void ProcEvent(Int_t event, Int_t px, Int_t py, TObject *sel)
{
// print event type and current cursor position
TCanvas *c = (TCanvas *) gTQSender;
TPad *pad = (TPad *) c->GetSelectedPad();
if(!pad) return;
gROOT->SetEditHistograms(kFALSE);
//printf("event=%d, px=%d, py=%d\n", event, px, py);
//Float_t x = pad->AbsPixeltoX(px);
//Float_t y = pad->AbsPixeltoY(py);
//x = pad->PadtoX(x);
//y = pad->PadtoY(y);
//printf("x=%.3g, y=%.3g\n",x,y);
if(event==kButton1Double){
pad->Pop();
//printf("%s %d\n",pad->GetName(),pad->GetNumber());
pad->cd();
TCanvas *c_blow;
TIter next(pad->GetListOfPrimitives());
if((TCanvas*)gROOT->GetListOfCanvases()->FindObject("c_blow")){
c_blow=(TCanvas*)gROOT->GetListOfCanvases()->FindObject("c_blow");
c_blow->Clear();
//printf("show %d\n",c_blow->GetUniqueID());
//c_blow->GetCanvasImp()->Show();
//c_blow->RaiseWindow();
//c_blow->GetCanvasImp()->RaiseWindow();
//c_blow->Flush();
//gVirtualX->RaiseWindow(c_blow->GetUniqueID());
//c_blow->Show();
}
else{
// c_blow = new TCanvas("c_blow","blowup",750,0,743,525);
c_blow = new TCanvas("c_blow","blowup",100,50,600,600);
c_blow->SetFillColor(10); //white
//c_blow->ToggleEventStatus();
//c_blow->SetCrosshair();
c_blow->Draw();
}
c_blow->cd();
gROOT->SetSelectedPad((TPad*)c_blow);
TPad *clone =(TPad*)pad->Clone();
clone->SetPad(0,0,1,1);
clone->Draw();
clone->Modified();
clone->Update();
c_blow->Show();
}
}
void tnail(){
TPad *sel = (TPad*)gPad->GetSelectedPad();
int px = gPad->GetEventX();
int py = gPad->GetEventY();
if (sel && sel != c && sel != ct) {
ct->cd();
TPad *newpad = (TPad*)sel->Clone();
ct->GetListOfPrimitives()->Add(newpad);
newpad->SetPad(0,0,1,1);
selold_tnail = newpad;
ct->Update();
ct->cd();
}
}
/**
* Draw the Poisson estimate of the occupancy in a given ring.
*
* @param p List
* @param d Detector
* @param r Ring
*
* @return The occupancy (in percent)
*
* @deprecated Use QATrender instead
* @ingroup pwglf_forward_scripts_qa
*/
Double_t
DrawRingOccupancy(TList* p, UShort_t d, Char_t r)
{
if (!p) return 0;
TList* ring = static_cast<TList*>(p->FindObject(Form("FMD%d%c",d,r)));
if (!ring) {
Error("DrawOccupancy", "List FMD%d%c not found in %s",d,r,p->GetName());
return 0;
}
TH1* corr = static_cast<TH1*>(ring->FindObject("occupancy"));
if (!corr) {
Error("DrawRingOccupancy", "Histogram occupancy not found in FMD%d%c",
d, r);
return 0;
}
corr->Rebin(4);
TPad* pad = static_cast<TPad*>(gPad);
pad->SetGridy();
pad->SetGridx();
pad->SetLogy();
pad->SetFillColor(0);
pad->SetRightMargin(0.01);
#if 0
if (d == 3) {
pad->SetPad(pad->GetXlowNDC(), pad->GetYlowNDC(), .99,
pad->GetYlowNDC()+pad->GetHNDC());
pad->SetRightMargin(0.15);
}
#endif
corr->Draw("hist");
TLatex* ltx = new TLatex(.95, .95, Form("FMD%d%c", d, r));
ltx->SetNDC();
ltx->SetTextAlign(33);
