SiPixelSCurveCalibrationAnalysis.cc

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#include "CalibTracker/SiPixelSCurveCalibration/interface/SiPixelSCurveCalibrationAnalysis.h"
#include "TMath.h"

#include <fstream>
#include <iostream>

#include "CondFormats/SiPixelObjects/interface/DetectorIndex.h"
#include "CondFormats/SiPixelObjects/interface/ElectronicIndex.h"
#include "CondFormats/SiPixelObjects/interface/LocalPixel.h"
#include "CondFormats/SiPixelObjects/interface/SiPixelFrameConverter.h"
#include "DataFormats/SiPixelDigi/interface/SiPixelCalibDigiError.h"
#include "Geometry/Records/interface/TrackerDigiGeometryRecord.h"
#include <sstream>

// initialize static members
std::vector<float> SiPixelSCurveCalibrationAnalysis::efficiencies_(0);
std::vector<float> SiPixelSCurveCalibrationAnalysis::effErrors_(0);

void SiPixelSCurveCalibrationAnalysis::calibrationEnd() {
  if (printoutthresholds_)
    makeThresholdSummary();
}

void SiPixelSCurveCalibrationAnalysis::makeThresholdSummary(void) {
  std::ofstream myfile;
  myfile.open(thresholdfilename_.c_str());
  for (detIDHistogramMap::iterator thisDetIdHistoGrams = histograms_.begin(); thisDetIdHistoGrams != histograms_.end();
       ++thisDetIdHistoGrams) {
    // loop over det id (det id = number (unsigned int) of pixel module
    const MonitorElement *sigmahist = (*thisDetIdHistoGrams).second[kSigmas];
    const MonitorElement *thresholdhist = (*thisDetIdHistoGrams).second[kThresholds];
    uint32_t detid = (*thisDetIdHistoGrams).first;
    std::string name = sigmahist->getTitle();
    std::string rocname = name.substr(0, name.size() - 7);
    rocname += "_ROC";
    int total_rows = sigmahist->getNbinsY();
    int total_columns = sigmahist->getNbinsX();
    // loop over all rows on columns on all ROCs
    for (int irow = 0; irow < total_rows; ++irow) {
      for (int icol = 0; icol < total_columns; ++icol) {
        float threshold_error = sigmahist->getBinContent(icol + 1, irow + 1);  // +1 because root bins start at 1
        if (writeZeroes_ || (!writeZeroes_ && threshold_error > 0)) {
          // changing from offline to online numbers
          int realfedID = -1;
          for (int fedid = 0; fedid <= 40; ++fedid) {
            SiPixelFrameConverter converter(theCablingMap_.product(), fedid);
            if (converter.hasDetUnit(detid)) {
              realfedID = fedid;
              break;
            }
          }
          if (realfedID == -1) {
            std::cout << "error: could not obtain real fed ID" << std::endl;
          }
          sipixelobjects::DetectorIndex detector = {detid, irow, icol};
          sipixelobjects::ElectronicIndex cabling;
          SiPixelFrameConverter formatter(theCablingMap_.product(), realfedID);
          formatter.toCabling(cabling, detector);
          // cabling should now contain cabling.roc and cabling.dcol  and
          // cabling.pxid however, the coordinates now need to be converted from
          // dcl,pxid to the row,col coordinates used in the calibration info
          sipixelobjects::LocalPixel::DcolPxid loc;
          loc.dcol = cabling.dcol;
          loc.pxid = cabling.pxid;
          // FIX to adhere to new cabling map. To be replaced with
          // CalibTracker/SiPixelTools detid - > hardware id classes ASAP.
          //        const sipixelobjects::PixelFEDCabling *theFed=
          //        theCablingMap.product()->fed(realfedID); const
          //        sipixelobjects::PixelFEDLink * link =
          //        theFed->link(cabling.link); const sipixelobjects::PixelROC
          //        *theRoc = link->roc(cabling.roc);
          sipixelobjects::LocalPixel locpixel(loc);
          sipixelobjects::CablingPathToDetUnit path = {static_cast<unsigned int>(realfedID),
                                                       static_cast<unsigned int>(cabling.link),
                                                       static_cast<unsigned int>(cabling.roc)};
          const sipixelobjects::PixelROC *theRoc = theCablingMap_->findItem(path);
          // END of FIX
          int newrow = locpixel.rocRow();
          int newcol = locpixel.rocCol();
          myfile << rocname << theRoc->idInDetUnit() << " " << newcol << " " << newrow << " "
                 << thresholdhist->getBinContent(icol + 1, irow + 1) << " "
                 << threshold_error;  // +1 because root bins start at 1
          myfile << "\n";
        }
      }
    }
  }
  myfile.close();
}

