[bi_ht], 2. )
+ pow( par_err_njet_fit[bi_nj]/par_val_njet[bi_nj], 2. )
+ pow( par_err_njet_syst[bi_nj]/par_val_njet[bi_nj], 2. )
+ pow( par_err_ht_mht[bi_ht][bi_mht]/par_val_ht_mht[bi_ht][bi_mht], 2. )
+ pow( par_err_nb[bi_nb]/par_val_nb[bi_nb], 2. )
) ;
printf(" %s : Nj %6.4f Nb %6.4f MHT %6.4f HT %6.4f model ratio = %6.4f +/- %6.4f\n", label,
par_val_njet[bi_nj], par_val_nb[bi_nb], par_val_ht_mht[bi_ht][bi_mht], par_val_ht[bi_ht], model_ratio_val, model_ratio_err ) ;
h_ratio_all -> GetXaxis() -> SetBinLabel( bi_hist_with_exclusion, label ) ;
h_ratio_all -> SetBinContent( bi_hist_with_exclusion, model_ratio_val ) ;
h_ratio_all -> SetBinError( bi_hist_with_exclusion, model_ratio_err ) ;
} // bi_htmht
} // bi_nb
} // bi_nj
gStyle -> SetOptStat(0) ;
gStyle -> SetPadBottomMargin(0.30) ;
h_ratio_all -> SetMarkerStyle( 22 ) ;
h_ratio_all -> SetMarkerColor( 2 ) ;
h_ratio_all -> GetXaxis() -> LabelsOption("v") ;
h_ratio_all -> Draw() ;
gPad -> SetGridy(1) ;
//---------------
TH1F* h_ratio_qcdmc_minus_model = new TH1F( "h_ratio_qcdmc_minus_model", "QCD H/L ratio difference (QCD MC - model)", nb_global_after_exclusion, 0.5, nb_global_after_exclusion + 0.5 ) ;
printf("\n\n") ;
bi_hist_with_exclusion = 0;
for ( int bi_nj=1; bi_nj<=nb_nj; bi_nj++ ) {
for ( int bi_nb=1; bi_nb<=nb_nb; bi_nb++ ) {
for ( int bi_htmht=4; bi_htmht<=nb_htmht; bi_htmht++ ) {
if ( is_this_bin_excluded(bi_nj-1, bi_nb-1, bi_htmht-1) ) continue;
bi_hist_with_exclusion++; // these few lines should be changed when we update the code that produces qcdmc-ratio-v3.root
float model_val = h_ratio_all -> GetBinContent( bi_hist_with_exclusion ) ;
float qcdmc_val = h_ratio_qcdmc -> GetBinContent( bi_hist_with_exclusion ) ;
float ldp_val = h_ldp_search_bins -> GetBinContent( bi_hist_with_exclusion ) ;
float hdp_val = h_hdp_search_bins -> GetBinContent( bi_hist_with_exclusion ) ;
float max_ldp_weight = h_max_ldp_weight_search_bins -> GetBinContent( bi_hist_with_exclusion ) ;
char label[100] ;
sprintf( label, "%s", h_ratio_all -> GetXaxis() -> GetBinLabel( bi_hist_with_exclusion ) ) ;
float diff_val(0.) ;
float diff_err(0.) ;
printf(" debug1 : model bin label = %s , qcdmc bin label = %s\n", h_ratio_all -> GetXaxis() -> GetBinLabel( bi_hist_with_exclusion ), h_ratio_qcdmc -> GetXaxis() -> GetBinLabel( bi_hist_with_exclusion ) ) ;
if ( hdp_val > 0 ) {
diff_val = qcdmc_val - model_val ;
std::cout << qcdmc_val << " " << model_val << " " << diff_val << std::endl;
diff_err = diff_val ;
printf(" %40s : LDP %7.1f HDP %7.1f max LDP weight %5.3f, diff err = %5.3f\n", label, ldp_val, hdp_val, max_ldp_weight, diff_err ) ;
} else {
diff_val = 0. ;
if ( ldp_val > 0 ) {
diff_err = max_ldp_weight / ldp_val ;
printf(" %40s : LDP %7.1f HDP %7.1f max LDP weight %5.3f, zero HDP H/L err = %5.3f\n", label, ldp_val, hdp_val, max_ldp_weight, diff_err ) ;
} else {
//diff_err = 0.5 ;
//diff_err = 0.2;
diff_err = 0.0;
printf(" %40s : LDP %7.1f HDP %7.1f max LDP weight %5.3f, *** both zero\n", label, ldp_val, hdp_val, max_ldp_weight ) ;
}
}
h_ratio_qcdmc_minus_model -> SetBinContent( bi_hist_with_exclusion, diff_val ) ;
h_ratio_qcdmc_minus_model -> SetBinError( bi_hist_with_exclusion, diff_err ) ;
