DQMHistAnalysisSVDEfficiency.cc

/**************************************************************************
 * basf2 (Belle II Analysis Software Framework)                           *
 * Author: The Belle II Collaboration                                     *
 *                                                                        *
 * See git log for contributors and copyright holders.                    *
 * This file is licensed under LGPL-3.0, see LICENSE.md.                  *
 **************************************************************************/
//+
// File : DQMHistAnalysisSVDEfficiency.cc
// Description : module for DQM histogram analysis of SVD sensors efficiencies
//-
 
 
#include <dqm/analysis/modules/DQMHistAnalysisSVDEfficiency.h>
#include <vxd/geometry/GeoCache.h>
 
#include <TROOT.h>
#include <TStyle.h>
#include <TString.h>
 
using namespace std;
using namespace Belle2;
 
//-----------------------------------------------------------------
//                 Register the Module
//-----------------------------------------------------------------
REG_MODULE(DQMHistAnalysisSVDEfficiency);
 
//-----------------------------------------------------------------
//                 Implementation
//-----------------------------------------------------------------
 
DQMHistAnalysisSVDEfficiencyModule::DQMHistAnalysisSVDEfficiencyModule()
  : DQMHistAnalysisModule(),
    m_effUstatus(good),
    m_effVstatus(good)
{
  //Parameter definition
  B2DEBUG(10, "DQMHistAnalysisSVDEfficiency: Constructor done.");
 
  setDescription("DQM Analysis Module that computes the average SVD sensor efficiency.");
 
  addParam("RefHistoFile", m_refFileName, "Reference histogram file name", std::string("SVDrefHisto.root"));
  addParam("effLevel_Error", m_effError, "Efficiency error (%) level (red)", double(0.9));
  addParam("effLevel_Warning", m_effWarning, "Efficiency WARNING (%) level (orange)", double(0.94));
  addParam("statThreshold", m_statThreshold, "minimal number of tracks per sensor to set green/red alert", double(100));
  addParam("samples3", m_3Samples, "if True 3 samples histograms analysis is performed", bool(false));
  addParam("PVPrefix", m_pvPrefix, "PV Prefix", std::string("SVD:"));
}
 
DQMHistAnalysisSVDEfficiencyModule::~DQMHistAnalysisSVDEfficiencyModule() { }
 
void DQMHistAnalysisSVDEfficiencyModule::initialize()
{
  B2DEBUG(10, "DQMHistAnalysisSVDEfficiency: initialize");
 
  //build the legend
  m_legProblem = new TPaveText(0.62, 0.22, 0.88, 0.35, "brNDC");
  m_legProblem->AddText("ERROR!");
  m_legProblem->AddText("at least one sensor with:");
  m_legProblem->AddText(Form("efficiency < %1.0f%%", m_effError * 100));
  m_legProblem->SetFillColor(c_ColorDefault);
  m_legProblem->SetLineColor(kBlack);
 
  m_legWarning = new TPaveText(0.62, 0.22, 0.88, 0.35, "brNDC");
  m_legWarning->AddText("WARNING!");
  m_legWarning->AddText("at least one sensor with:");
  m_legWarning->AddText(Form("%1.0f%% < efficiency < %1.0f%%", m_effError * 100, m_effWarning * 100));
  m_legWarning->SetFillColor(c_ColorDefault);
  m_legWarning->SetLineColor(kBlack);
 
  m_legNormal = new TPaveText(0.62, 0.22, 0.88, 0.35, "brNDC");
  m_legNormal->AddText("EFFICIENCY WITHIN LIMITS");
  m_legNormal->AddText(Form("efficiency > %1.0f%%", m_effWarning * 100));
  m_legNormal->SetFillColor(c_ColorDefault);
  m_legNormal->SetLineColor(kBlack);
 
  m_legEmpty = new TPaveText(0.62, 0.22, 0.88, 0.35, "brNDC");
  m_legEmpty->AddText("Not enough statistics,");
  m_legEmpty->AddText("check again in a few minutes");
  m_legEmpty->SetFillColor(c_ColorDefault);
  m_legEmpty->SetTextColor(kWhite);
  m_legEmpty->SetLineColor(kBlack);
 
 
  const VXD::GeoCache& geo = VXD::GeoCache::getInstance();
 
