std::pair<TH3F*,TH3F*> getEffHists(const char *file, const char *dirC,
const char *histN, const char *histD){
TFile *efile = new TFile(file,"read");
TDirectoryFile *efileDIR = (TDirectoryFile*) efile->GetDirectory(dirC);
TIter next(efileDIR->GetListOfKeys());
TKey *key;
Char_t name[100];
TH3F *hpneff3d=0;
TH3F *hpdeff3d=0;
while ((key=(TKey*)next())) {
sprintf(name,"%s",key->GetName());
if(strcmp((key->GetName()),(histN))==0){
//cout<<"[getEffHists] Your numerator for Eff "<<name<<endl;
hpneff3d = (TH3F*) efileDIR->Get(name);
}
if(strcmp((key->GetName()),(histD))==0){
//cout<<"[getEffHists] Your denominator for Eff "<<name<<endl;
hpdeff3d = (TH3F*) efileDIR->Get(name);
}
}
//efileDIR->Close();
//efile->Close();
return std::pair<TH3F*,TH3F*>(hpneff3d,hpdeff3d);
}
int
main (int argc, char *argv[])
{
map<string, string> opt;
vector<string> argVector;
parseOptions (argc, argv, opt, argVector);
if (argVector.size () != 1 || opt.count ("help"))
{
printHelp (argv[0]);
return 0;
}
TFile *fin;
if (!(fin = TFile::Open (argVector.at (0).c_str (), "update")))
{
cout << "Failed to open " << argVector.at (0) << "!" << endl;
return 0;
}
TIter next0 (fin->GetListOfKeys ());
TObject *obj0;
TH1D *cutFlow = 0;
TDirectoryFile *dir = 0;
while ((obj0 = next0 ()))
{
string obj0Class = ((TKey *) obj0)->GetClassName (),
obj0Name = obj0->GetName ();
if (obj0Class == "TDirectoryFile")
{
dir = (TDirectoryFile *) fin->Get (obj0Name.c_str ());
TIter next1 (dir->GetListOfKeys ());
TObject *obj1;
while ((obj1 = next1 ()))
{
string obj1Class = ((TKey *) obj1)->GetClassName (),
obj1Name = obj1->GetName ();
if (obj1Class == "TH1D" && obj1Name.length () >= 7 && ((obj1Name.substr (obj1Name.length () - 7, 7) == "CutFlow" || obj1Name.substr (obj1Name.length () - 7, 7) == "cutFlow")
|| (obj1Name.length () >= 9 && (obj1Name.substr (obj1Name.length () - 9, 9) == "Selection" || obj1Name.substr (obj1Name.length () - 9, 9) == "selection"))
|| (obj1Name.length () >= 8 && (obj1Name.substr (obj1Name.length () - 8, 8) == "MinusOne" || obj1Name.substr (obj1Name.length () - 8, 8) == "minusOne")))
&& !dir->Get ((obj1Name + "LowerLimit").c_str ()) && !dir->Get ((obj1Name + "UpperLimit").c_str ()))
{
cutFlow = (TH1D *) dir->Get (obj1Name.c_str ());
cutFlow->SetDirectory (0);
getLimits (cutFlow, dir);
}
}
}
}
fin->Close ();
return 0;
}
// Noise section
Stat_t AnalysisClass::doHisto(Char_t * Variable, Char_t *SubDetName, Char_t *Layer,Char_t *label){
TH1 *hHisto=0;
if (debug) cout << d1->GetTitle() << " " << Variable << " " << SubDetName << endl;
pPar[0]=0; pPar[1]=0;
TIter it(d1->GetListOfKeys());
TObject * o;
while ( (o = it()))
{
TObject * d = d1->Get(o->GetName());
if(d->IsA()->InheritsFrom("TDirectory") && strstr(d->GetName(),SubDetName)){
if (debug) cout << "Found SubDet " << SubDetName << endl;
TIter it2(((TDirectoryFile * )d)->GetListOfKeys());
TObject *o2;
while( ( o2 = it2()) ){
TObject *d2 = ((TDirectoryFile * )d)->Get(o2->GetName());
if(d2->IsA()->InheritsFrom("TDirectory") && strstr(d2->GetName(),Layer) ){
if (debug) cout << "Found Layer" << Layer << endl;
TIter it3(((TDirectoryFile * )d2)->GetListOfKeys());
TObject *o3;
while( ( o3 = it3()) ){
TObject *d3 = ((TDirectoryFile * )d2)->Get(o3->GetName());
if(strstr(d3->GetName(),Variable) && strstr(d3->GetName(),label)){
hHisto = (TH1*) d3;
if(hHisto->GetEntries()!=0) {
pPar[0]=hHisto->GetMean();
pPar[1]=hHisto->GetRMS();
if (debug) cout << "Histo Title " << hHisto->GetTitle() << " mean: " << hHisto->GetMean() << " rms: " << hHisto->GetRMS() << " " << hHisto->GetEntries() << endl;
}
else{
cout<<"Empty Histogram "<< hHisto->GetTitle() << endl;
pPar[0]=-10; pPar[1]=-10;
}
}
}
}
}
}
}
return hHisto->GetEntries();
}
// This will generate the following PDFs:
// -- hDQ_muScTDiff_[DetName]_[BankName].png
void GenerateTDiffPlots(std::string filename) {
std::cout << "Generating pulse shape plots..." << std::endl;
gROOT->Reset();
gROOT->SetStyle("Plain");
gStyle->SetCanvasBorderMode(0); // turn off canvas borders
TFile* file = new TFile(filename.c_str(), "READ");
// The histograms
TH1F *hDQ_muScTDiff;
// Loop through the histograms in the file and get the island histograms (bank and channel names may differ between runs)