// used for TMinuit fitting
void chi2toMinimize(int &npar, double *grad, double &fcnval, double *xval, int iflag) {
  TF1 *theFormula = SiPixelSCurveCalibrationAnalysis::fitFunction_;
  // setup function parameters
  for (int i = 0; i < npar; i++)
    theFormula->SetParameter(i, xval[i]);
  fcnval = 0;
  // compute Chi2 of all points
  const std::vector<short> *theVCalValues = SiPixelSCurveCalibrationAnalysis::getVcalValues();
  for (uint32_t i = 0; i < theVCalValues->size(); i++) {
    float chi = (SiPixelSCurveCalibrationAnalysis::efficiencies_[i] - theFormula->Eval((*theVCalValues)[i]));
    chi /= SiPixelSCurveCalibrationAnalysis::effErrors_[i];
    fcnval += chi * chi;
  }
}

void SiPixelSCurveCalibrationAnalysis::doSetup(const edm::ParameterSet &iConfig) {
  edm::LogInfo("SiPixelSCurveCalibrationAnalysis") << "Setting up calibration paramters.";
  std::vector<uint32_t> anEmptyDefaultVectorOfUInts;
  std::vector<uint32_t> detIDsToSaveVector_;
  useDetectorHierarchyFolders_ = iConfig.getUntrackedParameter<bool>("useDetectorHierarchyFolders", true);
  saveCurvesThatFlaggedBad_ = iConfig.getUntrackedParameter<bool>("saveCurvesThatFlaggedBad", false);
  detIDsToSaveVector_ =
      iConfig.getUntrackedParameter<std::vector<uint32_t>>("detIDsToSave", anEmptyDefaultVectorOfUInts);
  maxCurvesToSave_ = iConfig.getUntrackedParameter<uint32_t>("maxCurvesToSave", 1000);
  write2dHistograms_ = iConfig.getUntrackedParameter<bool>("write2dHistograms", true);
  write2dFitResult_ = iConfig.getUntrackedParameter<bool>("write2dFitResult", true);
  printoutthresholds_ = iConfig.getUntrackedParameter<bool>("writeOutThresholdSummary", true);
  thresholdfilename_ = iConfig.getUntrackedParameter<std::string>("thresholdOutputFileName", "thresholds.txt");
  minimumChi2prob_ = iConfig.getUntrackedParameter<double>("minimumChi2prob", 0);
  minimumThreshold_ = iConfig.getUntrackedParameter<double>("minimumThreshold", -10);
  maximumThreshold_ = iConfig.getUntrackedParameter<double>("maximumThreshold", 300);
  minimumSigma_ = iConfig.getUntrackedParameter<double>("minimumSigma", 0);
  maximumSigma_ = iConfig.getUntrackedParameter<double>("maximumSigma", 100);
  minimumEffAsymptote_ = iConfig.getUntrackedParameter<double>("minimumEffAsymptote", 0);
  maximumEffAsymptote_ = iConfig.getUntrackedParameter<double>("maximumEffAsymptote", 1000);
  maximumSigmaBin_ = iConfig.getUntrackedParameter<double>("maximumSigmaBin", 10);
  maximumThresholdBin_ = iConfig.getUntrackedParameter<double>("maximumThresholdBin", 255);

  writeZeroes_ = iConfig.getUntrackedParameter<bool>("alsoWriteZeroThresholds", false);

  // convert the vector into a map for quicker lookups.
  for (unsigned int i = 0; i < detIDsToSaveVector_.size(); i++)
    detIDsToSave_.insert(std::make_pair(detIDsToSaveVector_[i], true));
}