  //collect the list of all SVD Modules in the geometry here
  std::vector<VxdID> sensors = geo.getListOfSensors();
  for (VxdID& aVxdID : sensors) {
    VXD::SensorInfoBase info = geo.getSensorInfo(aVxdID);
    // B2INFO("VXD " << aVxdID);
    if (info.getType() != VXD::SensorInfoBase::SVD) continue;
    m_SVDModules.push_back(aVxdID); // reorder, sort would be better
  }
  std::sort(m_SVDModules.begin(), m_SVDModules.end());  // back to natural order
 
 
  gROOT->cd();
  m_cEfficiencyU = new TCanvas("SVDAnalysis/c_SVDEfficiencyU");
  m_cEfficiencyV = new TCanvas("SVDAnalysis/c_SVDEfficiencyV");
  m_cEfficiencyErrU = new TCanvas("SVDAnalysis/c_SVDEfficiencyErrU");
  m_cEfficiencyErrV = new TCanvas("SVDAnalysis/c_SVDEfficiencyErrV");
 
  m_hEfficiency = new SVDSummaryPlots("SVDEfficiency@view", "Summary of SVD efficiencies (%), @view/@side Side");
  m_hEfficiency->setStats(0);
  m_hEfficiencyErr = new SVDSummaryPlots("SVDEfficiencyErr@view", "Summary of SVD efficiencies errors (%), @view/@side Side");
  m_hEfficiencyErr->setStats(0);
 
 
  if (m_3Samples) {
    m_cEfficiencyU3Samples = new TCanvas("SVDAnalysis/c_SVDEfficiencyU3Samples");
    m_cEfficiencyV3Samples = new TCanvas("SVDAnalysis/c_SVDEfficiencyV3Samples");
    m_cEfficiencyErrU3Samples = new TCanvas("SVDAnalysis/c_SVDEfficiencyErrU3Samples");
    m_cEfficiencyErrV3Samples = new TCanvas("SVDAnalysis/c_SVDEfficiencyErrV3Samples");
 
    m_hEfficiency3Samples = new SVDSummaryPlots("SVD3Efficiency@view",
                                                "Summary of SVD efficiencies (%), @view/@side Side for 3 samples");
    m_hEfficiency3Samples->setStats(0);
 
    m_hEfficiencyErr3Samples = new SVDSummaryPlots("SVD3EfficiencyErr@view",
                                                   "Summary of SVD efficiencies errors (%), @view/@side Side for 3 samples");
    m_hEfficiencyErr3Samples->setStats(0);
 
  }
 
  //register limits for EPICS
  registerEpicsPV(m_pvPrefix + "efficiencyLimits", "effLimits");
 
  //find nEvents testing if histograms are present
  TH1* hnEvnts = findHist("SVDExpReco/SVDDQM_nEvents");
  if (hnEvnts == NULL) {
    B2INFO("no events, nothing to do here");
    return;
  }
 
}
 
void DQMHistAnalysisSVDEfficiencyModule::beginRun()
{
  B2DEBUG(10, "DQMHistAnalysisSVDEfficiency: beginRun called.");
 
  if (m_cEfficiencyU)
    m_cEfficiencyU->Clear();
  if (m_cEfficiencyV)
    m_cEfficiencyV->Clear();
  if (m_cEfficiencyErrU)
    m_cEfficiencyErrU->Clear();
  if (m_cEfficiencyErrV)
    m_cEfficiencyErrV->Clear();
 
  if (m_3Samples) {
    if (m_cEfficiencyU3Samples)
      m_cEfficiencyU3Samples->Clear();
    if (m_cEfficiencyV3Samples)
      m_cEfficiencyV3Samples->Clear();
    if (m_cEfficiencyErrU3Samples)
      m_cEfficiencyErrU3Samples->Clear();
    if (m_cEfficiencyErrV3Samples)
      m_cEfficiencyErrV3Samples->Clear();
  }
 
