void PlotAlignmentValidation::
setDMRHistStyleAndLegend(TH1F* h, PlotAlignmentValidation::DMRPlotInfo& plotinfo, int direction, int layer)
{
std::pair<float,float> fitResults(9999., 9999.);
h->SetDirectory(0);
// The whole DMR plot is plotted with wider line than the split plots
// If only split plots are plotted, they will be stronger too, though
h->SetLineWidth((direction == 0 || (plotinfo.plotSplits && !plotinfo.plotPlain)) ? 2 : 1);
// These lines determine the style of the plots according to rules:
// -If the plot is for direction != 0, +1 or +2 is added to the given style for distinction
// -However if only direction split plots are to be plotted, the additions should be 0 and +1 respectively
// -Modulo 4 arithmetic, because the styles run from 1..4
int linestyle = plotinfo.vars->getLineStyle() - 1, linestyleplus = 0;
if (direction == 1) { linestyleplus = 1; }
if (direction == -1) { linestyleplus = 2; }
if (direction != 0 && plotinfo.plotSplits && !plotinfo.plotPlain) { linestyleplus--; }
linestyle = (linestyle + linestyleplus) % 4 + 1;
int linecolor = plotinfo.vars->getLineColor();
if (plotinfo.plotLayers && layer > 0) { linecolor += layer - 1; }
if (plotinfo.firsthisto) {
setHistStyle(*h, plotinfo.variable.c_str(), "#modules", 1); //set color later
plotinfo.firsthisto = false;
}
h->SetLineColor( linecolor );
h->SetLineStyle( linestyle );
if (plotinfo.maxY<h->GetMaximum()){
plotinfo.maxY=h->GetMaximum();
}
//fit histogram for median and mean
if (plotinfo.variable == "medianX" || plotinfo.variable == "meanX") {
fitResults = fitGauss(h, linecolor );
}
plotinfo.hstack->Add(h);
std::ostringstream legend;
legend.precision(2);
// Legend: header part
if (direction == -1 && plotinfo.subDetId != 2) { legend << "rDirection < 0: "; }
else if (direction == 1 && plotinfo.subDetId != 2) { legend << "rDirection > 0: "; }
else if (direction == -1 && plotinfo.subDetId == 2) { legend << "zDirection < 0: "; }
else if (direction == 1 && plotinfo.subDetId == 2) { legend << "zDirection > 0: "; }
else {
legend << plotinfo.vars->getName();
if (layer > 0) {
legend << ", layer " << layer << "";
}
legend << ":";
}
// Legend: Statistics
if (plotinfo.variable == "medianX" || plotinfo.variable == "meanX" ||
plotinfo.variable == "medianY" || plotinfo.variable == "meanY") {
if (useFit_) {
legend << "#mu = " << fitResults.first << " #mum, #sigma = " << fitResults.second << " #mum";
} else {
legend << "#mu = " << h->GetMean(1)*10000 << " #mum, rms = " << h->GetRMS(1)*10000 << " #mum";
}
} else if (plotinfo.variable == "rmsX" || plotinfo.variable == "rmsY") {
legend << "#mu = " << h->GetMean(1)*10000 << " #mum, rms = " << h->GetRMS(1)*10000 << " #mum";
} else if (plotinfo.variable == "meanNormX" || plotinfo.variable == "meanNormY" ||
plotinfo.variable == "rmsNormX" || plotinfo.variable == "rmsNormY") {
legend << "#mu = " << h->GetMean(1) << ", rms = " << h->GetRMS(1);
}
// Legend: Delta mu for split plots
if (plotinfo.h1 != 0 && plotinfo.h2 != 0 && plotinfo.plotSplits &&
plotinfo.plotPlain && direction == 0) {
std::string unit = " #mum";
float factor = 10000.0f;
if (plotinfo.variable == "meanNormX" || plotinfo.variable == "meanNormY" ||
plotinfo.variable == "rmsNormX" || plotinfo.variable == "rmsNormY") {
factor = 1.0f;
unit = "";
}
float deltamu = factor*(plotinfo.h2->GetMean(1) - plotinfo.h1->GetMean(1));
legend << ", #Delta#mu = " << deltamu << unit;
}
plotinfo.legend->AddEntry(h, legend.str().c_str(), "l");
}
void PlotAlignmentValidation::plotDMR(const std::string variable, Int_t minHits )
{
setNiceStyle();
gStyle->SetOptStat(0);
// TList treeList=getTreeList();
TCanvas *c = new TCanvas("canv", "canv", 600, 600);
setCanvasStyle( *c );
