MuScleFit.cc

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//  \class MuScleFit
//  Fitter of momentum scale and resolution from resonance decays to muon track pairs
//
//  \author R. Bellan, C.Mariotti, S.Bolognesi - INFN Torino / T.Dorigo, M.De Mattia - INFN Padova
// revised S. Casasso, E. Migliore - UniTo & INFN Torino
//
//  Recent additions:
//  - several parameters allow a more flexible use, tests, and control handles
//    for the likelihood. In particular, a set of integers controls the order
//    with which parameters are released; another controls which parameters are
//    fixed. A function allows to smear momenta and angles of muons from the
//    resonance before any correction, using a set of random numbers generated
//    once and for all in the constructor (this way the smearing remains the same
//    for any given muon no matter how many times one loops and what corrections
//    one applies).
//    For a correct use of these flags, please see the function minimizeLikelihood() in
//    MuScleFitUtils.cc
//  - the fit now allows to extract resolution functions simultaneously with the
//    momentum scale. So far a simple parametrization
//    of muon momentum resolution and angle resolution has been implemented, but
//    extensions are straightforward.
//  - It is however advisable to fit separately resolution and scale. The suggested
//    course of action is:
//    1) fit the scale with a simple parametrization
//    2) check results, fit with more complicated forms
//    3) verify which is a sufficiently accurate description of the data
//    4) fix scale parameters and fit for the resolution
//    5) go back to fitting the scale with resolution parameters fixed to fitted values
//  - Also note that resolution fits may fail to converge due to instability of the
//    probability distribution to the limit of large widths. Improvements here are
//    advisable.
//  - The treatment of signal windows in the Y region
//    has to be refined because of overlaps. More work is needed here, assigning a different
//    weight to different hypothesis of the resonance producing a given mass, if there are
//    multiple candidates.
//  - Also, larger windows are to be allowed for fits to SA muons.
//  - File Probs_1000.root contains the probability distribution of lorentzians convoluted
//    with gaussian smearing functions, for the six resonances. A 1000x1000 grid
//    in mass,sigma has been computed (using root macro Probs.C).
//    A wider interval of masses for each resonance should be computed, to be used for standalone muons
//
//
//  Notes on additions, TD 31/3/08
//
//  - background model: at least a couple of different models, with two parameters,
//    should be included in the fitting procedure such that the function massprob(),
//    which produces the probability in the likelihood computation, incorporates the
//    probability that the event is from background. That is, if the fitting function
//    knows the shape of the mass spectrum ( say, a falling exponential plus a gaussian
//    signal) it becomes possible to fit the scale together with the background shape
//    and normalization parameters. Of course, one should do one thing at a time: first
//    a scale fit, then a shape fit with scale parameters fixed, and then a combined
//    fit. Convergence issues should be handled case by case.
//  - The correct implementation of the above idea requires a reorganization of pass
//    parameters (in the cfg) and fit parameters. The user has to be able to smear,
//    bias, fix parameters, choose scale fitting functions, resolution fitting functions,
//    and background functions. It should be possible to separate the fit functions from
//    the biasing ones, which would allow a more thorough testing.
//  - all the above can be obtained by making the .cfg instructions heavier. Since this
//    is a routine operated by experts only, it is a sensible choice.
//  - One should thus envision the following:
//      1) a set of parameters controlling the biasing function: parBias()
//      2) a set of parameters controlling the smearing function: parSmear()
//      3) a set of parameters to define resolution modeling and initial values: parResol()
//      3b) parResol() gets fix and order bits by parResolFix() and parResolOrder()
//      4) a set of parameters to define scale modeling and initial values: parScale()
//      4b) parScale() gets fix and order bits by parScaleFix() and parScaleOrder()
//      5) a set of parameters controlling the background shape and normalization: parNorm()
//      5b) parNorm() gets fix and order bits by parNormFix() and parNormOrder()
//    The likelihood parameters then become a vector which is dynamically composed of
//    sets 3), 4), and 5): parval() = parResol()+parScale()+parNorm()
//  - In order to study better the likelihood behavior it would be advisable to introduce
//    some histogram filling on the last iteration of the likelihood. It is not clear
//    how best to achieve that: probably the simplest way is to make a histogram filling
//    function run just after the likelihood computation, such that the best value of the
//    fit parameters is used.
//  - The muon pair which we call our resonance must be chosen in a way which does not
//    bias our likelihood: we cannot just choose the pair closest to a resonance.
//
//
//    Notes on additions, T.Dorigo 22/12/2008
//    ---------------------------------------
//
//  - File Probs_new_1000_CTEQ.root now contains a set of 24 additional two-dim histograms,
//    defining the probability distribution of Z boson decays as a function of measured mass
//    and expected sigma in 24 different bins of Z rapidity, extracted from CTEQ 6 PDF (at
//    Leading Order) from the convolution in the factorization integral. See programs CTEQ.cpp
//    and Fits.C.
//  - The probability for Z boson events now thus depends on the measured rapidity of the dimuon
//    system. All functions in file MuScleFitUtils.cc have been suitably changed.
//
// ----------------------------------------------------------------------------------
//    Modifications by M. De Mattia 13/3/2009
//    ---------------------------------------
//  - The histograms map was moved to a base class (MuScleFitBase) from which this one inherits.
//
//    Modifications by M. De Mattia 20/7/2009
//    ---------------------------------------
//  - Reworked background fit based on ranges. See comments in the code for more details.
// ---------------------------------------------------------------------------------------------
// Base Class Headers
// ------------------
#include "FWCore/Framework/interface/EDLooper.h"
#include "FWCore/Framework/interface/LooperFactory.h"
#include "FWCore/Utilities/interface/InputTag.h"
#include "FWCore/Framework/interface/Frameworkfwd.h"
#include "FWCore/Framework/interface/Event.h"
#include "FWCore/ParameterSet/interface/ParameterSet.h"

#include <CLHEP/Vector/LorentzVector.h>
#include <memory>

#include <vector>

#include "FWCore/Framework/interface/EventSetup.h"
#include "FWCore/Framework/interface/ESHandle.h"
#include "FWCore/ServiceRegistry/interface/Service.h"

#include "MuScleFitBase.h"
#include "Histograms.h"
#include "MuScleFitPlotter.h"
#include "MuonAnalysis/MomentumScaleCalibration/interface/Functions.h"
#include "MuonAnalysis/MomentumScaleCalibration/interface/RootTreeHandler.h"
#include "MuonAnalysis/MomentumScaleCalibration/interface/Muon.h"
#include "MuonAnalysis/MomentumScaleCalibration/interface/Event.h"
#include "MuScleFitMuonSelector.h"

#include "DataFormats/TrackReco/interface/Track.h"
#include "DataFormats/MuonReco/interface/Muon.h"
#include "DataFormats/MuonReco/interface/CaloMuon.h"
#include "DataFormats/MuonReco/interface/MuonFwd.h"

#include "RecoMuon/TrackingTools/interface/MuonPatternRecoDumper.h"
#include "RecoMuon/TrackingTools/interface/MuonServiceProxy.h"

#include "DataFormats/PatCandidates/interface/Muon.h"
#include "DataFormats/PatCandidates/interface/CompositeCandidate.h"
#include "DataFormats/Candidate/interface/LeafCandidate.h"
#include "DataFormats/Common/interface/TriggerResults.h"
#include "FWCore/Common/interface/TriggerNames.h"

#include "HLTrigger/HLTcore/interface/HLTConfigProvider.h"

#include "HepPDT/defs.h"
#include "HepPDT/TableBuilder.hh"
#include "HepPDT/ParticleDataTable.hh"

#include "HepMC/GenParticle.h"
#include "HepMC/GenEvent.h"

#include "SimGeneral/HepPDTRecord/interface/ParticleDataTable.h"
#include "SimDataFormats/Track/interface/SimTrackContainer.h"
#include "SimDataFormats/Vertex/interface/SimVertexContainer.h"
#include "SimDataFormats/GeneratorProducts/interface/HepMCProduct.h"

#include "DataFormats/VertexReco/interface/Vertex.h"
#include "SimDataFormats/PileupSummaryInfo/interface/PileupSummaryInfo.h"
#include "SimDataFormats/GeneratorProducts/interface/GenEventInfoProduct.h"

#include "TFile.h"
#include "TTree.h"
#include "TMinuit.h"

// To use callgrind for code profiling uncomment also the following define.
// #define USE_CALLGRIND

#ifdef USE_CALLGRIND
#include "valgrind/callgrind.h"
#endif

// To read likelihood distributions from the database.
//#include "CondFormats/RecoMuonObjects/interface/MuScleFitLikelihoodPdf.h"
//#include "CondFormats/DataRecord/interface/MuScleFitLikelihoodPdfRcd.h"

namespace edm {
  class ParameterSet;
  class Event;
  class EventSetup;
}  // namespace edm

class MuScleFit : public edm::EDLooper, MuScleFitBase {
public:
  // Constructor
  // -----------
  MuScleFit(const edm::ParameterSet& pset);

  // Destructor
  // ----------
  ~MuScleFit() override;

  // Operations
  // ----------
  void beginOfJobInConstructor();
  // void beginOfJob( const edm::EventSetup& eventSetup );
  // virtual void beginOfJob();
  void endOfJob() override;

  void startingNewLoop(unsigned int iLoop) override;

  edm::EDLooper::Status endOfLoop(const edm::EventSetup& eventSetup, unsigned int iLoop) override;
  virtual void endOfFastLoop(const unsigned int iLoop);

  edm::EDLooper::Status duringLoop(const edm::Event& event, const edm::EventSetup& eventSetup) override;
  virtual void duringFastLoop();

  template <typename T>
  std::vector<MuScleFitMuon> fillMuonCollection(const std::vector<T>& tracks);

private:
protected:
  void selectMuons(const edm::Event& event);
  void selectMuons(const int maxEvents, const TString& treeFileName);

  template <typename T>
  void takeSelectedMuonType(const T& muon, std::vector<reco::Track>& tracks);
  bool selGlobalMuon(const pat::Muon* aMuon);
  bool selTrackerMuon(const pat::Muon* aMuon);

  bool checkDeltaR(reco::Particle::LorentzVector& genMu, reco::Particle::LorentzVector& recMu);
  void fillComparisonHistograms(const reco::Particle::LorentzVector& genMu,
                                const reco::Particle::LorentzVector& recoMu,
                                const std::string& inputName,
                                const int charge);

  void applySmearing(reco::Particle::LorentzVector& mu);
  void applyBias(reco::Particle::LorentzVector& mu, const int charge);

  void checkParameters();