  //Retrieve limits from EPICS
  double effErrorLo = 0.;
  double effWarnLo = 0.;
 
  requestLimitsFromEpicsPVs("effLimits", effErrorLo, effWarnLo, m_effWarning,  m_effError);
 
  B2DEBUG(10, " SVD efficiency thresholds taken from EPICS configuration file:");
  B2DEBUG(10, "  EFFICIENCY: normal > " << m_effWarning << " > warning > " << m_effError << " > error with minimum statistics of " <<
          m_statThreshold);
}
 
void DQMHistAnalysisSVDEfficiencyModule::event()
{
  B2DEBUG(10, "DQMHistAnalysisSVDEfficiency: event called.");
 
  //find nEvents
  TH1* hnEvnts = findHist("SVDExpReco/SVDDQM_nEvents", true);
  if (hnEvnts == NULL) {
    B2INFO("no events, nothing to do here");
    return;
  } else {
    B2DEBUG(10, "SVDExpReco/SVDDQM_nEvents found");
  }
 
  TString tmp = hnEvnts->GetTitle();
  Int_t pos = tmp.Last('~');
  if (pos == -1) pos = 0;
 
  TString runID = tmp(pos, tmp.Length() - pos);
  B2INFO("DQMHistAnalysisSVDEfficiencyModule::runID = " << runID);
 
  gStyle->SetOptStat(0);
  gStyle->SetPaintTextFormat("2.1f");
 
  // do it by nhand, the interface of the SVDSummaryPlots does not allow to change the title after cstr
  if (m_hEfficiency) {
    m_hEfficiency->reset();
    m_hEfficiency->setRunID(runID);
  }
 
  if (m_hEfficiencyErr) {
    m_hEfficiencyErr->reset();
    m_hEfficiencyErr->setRunID(runID);
  }
 
  if (m_3Samples) {
    if (m_hEfficiency3Samples) {
      m_hEfficiency3Samples->reset();
      m_hEfficiency3Samples->setRunID(runID);
    }
 
    if (m_hEfficiencyErr3Samples) {
      m_hEfficiencyErr3Samples->reset();
      m_hEfficiencyErr3Samples->setRunID(runID);
    }
  }
 
  Float_t effU = -1;
  Float_t effV = -1;
  Float_t erreffU = -1;
  Float_t erreffV = -1;
 
  // Efficiency for the U side
  TH2F* found_tracksU = (TH2F*)findHist("SVDEfficiency/TrackHitsU");
  TH2F* matched_clusU = (TH2F*)findHist("SVDEfficiency/MatchedHitsU");
 
  if (matched_clusU == NULL || found_tracksU == NULL) {
    B2INFO("Histograms needed for Efficiency computation are not found");
    m_cEfficiencyU->Draw();
    m_cEfficiencyU->cd();
    m_hEfficiency->getHistogram(1)->Draw("text");
    colorizeCanvas(m_cEfficiencyU, c_StatusDefault);
  } else {
    B2DEBUG(10, "U-side Before loop on sensors, size :" << m_SVDModules.size());
    m_effUstatus = good;
    for (unsigned int i = 0; i < m_SVDModules.size(); i++) {
      B2DEBUG(10, "module " << i << "," << m_SVDModules[i]);
      int bin = found_tracksU->FindBin(m_SVDModules[i].getLadderNumber(), findBinY(m_SVDModules[i].getLayerNumber(),
                                       m_SVDModules[i].getSensorNumber()));
      float numU = matched_clusU->GetBinContent(bin);
      float denU = found_tracksU->GetBinContent(bin);
      if (denU > 0)
        effU = numU / denU;
      else
        effU = -1;
      B2DEBUG(10, "effU  = " << numU << "/" << denU << " = " << effU);
      m_hEfficiency->fill(m_SVDModules[i], 1, effU * 100);
      if (effU == -1)
        erreffU = -1;
      else
        erreffU = std::sqrt(effU * (1 - effU) / denU);
      m_hEfficiencyErr->fill(m_SVDModules[i], 1, erreffU * 100);
 