TDirectoryFile* dir = (TDirectoryFile*) file->Get("DataQuality_LowLevel");
TIter nextDirKey(dir->GetListOfKeys()); // get the list of keys in the directory (all histograms should be in this folder)
TKey *dirKey;
while ( (dirKey = (TKey*)nextDirKey()) ) {
// Get the names of all the histograms and count them up
if (strcmp(dirKey->ReadObj()->ClassName(), "TH1F") == 0) {
TCanvas *c1 = new TCanvas();
std::string histogram_name = dirKey->ReadObj()->GetName();
std::string histogram_location = "DataQuality_LowLevel/" + histogram_name;
std::string pngname = "data_quality_figs/" + histogram_name + ".png";
if (histogram_name.find("muScTDiff") != std::string::npos) {
file->GetObject(histogram_location.c_str(),hDQ_muScTDiff);
hDQ_muScTDiff->GetYaxis()->SetTitleOffset(1.3);
hDQ_muScTDiff->Draw();
c1->Print(pngname.c_str());
}
}
}
}
void advancedNoiseAnalysis( unsigned int runNumber, unsigned int loop = 1) {
string inputFileName = "./histo/run00" + toString( runNumber ) + "-ped-histo.root";
string outputFileName = "./histo/run00" + toString( runNumber ) + "-adv-noise.root";
// before opening the input and the output files, try to see if they
// are not opened yet and in case close them before continue
TList * listOfOpenedFile = (TList*) gROOT->GetListOfFiles();
for ( int i = 0; i < listOfOpenedFile->GetSize() ; ++i ) {
TFile * file = (TFile*) listOfOpenedFile->At( i ) ;
TString fileName(file->GetName());
TString inputFileName1( inputFileName.c_str() );
TString outputFileName1( outputFileName.c_str() );
if ( ( fileName.Contains( inputFileName1 ) ) ||
( inputFileName1.Contains( fileName ) ) ||
( fileName.Contains( outputFileName1 ) ) ||
( outputFileName1.Contains( fileName ) ) ) {
cout << "Closing " << fileName << " before reopen " << endl;
file->Close();
}
}
// close also all the previously opened canvas
TList * listOfOpenedCanvas = (TList*) gROOT->GetListOfCanvases();
for ( int i = 0 ; i < listOfOpenedCanvas->GetSize() ; ++i ) {
TCanvas * canvas = (TCanvas*) listOfOpenedCanvas->At( i );
TString canvasName2 = canvas->GetName();
if ( canvasName2.Contains( "det" ) ) {
canvas->Close();
}
}
// now safely open the file
TFile * inputFile = TFile::Open( inputFileName.c_str() ) ;
TFile * outputFile = TFile::Open( outputFileName.c_str(), "RECREATE") ;
TList * outputHistoList = new TList;
// look into the inputFile for a folder named
string pedeProcessorFolderName = "PedestalAndNoiseCalculator";
TDirectoryFile * pedeProcessorFolder = (TDirectoryFile*) inputFile->Get( pedeProcessorFolderName.c_str() );
if ( pedeProcessorFolder == 0 ) {
cerr << "No pedestal processor folder found in file " << inputFileName << endl;
return ;
}
// this folder should contain one folder for each loop.
string loopFolderName = "loop-" + toString( loop );
TDirectoryFile * loopFolder = (TDirectoryFile *) pedeProcessorFolder->Get( loopFolderName.c_str() );
if ( loopFolder == 0 ) {
cerr << "No " << loopFolderName << " found in file " << inputFileName << endl;
return ;
}
// guess the number of sensors from the number of subfolder in the loopfolder
size_t nDetector = loopFolder->GetListOfKeys()->GetSize();
cout << "This file contains " << nDetector << " detectors" << endl;
// prepare arrays to store the mean and the rms of the noise distribution
if ( noiseMean == NULL ) {
delete [] noiseMean;
noiseMean = NULL;
}
if ( noiseRMS == NULL ) {
delete [] noiseRMS;
noiseRMS = NULL;
}
if ( channel == NULL ) {
delete [] channel;
channel = NULL;
}
noiseMean = new double[ nDetector * kNChan ];
noiseRMS = new double[ nDetector * kNChan ];
channel = new double[ kNChan ];
string canvasName = "comparison";
string canvasTitle = "Noise comparison";
TCanvas * comparisonCanvas = new TCanvas( canvasName.c_str(), canvasTitle.c_str(), 1000, 500 );
comparisonCanvas->Divide(1,2);
TPad * topPad = (TPad*) comparisonCanvas->cd(1);
topPad->Divide( nDetector );
TPad * middlePad = (TPad *) comparisonCanvas->cd(2);
middlePad->Divide( kNChan );
// for each detector we have to get the noise map and to prepare 4
// separe histos and maps
for ( unsigned int iDetector = 0; iDetector < nDetector; iDetector++ ) {
// get the noise map.