  MuonServiceProxy* theService;

  // Counters
  // --------
  int numberOfSimTracks;
  int numberOfSimMuons;
  int numberOfSimVertices;
  int numberOfEwkZ;

  bool ifHepMC;
  bool ifGenPart;

  // Constants
  // ---------
  double minResMass_hwindow[6];
  double maxResMass_hwindow[6];

  // Total number of loops
  // ---------------------
  unsigned int maxLoopNumber;
  unsigned int loopCounter;

  bool fastLoop;

  MuScleFitPlotter* plotter;

  // The reconstructed muon 4-momenta to be put in the tree
  // ------------------------------------------------------
  reco::Particle::LorentzVector recMu1, recMu2;
  MuScleFitMuon recMuScleMu1, recMuScleMu2;
  int iev;
  int totalEvents_;

  bool compareToSimTracks_;
  edm::InputTag simTracksCollection_;
  bool PATmuons_;
  std::string genParticlesName_;

  // Input Root Tree file name. If empty events are read from the edm root file.
  std::string inputRootTreeFileName_;
  // Output Root Tree file name. If not empty events are dumped to this file at the end of the last iteration.
  std::string outputRootTreeFileName_;
  // Maximum number of events from root tree. It works in the same way as the maxEvents to configure a input source.
  int maxEventsFromRootTree_;

  std::string triggerResultsLabel_;
  std::string triggerResultsProcess_;
  std::vector<std::string> triggerPath_;
  bool negateTrigger_;
  bool saveAllToTree_;

  // input collections for PU related infos
  edm::InputTag puInfoSrc_;
  edm::InputTag vertexSrc_;

  std::unique_ptr<MuScleFitMuonSelector> muonSelector_;
};

template <typename T>
std::vector<MuScleFitMuon> MuScleFit::fillMuonCollection(const std::vector<T>& tracks) {
  std::vector<MuScleFitMuon> muons;
  typename std::vector<T>::const_iterator track;
  for (track = tracks.begin(); track != tracks.end(); ++track) {
    reco::Particle::LorentzVector mu;
    mu = reco::Particle::LorentzVector(
        track->px(), track->py(), track->pz(), sqrt(track->p() * track->p() + MuScleFitUtils::mMu2));
    // Apply smearing if needed, and then bias
    // ---------------------------------------
    MuScleFitUtils::goodmuon++;
    if (debug_ > 0)
      std::cout << std::setprecision(9) << "Muon #" << MuScleFitUtils::goodmuon << ": initial value   Pt = " << mu.Pt()
                << std::endl;

    applySmearing(mu);
    applyBias(mu, track->charge());
    if (debug_ > 0)
      std::cout << "track charge: " << track->charge() << std::endl;

    Double_t hitsTk = track->innerTrack()->hitPattern().numberOfValidTrackerHits();
    Double_t hitsMuon = track->innerTrack()->hitPattern().numberOfValidMuonHits();
    Double_t ptError = track->innerTrack()->ptError();
    MuScleFitMuon muon(mu, track->charge(), ptError, hitsTk, hitsMuon, false);
    if (debug_ > 0) {
      std::cout << "[MuScleFit::fillMuonCollection]" << std::endl;
      std::cout << "  muon = " << muon << std::endl;
    }

    // Store modified muon
    // -------------------
    muons.push_back(muon);
  }
  return muons;
}

template <typename T>
void MuScleFit::takeSelectedMuonType(const T& muon, std::vector<reco::Track>& tracks) {
  // std::cout<<"muon "<<muon->isGlobalMuon()<<muon->isStandAloneMuon()<<muon->isTrackerMuon()<<std::endl;
  //NNBB: one muon can be of many kinds at once but with the theMuonType_ we are sure
  // to avoid double counting of the same muon
  if (muon->isGlobalMuon() && theMuonType_ == 1)
    tracks.push_back(*(muon->globalTrack()));
  else if (muon->isStandAloneMuon() && theMuonType_ == 2)
    tracks.push_back(*(muon->outerTrack()));
  else if (muon->isTrackerMuon() && theMuonType_ == 3)
    tracks.push_back(*(muon->innerTrack()));

  else if (theMuonType_ == 10 && !(muon->isStandAloneMuon()))  //particular case!!
    tracks.push_back(*(muon->innerTrack()));
  else if (theMuonType_ == 11 && muon->isGlobalMuon())
    tracks.push_back(*(muon->innerTrack()));
  else if (theMuonType_ == 13 && muon->isTrackerMuon())
    tracks.push_back(*(muon->innerTrack()));
}

// Constructor
// -----------
MuScleFit::MuScleFit(const edm::ParameterSet& pset) : MuScleFitBase(pset), totalEvents_(0) {
  MuScleFitUtils::debug = debug_;
  if (debug_ > 0)
    std::cout << "[MuScleFit]: Constructor" << std::endl;

  if ((theMuonType_ < -4 || theMuonType_ > 5) && theMuonType_ < 10) {
    std::cout << "[MuScleFit]: Unknown muon type! Aborting." << std::endl;
    abort();
  }

  loopCounter = 0;

  // Boundaries for h-function computation (to be improved!)
  // -------------------------------------------------------
  minResMass_hwindow[0] = 71.1876;  // 76.;
  maxResMass_hwindow[0] = 111.188;  // 106.;
  minResMass_hwindow[1] = 10.15;
  maxResMass_hwindow[1] = 10.55;
  minResMass_hwindow[2] = 9.8;
  maxResMass_hwindow[2] = 10.2;
  minResMass_hwindow[3] = 9.25;
  maxResMass_hwindow[3] = 9.65;
  minResMass_hwindow[4] = 3.58;
  maxResMass_hwindow[4] = 3.78;
  minResMass_hwindow[5] = 3.0;
  maxResMass_hwindow[5] = 3.2;

  // Max number of loops (if > 2 then try to minimize likelihood more than once)
  // ---------------------------------------------------------------------------
  maxLoopNumber = pset.getUntrackedParameter<int>("maxLoopNumber", 2);
  fastLoop = pset.getUntrackedParameter<bool>("FastLoop", true);

  // Selection of fits according to loop
  MuScleFitUtils::doResolFit = pset.getParameter<std::vector<int> >("doResolFit");
  MuScleFitUtils::doScaleFit = pset.getParameter<std::vector<int> >("doScaleFit");
  MuScleFitUtils::doCrossSectionFit = pset.getParameter<std::vector<int> >("doCrossSectionFit");
  MuScleFitUtils::doBackgroundFit = pset.getParameter<std::vector<int> >("doBackgroundFit");

  // Bias and smear types
  // --------------------
  int biasType = pset.getParameter<int>("BiasType");
  MuScleFitUtils::BiasType = biasType;
  // No error, the scale functions are used also for the bias
  MuScleFitUtils::biasFunction = scaleFunctionVecService(biasType);
  int smearType = pset.getParameter<int>("SmearType");
  MuScleFitUtils::SmearType = smearType;
  MuScleFitUtils::smearFunction = smearFunctionService(smearType);

  // Fit types
  // ---------
  int resolFitType = pset.getParameter<int>("ResolFitType");
  MuScleFitUtils::ResolFitType = resolFitType;
  MuScleFitUtils::resolutionFunction = resolutionFunctionService(resolFitType);
  MuScleFitUtils::resolutionFunctionForVec = resolutionFunctionVecService(resolFitType);
  int scaleType = pset.getParameter<int>("ScaleFitType");
  MuScleFitUtils::ScaleFitType = scaleType;
  MuScleFitUtils::scaleFunction = scaleFunctionService(scaleType);
  MuScleFitUtils::scaleFunctionForVec = scaleFunctionVecService(scaleType);

  // Initial parameters values
  // -------------------------
  MuScleFitUtils::parBias = pset.getParameter<std::vector<double> >("parBias");
  MuScleFitUtils::parSmear = pset.getParameter<std::vector<double> >("parSmear");
  MuScleFitUtils::parResol = pset.getParameter<std::vector<double> >("parResol");
  MuScleFitUtils::parResolStep =
      pset.getUntrackedParameter<std::vector<double> >("parResolStep", std::vector<double>());
  MuScleFitUtils::parResolMin = pset.getUntrackedParameter<std::vector<double> >("parResolMin", std::vector<double>());
  MuScleFitUtils::parResolMax = pset.getUntrackedParameter<std::vector<double> >("parResolMax", std::vector<double>());
  MuScleFitUtils::parScale = pset.getParameter<std::vector<double> >("parScale");
  MuScleFitUtils::parScaleStep =
      pset.getUntrackedParameter<std::vector<double> >("parScaleStep", std::vector<double>());
  MuScleFitUtils::parScaleMin = pset.getUntrackedParameter<std::vector<double> >("parScaleMin", std::vector<double>());
  MuScleFitUtils::parScaleMax = pset.getUntrackedParameter<std::vector<double> >("parScaleMax", std::vector<double>());
  MuScleFitUtils::parCrossSection = pset.getParameter<std::vector<double> >("parCrossSection");
  MuScleFitUtils::parBgr = pset.getParameter<std::vector<double> >("parBgr");
  MuScleFitUtils::parResolFix = pset.getParameter<std::vector<int> >("parResolFix");
  MuScleFitUtils::parScaleFix = pset.getParameter<std::vector<int> >("parScaleFix");
  MuScleFitUtils::parCrossSectionFix = pset.getParameter<std::vector<int> >("parCrossSectionFix");
  MuScleFitUtils::parBgrFix = pset.getParameter<std::vector<int> >("parBgrFix");
  MuScleFitUtils::parResolOrder = pset.getParameter<std::vector<int> >("parResolOrder");
  MuScleFitUtils::parScaleOrder = pset.getParameter<std::vector<int> >("parScaleOrder");
  MuScleFitUtils::parCrossSectionOrder = pset.getParameter<std::vector<int> >("parCrossSectionOrder");
  MuScleFitUtils::parBgrOrder = pset.getParameter<std::vector<int> >("parBgrOrder");