ltx->SetTextSize(.08);
ltx->Draw();
return corr->GetMean();
}
//------------------------------------------------------------------------------
void PlotAlignmentValidation::plotOutlierModules(const char *outputFileName, std::string plotVariable,
float plotVariable_cut ,int unsigned minHits)
{
Int_t counter=0;
setNiceStyle();
gStyle->SetOptStat(111111);
gStyle->SetStatY(0.9);
//TList treelist=getTreeList();
TCanvas *c1 = new TCanvas("canv", "canv", 800, 500);
//setCanvasStyle( *c1 );
outputFile = outputDir +'/'+ outputFileName;
c1->Print( (outputFile+'[').Data() );
c1->Divide(2,1);
TTree *tree= (*sourceList.begin())->getTree();
TkOffTreeVariables *treeMem = 0; // ROOT will initilise
tree->SetBranchAddress("TkOffTreeVariables", &treeMem);
Long64_t nentries = tree->GetEntriesFast();
for (Long64_t i = 0; i < nentries; i++){
tree->GetEntry(i);
float var = 0;
if (plotVariable == "chi2PerDofX") var =treeMem->chi2PerDofX;
else if(plotVariable == "chi2PerDofY") var =treeMem->chi2PerDofY;
else if(plotVariable == "fitMeanX") var =treeMem->fitMeanX;
else if(plotVariable == "fitMeanY") var =treeMem->fitMeanY;
else if(plotVariable == "fitSigmaX") var =treeMem->fitSigmaX;
else if(plotVariable == "fitSigmaY") var =treeMem->fitSigmaY;
else {
cout<<"There is no variable "<<plotVariable<<" included in the tree."<<endl;
break;
}
// cout<<"treeMem->entries "<<treeMem->entries<<endl;
// cout<<"var "<<var<<endl;
// cout<<"plotVariable_cut "<<plotVariable_cut<<endl;
if (var > plotVariable_cut && treeMem->entries > minHits)
{
TFile *f=(*sourceList.begin())->getFile();//(TFile*)sourcelist->First();
if(f->FindKeyAny(treeMem->histNameX.c_str())!=0){
TH1 *h = (TH1*) f->FindKeyAny(treeMem->histNameX.c_str())->ReadObj();//f->FindObjectAny(treeMem->histNameX.c_str());
gStyle->SetOptFit(0111);
cout<<"hist name "<<h->GetName()<<endl;
TString path =(char*)strstr( gDirectory->GetPath(), "TrackerOfflineValidation" );
//cout<<"hist path "<<path<<endl;
//cout<<"wrote text "<<endl;
if(h) cout<<h->GetEntries()<<endl;
//modules' location as title
c1->cd(0);
TPaveText * text=new TPaveText(0,0.95,0.99,0.99);
text->AddText(path);
text->SetFillColor(0);
text->SetShadowColor(0);
text->SetBorderSize( 0 );
text->Draw();
//residual histogram
c1->cd(1);
TPad *subpad = (TPad*)c1->GetPad(1);
subpad->SetPad(0,0,0.5,0.94);
h->Draw();
//norm. residual histogram
h = (TH1*) f->FindObjectAny(treeMem->histNameNormX.c_str());
if(h) cout<<h->GetEntries()<<endl;
c1->cd(2);
TPad *subpad2 = (TPad*)c1->GetPad(2);
subpad2->SetPad(0.5,0,0.99,0.94);
h->Draw();
c1->Print(outputFile);
counter++;
}
else{
cout<<"There are no residual histograms on module level stored!"<<endl;
cout<<"Please make sure that moduleLevelHistsTransient = cms.bool(False) in the validation job!"<<endl;
break;
}