string noiseMapName = "detector-" + toString( iDetector ) ;
noiseMapName += "/NoiseMap-d" + toString( iDetector ) ;
noiseMapName += "-l" + toString( loop ) ;
TH2D * noiseMap = ( TH2D* ) loopFolder->Get( noiseMapName.c_str() );
// create a folder in the output file
TDirectory * subfolder = outputFile->mkdir( string( "detector_" + toString( iDetector ) ).c_str(),
string( "detector_" + toString( iDetector ) ).c_str()
);
subfolder->cd();
string canvasName = "det" + toString( iDetector );
string canvasTitle = "Detector " + toString( iDetector );
TCanvas * canvas = new TCanvas( canvasName.c_str(), canvasTitle.c_str(), 1000, 500 );
canvas->Divide( kNChan, 2 );
// ok now start the loop on channels
for ( size_t iChan = 0 ; iChan < kNChan ; ++iChan ) {
if ( iDetector == 0 ) channel[iChan] = iChan - 0.5;
string tempName = "NoiseMap_d" + toString( iDetector ) + "_l" + toString( loop ) + "_ch" + toString( iChan ) ;
string tempTitle = "NoiseMap Det. " + toString( iDetector ) + " - Ch. " + toString( iChan ) ;
TH2D * noiseMapCh = new TH2D ( tempName.c_str() , tempTitle.c_str(),
kXPixel / kNChan , -0.5 + xLimit[ iChan ] , -0.5 + xLimit[ iChan + 1 ],
kYPixel, -0.5, -0.5 + kYPixel );
noiseMapCh->SetXTitle("X [pixel]");
noiseMapCh->SetYTitle("Y [pixel]");
noiseMapCh->SetZTitle("Noise [ADC]");
noiseMapCh->SetStats( false );
outputHistoList->Add( noiseMapCh ) ;
tempName = "NoiseDist_d" + toString( iDetector ) + "_l" + toString( loop ) + "_ch" + toString( iChan ) ;
tempTitle = "NoiseDist Det. " + toString( iDetector ) + " - Ch. " + toString( iChan ) ;
TH1D * noiseDistCh = new TH1D( tempName.c_str(), tempTitle.c_str(), 50, 0., 10. );
noiseDistCh->SetXTitle("Noise [ADC]");
noiseDistCh->SetLineColor( kColor[iDetector] );
noiseDistCh->SetLineStyle( iChan + 2 );
noiseDistCh->SetLineWidth( 2 );
outputHistoList->Add( noiseDistCh );
// let's start looping on pixels now
for ( size_t yPixel = 1 ; yPixel <= kYPixel ; ++yPixel ) {
for ( size_t xPixel = xLimit[ iChan ] + 1; xPixel <= xLimit[ iChan +1 ] ; ++xPixel ) {
double noise = noiseMap->GetBinContent( xPixel , yPixel );
noiseMapCh->Fill( xPixel - 1 , yPixel - 1, noise );
noiseDistCh->Fill( noise );
}
}
canvas->cd( iChan + 1 ) ;
noiseMapCh->Draw("colz");
canvas->cd( iChan + kNChan + 1 );
noiseDistCh->Draw();
topPad->cd( iDetector + 1 );
if ( iChan == 0 ) {
noiseDistCh->Draw();
} else {
noiseDistCh->Draw("same");
}
middlePad->cd( iChan + 1 );
if ( iDetector == 0 ) {
noiseDistCh->Draw();
} else {
noiseDistCh->Draw("same");
}
noiseMean[ kNChan * iDetector + iChan ] = noiseDistCh->GetMean();
noiseRMS[ kNChan * iDetector + iChan ] = noiseDistCh->GetRMS();
}
canvas->Write();
}
canvasName = "summary";
canvasTitle = "Noise summary";
TCanvas * summaryCanvas = new TCanvas( canvasName.c_str(), canvasTitle.c_str(), 1000, 500 );
summaryCanvas->SetGridx(1);
TLegend * legend = new TLegend(0.5, 4.8, 1.5, 4.3,"","br");;
for ( size_t iDetector = 0 ; iDetector < nDetector ; ++iDetector ) {
TGraphErrors * gr = new TGraphErrors( kNChan, channel, &noiseMean[ iDetector * kNChan ], NULL, &noiseRMS[ iDetector * kNChan ] );
gr->SetName( string( "NoisePerChannel_d" + toString( iDetector )).c_str());
gr->SetTitle(string("Detector " + toString( iDetector )).c_str());
gr->GetXaxis()->SetTitle("Channel #");
gr->GetYaxis()->SetTitle("Noise [ADC]");
gr->GetXaxis()->SetNdivisions( 5 );
gr->GetXaxis()->SetLabelSize( 0 );
gr->SetMarkerStyle( iDetector + 1 );
gr->SetMarkerColor( kColor[iDetector] );
gr->SetLineColor( kColor[iDetector] );
gr->SetLineWidth( 2 );
legend->AddEntry( gr, string("Detector " + toString( iDetector )).c_str(), "LP");
if ( iDetector == 0 ) {
gr->Draw("ALP");
} else {
gr->Draw("LP");
}
}
legend->Draw();
for ( size_t iChan = 0 ; iChan < kNChan ; ++iChan ) {
TPaveLabel * label = new TPaveLabel( iChan - 0.75 , 3.2 , iChan -0.25 , 3, string("Ch " + toString( iChan ) ).c_str());
label->Draw();
}
summaryCanvas->Write();
comparisonCanvas->Write();
outputHistoList->Write();
}