  MuScleFitUtils::resfind = pset.getParameter<std::vector<int> >("resfind");
  MuScleFitUtils::FitStrategy = pset.getParameter<int>("FitStrategy");

  // Option to skip unnecessary stuff
  // --------------------------------
  MuScleFitUtils::speedup = pset.getParameter<bool>("speedup");

  // Option to skip simTracks comparison
  compareToSimTracks_ = pset.getParameter<bool>("compareToSimTracks");
  simTracksCollection_ = pset.getUntrackedParameter<edm::InputTag>("SimTracksCollection", edm::InputTag("g4SimHits"));

  triggerResultsLabel_ = pset.getUntrackedParameter<std::string>("TriggerResultsLabel");
  triggerResultsProcess_ = pset.getUntrackedParameter<std::string>("TriggerResultsProcess");
  triggerPath_ = pset.getUntrackedParameter<std::vector<std::string> >("TriggerPath");
  negateTrigger_ = pset.getUntrackedParameter<bool>("NegateTrigger", false);
  saveAllToTree_ = pset.getUntrackedParameter<bool>("SaveAllToTree", false);

  // input collections for PU related infos
  puInfoSrc_ = pset.getUntrackedParameter<edm::InputTag>("PileUpSummaryInfo");
  vertexSrc_ = pset.getUntrackedParameter<edm::InputTag>("PrimaryVertexCollection");

  PATmuons_ = pset.getUntrackedParameter<bool>("PATmuons", false);
  genParticlesName_ = pset.getUntrackedParameter<std::string>("GenParticlesName", "genParticles");

  // Use the probability file or not. If not it will perform a simpler selection taking the muon pair with
  // invariant mass closer to the pdf value and will crash if some fit is attempted.
  MuScleFitUtils::useProbsFile_ = pset.getUntrackedParameter<bool>("UseProbsFile", true);

  // This must be set to true if using events generated with Sherpa
  MuScleFitUtils::sherpa_ = pset.getUntrackedParameter<bool>("Sherpa", false);

  MuScleFitUtils::rapidityBinsForZ_ = pset.getUntrackedParameter<bool>("RapidityBinsForZ", true);

  // Set the cuts on muons to be used in the fit
  MuScleFitUtils::separateRanges_ = pset.getUntrackedParameter<bool>("SeparateRanges", true);
  MuScleFitUtils::maxMuonPt_ = pset.getUntrackedParameter<double>("MaxMuonPt", 100000000.);
  MuScleFitUtils::minMuonPt_ = pset.getUntrackedParameter<double>("MinMuonPt", 0.);
  MuScleFitUtils::minMuonEtaFirstRange_ = pset.getUntrackedParameter<double>("MinMuonEtaFirstRange", -6.);
  MuScleFitUtils::maxMuonEtaFirstRange_ = pset.getUntrackedParameter<double>("MaxMuonEtaFirstRange", 6.);
  MuScleFitUtils::minMuonEtaSecondRange_ = pset.getUntrackedParameter<double>("MinMuonEtaSecondRange", -100.);
  MuScleFitUtils::maxMuonEtaSecondRange_ = pset.getUntrackedParameter<double>("MaxMuonEtaSecondRange", 100.);
  MuScleFitUtils::deltaPhiMinCut_ = pset.getUntrackedParameter<double>("DeltaPhiMinCut", -100.);
  MuScleFitUtils::deltaPhiMaxCut_ = pset.getUntrackedParameter<double>("DeltaPhiMaxCut", 100.);

  MuScleFitUtils::debugMassResol_ = pset.getUntrackedParameter<bool>("DebugMassResol", false);
  // MuScleFitUtils::massResolComponentsStruct MuScleFitUtils::massResolComponents;

  // Check for parameters consistency
  // it will abort in case of errors.
  checkParameters();

  // Generate array of gaussian-distributed numbers for smearing
  // -----------------------------------------------------------
  if (MuScleFitUtils::SmearType > 0) {
    std::cout << "[MuScleFit-Constructor]: Generating random values for smearing" << std::endl;
    TF1 G("G", "[0]*exp(-0.5*pow(x,2))", -5., 5.);
    double norm = 1 / sqrt(2 * TMath::Pi());
    G.SetParameter(0, norm);
    for (int i = 0; i < 10000; i++) {
      for (int j = 0; j < 7; j++) {
        MuScleFitUtils::x[j][i] = G.GetRandom();
      }
    }
  }
  MuScleFitUtils::goodmuon = 0;

  if (theMuonType_ > 0 && theMuonType_ < 4) {
    MuScleFitUtils::MuonTypeForCheckMassWindow = theMuonType_ - 1;
    MuScleFitUtils::MuonType = theMuonType_ - 1;
  } else if (theMuonType_ == 0 || theMuonType_ == 4 || theMuonType_ == 5 || theMuonType_ >= 10 || theMuonType_ == -1 ||
             theMuonType_ == -2 || theMuonType_ == -3 || theMuonType_ == -4) {
    MuScleFitUtils::MuonTypeForCheckMassWindow = 2;
    MuScleFitUtils::MuonType = 2;
  } else {
    std::cout << "Wrong muon type " << theMuonType_ << std::endl;
    exit(1);
  }

  // When using standalone muons switch to the single Z pdf
  if (theMuonType_ == 2) {
    MuScleFitUtils::rapidityBinsForZ_ = false;
  }

  // Initialize ResMaxSigma And ResHalfWidth - 0 = global, 1 = SM, 2 = tracker
  // -------------------------------------------------------------------------
  MuScleFitUtils::massWindowHalfWidth[0][0] = 20.;
  MuScleFitUtils::massWindowHalfWidth[0][1] = 0.35;
  MuScleFitUtils::massWindowHalfWidth[0][2] = 0.35;
  MuScleFitUtils::massWindowHalfWidth[0][3] = 0.35;
  MuScleFitUtils::massWindowHalfWidth[0][4] = 0.2;
  MuScleFitUtils::massWindowHalfWidth[0][5] = 0.2;
  MuScleFitUtils::massWindowHalfWidth[1][0] = 20.;
  MuScleFitUtils::massWindowHalfWidth[1][1] = 0.35;
  MuScleFitUtils::massWindowHalfWidth[1][2] = 0.35;
  MuScleFitUtils::massWindowHalfWidth[1][3] = 0.35;
  MuScleFitUtils::massWindowHalfWidth[1][4] = 0.2;
  MuScleFitUtils::massWindowHalfWidth[1][5] = 0.2;
  MuScleFitUtils::massWindowHalfWidth[2][0] = 20.;
  MuScleFitUtils::massWindowHalfWidth[2][1] = 0.35;
  MuScleFitUtils::massWindowHalfWidth[2][2] = 0.35;
  MuScleFitUtils::massWindowHalfWidth[2][3] = 0.35;
  MuScleFitUtils::massWindowHalfWidth[2][4] = 0.2;
  MuScleFitUtils::massWindowHalfWidth[2][5] = 0.2;

  muonSelector_ = std::make_unique<MuScleFitMuonSelector>(theMuonLabel_,
                                                          theMuonType_,
                                                          PATmuons_,
                                                          MuScleFitUtils::resfind,
                                                          MuScleFitUtils::speedup,
                                                          genParticlesName_,
                                                          compareToSimTracks_,
                                                          simTracksCollection_,
                                                          MuScleFitUtils::sherpa_,
                                                          debug_);

  MuScleFitUtils::backgroundHandler =
      new BackgroundHandler(pset.getParameter<std::vector<int> >("BgrFitType"),
                            pset.getParameter<std::vector<double> >("LeftWindowBorder"),
                            pset.getParameter<std::vector<double> >("RightWindowBorder"),
                            MuScleFitUtils::ResMass,
                            MuScleFitUtils::massWindowHalfWidth[MuScleFitUtils::MuonTypeForCheckMassWindow]);

  MuScleFitUtils::crossSectionHandler =
      new CrossSectionHandler(MuScleFitUtils::parCrossSection, MuScleFitUtils::resfind);

  // Build cross section scale factors
  // MuScleFitUtils::resfind

  MuScleFitUtils::normalizeLikelihoodByEventNumber_ =
      pset.getUntrackedParameter<bool>("NormalizeLikelihoodByEventNumber", true);
  if (debug_ > 0)
    std::cout << "End of MuScleFit constructor" << std::endl;

  inputRootTreeFileName_ = pset.getParameter<std::string>("InputRootTreeFileName");
  outputRootTreeFileName_ = pset.getParameter<std::string>("OutputRootTreeFileName");
  maxEventsFromRootTree_ = pset.getParameter<int>("MaxEventsFromRootTree");