}
}
c1->Print( (outputFile+"]").Data() );
if (counter == 0) cout<<"no bad modules found"<<endl;
//read the number of entries in the t3
//TTree* tree=0;
//tree=(TTree*)treeList->At(0);
//c1->Close();
}
void RooFitMacro()
{
gROOT->Reset();
gSystem->Load("libRooFit");
gROOT->LoadMacro("RooCMSShape.cc+");
//gStyle->SetOptStat(111111);
//gROOT->ProcessLine(".x ~/rootlogon.C");
TFile f("TagAndProbeResults_Marco.root");
TH1F * Z_mass = new TH1F("Z","Z" , 200, 0, 200);
//TH1D *results = new TH1D("results", "results", 200, 0, 200);
//results->Sumw2();
// We need to include NJetCut because there is depedence w.r.t. jet multiplicity
Z_mass = (TH1F*)f.Get("Zmass_Inclusive_NoElectronVeto_Numerator;1");
//Z_mass = (TH1F*)f.Get("Zmass_Inclusive_NoElectronVeto_Denominator;1");
//float bincontent = Z_mass->GetBinContent(60);
//cout << "60.bin content : " << bincontent << endl;
double hmin = 60;
double hmax = 120;
double r = .25;
double sl = 1. / ( 1. - r );
// Declare observable x
RooRealVar x("x","x",hmin,hmax) ;
RooDataHist dh("dh","dh",x,Import(*Z_mass)) ;
// Breit-Wigner Lineshape
// Parameters for Breit-Wigner Distribution
RooRealVar M("M_{Z^{0}}", "Z0 Resonance Mass", 91.18, 85.0, 95.0, "GeV/c^{2}");
RooRealVar gamma("#Gamma", "#Gamma", 2.4952, 2.0, 3.0, "GeV/c^{2}");
M.setConstant();
//gamma.setConstant();
RooBreitWigner bw("bw", "A Breit-Wigner Distribution", x, M, gamma);
// Mass resolution model - Crystal Ball Lineshape
// Parameters for Crystal Ball Lineshape
RooRealVar M_CB("#Delta m_{0}", "Bias", -2.0, -10.0, 10.0, "GeV/c^{2}");
RooRealVar sigma("#sigma_{CB}", "Width", 1.6, 0.1, 15.0, "GeV/c^{2}");
// RooRealVar sigma("#sigma_{CB}", "Width", 2.5, 0.1, 15.0, "GeV/c^{2}");
RooRealVar alpha("#alpha", "Cut", 1.5, 0.1, 15.0);
RooRealVar n("n", "Power", 1.8, 0.5, 5.0);
RooCBShape cb("resCBF", "A Crystal Ball Lineshape", x, M_CB, sigma, alpha, n);
// background p.d.f
RooRealVar cms_alpha("alpha", "alpha", 60, 50, 70);
RooRealVar cms_beta("beta", "beta", 0.01, 0.001, 0.05);
RooRealVar cms_gamma("gamma", "gamma", 0.05, 0.005, 0.5);
RooRealVar peak("peak", "peak", 60, 50, 70);
RooCMSShape bag("bag", "RooCMSShape", x, cms_alpha, cms_beta, cms_gamma, peak);
RooRealVar frac("frac", "f", 0.01, 0, 1.0);
RooFFTConvPdf signal("signal", "Convolution", x, bw, cb);
RooRealVar signal_yield("signal_yield", "signal_yield", 100, 0, Z_mass->Integral());
RooRealVar bag_yield("bag_yield", "bag_yield", 0, 0, Z_mass->Integral());
RooArgList shapes;
RooArgList yields;
shapes.add(signal);
shapes.add(bag);
yields.add(signal_yield);
yields.add(bag_yield);
RooRealVar fsig("fsig", "fsig", 0, 0, 1.);
//RooAddPdf model("model","model",shapes,yields);
// model = fsig x signal + (1-fsig) x bag
RooAddPdf model("model","model",shapes,fsig,kTRUE);
// Signal p.d.f.