//loop over sub-detectors
for (int i=1;i<7;++i){
int histo_Counter=1;
TLegend *leg_hist = new TLegend(0.17,0.8,0.85,0.88);
setLegendStyle(*leg_hist);
//loop over file list
//TTree *tree= (TTree*)treeList.First();
//binning
int nbinsX=100;
double xmin=0;
double xmax=0;
float maxY=0;
bool isHisto = false;
std::string plotVar=variable;
THStack *hstack=new THStack("hstack","hstack");
for(std::vector<TkOfflineVariables*>::iterator it = sourceList.begin();
it != sourceList.end(); ++it){
//while ( tree ){
plotVar=variable;
TString subdet = "entries>=";
subdet+=minHits;
subdet+=" && subDetId==";
subdet+=i;
char binning [50]="";
sprintf (binning, ">>myhisto(%d, %f , %f)", nbinsX, xmin, xmax);
TH1F *h = 0;
if (histo_Counter==1&&plotVar=="meanX")(*it)->getTree()->Draw( (plotVar+=">>myhisto(50,-0.005,0.005)").c_str(),subdet,"goff");
else if (histo_Counter==1&&plotVar=="meanY")(*it)->getTree()->Draw( (plotVar+=">>myhisto(50,-0.005,0.005)").c_str(),subdet,"goff");
else if (histo_Counter==1&&plotVar=="medianX")(*it)->getTree()->Draw( (plotVar+=">>myhisto(50,-0.005,0.005)").c_str(),subdet,"goff");
else if (histo_Counter==1&&plotVar=="meanNormX")(*it)->getTree()->Draw( (plotVar+=">>myhisto(100,-2,2)").c_str(),subdet,"goff");
else if (histo_Counter==1&&plotVar=="rmsX")(*it)->getTree()->Draw( (plotVar+=">>myhisto(100,0.,0.1)").c_str(),subdet,"goff");
else if (histo_Counter!=1)(*it)->getTree()->Draw( (plotVar+=binning).c_str(),subdet,"goff");
if (gDirectory) gDirectory->GetObject("myhisto", h);
std::pair<float,float> fitResults(9999., 9999.);
if (h){
if (h->GetEntries()>0) {
isHisto = true;
h->SetDirectory(0);
//general draw options
h->SetLineWidth(2);
//first histo only, setting optStat...
if (histo_Counter==1)
setHistStyle(*h,plotVar.c_str() ,"#modules", 1 ); //set color later
h->SetLineColor( (*it)->getLineColor() );
h->SetLineStyle( (*it)->getLineStyle() );
//h->SetMarkerStyle(20+file_Counter);
//draw options
if (maxY<h->GetMaximum()){
maxY=h->GetMaximum();
}
//fit histogram for median and mean
if (variable=="medianX"||variable =="meanX")fitResults=fitGauss(h, (*it)->getLineColor() );
if (histo_Counter==1){
//get mean and sigma from fit: gauss for 2sigma range
hstack->Add(h);
nbinsX=h->GetXaxis()->GetNbins();
xmin=h->GetXaxis()->GetXmin();
xmax=h->GetXaxis()->GetXmax();
}else if (histo_Counter!=1 && h->GetEntries()>0)hstack->Add(h);
char legend [50]="";
std::string legEntry = (*it)->getName();
if (variable=="medianX"||variable =="meanX")sprintf (legend, "%s: #mu = %4.2f#mum, #sigma = %4.2f#mum ",legEntry.c_str(),fitResults.first ,fitResults.second);
else sprintf (legend, "%s ",legEntry.c_str());
if(h)
leg_hist->AddEntry(h,legend,"l");
else
std::cerr<< "histogram did not exist!";
}
}
// tree= (TTree*)treeList.After( tree );
// file_Counter++;
histo_Counter++;
}
if (isHisto){
hstack->Draw("nostack");
hstack->SetMaximum(maxY*1.3);
setTitleStyle(*hstack,plotVar.c_str() ,"#modules",i);
setHistStyle(*hstack->GetHistogram(),plotVar.c_str() ,"#modules", 1 );
leg_hist->Draw();
std::string histName="D";
if (variable=="medianX") histName+="medianR_";
else if (variable=="meanX") histName+="meanR_";
else if (variable=="meanY") histName+="meanYR_";
else if (variable=="rmsX") histName+="rmsR_";
std::string subDetector ="";
switch (i){
case 1 : subDetector+="TPB";break;
case 2 : subDetector+="TPE";break;
case 3 : subDetector+="TIB";break;
case 4 : subDetector+="TID";break;
case 5 : subDetector+="TOB";break;
case 6 : subDetector+="TEC";break;
}
char PlotName[100];
sprintf( PlotName, "%s/%s%s.eps",outputDir.c_str(), histName.c_str(), subDetector.c_str() );
c->Update();
c->Print(PlotName);
//c->Update();
//c->Close();
}
delete hstack;
hstack=0;
}
delete c;
c=0;
}