  MuScleFitUtils::startWithSimplex_ = pset.getParameter<bool>("StartWithSimplex");
  MuScleFitUtils::computeMinosErrors_ = pset.getParameter<bool>("ComputeMinosErrors");
  MuScleFitUtils::minimumShapePlots_ = pset.getParameter<bool>("MinimumShapePlots");

  beginOfJobInConstructor();
}

// Destructor
// ----------
MuScleFit::~MuScleFit() {
  if (debug_ > 0)
    std::cout << "[MuScleFit]: Destructor" << std::endl;
  std::cout << "Total number of analyzed events = " << totalEvents_ << std::endl;

  if (!(outputRootTreeFileName_.empty())) {
    // Save the events to a root tree unless we are reading from the edm root file and the SavedPair size is different from the totalEvents_
    if (!(inputRootTreeFileName_.empty() && (int(MuScleFitUtils::SavedPair.size()) != totalEvents_))) {
      std::cout << "Saving muon pairs to root tree" << std::endl;
      RootTreeHandler rootTreeHandler;
      if (MuScleFitUtils::speedup) {
        // rootTreeHandler.writeTree(outputRootTreeFileName_, &(MuScleFitUtils::SavedPair), theMuonType_, 0, saveAllToTree_);
        if (debug_ > 0) {
          std::vector<MuonPair>::const_iterator it = muonPairs_.begin();
          std::cout << "[MuScleFit::~MuScleFit] (Destructor)" << std::endl;
          for (; it < muonPairs_.end(); ++it) {
            std::cout << "  Debugging pairs that are going to be written to file" << std::endl;
            std::cout << "  muon1 = " << it->mu1 << std::endl;
            std::cout << "  muon2 = " << it->mu2 << std::endl;
          }
        }
        rootTreeHandler.writeTree(outputRootTreeFileName_, &(muonPairs_), theMuonType_, nullptr, saveAllToTree_);
      } else {
        // rootTreeHandler.writeTree(outputRootTreeFileName_, &(MuScleFitUtils::SavedPair), theMuonType_, &(MuScleFitUtils::genPair), saveAllToTree_ );
        rootTreeHandler.writeTree(
            outputRootTreeFileName_, &(muonPairs_), theMuonType_, &(genMuonPairs_), saveAllToTree_);
      }
    } else {
      std::cout << "ERROR: events in the vector = " << MuScleFitUtils::SavedPair.size()
                << " != totalEvents = " << totalEvents_ << std::endl;
    }
  }
}

// Begin job
// ---------
void MuScleFit::beginOfJobInConstructor()
// void MuScleFit::beginOfJob ()
// void MuScleFit::beginOfJob( const edm::EventSetup& eventSetup )
{
  if (debug_ > 0)
    std::cout << "[MuScleFit]: beginOfJob" << std::endl;
  //if(maxLoopNumber>1)
  if (MuScleFitUtils::useProbsFile_) {
    readProbabilityDistributionsFromFile();
  }

  if (debug_ > 0)
    std::cout << "[MuScleFit]: beginOfJob" << std::endl;

  // Create the root file
  // --------------------
  for (unsigned int i = 0; i < (maxLoopNumber); i++) {
    std::stringstream ss;
    ss << i;
    std::string rootFileName = ss.str() + "_" + theRootFileName_;
    if (theCompressionSettings_ > -1) {
      theFiles_.push_back(new TFile(rootFileName.c_str(), "RECREATE", "", theCompressionSettings_));
    } else {
      theFiles_.push_back(new TFile(rootFileName.c_str(), "RECREATE"));
    }
  }
  if (debug_ > 0)
    std::cout << "[MuScleFit]: Root file created" << std::endl;

  std::cout << "creating plotter" << std::endl;
  plotter = new MuScleFitPlotter(theGenInfoRootFileName_);
  plotter->debug = debug_;
}

// End of job method
// -----------------
void MuScleFit::endOfJob() {
  if (debug_ > 0)
    std::cout << "[MuScleFit]: endOfJob" << std::endl;
}

// New loop
// --------
void MuScleFit::startingNewLoop(unsigned int iLoop) {
  if (debug_ > 0)
    std::cout << "[MuScleFit]: Starting loop # " << iLoop << std::endl;

  // Number of muons used
  // --------------------
  MuScleFitUtils::goodmuon = 0;

  // Counters for problem std::cout-ing
  // -----------------------------
  MuScleFitUtils::counter_resprob = 0;

  // Create the root file
  // --------------------
  fillHistoMap(theFiles_[iLoop], iLoop);

  loopCounter = iLoop;
  MuScleFitUtils::loopCounter = loopCounter;

  iev = 0;
  MuScleFitUtils::iev_ = 0;

  MuScleFitUtils::oldNormalization_ = 0;
}

// End of loop routine
// -------------------
edm::EDLooper::Status MuScleFit::endOfLoop(const edm::EventSetup& eventSetup, unsigned int iLoop) {
  unsigned int iFastLoop = 1;

  // Read the events from the root tree if requested
  if (!(inputRootTreeFileName_.empty())) {
    selectMuons(maxEventsFromRootTree_, inputRootTreeFileName_);
    // When reading from local file all the loops are done here
    totalEvents_ = MuScleFitUtils::SavedPair.size();
    iFastLoop = 0;
  } else {
    endOfFastLoop(iLoop);
  }

  // If a fastLoop is required we do all the remaining iterations here
  if (fastLoop == true) {
    for (; iFastLoop < maxLoopNumber; ++iFastLoop) {
      std::cout << "Starting fast loop number " << iFastLoop << std::endl;

      // In the first loop is called by the framework
      // if( iFastLoop > 0 ) {
      startingNewLoop(iFastLoop);
      // }

      // std::vector<std::pair<lorentzVector,lorentzVector> >::const_iterator it = MuScleFitUtils::SavedPair.begin();
      // for( ; it != SavedPair.end(); ++it ) {
      while (iev < totalEvents_) {
        if (iev % 50000 == 0) {
          std::cout << "Fast looping on event number " << iev << std::endl;
        }
        // This reads muons from SavedPair using iev to keep track of the event
        duringFastLoop();
      }
      std::cout << "End of fast loop number " << iFastLoop << ". Ran on " << iev << " events" << std::endl;
      endOfFastLoop(iFastLoop);
    }
  }

  if (iFastLoop >= maxLoopNumber - 1) {
    return kStop;
  } else {
    return kContinue;
  }
}

void MuScleFit::endOfFastLoop(const unsigned int iLoop) {
  // std::cout<< "Inside endOfFastLoop, iLoop = " << iLoop << " and loopCounter = " << loopCounter << std::endl;

  if (loopCounter == 0) {
    // plotter->writeHistoMap();
    // The destructor will call the writeHistoMap after the cd to the output file
    delete plotter;
  }

  std::cout << "Ending loop # " << iLoop << std::endl;

  // Write the histos to file
  // ------------------------
  // theFiles_[iLoop]->cd();
  writeHistoMap(iLoop);

  // Likelihood minimization to compute corrections
  // ----------------------------------------------
  // theFiles_[iLoop]->cd();
  TDirectory* likelihoodDir = theFiles_[iLoop]->mkdir("likelihood");
  likelihoodDir->cd();
  MuScleFitUtils::minimizeLikelihood();

  // ATTENTION, this was put BEFORE the minimizeLikelihood. Check for problems.
  theFiles_[iLoop]->Close();
  // ATTENTION: Check that this delete does not give any problem
  delete theFiles_[iLoop];

  // Clear the histos
  // ----------------
  clearHistoMap();
}

// Stuff to do during loop
// -----------------------
edm::EDLooper::Status MuScleFit::duringLoop(const edm::Event& event, const edm::EventSetup& eventSetup) {
  edm::Handle<edm::TriggerResults> triggerResults;
  event.getByLabel(edm::InputTag(triggerResultsLabel_.c_str(), "", triggerResultsProcess_.c_str()), triggerResults);
  //event.getByLabel(InputTag(triggerResultsLabel_),triggerResults);
  bool isFired = false;

  if (triggerPath_[0].empty())
    isFired = true;
  else if (triggerPath_[0] == "All") {
    isFired = triggerResults->accept();
    if (debug_ > 0)
      std::cout << "Trigger " << isFired << std::endl;
  } else {
    bool changed;
    HLTConfigProvider hltConfig;
    hltConfig.init(event.getRun(), eventSetup, triggerResultsProcess_, changed);

    const edm::TriggerNames& triggerNames = event.triggerNames(*triggerResults);

    for (unsigned i = 0; i < triggerNames.size(); i++) {
      const std::string& hltName = triggerNames.triggerName(i);

      // match the path in the pset with the true name of the trigger
      for (unsigned int ipath = 0; ipath < triggerPath_.size(); ipath++) {
        if (hltName.find(triggerPath_[ipath]) != std::string::npos) {
          unsigned int triggerIndex(hltConfig.triggerIndex(hltName));

          // triggerIndex must be less than the size of HLTR or you get a CMSException: _M_range_check
          if (triggerIndex < triggerResults->size()) {
            isFired = triggerResults->accept(triggerIndex);
            if (debug_ > 0)
              std::cout << triggerPath_[ipath] << " " << hltName << " " << isFired << std::endl;
          }
        }  // end if (matching the path in the pset with the true trigger name
      }
    }
  }

  if (negateTrigger_ && isFired)
    return kContinue;
  else if (!(negateTrigger_) && !isFired)
    return kContinue;

#ifdef USE_CALLGRIND
  CALLGRIND_START_INSTRUMENTATION;
#endif

  if (debug_ > 0) {
    std::cout << "[MuScleFit-duringLoop]: loopCounter = " << loopCounter << " Run: " << event.id().run()
              << " Event: " << event.id().event() << std::endl;
  }

  // On the first iteration we read the bank, otherwise we fetch the information from the muon tree
  // ------------------------------------ Important Note --------------------------------------- //
  // The fillMuonCollection method applies any smearing or bias to the muons, so we NEVER use
  // unbiased muons.
  // ----------------------------------------------------------------------------------------------
  if (loopCounter == 0) {
    if (!fastLoop || inputRootTreeFileName_.empty()) {
      if (debug_ > 0)
        std::cout << "Reading from edm event" << std::endl;
      selectMuons(event);
      duringFastLoop();
      ++totalEvents_;
    }
  }

  return kContinue;

#ifdef USE_CALLGRIND
  CALLGRIND_STOP_INSTRUMENTATION;
  CALLGRIND_DUMP_STATS;
#endif
}

void MuScleFit::selectMuons(const edm::Event& event) {
  recMu1 = reco::Particle::LorentzVector(0, 0, 0, 0);
  recMu2 = reco::Particle::LorentzVector(0, 0, 0, 0);

  std::vector<MuScleFitMuon> muons;
  muonSelector_->selectMuons(event, muons, genMuonPairs_, MuScleFitUtils::simPair, plotter);
  //  plotter->fillRec(muons); // @EM method already invoked inside MuScleFitMuonSelector::selectMuons()

  if (debug_ > 0) {
    std::cout << "[MuScleFit::selectMuons] Debugging muons collections after call to muonSelector_->selectMuons"
              << std::endl;
    int iMu = 0;
    for (std::vector<MuScleFitMuon>::const_iterator it = muons.begin(); it < muons.end(); ++it) {
      std::cout << "  - muon n. " << iMu << " = " << (*it) << std::endl;
      ++iMu;
    }
  }