SiPixelSCurveCalibrationAnalysis::~SiPixelSCurveCalibrationAnalysis() {
  // do nothing
}

void SiPixelSCurveCalibrationAnalysis::buildACurveHistogram(const uint32_t &detid,
                                                            const uint32_t &row,
                                                            const uint32_t &col,
                                                            sCurveErrorFlag errorFlag,
                                                            const std::vector<float> &efficiencies,
                                                            const std::vector<float> &errors) {
  if (curvesSavedCounter_ > maxCurvesToSave_) {
    edm::LogWarning("SiPixelSCurveCalibrationAnalysis")
        << "WARNING: Request to save curve for [detid](col/row):  [" << detid << "](" << col << "/" << row
        << ") denied. Maximum number of saved curves (defined in .cfi) "
           "exceeded.";
    return;
  }
  std::ostringstream rootName;
  rootName << "SCurve_row_" << row << "_col_" << col;
  std::ostringstream humanName;
  humanName << translateDetIdToString(detid) << "_" << rootName.str() << "_ErrorFlag_" << (int)errorFlag;

  unsigned int numberOfVCalPoints = vCalPointsAsFloats_.size() - 1;  // minus one is necessary since the lower
                                                                     // edge of the last bin must be added
  if (efficiencies.size() != numberOfVCalPoints || errors.size() != numberOfVCalPoints) {
    edm::LogError("SiPixelSCurveCalibrationAnalysis")
        << "Error saving single curve histogram!  Number of Vcal values (" << numberOfVCalPoints
        << ") does not match number of efficiency points or error points!";
    return;
  }
  setDQMDirectory(detid);
  float *vcalValuesToPassToCrappyRoot = &vCalPointsAsFloats_[0];
  MonitorElement *aBadHisto =
      bookDQMHistogram1D(detid,
                         rootName.str(),
                         humanName.str(),
                         numberOfVCalPoints,
                         vcalValuesToPassToCrappyRoot);  // ROOT only takes an input as array. :(
                                                         // HOORAY FOR CINT!
  curvesSavedCounter_++;
  for (unsigned int iBin = 0; iBin < numberOfVCalPoints; ++iBin) {
    int rootBin = iBin + 1;  // root bins start at 1
    aBadHisto->setBinContent(rootBin, efficiencies[iBin]);
    aBadHisto->setBinError(rootBin, errors[iBin]);
  }
}

void SiPixelSCurveCalibrationAnalysis::calibrationSetup(const edm::EventSetup &iSetup) {
  edm::LogInfo("SiPixelSCurveCalibrationAnalysis")
      << "Calibration Settings: VCalLow: " << vCalValues_[0] << "  VCalHigh: " << vCalValues_[vCalValues_.size() - 1]
      << " nVCal: " << vCalValues_.size() << "  nTriggers: " << nTriggers_;
  curvesSavedCounter_ = 0;
  if (saveCurvesThatFlaggedBad_) {
    // build the vCal values as a vector of floats if we want to save single
    // curves
    const std::vector<short> *theVCalValues = this->getVcalValues();
    unsigned int numberOfVCalPoints = theVCalValues->size();
    edm::LogWarning("SiPixelSCurveCalibrationAnalysis")
        << "WARNING: Option set to save indiviual S-Curves - max number: " << maxCurvesToSave_
        << " This can lead to large memory consumption! (Got " << numberOfVCalPoints << " VCal Points";
    for (unsigned int i = 0; i < numberOfVCalPoints; i++) {
      vCalPointsAsFloats_.push_back(static_cast<float>((*theVCalValues)[i]));
      edm::LogInfo("SiPixelSCurveCalibrationAnalysis") << "Adding calibration Vcal: " << (*theVCalValues)[i];
    }
    // must add lower edge of last bin to the vector
    vCalPointsAsFloats_.push_back(vCalPointsAsFloats_[numberOfVCalPoints - 1] + 1);
  }

  fitFunction_ = new TF1("sCurve",
                         "0.5*[2]*(1+TMath::Erf( (x-[0]) / ([1]*sqrt(2)) ) )",
                         vCalValues_[0],
                         vCalValues_[vCalValues_.size() - 1]);
}