void CreatePictureBooks(const char* data_dir, int first_run, const int n_runs) {
gROOT->Reset();
gROOT->SetStyle("Plain");
gStyle->SetCanvasBorderMode(0); // turn off canvas borders
// Create the canvases
TCanvas* trend_canvas = new TCanvas("trend_canvas", "trend_canvas");
TFile* files[n_runs];
TCanvas* individual_canvases[n_runs];
// Names for opening, closing and saving to PDFs
std::stringstream individual_basepdfname[n_runs];
std::string individual_openpdfname[n_runs];
std::string individual_closepdfname[n_runs];
for (int iRun = 0; iRun < n_runs; ++iRun) {
int run_number = first_run + iRun;
// Open up the file for this run
std::stringstream filename;
filename << data_dir << "/hist/hist0" << run_number << ".root";
files[iRun] = new TFile(filename.str().c_str(), "READ");
// Create an individual canvas for this run
std::stringstream canvasname;
canvasname << "individual_canvas_run0" << run_number;
individual_canvases[iRun] = new TCanvas(canvasname.str().c_str(),canvasname.str().c_str());
// Open a PDF for each run
individual_basepdfname[iRun].str("");
individual_basepdfname[iRun] << "DQ_LowLevel_RunPlots_Run0" << run_number << ".pdf";
individual_openpdfname[iRun] = individual_basepdfname[iRun].str() + "[";
individual_closepdfname[iRun] = individual_basepdfname[iRun].str() + "]";
individual_canvases[iRun]->Print(individual_openpdfname[iRun].c_str());
}
// Get the names of all the histograms
std::vector<std::string> histogram_names;
TIter nextFileKey(files[0]->GetListOfKeys()); // get the list of keys for the top level in the first file (all files should be the same)
TKey *fileKey;
while (fileKey = (TKey*)nextFileKey()) {
// Get the directory for low-level data quality plots first
if (strcmp(fileKey->ReadObj()->ClassName(), "TDirectoryFile") == 0) {
// Check that the directory has the correct name
if (strcmp(fileKey->ReadObj()->GetName(), "DataQuality_LowLevel") == 0) {
TDirectoryFile* dir = (TDirectoryFile*) fileKey->ReadObj();
TIter nextDirKey(dir->GetListOfKeys()); // get the list of keys in the directory (all histograms should be in this folder)
TKey *dirKey;
while (dirKey = (TKey*)nextDirKey()) {
// Get the names of all the histograms and count them up
if (strcmp(dirKey->ReadObj()->ClassName(), "TH1F") == 0 ||
strcmp(dirKey->ReadObj()->ClassName(), "TH2F") == 0) {
histogram_names.push_back(dirKey->ReadObj()->GetName());
} // end if (class is TH1F)
} // end while loop (through keys in the directory)
} // end if (directory is DataQuality_LowLevel)
} // end if (class is TDirectoryFile)
} // end while loop (through keys in file)
// Reorder the histogram names so that channels from the same board are next to each other (might make it easier to print 4 plots on the same page)
std::vector<std::string> ordered_histogram_names = OrderHistogramNames(histogram_names);
std::stringstream trend_basepdfname;
trend_basepdfname << "DQ_LowLevel_TrendPlots_Runs0" << first_run << "-" << first_run + n_runs << ".pdf";
std::string trend_openpdfname = trend_basepdfname.str() + "[";
std::string trend_closepdfname = trend_basepdfname.str() + "]";
trend_canvas->Print(trend_openpdfname.c_str());
// Now we have the histogram names, so loop though them
for (int iHist = 0; iHist < ordered_histogram_names.size(); ++iHist) {
std::string histname = ordered_histogram_names.at(iHist);
std::string fullhistname = "DataQuality_LowLevel/" + histname;
// Check to see if we actually want this plot
if ( !WantPlot(histname)) {
continue;
}
// Create the trend plot
std::string trendplotname = histname + "_TrendPlot";
std::string trendplottitle = "Trend plot of " + histname;
// Get some useful information from the histogram in the first run file (for the y-axis range of the trend plot)
TH1F* hist = (TH1F*) files[0]->Get(fullhistname.c_str());
TH2F* trend_plot = new TH2F(trendplotname.c_str(), trendplottitle.c_str(), n_runs, first_run, first_run+n_runs, hist->GetNbinsX(), hist->GetXaxis()->GetXmin(), hist->GetXaxis()->GetXmax());