//RooFFTConvPdf sum("sum", "Convolution", x, bw, cb);
//RooAddPdf sum("sum","sum",bw,cb,frac);
//RooAddPdf model("model","model",RooArgList(sum, bag),frac);
//RooFFTConvPdf model("model","model",x,sum,bag);
//RooFitResult* filters = sum.fitTo(dh,Range(0,200),"qr");
//filters->Print("v");
//RooFitResult* filters = model.fitTo(dh,Range(0,200),"qr");
RooFitResult* filters = model.fitTo(dh, RooFit::Minimizer("Minuit", "migradimproved"), RooFit::NumCPU(4), RooFit::Save(true), RooFit::Extended(false), RooFit::PrintLevel(-1));
//RooFitResult* filters = model.fitTo(dh, RooFit::Extended(true), RooFit::PrintLevel(-1));
//RooFitResult* filters = model.fitTo(dh, "mhe");
//RooFitResult* filters = cb.fitTo(dh,Range(0,200),"qr");
//RooFitResult* filters = bw.fitTo(dh,Range(0,100),"qr");
//RooFitResult* filters = bag.fitTo(dh,"qr");
TCanvas* canvas = new TCanvas("ZmassHisto","ZmassHisto",0, 0, 1000,700) ;
canvas->cd() ; //gPad->SetLeftMargin(0.15);
//gPad->SetLogy();
RooPlot* frame = x.frame(Title("e #gamma invariant mass fit")) ;
dh.plotOn(frame,MarkerSize(0.5),Name("data_hist")); //this will show histogram data points on canvas
dh.statOn(frame,Layout(0.15,0.37,0.85),What("N")) ;
//dh.statOn(frame); //this will display hist stat on canvas
//sum.plotOn(frame,LineColor(4));//this will show fit overlay on canvas
//sum.paramOn(frame); //this will display the fit parameters on canvas
//bag.plotOn(frame,LineColor(2));//this will show fit overlay on canvas
//bag.paramOn(frame); //this will display the fit parameters on canvas
model.plotOn(frame,Components(bag),LineColor(2));//this will show fit overlay on canvas
model.plotOn(frame,Components(signal),LineColor(3));//this will show fit overlay on canvas
model.plotOn(frame,LineColor(kBlue),Name("main_curve"));//this will show fit overlay on canvas
// model.paramOn(frame); //this will display the fit parameters on canvas
model.paramOn(frame, Layout(0.6, 0.95, 0.92)); //this will display the fit parameters on canvas
//model.paramOn(frame, Layout(0.6, 0.99, 0.75));
// model.plotOn(frame,LineColor(4));//this will show fit overlay on canvas
// model.paramOn(frame); //this will display the fit parameters on canvas
RooHist* histogram = frame->getHist("data_hist");
RooCurve* curve = frame->getCurve("main_curve");
TH1D* hresidual = residualHist(histogram,curve);
hresidual->Sumw2();
canvas->Divide( 1, 2, .1, .1 );
TPad* padHisto = (TPad*) canvas->cd(1);
TPad* padResid = (TPad*) canvas->cd(2);
double small = 0.1;
padHisto->SetPad( 0., r , 1., 1. );
padHisto->SetBottomMargin( small );
padResid->SetPad( 0., 0., 1., r );
padResid->SetBottomMargin( 0.3 );
padResid->SetTopMargin ( small );
padHisto->cd();
//float fitvalue = frame.GetX()[60];
//Double_t nX = x.getVal();
//cout << "nX : " << nX << endl;
//results->SetBinContent(results->GetXaxis()->FindBin(60), nX);
//float fitvalue = results->GetBinContent(59);
//cout << "59.5daki fit value : " << fitvalue << endl;
//cb.plotOn(frame,LineColor(2));//this will show fit overlay on canvas
//cb.paramOn(frame); //this will display the fit parameters on canvas
//bw.plotOn(frame,LineColor(4));//this will show fit overlay on canvas
//bw.paramOn(frame); //this will display the fit parameters on canvas
//gPad->SetLogy();
cout << "chisquare : " << frame->chiSquare() << endl ;
//cout << "Total Number of events: " << Z_mass->Integral() << endl;
//cout << "Number of signal events: " << fsig.getVal() * Z_mass->Integral() << endl;
//cout << "Number of background events: " << (1 - fsig.getVal()) * Z_mass->Integral() << endl;
//Draw all frames on a canvas
//TPaveLabel *label1 = new TPaveLabel(1,500,15,700,"Chisquare:");