  // Find the two muons from the resonance, and set ResFound bool
  // ------------------------------------------------------------
  std::pair<MuScleFitMuon, MuScleFitMuon> recMuFromBestRes = MuScleFitUtils::findBestRecoRes(muons);

  if (MuScleFitUtils::ResFound) {
    if (debug_ > 0) {
      std::cout << std::setprecision(9) << "Pt after findbestrecores: " << (recMuFromBestRes.first).Pt() << " "
                << (recMuFromBestRes.second).Pt() << std::endl;
      std::cout << "recMu1 = " << recMu1 << std::endl;
      std::cout << "recMu2 = " << recMu2 << std::endl;
    }
    recMu1 = recMuFromBestRes.first.p4();
    recMu2 = recMuFromBestRes.second.p4();
    recMuScleMu1 = recMuFromBestRes.first;
    recMuScleMu2 = recMuFromBestRes.second;

    if (debug_ > 0) {
      std::cout << "after recMu1 = " << recMu1 << std::endl;
      std::cout << "after recMu2 = " << recMu2 << std::endl;
      std::cout << "mu1.pt = " << recMu1.Pt() << std::endl;
      std::cout << "mu2.pt = " << recMu2.Pt() << std::endl;
      std::cout << "after recMuScleMu1 = " << recMuScleMu1 << std::endl;
      std::cout << "after recMuScleMu2 = " << recMuScleMu2 << std::endl;
    }
    MuScleFitUtils::SavedPair.push_back(std::make_pair(recMu1, recMu2));
    MuScleFitUtils::SavedPairMuScleFitMuons.push_back(std::make_pair(recMuScleMu1, recMuScleMu2));
  } else {
    MuScleFitUtils::SavedPair.push_back(std::make_pair(lorentzVector(0., 0., 0., 0.), lorentzVector(0., 0., 0., 0.)));
    MuScleFitUtils::SavedPairMuScleFitMuons.push_back(std::make_pair(MuScleFitMuon(), MuScleFitMuon()));
  }
  // Save the events also in the external tree so that it can be saved late

  // Fetch extra information (per event)
  UInt_t the_NVtx(0);
  Int_t the_numPUvtx(0);
  Float_t the_TrueNumInteractions(0);

  // Fill pile-up related informations
  // --------------------------------
  edm::Handle<std::vector<PileupSummaryInfo> > puInfo;
  event.getByLabel(puInfoSrc_, puInfo);
  if (puInfo.isValid()) {
    std::vector<PileupSummaryInfo>::const_iterator PVI;
    for (PVI = puInfo->begin(); PVI != puInfo->end(); ++PVI) {
      int BX = PVI->getBunchCrossing();
      if (BX == 0) {  // "0" is the in-time crossing, negative values are the early crossings, positive are late
        the_TrueNumInteractions = PVI->getTrueNumInteractions();
        the_numPUvtx = PVI->getPU_NumInteractions();
      }
    }
  }

  edm::Handle<std::vector<reco::Vertex> > vertices;
  event.getByLabel(vertexSrc_, vertices);
  if (vertices.isValid()) {
    std::vector<reco::Vertex>::const_iterator itv;
    // now, count vertices
    for (itv = vertices->begin(); itv != vertices->end(); ++itv) {
      // require that the vertex meets certain criteria
      if (itv->ndof() < 5)
        continue;
      if (fabs(itv->z()) > 50.0)
        continue;
      if (fabs(itv->position().rho()) > 2.0)
        continue;
      ++the_NVtx;
    }
  }

  // get the MC event weight
  edm::Handle<GenEventInfoProduct> genEvtInfo;
  event.getByLabel("generator", genEvtInfo);
  double the_genEvtweight = 1.;
  if (genEvtInfo.isValid()) {
    the_genEvtweight = genEvtInfo->weight();
  }

  muonPairs_.push_back(MuonPair(
      MuScleFitUtils::SavedPairMuScleFitMuons.back().first,
      MuScleFitUtils::SavedPairMuScleFitMuons.back().second,
      MuScleFitEvent(
          event.run(), event.id().event(), the_genEvtweight, the_numPUvtx, the_TrueNumInteractions, the_NVtx)));
  // Fill the internal genPair tree from the external one
  if (MuScleFitUtils::speedup == false) {
    MuScleFitUtils::genPair.push_back(std::make_pair(genMuonPairs_.back().mu1.p4(), genMuonPairs_.back().mu2.p4()));
  }
}

void MuScleFit::selectMuons(const int maxEvents, const TString& treeFileName) {
  std::cout << "Reading muon pairs from Root Tree in " << treeFileName << std::endl;
  RootTreeHandler rootTreeHandler;
  std::vector<std::pair<unsigned int, unsigned long long> > evtRun;
  if (MuScleFitUtils::speedup) {
    rootTreeHandler.readTree(
        maxEvents, inputRootTreeFileName_, &(MuScleFitUtils::SavedPairMuScleFitMuons), theMuonType_, &evtRun);
  } else {
    rootTreeHandler.readTree(maxEvents,
                             inputRootTreeFileName_,
                             &(MuScleFitUtils::SavedPairMuScleFitMuons),
                             theMuonType_,
                             &evtRun,
                             &(MuScleFitUtils::genMuscleFitPair));
  }
  // Now loop on all the pairs and apply any smearing and bias if needed
  std::vector<std::pair<unsigned int, unsigned long long> >::iterator evtRunIt = evtRun.begin();
  std::vector<std::pair<MuScleFitMuon, MuScleFitMuon> >::iterator it = MuScleFitUtils::SavedPairMuScleFitMuons.begin();
  std::vector<std::pair<MuScleFitMuon, MuScleFitMuon> >::iterator genIt;
  if (MuScleFitUtils::speedup == false)
    genIt = MuScleFitUtils::genMuscleFitPair.begin();
  for (; it != MuScleFitUtils::SavedPairMuScleFitMuons.end(); ++it, ++evtRunIt) {
    // Apply any cut if requested
    // Note that cuts here are only applied to already selected muons. They should not be used unless
    // you are sure that the difference is negligible (e.g. the number of events with > 2 muons is negligible).
    double pt1 = it->first.pt();
    //std::cout << "pt1 = " << pt1 << std::endl;
    double pt2 = it->second.pt();
    //std::cout << "pt2 = " << pt2 << std::endl;
    double eta1 = it->first.eta();
    //std::cout << "eta1 = " << eta1 << std::endl;
    double eta2 = it->second.eta();
    //std::cout << "eta2 = " << eta2 << std::endl;
    // If they don't pass the cuts set to null vectors
    bool dontPass = false;
    bool eta1InFirstRange;
    bool eta2InFirstRange;
    bool eta1InSecondRange;
    bool eta2InSecondRange;

    int ch1 = it->first.charge();
    int ch2 = it->second.charge();

    if (MuScleFitUtils::separateRanges_) {
      eta1InFirstRange = eta1 >= MuScleFitUtils::minMuonEtaFirstRange_ && eta1 < MuScleFitUtils::maxMuonEtaFirstRange_;
      eta2InFirstRange = eta2 >= MuScleFitUtils::minMuonEtaFirstRange_ && eta2 < MuScleFitUtils::maxMuonEtaFirstRange_;
      eta1InSecondRange =
          eta1 >= MuScleFitUtils::minMuonEtaSecondRange_ && eta1 < MuScleFitUtils::maxMuonEtaSecondRange_;
      eta2InSecondRange =
          eta2 >= MuScleFitUtils::minMuonEtaSecondRange_ && eta2 < MuScleFitUtils::maxMuonEtaSecondRange_;

      // This is my logic, which should be erroneous, but certainly simpler...
      if (!(pt1 >= MuScleFitUtils::minMuonPt_ && pt1 < MuScleFitUtils::maxMuonPt_ &&
            pt2 >= MuScleFitUtils::minMuonPt_ && pt2 < MuScleFitUtils::maxMuonPt_ &&
            ((eta1InFirstRange && eta2InSecondRange && ch1 >= ch2) ||
             (eta1InSecondRange && eta2InFirstRange && ch1 < ch2))))
        dontPass = true;
    } else {
      eta1InFirstRange = eta1 >= MuScleFitUtils::minMuonEtaFirstRange_ && eta1 < MuScleFitUtils::maxMuonEtaFirstRange_;
      eta2InFirstRange = eta2 >= MuScleFitUtils::minMuonEtaFirstRange_ && eta2 < MuScleFitUtils::maxMuonEtaFirstRange_;
      eta1InSecondRange =
          eta1 >= MuScleFitUtils::minMuonEtaSecondRange_ && eta1 < MuScleFitUtils::maxMuonEtaSecondRange_;
      eta2InSecondRange =
          eta2 >= MuScleFitUtils::minMuonEtaSecondRange_ && eta2 < MuScleFitUtils::maxMuonEtaSecondRange_;
      if (!(pt1 >= MuScleFitUtils::minMuonPt_ && pt1 < MuScleFitUtils::maxMuonPt_ &&
            pt2 >= MuScleFitUtils::minMuonPt_ && pt2 < MuScleFitUtils::maxMuonPt_ &&
            (((eta1InFirstRange && !eta2InFirstRange) && (eta2InSecondRange && !eta1InSecondRange) && ch1 >= ch2) ||
             ((eta2InFirstRange && !eta1InFirstRange) && (eta1InSecondRange && !eta2InSecondRange) && ch1 < ch2))))
        dontPass = true;
    }