trend_plot->GetYaxis()->SetTitle(hist->GetXaxis()->GetTitle());
trend_plot->GetYaxis()->SetLabelSize(0.03);
trend_plot->GetXaxis()->SetTitle("Run Number");
trend_plot->GetXaxis()->SetLabelSize(0.03);
trend_plot->GetZaxis()->SetTitle(hist->GetYaxis()->GetTitle());
trend_plot->GetZaxis()->SetLabelSize(0.03);
trend_plot->GetZaxis()->SetTitleOffset(0.85);
trend_plot->GetZaxis()->SetTitleSize(0.03);
trend_plot->SetStats(false);
// Set the fraction trend plots to have a maximum of 1 so that red = bad
if (histname.find("Fraction") != std::string::npos) {
trend_plot->GetZaxis()->SetRangeUser(0,1);
}
// Copy the axis labels so that they show the detector and channel names
else if (histname.find("hDQ_IslandRate") != std::string::npos) {
for (int jBin = 1; jBin < hist->GetNbinsX(); ++jBin) {
trend_plot->GetYaxis()->SetBinLabel(jBin, hist->GetXaxis()->GetBinLabel(jBin));
}
trend_plot->GetYaxis()->SetTitle(false);
trend_plot->GetYaxis()->SetLabelSize(0.02);
trend_plot->GetZaxis()->SetLabelSize(0.02);
}
// Check to see if we want this histogram as an individual or a trend plot
bool want_trend_plot = WantAsTrendPlot(histname);
// Loop through the runs
for (int iRun = 0; iRun < n_runs; ++iRun) {
// Make sure this file exists (there may be some missing in our golden run ranges)
if (files[iRun]->IsZombie())
continue;
// Get the histogram
TH1* hist = (TH1*) files[iRun]->Get(fullhistname.c_str());
if (want_trend_plot == false) {
// Print the histogram out directly to the individual picture book
individual_canvases[iRun]->cd();
ZoomIndividualPlot(hist);
hist->Draw("COLZ");
individual_canvases[iRun]->SetLogz(WantLogZ(histname)); // change to a log-z scale if we want to
individual_canvases[iRun]->Update();
individual_canvases[iRun]->Print(individual_basepdfname[iRun].str().c_str());
}
else {
// Fill this histogram into the trend plot
for (int iBin = 1; iBin <= hist->GetNbinsX(); ++iBin) {
trend_plot->Fill(first_run + iRun, hist->GetBinCenter(iBin), hist->GetBinContent(iBin)); // (x = run #, y = time stamp, z = N_TPI)
} // end for loop (filling trend plot)
} // end if (trend plot)
} // end for loop (through runs)
// Now export the trend plot to PDF (if applicable)
if (want_trend_plot) {
trend_canvas->cd();
ZoomTrendPlot(trend_plot);
trend_plot->Draw("COLZ");
trend_canvas->Print(trend_basepdfname.str().c_str());
}
}
// Now go through and clean up
for (int iRun = 0; iRun < n_runs; ++iRun) {
individual_canvases[iRun]->Print(individual_closepdfname[iRun].c_str());
}
trend_canvas->Print(trend_closepdfname.c_str());
}
void makeMuonTimingPlot (std::string fname)
{
TFile file(fname.c_str());
TDirectoryFile *dir = (TDirectoryFile*)file.Get("Muons");
TList *hlist = dir->GetListOfKeys();
TH1F *h1;
bool foundHist = false;
for (auto hist : *hlist)
{
TString name = hist->GetName();
if (!name.Contains("hMuTimeP")) continue;
TH1F *h0 = (TH1F*)dir->Get(name.Data());
if (!foundHist)
{
h1 = (TH1F*)h0->Clone();
h1->Sumw2();
foundHist = true;
}
else
{
h1->Add(h0);
}
}
TH1F *h2 = new TH1F("h2", "h2", 200, -100, 100);
h2->GetXaxis()->SetTitle("muon time (ns)");
h2->GetYaxis()->SetTitle("Fraction of Muons/ns");
h2->GetYaxis()->SetTitleOffset(1.1);
h2->GetXaxis()->SetTitleOffset(0.8);
h2->SetTitle("CSC Muon Time");
h2->SetTitleFont(42);
h2->SetTitleSize(0.052);
h2->Sumw2();
h2->SetLineColor(kCyan+3);
h2->SetFillColor(kCyan+3);
for (int ibin = 1; ibin <= 200; ibin++)
{
h2->SetBinContent(ibin, h1->GetBinContent(ibin));
h2->SetBinError(ibin, h1->GetBinError(ibin));
if (ibin == 200)
h2->SetEntries(h1->GetEntries());
}
TCanvas c1("c1", "c1", 600, 400);
gStyle->SetOptStat("");
double rms = h2->GetRMS();
double avg = h2->GetMean();
TLatex cms(0.17, 0.83, "CMS");
cms.SetNDC();
cms.SetTextFont(61);
cms.SetTextSize(0.06);
TLatex prelim(0.17, 0.81, "Preliminary");
prelim.SetNDC();
prelim.SetTextAlign(13);
prelim.SetTextFont(52);
prelim.SetTextSize(0.0456);
TLatex data(0.17, 0.76, "Data 2016");
data.SetNDC();
data.SetTextAlign(13);
data.SetTextFont(52);
data.SetTextSize(0.0456);