      if (denU < m_statThreshold) {
        m_effUstatus = std::max(lowStat, m_effUstatus);
      } else if (effU > m_effWarning) {
        m_effUstatus = std::max(good, m_effUstatus);
      } else if ((effU <= m_effWarning) && (effU > m_effError)) {
        m_effUstatus = std::max(warning, m_effUstatus);
      } else if ((effU <= m_effError)) {
        m_effUstatus = std::max(error, m_effUstatus);
      }
      B2DEBUG(10, "Status is " << m_effUstatus);
    }
  }
 
  //Efficiency for the V side
  TH2F* found_tracksV = (TH2F*)findHist("SVDEfficiency/TrackHitsV");
  TH2F* matched_clusV = (TH2F*)findHist("SVDEfficiency/MatchedHitsV");
 
  if (matched_clusV == NULL || found_tracksV == NULL) {
    B2INFO("Histograms needed for Efficiency computation are not found");
    m_cEfficiencyV->cd();
    m_cEfficiencyV->Draw();
    m_hEfficiency->getHistogram(0)->Draw("text");
    colorizeCanvas(m_cEfficiencyV, c_StatusDefault);
  } else {
    B2DEBUG(10, "V-side Before loop on sensors, size :" << m_SVDModules.size());
    m_effVstatus = good;
    for (unsigned int i = 0; i < m_SVDModules.size(); i++) {
      B2DEBUG(10, "module " << i << "," << m_SVDModules[i]);
      int bin = found_tracksV->FindBin(m_SVDModules[i].getLadderNumber(), findBinY(m_SVDModules[i].getLayerNumber(),
                                       m_SVDModules[i].getSensorNumber()));
      float numV = matched_clusV->GetBinContent(bin);
      float denV = found_tracksV->GetBinContent(bin);
      if (denV > 0)
        effV = numV / denV;
      else
        effV = -1;
 
      B2DEBUG(10, "effV  = " << numV << "/" << denV << " = " << effV);
      m_hEfficiency->fill(m_SVDModules[i], 0, effV * 100);
      if (effV == -1)
        erreffV = -1;
      else
        erreffV = std::sqrt(effV * (1 - effV) / denV);
 
      m_hEfficiencyErr->fill(m_SVDModules[i], 0, erreffV * 100);
 
      if (denV < m_statThreshold) {
        m_effVstatus = std::max(lowStat, m_effVstatus);
      } else if (effV > m_effWarning) {
        m_effVstatus = std::max(good, m_effVstatus);
      } else if ((effV <= m_effWarning) && (effV > m_effError)) {
        m_effVstatus = std::max(warning, m_effVstatus);
      } else if ((effV <= m_effError)) {
        m_effVstatus = std::max(error, m_effVstatus);
      }
      B2DEBUG(10, "Status is " << m_effVstatus);
    }
  }
 
  // update summary for U side
  m_cEfficiencyU->Draw();
  m_cEfficiencyU->cd();
  if (m_hEfficiency)
    m_hEfficiency->getHistogram(1)->Draw("text");
 
  switch (m_effUstatus) {
    case good: {
      colorizeCanvas(m_cEfficiencyU, c_StatusGood);
      m_legNormal->Draw();
      break;
    }
    case error: {
      colorizeCanvas(m_cEfficiencyU, c_StatusError);
      m_legProblem->Draw();
      break;
    }
    case warning: {
      colorizeCanvas(m_cEfficiencyU, c_StatusWarning);
      m_legWarning->Draw();
      break;
    }
    case lowStat: {
      colorizeCanvas(m_cEfficiencyU, c_StatusTooFew);
      m_legEmpty->Draw();
      break;
    }
    default: {
      B2INFO("effUstatus not set properly: " << m_effUstatus);
      break;
    }
  }
//   setEpicsPV("EfficiencyUAlarm", alarm);
 
  m_cEfficiencyU->Update();
  m_cEfficiencyU->Modified();
  m_cEfficiencyU->Update();
 
