void QMessageWidgets::initUI()
{
QGridLayout *gridLay = getLayout();
QFrame *hline = new QFrame(getCenterPanel());
m_lbmsg = new QLabel(this);
m_lbmsg->setWordWrap(true);
gridLay->setContentsMargins(5,2,2,10);
hline->setFrameShape(QFrame::HLine);
hline->setFrameShadow(QFrame::Sunken);
gridLay->addWidget(hline,0,0,1,1);
gridLay->addWidget(m_lbmsg,1,0,1,1);
setTitleStyle("font: 75 12pt \"Aharoni\";");
}
//------------------------------------------------------------------------------
void PlotAlignmentValidation::plotDMR(const std::string& variable, Int_t minHits, const std::string& options)
{
// If several, comma-separated values are given,
// call plotDMR with each value separately.
// If a comma is found, the string is divided to two.
// (no space allowed)
std::size_t findres = variable.find(",");
if ( findres != std::string::npos) {
std::string substring1 = variable.substr(0, findres);
std::string substring2 = variable.substr(findres+1, std::string::npos);
plotDMR(substring1, minHits, options);
plotDMR(substring2, minHits, options);
return;
}
// Variable name should end with X or Y. If it doesn't, recursively calls plotDMR twice with
// X and Y added, respectively
if (variable == "mean" || variable == "median" || variable == "meanNorm" ||
variable == "rms" || variable == "rmsNorm") {
plotDMR(variable+"X", minHits, options);
plotDMR(variable+"Y", minHits, options);
return;
}
TRegexp layer_re("layer=[0-9]+");
bool plotPlain = false, plotSplits = false, plotLayers = false;
int plotLayerN = 0;
Ssiz_t index, len;
if (options.find("plain") != std::string::npos) { plotPlain = true; }
if (options.find("split") != std::string::npos) { plotSplits = true; }
if (options.find("layers") != std::string::npos) { plotLayers = true; }
if ((index = layer_re.Index(options, &len)) != -1) {
if (plotLayers) {
std::cerr << "Warning: option 'layers' overrides 'layer=N'" << std::endl;
} else {
std::string substr = options.substr(index+6, len-6);
plotLayerN = atoi(substr.c_str());
}
}
// Defaults to plotting only plain plot if empty (or invalid)
// option string is given
if (!plotPlain && !plotSplits) { plotPlain = true; }
// This boolean array tells for which detector modules to plot split DMR plots
// They are plotted for BPIX, FPIX, TIB and TOB
static bool plotSplitsFor[6] = { true, true, true, false, true, false };
// If layers are plotted, these are the numbers of layers for each subdetector
static int numberOfLayers[6] = { 3, 2, 4, 3, 6, 9 };
DMRPlotInfo plotinfo;
setNiceStyle();
gStyle->SetOptStat(0);
TCanvas c("canv", "canv", 600, 600);
setCanvasStyle( c );
plotinfo.variable = variable;
plotinfo.minHits = minHits;
plotinfo.plotPlain = plotPlain;
plotinfo.plotLayers = plotLayers;
if (variable == "meanX") { plotinfo.nbins = 50; plotinfo.min = -0.001; plotinfo.max = 0.001; }
else if (variable == "meanY") { plotinfo.nbins = 50; plotinfo.min = -0.005; plotinfo.max = 0.005; }
else if (variable == "medianX") { plotinfo.nbins = 50; plotinfo.min = -0.005; plotinfo.max = 0.005; }
else if (variable == "medianY") { plotinfo.nbins = 50; plotinfo.min = -0.005; plotinfo.max = 0.005; }
else if (variable == "meanNormX") { plotinfo.nbins = 100; plotinfo.min = -2.0; plotinfo.max = 2.0; }
else if (variable == "meanNormY") { plotinfo.nbins = 100; plotinfo.min = -2.0; plotinfo.max = 2.0; }
else if (variable == "rmsX") { plotinfo.nbins = 100; plotinfo.min = 0.0; plotinfo.max = 0.1; }
else if (variable == "rmsY") { plotinfo.nbins = 100; plotinfo.min = 0.0; plotinfo.max = 0.1; }
else if (variable == "rmsNormX") { plotinfo.nbins = 100; plotinfo.min = 0.3; plotinfo.max = 1.8; }
else if (variable == "rmsNormY") { plotinfo.nbins = 100; plotinfo.min = 0.3; plotinfo.max = 1.8; }
else {
std::cerr << "Unknown variable " << variable << std::endl;