frame->GetXaxis()->SetTitle("Invariant mass w/ NoElectronVeto photon (in GeV/c^{2})");
//frame->GetXaxis()->SetTitle("Invariant mass w/ TIGHT photon (in GeV/c^{2})");
//frame->GetXaxis()->SetTitleOffset(1.2);
frame->Draw();
//float binsize = Z_mass->GetBinWidth(1);
//char Bsize[50];
//sprintf(Bsize,"Events per %2.2f",binsize);
//frame->GetYaxis()->SetTitle(Bsize);
//frame->GetYaxis()->SetTitleOffset(1.2);
//results->Sumw2();
padResid->cd();
hresidual->Draw();
Lines( hresidual );
hresidual->Draw( "SAME" );
//frame->Draw();
//results->Draw();
//canvas->Update();
//title->Draw("same");
//hresidual->Draw();
canvas->SaveAs("pdf_TagAndProbe/ResidualNumerator_binned_negligible_errorfit.pdf");
//canvas->SaveAs("pdf_TagAndProbe/ResidualDenominator_binned_negligible_errorfit.pdf");
}
// Make main selection plots
// n-1, control type plots and plots after all cuts
void makePlot(const TString & histoName, TFile * outputFile, TString anaType,
const TString & xTitle, const double & xMin, const double & xMax,
const double & yMin = 0., const double & yMax = 0., bool logY=false,
const float lumi = 0, const bool plotData=false, bool drawRatioPlot=false )
{
std::cout << "----> Making plots for : " << histoName.Data() << std::endl;
std::cout << "Plotting data ? " << plotData << std::endl;
TH1::SetDefaultSumw2();
gStyle->SetOptStat(0);
gStyle->SetOptTitle(0);
// Keep track of integrals of background & data
double totalBkgMCIntegral = 0;
// double totalDataIntegral = 0;
//
// DATA
//
TH1F * histoData=0;
if (plotData) {
TFile * inputFile= new TFile ("CombinedFiles/Data_combined_"+anaType+".root", "READ");
histoData = (TH1F*)inputFile->Get(histoName);
// totalDataIntegral = histoData->Integral();
histoData->SetStats(0);
histoData->SetMarkerStyle(21);
histoData->SetMarkerSize(1);
}
//
// SIGNAL MC
//
// Not good at the moment - just taking one or two examples to plot and hard coded the names of the files here
TFile * signalInputFile1= new TFile (signal1+anaType+".root", "READ");
TH1F * histoSignal1 = (TH1F*)signalInputFile1->Get(histoName);
histoSignal1->SetStats(0);
histoSignal1->Scale(lumi);
TFile * signalInputFile2= new TFile (signal2+anaType+".root", "READ");
TH1F * histoSignal2 = (TH1F*)signalInputFile2->Get(histoName);
histoSignal2->SetStats(0);
histoSignal2->Scale(lumi);
int minIntegral=0;
int maxIntegral=histoSignal1->GetNbinsX();
// if ( histoName=="nMinus1_isolationLeptonH_removedLifetimeCuts" || histoName=="nMinus1_relIsolationLeptonH_removedLifetimeCuts" ) {
// // std::cout << find90Cut( histoSignal1 ) << std::endl;
// // std::cout << find90Cut( histoSignal2 ) << std::endl;
//
// minIntegral=histoSignal1->FindBin( find90Cut(histoSignal1) );
//
// // Check integral below specific cut
// if ( histoName=="nMinus1_relIsolationLeptonH_removedLifetimeCuts" ) {
// std::cout << "Signal 1" << std::endl;
// std::cout << "Efficiency with rel iso cut at 0.1 : " << histoSignal1->Integral( 1, histoSignal1->FindBin(0.1) ) / histoSignal1->Integral() << std::endl;
// std::cout << "Efficiency with rel iso cut at 0.05 : " << histoSignal1->Integral( 1, histoSignal1->FindBin(0.05) ) / histoSignal1->Integral() << std::endl;
// std::cout << "Signal 2" << std::endl;
// std::cout << "Efficiency with rel iso cut at 0.1 : " << histoSignal2->Integral( 1, histoSignal2->FindBin(0.1) ) / histoSignal2->Integral() << std::endl;
// std::cout << "Efficiency with rel iso cut at 0.05 : " << histoSignal2->Integral( 1, histoSignal2->FindBin(0.05) ) / histoSignal2->Integral() << std::endl;
// }
// }
TFile * signalInputFile3= new TFile (signal3+anaType+".root", "READ");
TH1F * histoSignal3 = (TH1F*)signalInputFile3->Get(histoName);