  // update summary for V side
  m_cEfficiencyV->cd();
  m_cEfficiencyV->Draw();
  if (m_hEfficiency)
    m_hEfficiency->getHistogram(0)->Draw("text");
 
  switch (m_effVstatus) {
    case good: {
      colorizeCanvas(m_cEfficiencyV, c_StatusGood);
      m_legNormal->Draw();
      break;
    }
    case error: {
      colorizeCanvas(m_cEfficiencyV, c_StatusError);
      m_legProblem->Draw();
      break;
    }
    case warning: {
      colorizeCanvas(m_cEfficiencyV, c_StatusWarning);
      m_legWarning->Draw();
      break;
    }
    case lowStat: {
      colorizeCanvas(m_cEfficiencyV, c_StatusTooFew);
      m_legEmpty->Draw();
      break;
    }
    default: {
      B2INFO("effVstatus not set properly: " << m_effVstatus);
      break;
    }
  }
 
  m_cEfficiencyV->Update();
  m_cEfficiencyV->Modified();
  m_cEfficiencyV->Update();
 
  m_cEfficiencyErrU->cd();
  if (m_hEfficiencyErr)
    m_hEfficiencyErr->getHistogram(1)->Draw("colztext");
  m_cEfficiencyErrU->Draw();
  m_cEfficiencyErrU->Update();
  m_cEfficiencyErrU->Modified();
  m_cEfficiencyErrU->Update();
 
  m_cEfficiencyErrV->cd();
  if (m_hEfficiencyErr)
    m_hEfficiencyErr->getHistogram(0)->Draw("colztext");
  m_cEfficiencyErrV->Draw();
  m_cEfficiencyErrV->Update();
  m_cEfficiencyErrV->Modified();
  m_cEfficiencyErrV->Update();
 
  if (m_3Samples) {
    m_hEfficiency3Samples->getHistogram(0)->Reset();
    m_hEfficiency3Samples->getHistogram(1)->Reset();
    m_hEfficiencyErr3Samples->getHistogram(0)->Reset();
    m_hEfficiencyErr3Samples->getHistogram(1)->Reset();
 
    // Efficiency for the U side - 3 samples
    TH2F* found3_tracksU = (TH2F*)findHist("SVDEfficiency/TrackHits3U");
    TH2F* matched3_clusU = (TH2F*)findHist("SVDEfficiency/MatchedHits3U");
 
    if (matched3_clusU == NULL || found3_tracksU == NULL) {
      B2INFO("Histograms needed for Efficiency computation are not found");
      m_cEfficiencyU3Samples->Draw();
      m_cEfficiencyU3Samples->cd();
      m_hEfficiency3Samples->getHistogram(1)->Draw("text");
      colorizeCanvas(m_cEfficiencyU3Samples, c_StatusDefault);
    } else {
      B2DEBUG(10, "U-side Before loop on sensors, size :" << m_SVDModules.size());
      m_effUstatus = good;
      for (unsigned int i = 0; i < m_SVDModules.size(); i++) {
        B2DEBUG(10, "module " << i << "," << m_SVDModules[i]);
        int bin = found3_tracksU->FindBin(m_SVDModules[i].getLadderNumber(), findBinY(m_SVDModules[i].getLayerNumber(),
                                          m_SVDModules[i].getSensorNumber()));
        float numU = matched3_clusU->GetBinContent(bin);
        float denU = found3_tracksU->GetBinContent(bin);
        if (denU > 0)
          effU = numU / denU;
        else
          effU = -1;
        B2DEBUG(10, "effU  = " << numU << "/" << denU << " = " << effU);
 