    // Additional check on deltaPhi
    double deltaPhi = MuScleFitUtils::deltaPhi(it->first.phi(), it->second.phi());
    if ((deltaPhi <= MuScleFitUtils::deltaPhiMinCut_) || (deltaPhi >= MuScleFitUtils::deltaPhiMaxCut_))
      dontPass = true;

    lorentzVector vec1 = it->first.p4();
    lorentzVector vec2 = it->second.p4();
    if (ch1 >= ch2) {
      lorentzVector vectemp = vec1;
      vec1 = vec2;
      vec2 = vectemp;
    }

    if (!dontPass) {
      // First is always mu-, second mu+
      if ((MuScleFitUtils::SmearType != 0) || (MuScleFitUtils::BiasType != 0)) {
        applySmearing(vec1);
        applyBias(vec1, -1);
        applySmearing(vec2);
        applyBias(vec2, 1);
      }

      MuScleFitUtils::SavedPair.push_back(std::make_pair(vec1, vec2));
    }

    //FIXME: we loose the additional information besides the 4-momenta
    muonPairs_.push_back(MuonPair(
        MuScleFitMuon(vec1, -1),
        MuScleFitMuon(vec2, +1),
        MuScleFitEvent(
            (*evtRunIt).first, (*evtRunIt).second, 0, 0, 0, 0))  // FIXME: order of event and run number mixed up!
    );

    // Fill the internal genPair tree from the external one
    if (!MuScleFitUtils::speedup) {
      MuScleFitUtils::genPair.push_back(std::make_pair(genIt->first.p4(), genIt->second.p4()));
      genMuonPairs_.push_back(GenMuonPair(genIt->first.p4(), genIt->second.p4(), 0));
      ++genIt;
    }
  }
  plotter->fillTreeRec(MuScleFitUtils::SavedPair);
  if (!(MuScleFitUtils::speedup)) {
    plotter->fillTreeGen(MuScleFitUtils::genPair);
  }
}

void MuScleFit::duringFastLoop() {
  // On loops>0 the two muons are directly obtained from the SavedMuon array
  // -----------------------------------------------------------------------
  MuScleFitUtils::ResFound = false;
  recMu1 = (MuScleFitUtils::SavedPair[iev].first);
  recMu2 = (MuScleFitUtils::SavedPair[iev].second);

  //std::cout << "iev = " << iev << ", recMu1 pt = " << recMu1.Pt() << ", recMu2 pt = " << recMu2.Pt() << std::endl;

  if (recMu1.Pt() > 0 && recMu2.Pt() > 0) {
    MuScleFitUtils::ResFound = true;
    if (debug_ > 0)
      std::cout << "Ev = " << iev << ": found muons in tree with Pt = " << recMu1.Pt() << " " << recMu2.Pt()
                << std::endl;
  }

  if (debug_ > 0)
    std::cout << "About to start lik par correction and histo filling; ResFound is " << MuScleFitUtils::ResFound
              << std::endl;
  // If resonance found, do the hard work
  // ------------------------------------
  if (MuScleFitUtils::ResFound) {
    // Find weight and reference mass for this muon pair
    // -------------------------------------------------
    // The last parameter = true means that we want to use always the background window to compute the weight,
    // otherwise the probability will be filled only for the resonance region.
    double weight = MuScleFitUtils::computeWeight((recMu1 + recMu2).mass(), iev, true);
    if (debug_ > 0) {
      std::cout << "Loop #" << loopCounter << "Event #" << iev << ": before correction     Pt1 = " << recMu1.Pt()
                << " Pt2 = " << recMu2.Pt() << std::endl;
    }
    // For successive iterations, correct the muons only if the previous iteration was a scale fit.
    // --------------------------------------------------------------------------------------------
    if (loopCounter > 0) {
      if (MuScleFitUtils::doScaleFit[loopCounter - 1]) {
        recMu1 = (MuScleFitUtils::applyScale(recMu1, MuScleFitUtils::parvalue[loopCounter - 1], -1));
        recMu2 = (MuScleFitUtils::applyScale(recMu2, MuScleFitUtils::parvalue[loopCounter - 1], 1));
      }
    }
    if (debug_ > 0) {
      std::cout << "Loop #" << loopCounter << "Event #" << iev << ": after correction      Pt1 = " << recMu1.Pt()
                << " Pt2 = " << recMu2.Pt() << std::endl;
    }

    reco::Particle::LorentzVector bestRecRes(recMu1 + recMu2);

    //Fill histograms
    //------------------

    mapHisto_["hRecBestMu"]->Fill(recMu1, -1, weight);
    mapHisto_["hRecBestMuVSEta"]->Fill(recMu1);
    mapHisto_["hRecBestMu"]->Fill(recMu2, +1, weight);
    mapHisto_["hRecBestMuVSEta"]->Fill(recMu2);
    mapHisto_["hDeltaRecBestMu"]->Fill(recMu1, recMu2);
    // Reconstructed resonance
    mapHisto_["hRecBestRes"]->Fill(bestRecRes, +1, weight);
    mapHisto_["hRecBestResAllEvents"]->Fill(bestRecRes, +1, 1.);
    //     // Fill histogram of Res mass vs muon variables
    //     mapHisto_["hRecBestResVSMu"]->Fill (recMu1, bestRecRes, -1);
    //     mapHisto_["hRecBestResVSMu"]->Fill (recMu2, bestRecRes, +1);
    //     // Fill also the mass mu+/mu- comparisons
    //     mapHisto_["hRecBestResVSMu"]->Fill(recMu1, recMu2, bestRecRes);

    mapHisto_["hRecBestResVSMu"]->Fill(recMu1, bestRecRes, -1, weight);
    mapHisto_["hRecBestResVSMu"]->Fill(recMu2, bestRecRes, +1, weight);
    // Fill also the mass mu+/mu- comparisons
    mapHisto_["hRecBestResVSMu"]->Fill(recMu1, recMu2, bestRecRes, weight);

    //-- rc 2010 filling histograms for mu+ /mu- ------
    //  mapHisto_["hRecBestResVSMuMinus"]->Fill (recMu1, bestRecRes, -1);
    // mapHisto_["hRecBestResVSMuPlus"]->Fill (recMu2, bestRecRes, +1);

    //-- rc 2010 filling histograms MassVsMuEtaPhi------
    //  mapHisto_["hRecBestResVSMuEtaPhi"]->Fill (recMu1, bestRecRes,-1);
    //  mapHisto_["hRecBestResVSMuEtaPhi"]->Fill (recMu2, bestRecRes,+1);

    // Fill histogram of Res mass vs Res variables
    // mapHisto_["hRecBestResVSRes"]->Fill (bestRecRes, bestRecRes, +1);
    mapHisto_["hRecBestResVSRes"]->Fill(bestRecRes, bestRecRes, +1, weight);

    std::vector<double>* parval;
    std::vector<double> initpar;
    // Store a pointer to the vector of parameters of the last iteration, or the initial
    // parameters if this is the first iteration
    if (loopCounter == 0) {
      initpar = MuScleFitUtils::parResol;
      initpar.insert(initpar.end(), MuScleFitUtils::parScale.begin(), MuScleFitUtils::parScale.end());
      initpar.insert(initpar.end(), MuScleFitUtils::parCrossSection.begin(), MuScleFitUtils::parCrossSection.end());
      initpar.insert(initpar.end(), MuScleFitUtils::parBgr.begin(), MuScleFitUtils::parBgr.end());
      parval = &initpar;
    } else {
      parval = &(MuScleFitUtils::parvalue[loopCounter - 1]);
    }

    //Compute pt resolution w.r.t generated and simulated muons
    //--------------------------------------------------------
    if (!MuScleFitUtils::speedup) {
      //first is always mu-, second is always mu+
      if (checkDeltaR(MuScleFitUtils::genPair[iev].first, recMu1)) {
        fillComparisonHistograms(MuScleFitUtils::genPair[iev].first, recMu1, "Gen", -1);
      }
      if (checkDeltaR(MuScleFitUtils::genPair[iev].second, recMu2)) {
        fillComparisonHistograms(MuScleFitUtils::genPair[iev].second, recMu2, "Gen", +1);
      }
      if (compareToSimTracks_) {
        //first is always mu-, second is always mu+
        if (checkDeltaR(MuScleFitUtils::simPair[iev].first, recMu1)) {
          fillComparisonHistograms(MuScleFitUtils::simPair[iev].first, recMu1, "Sim", -1);
        }
        if (checkDeltaR(MuScleFitUtils::simPair[iev].second, recMu2)) {
          fillComparisonHistograms(MuScleFitUtils::simPair[iev].second, recMu2, "Sim", +1);
        }
      }
    }

    // ATTENTION: this was done only when a matching was found. Moved it outside because, genInfo or not, we still want to see the resolution function
    // Fill also the resolution histogramsm using the resolution functions:
    // the parameters are those from the last iteration, as the muons up to this point have also the corrections from the same iteration.
    // Need to use a different array (ForVec), containing functors able to operate on std::vector<double>
    mapHisto_["hFunctionResolPt"]->Fill(
        recMu1, MuScleFitUtils::resolutionFunctionForVec->sigmaPt(recMu1.Pt(), recMu1.Eta(), *parval), -1);
    mapHisto_["hFunctionResolCotgTheta"]->Fill(
        recMu1, MuScleFitUtils::resolutionFunctionForVec->sigmaCotgTh(recMu1.Pt(), recMu1.Eta(), *parval), -1);
    mapHisto_["hFunctionResolPhi"]->Fill(
        recMu1, MuScleFitUtils::resolutionFunctionForVec->sigmaPhi(recMu1.Pt(), recMu1.Eta(), *parval), -1);
    mapHisto_["hFunctionResolPt"]->Fill(
        recMu2, MuScleFitUtils::resolutionFunctionForVec->sigmaPt(recMu2.Pt(), recMu2.Eta(), *parval), +1);
    mapHisto_["hFunctionResolCotgTheta"]->Fill(
        recMu2, MuScleFitUtils::resolutionFunctionForVec->sigmaCotgTh(recMu2.Pt(), recMu2.Eta(), *parval), +1);
    mapHisto_["hFunctionResolPhi"]->Fill(
        recMu2, MuScleFitUtils::resolutionFunctionForVec->sigmaPhi(recMu2.Pt(), recMu2.Eta(), *parval), +1);