bool SiPixelSCurveCalibrationAnalysis::checkCorrectCalibrationType() {
  if (calibrationMode_ == "SCurve")
    return true;
  else if (calibrationMode_ == "unknown") {
    edm::LogInfo("SiPixelSCurveCalibrationAnalysis")
        << "calibration mode is: " << calibrationMode_ << ", continuing anyway...";
    return true;
  } else {
    //    edm::LogDebug("SiPixelSCurveCalibrationAnalysis") << "unknown
    //    calibration mode for SCurves, should be \"SCurve\" and is \"" <<
    //    calibrationMode_ << "\"";
  }
  return false;
}

sCurveErrorFlag SiPixelSCurveCalibrationAnalysis::estimateSCurveParameters(const std::vector<float> &eff,
                                                                           float &threshold,
                                                                           float &sigma) {
  sCurveErrorFlag output = errAllZeros;
  bool allZeroSoFar = true;
  int turnOnBin = -1;
  int saturationBin = -1;
  for (uint32_t iVcalPt = 0; iVcalPt < eff.size(); iVcalPt++) {
    if (allZeroSoFar && eff[iVcalPt] != 0) {
      turnOnBin = iVcalPt;
      allZeroSoFar = false;
      output = errNoTurnOn;
    } else if (eff[iVcalPt] > 0.90) {
      saturationBin = iVcalPt;
      short turnOnVcal = vCalValues_[turnOnBin];
      short saturationVcal = vCalValues_[saturationBin];
      short delta = saturationVcal - turnOnVcal;
      sigma = delta * 0.682;
      if (sigma < 1)  // check to make sure sigma guess is larger than our X resolution.
                      // Hopefully prevents Minuit from getting stuck at boundary
        sigma = 1;
      threshold = turnOnVcal + (0.5 * delta);
      return errOK;
    }
  }
  return output;
}

sCurveErrorFlag SiPixelSCurveCalibrationAnalysis::fittedSCurveSanityCheck(float threshold,
                                                                          float sigma,
                                                                          float amplitude) {
  // check if nonsensical
  if (threshold > vCalValues_[vCalValues_.size() - 1] || threshold < vCalValues_[0] ||
      sigma > vCalValues_[vCalValues_.size() - 1] - vCalValues_[0])
    return errFitNonPhysical;

  if (threshold < minimumThreshold_ || threshold > maximumThreshold_ || sigma < minimumSigma_ ||
      sigma > maximumSigma_ || amplitude < minimumEffAsymptote_ || amplitude > maximumEffAsymptote_)
    return errFlaggedBadByUser;

  return errOK;
}

void calculateEffAndError(int nADCResponse, int nTriggers, float &eff, float &error) {
  eff = (float)nADCResponse / (float)nTriggers;
  double effForErrorCalculation = eff;
  if (eff <= 0 || eff >= 1)
    effForErrorCalculation = 0.5 / (double)nTriggers;
  error = TMath::Sqrt(effForErrorCalculation * (1 - effForErrorCalculation) / (double)nTriggers);
}

// book histograms when new DetID is encountered in Event Record
void SiPixelSCurveCalibrationAnalysis::newDetID(uint32_t detid) {
  edm::LogInfo("SiPixelSCurveCalibrationAnalysis")
      << "Found a new DetID (" << detid << ")!  Checking to make sure it has not been added.";
  // ensure that this DetID has not been added yet
  sCurveHistogramHolder tempMap;
  std::pair<detIDHistogramMap::iterator, bool> insertResult;
  insertResult = histograms_.insert(std::make_pair(detid, tempMap));
  if (insertResult.second)  // indicates successful insertion
  {
    edm::LogInfo("SiPixelSCurveCalibrationAnalysisHistogramReport")
        << "Histogram Map.insert() returned true!  Booking new histogrames for "
           "detID: "
        << detid;
    // use detector hierarchy folders if desired
    if (useDetectorHierarchyFolders_)
      setDQMDirectory(detid);