h_ratio_qcdmc_minus_model -> GetXaxis() -> SetBinLabel( bi_hist_with_exclusion, label ) ;
} // bi_htmht
}//bi_nb
}//bi_nj
printf("\n\n") ;
h_ratio_qcdmc_minus_model -> GetXaxis() -> LabelsOption( "v" ) ;
saveHist("outputfiles/model-ratio-hist1.root", "h*" ) ;
} // create_model_ratio_hist1
int
main (int argc, char** argv)
{
int k = 6;
double thresh = DBL_MAX; // No threshold, disabled by default
if (argc < 2)
{
pcl::console::print_error
("Need at least three parameters! Syntax is: %s <query_vfh_model.pcd> [options] {kdtree.idx} {training_data.h5} {training_data.list}\n", argv[0]);
pcl::console::print_info (" where [options] are: -k = number of nearest neighbors to search for in the tree (default: ");
pcl::console::print_value ("%d", k); pcl::console::print_info (")\n");
pcl::console::print_info (" -thresh = maximum distance threshold for a model to be considered VALID (default: ");
pcl::console::print_value ("%f", thresh); pcl::console::print_info (")\n\n");
return (-1);
}
// this won't be needed for flann > 1.6.10
flann::ObjectFactory<flann::IndexParams, flann_algorithm_t>::instance().register_<flann::LinearIndexParams>(FLANN_INDEX_LINEAR);
std::string extension (".pcd");
transform (extension.begin (), extension.end (), extension.begin (), (int(*)(int))tolower);
// Load the test histogram
std::vector<int> pcd_indices = pcl::console::parse_file_extension_argument (argc, argv, ".pcd");
vfh_model histogram;
if (!loadHist (argv[pcd_indices.at (0)], histogram))
{
pcl::console::print_error ("Cannot load test file %s\n", argv[pcd_indices.at (0)]);
return (-1);
}
pcl::console::parse_argument (argc, argv, "-thresh", thresh);
// Search for the k closest matches
pcl::console::parse_argument (argc, argv, "-k", k);
pcl::console::print_highlight ("Using "); pcl::console::print_value ("%d", k); pcl::console::print_info (" nearest neighbors.\n");
std::string kdtree_idx_file_name = "kdtree.idx";
std::string training_data_h5_file_name = "training_data.h5";
std::string training_data_list_file_name = "training_data.list";
std::vector<vfh_model> models;
flann::Matrix<int> k_indices;
flann::Matrix<float> k_distances;
flann::Matrix<float> data;
// Check if the data has already been saved to disk
if (!boost::filesystem::exists ("training_data.h5") || !boost::filesystem::exists ("training_data.list"))
{
pcl::console::print_error ("Could not find training data models files %s and %s!\n",
training_data_h5_file_name.c_str (), training_data_list_file_name.c_str ());
return (-1);
}
else
{
loadFileList (models, training_data_list_file_name);
flann::load_from_file (data, training_data_h5_file_name, "training_data");
pcl::console::print_highlight ("Training data found. Loaded %d VFH models from %s/%s.\n",
(int)data.rows, training_data_h5_file_name.c_str (), training_data_list_file_name.c_str ());
}
// Check if the tree index has already been saved to disk
if (!boost::filesystem::exists (kdtree_idx_file_name))
{
pcl::console::print_error ("Could not find kd-tree index in file %s!", kdtree_idx_file_name.c_str ());
return (-1);
}
else
{
flann::Index<flann::ChiSquareDistance<float> > index (data, flann::SavedIndexParams ("kdtree.idx"));
index.buildIndex ();
nearestKSearch (index, histogram, k, k_indices, k_distances);
}
// Output the results on screen