    // Compute likelihood histograms
    // -----------------------------
    if (debug_ > 0)
      std::cout << "mass = " << bestRecRes.mass() << std::endl;
    if (weight != 0.) {
      double massResol;
      double prob;
      double deltalike;
      if (loopCounter == 0) {
        std::vector<double> initpar;
        initpar.reserve((int)(MuScleFitUtils::parResol.size()));
        for (int i = 0; i < (int)(MuScleFitUtils::parResol.size()); i++) {
          initpar.push_back(MuScleFitUtils::parResol[i]);
        }
        for (int i = 0; i < (int)(MuScleFitUtils::parScale.size()); i++) {
          initpar.push_back(MuScleFitUtils::parScale[i]);
        }
        //  for (int i=0; i<(int)(MuScleFitUtils::parCrossSection.size()); i++) {
        //    initpar.push_back(MuScleFitUtils::parCrossSection[i]);
        //  }
        MuScleFitUtils::crossSectionHandler->addParameters(initpar);

        for (int i = 0; i < (int)(MuScleFitUtils::parBgr.size()); i++) {
          initpar.push_back(MuScleFitUtils::parBgr[i]);
        }
        massResol = MuScleFitUtils::massResolution(recMu1, recMu2, initpar);
        // prob      = MuScleFitUtils::massProb( bestRecRes.mass(), bestRecRes.Eta(), bestRecRes.Rapidity(), massResol, initpar, true );
        prob = MuScleFitUtils::massProb(bestRecRes.mass(),
                                        bestRecRes.Eta(),
                                        bestRecRes.Rapidity(),
                                        massResol,
                                        initpar,
                                        true,
                                        recMu1.eta(),
                                        recMu2.eta());
      } else {
        massResol = MuScleFitUtils::massResolution(recMu1, recMu2, MuScleFitUtils::parvalue[loopCounter - 1]);
        // prob      = MuScleFitUtils::massProb( bestRecRes.mass(), bestRecRes.Eta(), bestRecRes.Rapidity(),
        //                                       massResol, MuScleFitUtils::parvalue[loopCounter-1], true );
        prob = MuScleFitUtils::massProb(bestRecRes.mass(),
                                        bestRecRes.Eta(),
                                        bestRecRes.Rapidity(),
                                        massResol,
                                        MuScleFitUtils::parvalue[loopCounter - 1],
                                        true,
                                        recMu1.eta(),
                                        recMu2.eta());
      }
      if (debug_ > 0)
        std::cout << "inside weight: mass = " << bestRecRes.mass() << ", prob = " << prob << std::endl;
      if (prob > 0) {
        if (debug_ > 0)
          std::cout << "inside prob: mass = " << bestRecRes.mass() << ", prob = " << prob << std::endl;

        deltalike = log(prob) * weight;  // NB maximum likelihood --> deltalike is maximized
        mapHisto_["hLikeVSMu"]->Fill(recMu1, deltalike);
        mapHisto_["hLikeVSMu"]->Fill(recMu2, deltalike);
        mapHisto_["hLikeVSMuMinus"]->Fill(recMu1, deltalike);
        mapHisto_["hLikeVSMuPlus"]->Fill(recMu2, deltalike);

        double recoMass = (recMu1 + recMu2).mass();
        if (recoMass != 0) {
          // IMPORTANT: massResol is not a relative resolution
          mapHisto_["hResolMassVSMu"]->Fill(recMu1, massResol, -1);
          mapHisto_["hResolMassVSMu"]->Fill(recMu2, massResol, +1);
          mapHisto_["hFunctionResolMassVSMu"]->Fill(recMu1, massResol / recoMass, -1);
          mapHisto_["hFunctionResolMassVSMu"]->Fill(recMu2, massResol / recoMass, +1);
        }

        if (MuScleFitUtils::debugMassResol_) {
          mapHisto_["hdMdPt1"]->Fill(recMu1, MuScleFitUtils::massResolComponents.dmdpt1, -1);
          mapHisto_["hdMdPt2"]->Fill(recMu2, MuScleFitUtils::massResolComponents.dmdpt2, +1);
          mapHisto_["hdMdPhi1"]->Fill(recMu1, MuScleFitUtils::massResolComponents.dmdphi1, -1);
          mapHisto_["hdMdPhi2"]->Fill(recMu2, MuScleFitUtils::massResolComponents.dmdphi2, +1);
          mapHisto_["hdMdCotgTh1"]->Fill(recMu1, MuScleFitUtils::massResolComponents.dmdcotgth1, -1);
          mapHisto_["hdMdCotgTh2"]->Fill(recMu2, MuScleFitUtils::massResolComponents.dmdcotgth2, +1);
        }

        if (!MuScleFitUtils::speedup) {
          double genMass = (MuScleFitUtils::genPair[iev].first + MuScleFitUtils::genPair[iev].second).mass();
          // Fill the mass resolution (computed from MC), we use the covariance class to compute the variance
          if (genMass != 0) {
            mapHisto_["hGenResVSMu"]->Fill((MuScleFitUtils::genPair[iev].first),
                                           (MuScleFitUtils::genPair[iev].first + MuScleFitUtils::genPair[iev].second),
                                           -1);
            mapHisto_["hGenResVSMu"]->Fill((MuScleFitUtils::genPair[iev].second),
                                           (MuScleFitUtils::genPair[iev].first + MuScleFitUtils::genPair[iev].second),
                                           +1);
            double diffMass = (recoMass - genMass) / genMass;
            // double diffMass = recoMass - genMass;
            // Fill if for both muons
            double pt1 = recMu1.pt();
            double eta1 = recMu1.eta();
            double pt2 = recMu2.pt();
            double eta2 = recMu2.eta();
            // This is to avoid nan
            if (diffMass == diffMass) {
              // Mass relative difference vs Pt and Eta. To be used to extract the true mass resolution
              mapHisto_["hDeltaMassOverGenMassVsPt"]->Fill(pt1, diffMass);
              mapHisto_["hDeltaMassOverGenMassVsPt"]->Fill(pt2, diffMass);
              mapHisto_["hDeltaMassOverGenMassVsEta"]->Fill(eta1, diffMass);
              mapHisto_["hDeltaMassOverGenMassVsEta"]->Fill(eta2, diffMass);
              // This is used for the covariance comparison
              mapHisto_["hMassResolutionVsPtEta"]->Fill(pt1, eta1, diffMass, diffMass);
              mapHisto_["hMassResolutionVsPtEta"]->Fill(pt2, eta2, diffMass, diffMass);
            } else {
              std::cout << "Error, there is a nan: recoMass = " << recoMass << ", genMass = " << genMass << std::endl;
            }
          }
          // Fill with mass resolution from resolution function
          double massRes = MuScleFitUtils::massResolution(recMu1, recMu2, MuScleFitUtils::parResol);
          mapHisto_["hFunctionResolMass"]->Fill(recMu1, std::pow(massRes, 2), -1);
          mapHisto_["hFunctionResolMass"]->Fill(recMu2, std::pow(massRes, 2), +1);
        }

        mapHisto_["hMass_P"]->Fill(bestRecRes.mass(), prob);
        if (debug_ > 0)
          std::cout << "mass = " << bestRecRes.mass() << ", prob = " << prob << std::endl;
        mapHisto_["hMass_fine_P"]->Fill(bestRecRes.mass(), prob);

        mapHisto_["hMassProbVsRes"]->Fill(bestRecRes, bestRecRes, +1, prob);
        mapHisto_["hMassProbVsMu"]->Fill(recMu1, bestRecRes, -1, prob);
        mapHisto_["hMassProbVsMu"]->Fill(recMu2, bestRecRes, +1, prob);
        mapHisto_["hMassProbVsRes_fine"]->Fill(bestRecRes, bestRecRes, +1, prob);
        mapHisto_["hMassProbVsMu_fine"]->Fill(recMu1, bestRecRes, -1, prob);
        mapHisto_["hMassProbVsMu_fine"]->Fill(recMu2, bestRecRes, +1, prob);
      }
    }
  }  // end if ResFound

  // Fill the pair
  // -------------
  if (loopCounter > 0) {
    if (debug_ > 0)
      std::cout << "[MuScleFit]: filling the pair" << std::endl;
    MuScleFitUtils::SavedPair[iev] = std::make_pair(recMu1, recMu2);
  }

  iev++;
  MuScleFitUtils::iev_++;

  // return kContinue;
}

bool MuScleFit::checkDeltaR(reco::Particle::LorentzVector& genMu, reco::Particle::LorentzVector& recMu) {
  //first is always mu-, second is always mu+
  double deltaR =
      sqrt(MuScleFitUtils::deltaPhi(recMu.Phi(), genMu.Phi()) * MuScleFitUtils::deltaPhi(recMu.Phi(), genMu.Phi()) +
           ((recMu.Eta() - genMu.Eta()) * (recMu.Eta() - genMu.Eta())));
  if (deltaR < 0.01)
    return true;
  else if (debug_ > 0) {
    std::cout << "Reco muon " << recMu << " with eta " << recMu.Eta() << " and phi " << recMu.Phi() << std::endl
              << " DOES NOT MATCH with generated muon from resonance: " << std::endl
              << genMu << " with eta " << genMu.Eta() << " and phi " << genMu.Phi() << std::endl;
  }
  return false;
}

void MuScleFit::fillComparisonHistograms(const reco::Particle::LorentzVector& genMu,
                                         const reco::Particle::LorentzVector& recMu,
                                         const std::string& inputName,
                                         const int charge) {
  std::string name(inputName + "VSMu");
  mapHisto_["hResolPt" + name]->Fill(recMu, (-genMu.Pt() + recMu.Pt()) / genMu.Pt(), charge);
  mapHisto_["hResolTheta" + name]->Fill(recMu, (-genMu.Theta() + recMu.Theta()), charge);
  mapHisto_["hResolCotgTheta" + name]->Fill(
      recMu, (-cos(genMu.Theta()) / sin(genMu.Theta()) + cos(recMu.Theta()) / sin(recMu.Theta())), charge);
  mapHisto_["hResolEta" + name]->Fill(recMu, (-genMu.Eta() + recMu.Eta()), charge);
  mapHisto_["hResolPhi" + name]->Fill(recMu, MuScleFitUtils::deltaPhiNoFabs(recMu.Phi(), genMu.Phi()), charge);