TLatex lumi(0.9, 0.93, "4.0 fb^{-1} (13 TeV)");
lumi.SetNDC();
lumi.SetTextAlign(31);
lumi.SetTextFont(42);
lumi.SetTextSize(0.052);
TLatex mean(0.7, 0.81, Form("Mean %2.1f", avg));
mean.SetNDC();
mean.SetTextAlign(11);
mean.SetTextFont(61);
mean.SetTextSize(0.06);
TLatex stdev(0.7, 0.76, Form("RMS %2.1f", rms));
stdev.SetNDC();
stdev.SetTextAlign(11);
stdev.SetTextFont(61);
stdev.SetTextSize(0.06);
h2->GetXaxis()->SetRangeUser(-6*rms,6*rms);
TH1F* h2norm = (TH1F*)h2->DrawNormalized("hist");
gPad->Update();
cms.Draw();
prelim.Draw();
data.Draw();
lumi.Draw();
mean.Draw();
stdev.Draw();
TPaveText *title = (TPaveText*)gPad->GetPrimitive("title");
title->SetBorderSize(0);
title->SetFillColor(0);
title->SetFillStyle(0);
title->SetX1NDC(0.13);
title->SetY1NDC(0.88);
title->SetX2NDC(0.9);
title->SetY2NDC(0.98);
title->SetTextFont(42);
title->SetTextSize(0.052);
title->SetTextAlign(11);
c1.Print("plots/muon_time_all.pdf");
c1.Print("plots/muon_time_all.png");
c1.Print("plots/muon_time_all.root");
}
//Noise section
Stat_t AnalysisClass::doNoiseFit(Int_t RunNumber, Char_t *Variable, Char_t *SubDetName, Char_t *Layer, Char_t *label){
TH1 *hNtoFit=0;
if (debug) cout << d1->GetTitle() << " " << Variable << " " << SubDetName << endl;
pPar[0]=0; pPar[1]=0;
TIter it(d1->GetListOfKeys());
TObject * o;
while ( (o = it()))
{
TObject * d = d1->Get(o->GetName());
if(d->IsA()->InheritsFrom("TDirectory") && strstr(d->GetName(),SubDetName)){
if (debug) cout << "Found " << SubDetName << endl;
TIter it2(((TDirectoryFile * )d)->GetListOfKeys());
TObject *o2;
while( ( o2 = it2()) ){
TObject *d2 = ((TDirectoryFile * )d)->Get(o2->GetName());
if(d2->IsA()->InheritsFrom("TDirectory") && strstr(d2->GetName(),Layer) ){
if (debug) cout << "Found Layer" << Layer << endl;
TIter it3(((TDirectoryFile * )d2)->GetListOfKeys());
TObject *o3;
while( ( o3 = it3()) ){
TObject *d3 = ((TDirectoryFile * )d2)->Get(o3->GetName());
if(strstr(d3->GetName(),Variable) && strstr(d3->GetName(),label)){
hNtoFit = (TH1*) d3;
if (debug) cout << "Found " << Variable << endl;
if (hNtoFit->GetEntries()!=0) {
cout<<"Fitting "<< hNtoFit->GetTitle() <<endl;
// Setting fit range and start values
Double_t fr[2];
Double_t sv[3], pllo[3], plhi[3];
fr[0]=hNtoFit->GetMean()-5*hNtoFit->GetRMS();
fr[1]=hNtoFit->GetMean()+5*hNtoFit->GetRMS();
Int_t imax=hNtoFit->GetMaximumBin();
Double_t xmax=hNtoFit->GetBinCenter(imax);
Double_t ymax=hNtoFit->GetBinContent(imax);
Int_t i[2];
Int_t iArea[2];
i[0]=hNtoFit->GetXaxis()->FindBin(fr[0]);
i[1]=hNtoFit->GetXaxis()->FindBin(fr[1]);
iArea[0]=hNtoFit->GetXaxis()->FindBin(fr[0]);
iArea[1]=hNtoFit->GetXaxis()->FindBin(fr[1]);
Double_t AreaFWHM=hNtoFit->Integral(iArea[0],iArea[1],"width");
sv[2]=AreaFWHM/(4*ymax);
sv[1]=xmax;
sv[0]=hNtoFit->Integral(i[0],i[1],"width");
plhi[0]=1000000.0; plhi[1]=10.0; plhi[2]=10.;
pllo[0]=1.5 ; pllo[1]=0.1; pllo[2]=0.3;
Char_t FunName[100];
sprintf(FunName,"FitfcnLG_%s%d",hNtoFit->GetName(),fRun);
TF1 *ffitold = (TF1*)gROOT->GetListOfFunctions()->FindObject(FunName);
if (ffitold) delete ffitold;
gausFit = new TF1(FunName,Gauss,fr[0],fr[1],3);
gausFit->SetParameters(sv);
gausFit->SetParNames("Constant","GaussPeak","Sigma");
for (Int_t i=0; i<3; i++) {
gausFit->SetParLimits(i,pllo[i],plhi[i]);
}
hNtoFit->Fit(gausFit,"R0");
gausFit->SetRange(fr[0],fr[1]);
pGausS=gausFit->GetParameters();
epGausS=gausFit->GetParErrors();
chi2GausS =langausFit->GetChisquare(); // obtain chi^2
nDofGausS = langausFit->GetNDF();// obtain ndf
TCanvas *cAllN = new TCanvas("NoiseFit",hNtoFit->GetTitle(),1);
Char_t fitFileName[60];
sprintf(fitFileName,"Fits/Run_%d/%s/Fit_%s.png",RunNumber,SubDetName,hNtoFit->GetTitle());
hNtoFit->Draw("pe");
gStyle->SetOptFit(1111111);
gausFit->Draw("lsame");
cAllN->Print(fitFileName,"png");
}else {
pGausS[0]=-10; pGausS[1]=-10; pGausS[2]=-10;
epGausS[0]=-10; epGausS[1]=-10; epGausS[2]=-10;
}
}
}
}
}
}
}
return hNtoFit->GetEntries();
}