        m_hEfficiency3Samples->fill(m_SVDModules[i], 1, effU * 100);
        if (effU == -1)
          erreffU = -1;
        else
          erreffU = std::sqrt(effU * (1 - effU) / denU);
        m_hEfficiencyErr3Samples->fill(m_SVDModules[i], 1, erreffU * 100);
 
        if (denU < m_statThreshold) {
          m_effUstatus = std::max(lowStat, m_effUstatus);
        } else if (effU > m_effWarning) {
          m_effUstatus = std::max(good, m_effUstatus);
        } else if ((effU <= m_effWarning) && (effU > m_effError)) {
          m_effUstatus = std::max(warning, m_effUstatus);
        } else if ((effU <= m_effError)) {
          m_effUstatus = std::max(error, m_effUstatus);
        }
        B2DEBUG(10, "Status is " << m_effUstatus);
      }
    }
 
    //Efficiency for the V side - 3 samples
    TH2F* found3_tracksV = (TH2F*)findHist("SVDEfficiency/TrackHits3V");
    TH2F* matched3_clusV = (TH2F*)findHist("SVDEfficiency/MatchedHits3V");
 
    if (matched3_clusV == NULL || found3_tracksV == NULL) {
      B2INFO("Histograms needed for Efficiency computation are not found");
      m_cEfficiencyV3Samples->Draw();
      m_cEfficiencyV3Samples->cd();
      m_hEfficiency3Samples->getHistogram(1)->Draw("text");
      colorizeCanvas(m_cEfficiencyV3Samples, c_StatusDefault);
    } else {
      B2DEBUG(10, "V-side Before loop on sensors, size :" << m_SVDModules.size());
      m_effVstatus = good;
      for (unsigned int i = 0; i < m_SVDModules.size(); i++) {
        B2DEBUG(10, "module " << i << "," << m_SVDModules[i]);
        int bin = found3_tracksV->FindBin(m_SVDModules[i].getLadderNumber(), findBinY(m_SVDModules[i].getLayerNumber(),
                                          m_SVDModules[i].getSensorNumber()));
        float numV = matched3_clusV->GetBinContent(bin);
        float denV = found3_tracksV->GetBinContent(bin);
        if (denV > 0)
          effV = numV / denV;
        else
          effV = -1;
 
        B2DEBUG(10, "effV  = " << numV << "/" << denV << " = " << effV);
        m_hEfficiency3Samples->fill(m_SVDModules[i], 0, effV * 100);
        if (effV == -1)
          erreffV = -1;
        else
          erreffV = std::sqrt(effV * (1 - effV) / denV);
 
        m_hEfficiencyErr3Samples->fill(m_SVDModules[i], 0, erreffV * 100);
 
        if (denV < m_statThreshold) {
          m_effVstatus = std::max(lowStat, m_effVstatus);
        } else if (effV > m_effWarning) {
          m_effVstatus = std::max(good, m_effVstatus);
        } else if ((effV <= m_effWarning) && (effV > m_effError)) {
          m_effVstatus = std::max(warning, m_effVstatus);
        } else if ((effV <= m_effError)) {
          m_effVstatus = std::max(error, m_effVstatus);
        }
        B2DEBUG(10, "Status is " << m_effVstatus);
      }
    }
 
    // update summary for U side
    m_cEfficiencyU3Samples->Draw();
    m_cEfficiencyU3Samples->cd();
    if (m_hEfficiency3Samples)
      m_hEfficiency3Samples->getHistogram(1)->Draw("text");
 
    switch (m_effUstatus) {
      case good: {
        colorizeCanvas(m_cEfficiencyU3Samples, c_StatusGood);
        m_legNormal->Draw();
        break;
      }
      case error: {
        colorizeCanvas(m_cEfficiencyU3Samples, c_StatusError);
        m_legProblem->Draw();
        break;
      }
      case warning: {
        colorizeCanvas(m_cEfficiencyU3Samples, c_StatusWarning);
        m_legWarning->Draw();
        break;
      }
      case lowStat: {
        colorizeCanvas(m_cEfficiencyU3Samples, c_StatusTooFew);
        m_legEmpty->Draw();
        break;
      }
      default: {
        B2INFO("effUstatus not set properly: " << m_effUstatus);
        break;
      }
    }
 
    m_cEfficiencyU3Samples->Update();
    m_cEfficiencyU3Samples->Modified();
    m_cEfficiencyU3Samples->Update();
 