pcl::console::print_highlight ("The closest %d neighbors for %s are:\n", k, argv[pcd_indices[0]]);
for (int i = 0; i < k; ++i)
pcl::console::print_info (" %d - %s (%d) with a distance of: %f\n",
i, models.at (k_indices[0][i]).first.c_str (), k_indices[0][i], k_distances[0][i]);
// Load the results
pcl::visualization::PCLVisualizer p (argc, argv, "VFH Cluster Classifier");
int y_s = (int)floor (sqrt ((double)k));
int x_s = y_s + (int)ceil ((k / (double)y_s) - y_s);
double x_step = (double)(1 / (double)x_s);
double y_step = (double)(1 / (double)y_s);
pcl::console::print_highlight ("Preparing to load ");
pcl::console::print_value ("%d", k);
pcl::console::print_info (" files (");
pcl::console::print_value ("%d", x_s);
pcl::console::print_info ("x");
pcl::console::print_value ("%d", y_s);
pcl::console::print_info (" / ");
pcl::console::print_value ("%f", x_step);
pcl::console::print_info ("x");
pcl::console::print_value ("%f", y_step);
pcl::console::print_info (")\n");
int viewport = 0, l = 0, m = 0;
for (int i = 0; i < k; ++i)
{
std::string cloud_name = models.at (k_indices[0][i]).first;
boost::replace_last (cloud_name, "_vfh", "");
p.createViewPort (l * x_step, m * y_step, (l + 1) * x_step, (m + 1) * y_step, viewport);
l++;
if (l >= x_s)
{
l = 0;
m++;
}
sensor_msgs::PointCloud2 cloud;
pcl::console::print_highlight (stderr, "Loading "); pcl::console::print_value (stderr, "%s ", cloud_name.c_str ());
if (pcl::io::loadPCDFile (cloud_name, cloud) == -1)
break;
// Convert from blob to PointCloud
pcl::PointCloud<pcl::PointXYZ> cloud_xyz;
pcl::fromROSMsg (cloud, cloud_xyz);
if (cloud_xyz.points.size () == 0)
break;
pcl::console::print_info ("[done, ");
pcl::console::print_value ("%d", (int)cloud_xyz.points.size ());
pcl::console::print_info (" points]\n");
pcl::console::print_info ("Available dimensions: ");
pcl::console::print_value ("%s\n", pcl::getFieldsList (cloud).c_str ());
// Demean the cloud
Eigen::Vector4f centroid;
pcl::compute3DCentroid (cloud_xyz, centroid);
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_xyz_demean (new pcl::PointCloud<pcl::PointXYZ>);
pcl::demeanPointCloud<pcl::PointXYZ> (cloud_xyz, centroid, *cloud_xyz_demean);
// Add to renderer*
p.addPointCloud (cloud_xyz_demean, cloud_name, viewport);
// Check if the model found is within our inlier tolerance
std::stringstream ss;
ss << k_distances[0][i];
if (k_distances[0][i] > thresh)
{
p.addText (ss.str (), 20, 30, 1, 0, 0, ss.str (), viewport); // display the text with red
// Create a red line
pcl::PointXYZ min_p, max_p;
pcl::getMinMax3D (*cloud_xyz_demean, min_p, max_p);
std::stringstream line_name;
line_name << "line_" << i;
p.addLine (min_p, max_p, 1, 0, 0, line_name.str (), viewport);
p.setShapeRenderingProperties (pcl::visualization::PCL_VISUALIZER_LINE_WIDTH, 5, line_name.str (), viewport);
}
else
p.addText (ss.str (), 20, 30, 0, 1, 0, ss.str (), viewport);
// Increase the font size for the score*
p.setShapeRenderingProperties (pcl::visualization::PCL_VISUALIZER_FONT_SIZE, 18, ss.str (), viewport);
// Add the cluster name
p.addText (cloud_name, 20, 10, cloud_name, viewport);
}
// Add coordianate systems to all viewports
p.addCoordinateSystem (0.1, 0);
p.spin ();
return (0);
}