  // Fill only if it was matched to a genMu and this muon is valid
  if ((genMu.Pt() != 0) && (recMu.Pt() != 0)) {
    mapHisto_["hPtRecoVsPt" + inputName]->Fill(genMu.Pt(), recMu.Pt());
  }
}

void MuScleFit::applySmearing(reco::Particle::LorentzVector& mu) {
  if (MuScleFitUtils::SmearType > 0) {
    mu = MuScleFitUtils::applySmearing(mu);
    if (debug_ > 0)
      std::cout << "Muon #" << MuScleFitUtils::goodmuon << ": after smearing  Pt = " << mu.Pt() << std::endl;
  }
}

void MuScleFit::applyBias(reco::Particle::LorentzVector& mu, const int charge) {
  if (MuScleFitUtils::BiasType > 0) {
    mu = MuScleFitUtils::applyBias(mu, charge);
    if (debug_ > 0)
      std::cout << "Muon #" << MuScleFitUtils::goodmuon << ": after bias      Pt = " << mu.Pt() << std::endl;
  }
}

// Simple method to check parameters consistency. It aborts the job if the parameters
// are not consistent.
void MuScleFit::checkParameters() {
  // Fits selection dimension check
  if (MuScleFitUtils::doResolFit.size() != maxLoopNumber) {
    std::cout << "[MuScleFit-Constructor]: wrong size of resolution fits selector = "
              << MuScleFitUtils::doResolFit.size() << std::endl;
    std::cout << "it must have as many values as the number of loops, which is = " << maxLoopNumber << std::endl;
    abort();
  }
  if (MuScleFitUtils::doScaleFit.size() != maxLoopNumber) {
    std::cout << "[MuScleFit-Constructor]: wrong size of scale fits selector = " << MuScleFitUtils::doScaleFit.size()
              << std::endl;
    std::cout << "it must have as many values as the number of loops, which is = " << maxLoopNumber << std::endl;
    abort();
  }
  if (MuScleFitUtils::doCrossSectionFit.size() != maxLoopNumber) {
    std::cout << "[MuScleFit-Constructor]: wrong size of cross section fits selector = "
              << MuScleFitUtils::doCrossSectionFit.size() << std::endl;
    std::cout << "it must have as many values as the number of loops, which is = " << maxLoopNumber << std::endl;
    abort();
  }
  if (MuScleFitUtils::doBackgroundFit.size() != maxLoopNumber) {
    std::cout << "[MuScleFit-Constructor]: wrong size of background fits selector = "
              << MuScleFitUtils::doBackgroundFit.size() << std::endl;
    std::cout << "it must have as many values as the number of loops, which is = " << maxLoopNumber << std::endl;
    abort();
  }

  // Bias parameters: dimension check
  // --------------------------------
  if ((MuScleFitUtils::BiasType == 1 && MuScleFitUtils::parBias.size() != 2) ||  // linear in pt
      (MuScleFitUtils::BiasType == 2 && MuScleFitUtils::parBias.size() != 2) ||  // linear in |eta|
      (MuScleFitUtils::BiasType == 3 && MuScleFitUtils::parBias.size() != 4) ||  // sinusoidal in phi
      (MuScleFitUtils::BiasType == 4 && MuScleFitUtils::parBias.size() != 3) ||  // linear in pt and |eta|
      (MuScleFitUtils::BiasType == 5 && MuScleFitUtils::parBias.size() != 3) ||  // linear in pt and sinusoidal in phi
      (MuScleFitUtils::BiasType == 6 &&
       MuScleFitUtils::parBias.size() != 3) ||  // linear in |eta| and sinusoidal in phi
      (MuScleFitUtils::BiasType == 7 &&
       MuScleFitUtils::parBias.size() != 4) ||  // linear in pt and |eta| and sinusoidal in phi
      (MuScleFitUtils::BiasType == 8 && MuScleFitUtils::parBias.size() != 4) ||   // linear in pt and parabolic in |eta|
      (MuScleFitUtils::BiasType == 9 && MuScleFitUtils::parBias.size() != 2) ||   // exponential in pt
      (MuScleFitUtils::BiasType == 10 && MuScleFitUtils::parBias.size() != 3) ||  // parabolic in pt
      (MuScleFitUtils::BiasType == 11 &&
       MuScleFitUtils::parBias.size() != 4) ||  // linear in pt and sin in phi with chg
      (MuScleFitUtils::BiasType == 12 &&
       MuScleFitUtils::parBias.size() != 6) ||  // linear in pt and para in plus sin in phi with chg
      (MuScleFitUtils::BiasType == 13 &&
       MuScleFitUtils::parBias.size() != 8) ||  // linear in pt and para in plus sin in phi with chg
      MuScleFitUtils::BiasType < 0 ||
      MuScleFitUtils::BiasType > 13) {
    std::cout << "[MuScleFit-Constructor]: Wrong bias type or number of parameters: aborting!" << std::endl;
    abort();
  }
  // Smear parameters: dimension check
  // ---------------------------------
  if ((MuScleFitUtils::SmearType == 1 && MuScleFitUtils::parSmear.size() != 3) ||
      (MuScleFitUtils::SmearType == 2 && MuScleFitUtils::parSmear.size() != 4) ||
      (MuScleFitUtils::SmearType == 3 && MuScleFitUtils::parSmear.size() != 5) ||
      (MuScleFitUtils::SmearType == 4 && MuScleFitUtils::parSmear.size() != 6) ||
      (MuScleFitUtils::SmearType == 5 && MuScleFitUtils::parSmear.size() != 7) ||
      (MuScleFitUtils::SmearType == 6 && MuScleFitUtils::parSmear.size() != 16) ||
      (MuScleFitUtils::SmearType == 7 && !MuScleFitUtils::parSmear.empty()) || MuScleFitUtils::SmearType < 0 ||
      MuScleFitUtils::SmearType > 7) {
    std::cout << "[MuScleFit-Constructor]: Wrong smear type or number of parameters: aborting!" << std::endl;
    abort();
  }
  // Protect against bad size of parameters
  // --------------------------------------
  if (MuScleFitUtils::parResol.size() != MuScleFitUtils::parResolFix.size() ||
      MuScleFitUtils::parResol.size() != MuScleFitUtils::parResolOrder.size()) {
    std::cout << "[MuScleFit-Constructor]: Mismatch in number of parameters for Resol: aborting!" << std::endl;
    abort();
  }
  if (MuScleFitUtils::parScale.size() != MuScleFitUtils::parScaleFix.size() ||
      MuScleFitUtils::parScale.size() != MuScleFitUtils::parScaleOrder.size()) {
    std::cout << "[MuScleFit-Constructor]: Mismatch in number of parameters for Scale: aborting!" << std::endl;
    abort();
  }
  if (MuScleFitUtils::parCrossSection.size() != MuScleFitUtils::parCrossSectionFix.size() ||
      MuScleFitUtils::parCrossSection.size() != MuScleFitUtils::parCrossSectionOrder.size()) {
    std::cout << "[MuScleFit-Constructor]: Mismatch in number of parameters for Bgr: aborting!" << std::endl;
    abort();
  }
  if (MuScleFitUtils::parBgr.size() != MuScleFitUtils::parBgrFix.size() ||
      MuScleFitUtils::parBgr.size() != MuScleFitUtils::parBgrOrder.size()) {
    std::cout << "[MuScleFit-Constructor]: Mismatch in number of parameters for Bgr: aborting!" << std::endl;
    abort();
  }

  // Protect against an incorrect number of resonances
  // -------------------------------------------------
  if (MuScleFitUtils::resfind.size() != 6) {
    std::cout << "[MuScleFit-Constructor]: resfind must have 6 elements (1 Z, 3 Y, 2 Psi): aborting!" << std::endl;
    abort();
  }
}

bool MuScleFit::selGlobalMuon(const pat::Muon* aMuon) {
  reco::TrackRef iTrack = aMuon->innerTrack();
  const reco::HitPattern& p = iTrack->hitPattern();

  reco::TrackRef gTrack = aMuon->globalTrack();
  const reco::HitPattern& q = gTrack->hitPattern();

  return (  //isMuonInAccept(aMuon) &&// no acceptance cuts!
      iTrack->found() > 11 && gTrack->chi2() / gTrack->ndof() < 20.0 && q.numberOfValidMuonHits() > 0 &&
      iTrack->chi2() / iTrack->ndof() < 4.0 && aMuon->muonID("TrackerMuonArbitrated") &&
      aMuon->muonID("TMLastStationAngTight") && p.pixelLayersWithMeasurement() > 1 &&
      fabs(iTrack->dxy()) < 3.0 &&  //should be done w.r.t. PV!
      fabs(iTrack->dz()) < 15.0);   //should be done w.r.t. PV!
}

bool MuScleFit::selTrackerMuon(const pat::Muon* aMuon) {
  reco::TrackRef iTrack = aMuon->innerTrack();
  const reco::HitPattern& p = iTrack->hitPattern();

  return (  //isMuonInAccept(aMuon) // no acceptance cuts!
      iTrack->found() > 11 && iTrack->chi2() / iTrack->ndof() < 4.0 && aMuon->muonID("TrackerMuonArbitrated") &&
      aMuon->muonID("TMLastStationAngTight") && p.pixelLayersWithMeasurement() > 1 &&
      fabs(iTrack->dxy()) < 3.0 &&  //should be done w.r.t. PV!
      fabs(iTrack->dz()) < 15.0);   //should be done w.r.t. PV!
}

#include "FWCore/Framework/interface/MakerMacros.h"
DEFINE_FWK_LOOPER(MuScleFit);