plotinfo.nbins = 100; plotinfo.min = -0.1; plotinfo.max = 0.1;
}
for (int i=1; i<=6; ++i) {
// Skip strip detectors if plotting any "Y" variable
if (i != 1 && i != 2 && variable.length() > 0 && variable[variable.length()-1] == 'Y') {
continue;
}
// Skips plotting too high layers
if (plotLayerN > numberOfLayers[i-1]) {
continue;
}
plotinfo.plotSplits = plotSplits && plotSplitsFor[i-1];
if (!plotinfo.plotPlain && !plotinfo.plotSplits) {
continue;
}
// Sets dimension of legend according to the number of plots
int nPlots = 1;
if (plotinfo.plotSplits) { nPlots = 3; }
if (plotinfo.plotLayers) { nPlots *= numberOfLayers[i-1]; }
nPlots *= sourceList.size();
double legendY = 0.80;
if (nPlots > 3) { legendY -= 0.01 * (nPlots - 3); }
if (legendY < 0.6) {
std::cerr << "Warning: Huge legend!" << std::endl;
legendY = 0.6;
}
THStack hstack("hstack", "hstack");
plotinfo.maxY = 0;
plotinfo.subDetId = i;
plotinfo.nLayers = numberOfLayers[i-1];
plotinfo.legend = new TLegend(0.17, legendY, 0.85, 0.88);
setLegendStyle(*plotinfo.legend);
plotinfo.hstack = &hstack;
plotinfo.h = plotinfo.h1 = plotinfo.h2 = 0;
plotinfo.firsthisto = true;
for(std::vector<TkOfflineVariables*>::iterator it = sourceList.begin();
it != sourceList.end(); ++it) {
int minlayer = plotLayers ? 1 : plotLayerN;
int maxlayer = plotLayers ? plotinfo.nLayers : plotLayerN;
plotinfo.vars = *it;
for (int layer = minlayer; layer <= maxlayer; layer++) {
if (plotinfo.plotPlain) {
plotDMRHistogram(plotinfo, 0, layer);
}
if (plotinfo.plotSplits) {
plotDMRHistogram(plotinfo, -1, layer);
plotDMRHistogram(plotinfo, 1, layer);
}
if (plotinfo.plotPlain) {
if (plotinfo.h) { setDMRHistStyleAndLegend(plotinfo.h, plotinfo, 0, layer); }
}
if (plotinfo.plotSplits) {
// Add delta mu to the histogram
if (plotinfo.h1 != 0 && plotinfo.h2 != 0 && !plotinfo.plotPlain) {
std::ostringstream legend;
std::string unit = " #mum";
legend.precision(2);
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 << plotinfo.vars->getName();
if (layer > 0) {
legend << ", layer " << layer;
}
legend << ": #Delta#mu = " << deltamu << unit;
plotinfo.legend->AddEntry(static_cast<TObject*>(0), legend.str().c_str(), "");
}
if (plotinfo.h1) { setDMRHistStyleAndLegend(plotinfo.h1, plotinfo, -1, layer); }
if (plotinfo.h2) { setDMRHistStyleAndLegend(plotinfo.h2, plotinfo, 1, layer); }
}
}
}
if (plotinfo.h != 0 || plotinfo.h1 != 0 || plotinfo.h2 != 0) {
hstack.Draw("nostack");
hstack.SetMaximum(plotinfo.maxY*1.3);
setTitleStyle(hstack, variable.c_str(), "#modules", plotinfo.subDetId);
setHistStyle(*hstack.GetHistogram(), variable.c_str(), "#modules", 1);
plotinfo.legend->Draw();
std::ostringstream plotName;
plotName << outputDir << "/D";
if (variable=="medianX") plotName << "medianR_";
else if (variable=="medianY") plotName << "medianYR_";
else if (variable=="meanX") plotName << "meanR_";
else if (variable=="meanY") plotName << "meanYR_";
else if (variable=="meanNormX") plotName << "meanNR_";
else if (variable=="meanNormY") plotName << "meanNYR_";
else if (variable=="rmsX") plotName << "rmsR_";
else if (variable=="rmsY") plotName << "rmsYR_";
else if (variable=="rmsNormX") plotName << "rmsNR_";
else if (variable=="rmsNormY") plotName << "rmsNYR_";
switch (i) {
case 1: plotName << "BPIX"; break;
case 2: plotName << "FPIX"; break;
case 3: plotName << "TIB"; break;
case 4: plotName << "TID"; break;
case 5: plotName << "TOB"; break;
case 6: plotName << "TEC"; break;
}
if (plotPlain && !plotSplits) { plotName << "_plain"; }
else if (!plotPlain && plotSplits) { plotName << "_split"; }
if (plotLayers) { plotName << "_layers"; }
if (plotLayerN > 0) { plotName << "_layer" << plotLayerN; }
plotName << ".eps";
c.Update();
c.Print(plotName.str().c_str());
}
}
}
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;
}