    std::string detIdName = translateDetIdToString(detid);
    if (write2dHistograms_) {
      MonitorElement *D2sigma = bookDQMHistoPlaquetteSummary2D(detid, "ScurveSigmas", detIdName + " Sigmas");
      MonitorElement *D2thresh = bookDQMHistoPlaquetteSummary2D(detid, "ScurveThresholds", detIdName + " Thresholds");
      MonitorElement *D2chi2 = bookDQMHistoPlaquetteSummary2D(detid, "ScurveChi2Prob", detIdName + " Chi2Prob");
      insertResult.first->second.insert(std::make_pair(kSigmas, D2sigma));
      insertResult.first->second.insert(std::make_pair(kThresholds, D2thresh));
      insertResult.first->second.insert(std::make_pair(kChi2s, D2chi2));
    }
    if (write2dFitResult_) {
      MonitorElement *D2FitResult = bookDQMHistoPlaquetteSummary2D(detid, "ScurveFitResult", detIdName + " Fit Result");
      insertResult.first->second.insert(std::make_pair(kFitResults, D2FitResult));
    }
    MonitorElement *D1sigma =
        bookDQMHistogram1D(detid, "ScurveSigmasSummary", detIdName + " Sigmas Summary", 100, 0, maximumSigmaBin_);
    MonitorElement *D1thresh = bookDQMHistogram1D(
        detid, "ScurveThresholdSummary", detIdName + " Thresholds Summary", 255, 0, maximumThresholdBin_);
    MonitorElement *D1chi2 =
        bookDQMHistogram1D(detid, "ScurveChi2ProbSummary", detIdName + " Chi2Prob Summary", 101, 0, 1.01);
    MonitorElement *D1FitResult =
        bookDQMHistogram1D(detid, "ScurveFitResultSummary", detIdName + " Fit Result Summary", 10, -0.5, 9.5);
    insertResult.first->second.insert(std::make_pair(kSigmaSummary, D1sigma));
    insertResult.first->second.insert(std::make_pair(kThresholdSummary, D1thresh));
    insertResult.first->second.insert(std::make_pair(kChi2Summary, D1chi2));
    insertResult.first->second.insert(std::make_pair(kFitResultSummary, D1FitResult));
  }
}

bool SiPixelSCurveCalibrationAnalysis::doFits(uint32_t detid, std::vector<SiPixelCalibDigi>::const_iterator calibDigi) {
  sCurveErrorFlag errorFlag = errOK;
  uint32_t nVCalPts = calibDigi->getnpoints();
  // reset and fill static datamembers with vector of points and errors
  efficiencies_.resize(0);
  effErrors_.resize(0);
  for (uint32_t iVcalPt = 0; iVcalPt < nVCalPts; iVcalPt++) {
    float eff;
    float error;
    calculateEffAndError(calibDigi->getnentries(iVcalPt), nTriggers_, eff, error);
    edm::LogInfo("SiPixelSCurveCalibrationAnalysis")
        << "Eff: " << eff << " Error:  " << error << "  nEntries: " << calibDigi->getnentries(iVcalPt)
        << "  nTriggers: " << nTriggers_ << " VCalPt " << vCalValues_[iVcalPt];
    efficiencies_.push_back(eff);
    effErrors_.push_back(error);
  }

  // estimate the S-Curve parameters
  float thresholdGuess = -1.0;
  float sigmaGuess = -1.0;
  errorFlag = estimateSCurveParameters(efficiencies_, thresholdGuess, sigmaGuess);

  // these -1.0 default values will only be filled if the curve is all zeroes,
  // or doesn't turn on, WHICH INDICATES A SERIOUS PROBLEM
  Double_t sigma = -1.0;
  Double_t sigmaError = -1.0;
  Double_t threshold = -1.0;
  Double_t thresholdError = -1.0;
  Double_t amplitude = -1.0;
  Double_t amplitudeError = -1.0;
  Double_t chi2 = -1.0;
  // calculate NDF
  Int_t nDOF = vCalValues_.size() - 3;
  Double_t chi2probability = 0;

  if (errorFlag == errOK)  // only do fit if curve is fittable
  {
    // set up minuit fit
    TMinuit *gMinuit = new TMinuit(3);
    gMinuit->SetPrintLevel(-1);  // save ourselves from gigabytes of stdout
    gMinuit->SetFCN(chi2toMinimize);