histoSignal3->SetStats(0);
histoSignal3->Scale(lumi);
//
// BACKGROUND MC
//
THStack stack("Background MC","");
setPlotTitle(stack, lumi);
// Add all different background MC to this stack
TLegend *legend= new TLegend(0.5,0.6,0.85,0.85);
totalBkgMCIntegral = addBackgroundHistos(anaType, histoName, stack, legend, lumi, minIntegral, maxIntegral);
// if ( histoName=="nMinus1_isolationLeptonH_removedLifetimeCuts" || histoName=="nMinus1_relIsolationLeptonH_removedLifetimeCuts" ) {
// std::cout << "Integral of background between " << minIntegral << " and " << maxIntegral << " : " << totalBkgMCIntegral << std::endl;
// }
// Output histograms to file
outputFile->cd();
// Setup canvas
TCanvas canvas(histoName);
canvas.cd();
// Draw one or two pads
TPad * up = new TPad("u","u",0.01,0.25,0.99,0.99);
up->SetNumber(1);
up->Draw();
TPad * dp = new TPad("d","d",0.01,0.01,0.99,0.25);
if ( drawRatioPlot ) {
dp->SetNumber(2);
dp->UseCurrentStyle();
dp->Draw();
}
else {
up->SetPad(0.01,0.01,0.99,0.99);
up->Draw();
}
if ( logY ) up->SetLogy();
canvas.Draw();
canvas.cd(1);
up->cd();
canvas.SetFillColor(kWhite);
canvas.SetBorderMode(0);
// Draw background MC
// There may be zero entries, which will mess up drawing options
// Not a good fix at the moment
bool axesExist=false;
if (totalBkgMCIntegral>0) {
axesExist=true;
stack.Draw("HISTE");
stack.GetXaxis()->SetRangeUser(xMin, xMax);
stack.SetMaximum(yMax);
stack.SetMinimum(yMin);
stack.GetXaxis()->SetTitle(xTitle);
stack.GetYaxis()->SetTitle("Entries");
}
std::cout << "Drawing signal histos" << std::endl;
// Draw signal MC
histoSignal1->SetLineStyle(2);
histoSignal1->SetLineColor(kMagenta+2);
histoSignal1->SetLineWidth(2);
if(axesExist) histoSignal1->Draw("same,HIST");
else histoSignal1->Draw("HIST");
histoSignal2->SetLineStyle(2);
histoSignal2->SetLineColor(kGreen+2);
histoSignal2->SetLineWidth(2);
if(axesExist) histoSignal2->Draw("same,HIST");
else histoSignal2->Draw("HIST");
// histoSignal3->SetLineStyle(2);
// histoSignal3->SetLineColor(4);
// histoSignal3->SetLineWidth(2);
// histoSignal3->Draw("same,HIST");
// Draw data
if ( plotData ) {
if (axesExist) histoData->Draw("same,P,E,X0");
else histoData->Draw("P,E,X0");
}
// Draw legend
legend->SetBorderSize(0);
legend->SetFillStyle(0);
if ( plotData ) legend->AddEntry(histoData,"data","p");
legend->AddEntry(histoSignal1,"m_{H}=1000 GeV/c^{2} m_{X}=350 GeV/c^{2}","l");
legend->AddEntry(histoSignal2,"m_{H}=400 GeV/c^{2} m_{X}=50 GeV/c^{2}","l");
// legend->AddEntry(histoSignal3,"m_{squark}=350 GeV/c^{2} m_{#Chi}=148 GeV/c^{2}","l");
legend->Draw();
canvas.Update();
// Draw mc/data ratio
if ( drawRatioPlot ) {
dp->cd();
TH1F ratioHist( drawMCDataRatio( ((TH1*)stack.GetStack()->Last()), histoData ) );
// Check content of ratioHist
ratioHist.GetXaxis()->SetRangeUser(xMin, xMax);
ratioHist.SetMarkerStyle(20);
ratioHist.GetYaxis()->SetNdivisions(5,0,0);
ratioHist.GetYaxis()->SetTickLength(0.01);
dp->SetGridy();
ratioHist.Draw("P");
canvas.Update();
canvas.Write();
}
else canvas.Write();
// Draw systematic errors for reco PV plot
// FIXME For some reason, old canvas can't handle this!
if ( histoName=="nRecoPV" ) {
TGraphAsymmErrors gr( makePUPlot( stack, anaType, lumi ) );
// Move back to output file (as other files have been opened and closed in makePUPlot
outputFile->cd();
gr.SetFillColor(1);
gr.SetFillStyle(3001);
gr.Draw("2P0");
canvas.Update();
// Test
TCanvas can("puSystematic");
can.cd();
// can.SetLogy();
can.Draw();
gr.SetTitle("TGraphAsymmErrors Example");
stack.Draw("HISTE");
gr.Draw("2P0");
histoData->Draw("P,E,X0SAME");
legend->Draw();
can.Update();
can.Write();
}
}