Stat_t AnalysisClass::doFit(Int_t RunNumber,Char_t *Variable, Char_t *SubDetName, Char_t *Layer,Char_t *label){
TH1 *htoFit=0;
pLanGausS[0]=0; pLanGausS[1]=0; pLanGausS[2]=0; pLanGausS[3]=0;
epLanGausS[0]=0; epLanGausS[1]=0; epLanGausS[2]=0; epLanGausS[3]=0;
if (debug) cout << d1->GetTitle() << " " << Variable << " " << SubDetName << endl;
pPar[0]=0; pPar[1]=0;
TIter it(d1->GetListOfKeys());
TObject * o;
while ( (o = it()))
{
TObject * d = d1->Get(o->GetName());
if(d->IsA()->InheritsFrom("TDirectory") && strstr(d->GetName(),SubDetName)){
if (debug) cout << "Found " << SubDetName << endl;
TIter it2(((TDirectoryFile * )d)->GetListOfKeys());
TObject *o2;
while( ( o2 = it2()) ){
TObject *d2 = ((TDirectoryFile * )d)->Get(o2->GetName());
if(d2->IsA()->InheritsFrom("TDirectory") && strstr(d2->GetName(),Layer) ){
if (debug) cout << "Found Layer" << Layer << endl;
TIter it3(((TDirectoryFile * )d2)->GetListOfKeys());
TObject *o3;
while( ( o3 = it3()) ){
TObject *d3 = ((TDirectoryFile * )d2)->Get(o3->GetName());
if(strstr(d3->GetName(),Variable) && strstr(d3->GetName(),label)){
htoFit = (TH1*) d3;
if (debug) cout << "Found " << Variable << endl;
if (htoFit->GetEntries()!=0) {
cout<<"Fitting "<< htoFit->GetTitle() <<endl;
// Setting fit range and start values
Double_t fr[2];
Double_t sv[4], pllo[4], plhi[4];
fr[0]=0.5*htoFit->GetMean();
fr[1]=3.0*htoFit->GetMean();
// (EM) parameters setting good for signal only
Int_t imax=htoFit->GetMaximumBin();
Double_t xmax=htoFit->GetBinCenter(imax);
Double_t ymax=htoFit->GetBinContent(imax);
Int_t i[2];
Int_t iArea[2];
i[0]=htoFit->GetXaxis()->FindBin(fr[0]);
i[1]=htoFit->GetXaxis()->FindBin(fr[1]);
iArea[0]=htoFit->GetXaxis()->FindBin(fr[0]);
iArea[1]=htoFit->GetXaxis()->FindBin(fr[1]);
Double_t AreaFWHM=htoFit->Integral(iArea[0],iArea[1],"width");
sv[1]=xmax;
sv[2]=htoFit->Integral(i[0],i[1],"width");
sv[3]=AreaFWHM/(4*ymax);
sv[0]=sv[3];
plhi[0]=25.0; plhi[1]=200.0; plhi[2]=1000000.0; plhi[3]=50.0;
pllo[0]=1.5 ; pllo[1]=10.0 ; pllo[2]=1.0 ; pllo[3]= 1.0;
// create different landau+gaussians for different runs
Char_t FunName[100];
sprintf(FunName,"FitfcnLG_%s%d",htoFit->GetName(),fRun);
TF1 *ffitold = (TF1*)gROOT->GetListOfFunctions()->FindObject(FunName);
if (ffitold) delete ffitold;
langausFit = new TF1(FunName,langaufun,fr[0],fr[1],4);
langausFit->SetParameters(sv);
langausFit->SetParNames("Width","MP","Area","GSigma");
for (Int_t i=0; i<4; i++) {
langausFit->SetParLimits(i,pllo[i],plhi[i]);
}
htoFit->Fit(langausFit,"R0"); // "R" fit in a range,"0" quiet fit
langausFit->SetRange(fr[0],fr[1]);
pLanGausS=langausFit->GetParameters();
epLanGausS=langausFit->GetParErrors();
chi2GausS =langausFit->GetChisquare(); // obtain chi^2
nDofGausS = langausFit->GetNDF(); // obtain ndf
Double_t sPeak, sFWHM;
langaupro(pLanGausS,sPeak,sFWHM);
pLanConv[0]=sPeak;
pLanConv[1]=sFWHM;
cout << "langaupro: max " << sPeak << endl;
cout << "langaupro: FWHM " << sFWHM << endl;
TCanvas *cAll = new TCanvas("Fit",htoFit->GetTitle(),1);
Char_t fitFileName[60];
sprintf(fitFileName,"Fits/Run_%d/%s/Fit_%s.png",RunNumber,SubDetName,htoFit->GetTitle());
htoFit->Draw("pe");
htoFit->SetStats(100);
langausFit->Draw("lsame");
gStyle->SetOptFit(1111111);
cAll->Print(fitFileName,"png");
}
else {
pLanGausS[0]=-10; pLanGausS[1]=-10; pLanGausS[2]=-10; pLanGausS[3]=-10;
epLanGausS[0]=-10; epLanGausS[1]=-10; epLanGausS[2]=-10; epLanGausS[3]=-10;
pLanConv[0]=-10; pLanConv[1]=-10; chi2GausS=-10; nDofGausS=-10;
}
}
}
}
}
}
}
return htoFit->GetEntries();
}
void mergeForest(TString fname = "/data/jisun/temp/*.root",
TString outfile="/data/jisun/pp_2015_HeavyFlavor_AOD_tkpt1_D0pt1_eta2p5_D3d1_Prob0p05_1202.root",
bool failOnError = true)
{
// First, find on of the files within 'fname' and use it to make a
// list of trees. Unfortunately we have to know in advance at least
// one of the tree names. hiEvtAnalyzer/HiTree is a safe choice for
// HiForests. We also assume that every TTree is inside a
// TDirectoryFile which is in the top level of the root file.