    // define threshold parameters - choose step size 1, max 300, min -50
    gMinuit->DefineParameter(0, "Threshold", (Double_t)thresholdGuess, 1, -50, 300);
    // sigma
    gMinuit->DefineParameter(1, "Sigma", (Double_t)sigmaGuess, 0.1, 0, 255);
    // amplitude
    gMinuit->DefineParameter(2, "Amplitude", 1, 0.1, -0.001, 200);

    // Do Chi2 minimazation
    gMinuit->Migrad();
    gMinuit->GetParameter(0, threshold, thresholdError);
    gMinuit->GetParameter(1, sigma, sigmaError);
    gMinuit->GetParameter(2, amplitude, amplitudeError);

    // get Chi2
    Double_t params[3] = {threshold, sigma, amplitude};
    gMinuit->Eval(3, nullptr, chi2, params, 0);
    // calculate Chi2 proability
    if (nDOF <= 0)
      chi2probability = 0;
    else
      chi2probability = TMath::Prob(chi2, nDOF);

    // check to make sure output makes sense (i.e. threshold > 0)
    if (chi2probability > minimumChi2prob_)
      errorFlag = fittedSCurveSanityCheck(threshold, sigma, amplitude);
    else
      errorFlag = errBadChi2Prob;

    edm::LogInfo("SiPixelSCurveCalibrationAnalysis")
        << "Fit finished with errorFlag: " << errorFlag << " - threshold: " << threshold << "  sigma: " << sigma
        << "  chi2: " << chi2 << "  nDOF: " << nDOF << " chi2Prob: " << chi2probability
        << " chi2MinUser: " << minimumChi2prob_;

    delete gMinuit;
  }
  // get row and column for this pixel
  uint32_t row = calibDigi->row();
  uint32_t col = calibDigi->col();

  // get iterator to histogram holder for this detid
  detIDHistogramMap::iterator thisDetIdHistoGrams;
  thisDetIdHistoGrams = histograms_.find(detid);
  if (thisDetIdHistoGrams != histograms_.end()) {
    edm::LogInfo("SiPixelSCurveCalibrationAnalysisHistogramReport")
        << "Filling histograms for [detid](col/row):  [" << detid << "](" << col << "/" << row
        << ") ErrorFlag: " << errorFlag;
    // always fill fit result
    (*thisDetIdHistoGrams).second[kFitResultSummary]->Fill(errorFlag);
    if (write2dFitResult_)
      (*thisDetIdHistoGrams)
          .second[kFitResults]
          ->setBinContent(col + 1,
                          row + 1,
                          errorFlag);  // +1 because root bins start at 1

    // fill sigma/threshold result
    (*thisDetIdHistoGrams).second[kSigmaSummary]->Fill(sigma);
    (*thisDetIdHistoGrams).second[kThresholdSummary]->Fill(threshold);
    if (write2dHistograms_) {
      (*thisDetIdHistoGrams)
          .second[kSigmas]
          ->setBinContent(col + 1,
                          row + 1,
                          sigma);  // +1 because root bins start at 1
      (*thisDetIdHistoGrams)
          .second[kThresholds]
          ->setBinContent(col + 1,
                          row + 1,
                          threshold);  // +1 because root bins start at 1
    }
    // fill chi2
    (*thisDetIdHistoGrams).second[kChi2Summary]->Fill(chi2probability);
    if (write2dHistograms_)
      (*thisDetIdHistoGrams).second[kChi2s]->Fill(col, row, chi2probability);
  }
  // save individual curves, if requested
  if (saveCurvesThatFlaggedBad_) {
    bool thisDetIDinList = false;
    if (detIDsToSave_.find(detid) != detIDsToSave_.end())  // see if we want to save this histogram
      thisDetIDinList = true;

    if (errorFlag != errOK || thisDetIDinList) {
      edm::LogError("SiPixelSCurveCalibrationAnalysis") << "Saving error histogram for [detid](col/row):  [" << detid
                                                        << "](" << col << "/" << row << ") ErrorFlag: " << errorFlag;
      buildACurveHistogram(detid, row, col, errorFlag, efficiencies_, effErrors_);
    }
  }

  return true;
}