    // update summary for V side
    m_cEfficiencyV3Samples->Draw();
    m_cEfficiencyV3Samples->cd();
    if (m_hEfficiency3Samples)
      m_hEfficiency3Samples->getHistogram(0)->Draw("text");
 
    switch (m_effVstatus) {
      case good: {
        colorizeCanvas(m_cEfficiencyV3Samples, c_StatusGood);
        m_legNormal->Draw();
        break;
      }
      case error: {
        colorizeCanvas(m_cEfficiencyV3Samples, c_StatusError);
        m_legProblem->Draw();
        break;
      }
      case warning: {
        colorizeCanvas(m_cEfficiencyV3Samples, c_StatusWarning);
        m_legWarning->Draw();
        break;
      }
      case lowStat: {
        colorizeCanvas(m_cEfficiencyV3Samples, c_StatusTooFew);
        m_legEmpty->Draw();
        break;
      }
      default: {
        B2INFO("effVstatus not set properly: " << m_effVstatus);
        break;
      }
    }
 
    m_cEfficiencyV3Samples->Update();
    m_cEfficiencyV3Samples->Modified();
    m_cEfficiencyV3Samples->Update();
 
    m_cEfficiencyErrU3Samples->cd();
    if (m_hEfficiencyErr3Samples)
      m_hEfficiencyErr3Samples->getHistogram(1)->Draw("colztext");
    m_cEfficiencyErrU3Samples->Draw();
    m_cEfficiencyErrU3Samples->Update();
    m_cEfficiencyErrU3Samples->Modified();
    m_cEfficiencyErrU3Samples->Update();
 
    m_cEfficiencyErrV3Samples->cd();
    if (m_hEfficiencyErr3Samples)
      m_hEfficiencyErr3Samples->getHistogram(0)->Draw("colztext");
    m_cEfficiencyErrV3Samples->Draw();
    m_cEfficiencyErrV3Samples->Update();
    m_cEfficiencyErrV3Samples->Modified();
    m_cEfficiencyErrV3Samples->Update();
  }
}
 
void DQMHistAnalysisSVDEfficiencyModule::endRun()
{
  B2DEBUG(10, "DQMHistAnalysisSVDEfficiency:  endRun called");
}
 
void DQMHistAnalysisSVDEfficiencyModule::terminate()
{
  B2DEBUG(10, "DQMHistAnalysisSVDEfficiency: terminate called");
 
  delete m_refFile;
  delete m_legProblem;
  delete m_legWarning;
  delete m_legNormal;
  delete m_legEmpty;
 
  delete m_hEfficiency;
  delete m_cEfficiencyU;
  delete m_cEfficiencyV;
  delete m_hEfficiencyErr;
  delete m_cEfficiencyErrU;
  delete m_cEfficiencyErrV;
 
  if (m_3Samples) {
    delete m_hEfficiency3Samples;
    delete m_cEfficiencyU3Samples;
    delete m_cEfficiencyV3Samples;
    delete m_hEfficiencyErr3Samples;
    delete m_cEfficiencyErrU3Samples;
    delete m_cEfficiencyErrV3Samples;
  }
}
 
// return y coordinate in TH2F histogram for specified sensor
Int_t DQMHistAnalysisSVDEfficiencyModule::findBinY(Int_t layer, Int_t sensor)
{
  if (layer == 3)
    return sensor; //2 -> 1,2
  if (layer == 4)
    return 2 + 1 + sensor; //6 -> 4,5,6
  if (layer == 5)
    return 6 + 1 + sensor; // 11 -> 8, 9, 10, 11
  if (layer == 6)
    return 11 + 1 + sensor; // 17 -> 13, 14, 15, 16, 17
  else
    return -1;
}