TChain *dummyChain = new TChain("hltanalysis/HltTree");
dummyChain->Add(fname);
TFile *testFile = dummyChain->GetFile();
TList *topKeyList = testFile->GetListOfKeys();
std::vector<TString> trees;
std::vector<TString> dir;
for(int i = 0; i < topKeyList->GetEntries(); ++i)
{
TDirectoryFile *dFile = (TDirectoryFile*)testFile->Get(topKeyList->At(i)->GetName());
if(strcmp(dFile->ClassName(), "TDirectoryFile") != 0) continue;
TList *bottomKeyList = dFile->GetListOfKeys();
for(int j = 0; j < bottomKeyList->GetEntries(); ++j)
{
TString treeName = dFile->GetName();
treeName += "/";
treeName += bottomKeyList->At(j)->GetName();
TTree* tree = (TTree*)testFile->Get(treeName);
if(strcmp(tree->ClassName(), "TTree") != 0 && strcmp(tree->ClassName(), "TNtuple") != 0) continue;
trees.push_back(treeName);
dir.push_back(dFile->GetName());
}
}
testFile->Close();
delete dummyChain;
// Now use the list of tree names to make a new root file, filling
// it with the trees from 'fname'.
const int Ntrees = trees.size();
TChain* ch[Ntrees];
Long64_t nentries = 0;
for(int i = 0; i < Ntrees; ++i){
ch[i] = new TChain(trees[i]);
ch[i]->Add(fname);
std::cout << "Tree loaded : " << trees[i] << std::endl;
std::cout << "Entries : " << ch[i]->GetEntries() << std::endl;
// If the number of entries in this tree is different from other
// trees there is a problem. Quit and inform the user without
// producing output.
if(failOnError)
{
if(strcmp(trees[i],"HiForest/HiForestVersion") == 0) continue;
if(i == 0) nentries = ch[i]->GetEntries();
else if (nentries != ch[i]->GetEntries())
{
std::cout << "ERROR: number of entries in this tree does not match." << std::endl;
std::cout << "First inconsistent file: " <<ch[i]->GetFile()->GetName()<<std::endl;
std::cout << "Exiting. Please check input." << std::endl;
return;
}
}
else
{
std::cout << "WARN: error checking disabled" << std::endl;
}
}
TFile* file = new TFile(outfile, "RECREATE");
for(int i = 0; i < Ntrees; ++i)
{
file->cd();
std::cout << trees[i] << std::endl;
if (i==0)
{
file->mkdir(dir[i])->cd();
}
else
{
if ( dir[i] != dir[i-1] )
file->mkdir(dir[i])->cd();
else
file->cd(dir[i]);
}
ch[i]->Merge(file,0,"keep");
delete ch[i];
}
//file->Write();
file->Close();
std::cout << "Done. Output: " << outfile << std::endl;
}
void RunPlots(const char* data_dir, int first_run, const int n_runs) {
gROOT->Reset();
gROOT->SetStyle("Plain");
gStyle->SetCanvasBorderMode(0); // turn off canvas borders
TCanvas* c1 = new TCanvas("c1", "c1");
// Go through the runs and create a PDF for each one
for (int iRun = 0; iRun < n_runs; ++iRun) {
// Open up the file for this run
std::stringstream filename;
filename << data_dir << "/hist/hist0" << first_run + iRun << ".root";
TFile* file = new TFile(filename.str().c_str(), "READ");
// Create the output PDF file to save all the plots to
std::stringstream basepdfname;
basepdfname << "DQ_LowLevel_RunPlots_Run0" << first_run + iRun << ".pdf";
std::string openpdfname = basepdfname.str() + "[";
std::string closepdfname = basepdfname.str() + "]";
c1->Print(openpdfname.c_str());
TIter nextFileKey(file->GetListOfKeys()); // get the list of keys in this file
TKey *fileKey;
while (fileKey = (TKey*)nextFileKey()) {
// Get the directory for low-level data quality plots
if (strcmp(fileKey->ReadObj()->ClassName(), "TDirectoryFile") == 0) {
// Check that the directory has the correct name
if (strcmp(fileKey->ReadObj()->GetName(), "DataQuality_LowLevel") == 0) {
TDirectoryFile* dir = (TDirectoryFile*) fileKey->ReadObj();
TIter nextDirKey(dir->GetListOfKeys()); // get the list of keys in the directory (all histograms should be in this folder)
TKey *dirKey;
while (dirKey = (TKey*)nextDirKey()) {
if (strcmp(dirKey->ReadObj()->ClassName(), "TH1F") == 0) {
// Get histogram and print
TH1F* hist = (TH1F*) dirKey->ReadObj();
hist->Draw();
c1->Update();
c1->Print(basepdfname.str().c_str());
}
else if (strcmp(dirKey->ReadObj()->ClassName(), "TH2F") == 0) {
TH2F* hist = (TH2F*) dirKey->ReadObj();
// Search through the histogram name
if (strstr(hist->GetName(), "PulseShapes") != NULL) {
c1->SetLogz();
}
hist->Draw("COLZ");
c1->Update();
c1->Print(basepdfname.str().c_str());
} // end if statements
// Undo any c1 log scales
c1->SetLogz(0);
} // end while loop through histograms in directory
} // end if correctly name directory
} // end if the key is a directory
} // end while loop through keys in file
// Close the PDF file
c1->Print(closepdfname.c_str());
} // end loop through each run file
}
