APWeightSumEnsemble Class Reference

#include <APWeightSumEnsemble.h>

Inheritance diagram for APWeightSumEnsemble:

Collaboration diagram for APWeightSumEnsemble:

Public Member Functions
	APWeightSumEnsemble ()
	Default constructor. More...
virtual	~APWeightSumEnsemble ()
	Default destructor. More...
void	SetRelPrecision (double rel_prec)
	Sets the relative precision of the gaussian fit to stop the ensemble test at. More...
void	AddWeightToEvt (APWeightEntry *weight)
	Adds a weight to the sum of weights. More...
void	FinishEvt (double ext_weight=1.0)
	Finishes the current event and calculates the event weight. More...
double	GetQuantile (const double prob)
	Returns the quantlile for p=prob for the distribution. More...
double	GetRandom ()
	Returns a random value according to the pdf. More...
double	GetEnsemblePDFMode ()
	Returns the Mode (= sum of weights from PDF). More...
double	GetEnsemblePDFStdDev ()
	Returns the standard deviation from PDF . More...
TH1F *	GetPDF ()
	Returns the calculated PDF. More...
void	AddEvt (APEvtWeight *evt_weight, double ext_weight=1.0)
	Adds an event with an externally calculated EvtWeight object. More...
double	GetSumW () const
	Returns the sum of weights. More...
double	GetSumW2 () const
	Returns sum of (weights^2). More...
double	GetSumWExternal () const
	Returns the sum of weights without taking into account the trigger weighting (external weights only) to allow switching trigger weighting on/off. More...
double	GetStdDev ()
	Returns the standard deviation. More...
double	GetVariance ()
	Returns the variance. More...
double	GetVarianceNoCorr ()
	Returns the variance, assuming no correlations. More...
double	GetVarianceFullCorr ()
	Returns the variance, assuming full correlation amongst objects. More...
double	GetSysUncert () const
	Returns the systematic uncertainty (from systematics assigned to weights). More...
unsigned long	GetKUnweighted () const
	Returns the unweighted sum of entries. More...
THnSparse *	GetUncertHistogram (APReweightBase *weighter)
	Returns THnSparse holding the uncertainties for given APReweightBase instance. More...
std::vector< THnSparse * >	GetAllUncertHistograms ()
	Returns vector of THnSparses holding the uncertainties for all APReweight IDs. More...

Public Attributes
ClassDef(APWeightSumEnsemble, 1) private std::vector< std::vector< APWeightEntry * > >	m_weight_vector
	< Performs the ensemble test to model final PDF. More...
std::vector< APWeightEntry * >	m_current_evt_pdfs
	Holds the weight objects for the current event. More...
std::vector< double >	m_ext_weights
	Holds the external event weight provided when finishing the respective events. More...
double	m_rel_prec
	Holds the relative precision of the gaussian fit to stop the ensemble test at. More...
TH1F *	m_pdf
	Holds the TH1F instance from the arrays if computed. More...
double	m_ensemble_mode
	Holds the Mode (= sum of weights from PDF) from ensemble test. More...
double	m_ensemble_sigma
	Holds the standard deviation from ensemble test. More...
bool	m_ensembleTest_done
	Flag if the ensemble test has been performed with the current set of weights. More...
ClassDef(APWeightSum, 1) protected std::vector< APWeightEntry * >	m_current_evt_weights
	< Calculates the final uncertainties including correlations. More...
std::vector< THnSparse * >	m_linear_uncert
	Holds all histograms for uncertainties. More...
unsigned long int	m_k_evt_orig
	Holds the original amount of unweighted counts ("sum of 1's"). More...
double	m_k_evt_weight
	Holds the sum of weights. More...
double	m_k_evt_weight2
	Holds the sum of squared weights. More...
double	m_k_evt_weight_external
	Holds the sum of external weights (no trigger weighting). More...
double	m_variance
	Holds the variance. More...
double	m_variance_nocorr
	Holds the variance, assuming no correlations. More...
double	m_variance_fullcorr
	Holds the variance, assuming full correlation amongst objects. More...
double	m_variance_sys
	Holds the systematic variance (from systematics assigned to weights). More...
bool	m_isComputed

Detailed Description

Class to calculate the sum of weights ("weighted counter")

Calculates the sum of weights taking into account the underlying asymmetric probability distribution. This is done by modelling the pdf and then extracting the corresponding quantiles.

Author

fabia.nosp@m.n.Ko.nosp@m.hn@ce.nosp@m.rn.c.nosp@m.h

Definition at line 28 of file APWeightSumEnsemble.h.

Constructor & Destructor Documentation

APWeightSumEnsemble()

APWeightSumEnsemble::APWeightSumEnsemble

(

)

Default constructor.

Definition at line 13 of file APWeightSumEnsemble.cxx.

                                         {
  m_k_evt_orig = 0;
  m_ensembleTest_done = false;
  m_pdf = 0;
  m_ensemble_mode = 0.;
  m_ensemble_sigma = 0.;
  m_rel_prec = 0.01;
}

~APWeightSumEnsemble()

APWeightSumEnsemble::~APWeightSumEnsemble ( )

virtual

Default destructor.

Definition at line 22 of file APWeightSumEnsemble.cxx.

                                          {
  delete m_pdf;
}

Member Function Documentation

AddEvt()

void APWeightSum::AddEvt ( APEvtWeight *  evt_weight, double  ext_weight = 1.0  )

inherited

Adds an event with an externally calculated EvtWeight object.

Takes an optional external weight factor (e.g. mc weight).

Definition at line 100 of file APWeightSum.cxx.

                                                                   {
  ++m_k_evt_orig;
  m_k_evt_weight += ext_weight * evt_weight->GetWeight();
  m_k_evt_weight2 += m_k_evt_weight*m_k_evt_weight;
  m_k_evt_weight_external += ext_weight;
 
  vector<APWeightEntry*> temp_vec_mu = evt_weight->GetWeightObjects(APEvtWeight::kMuon);
  vector<APWeightEntry*> temp_vec_dimu = evt_weight->GetWeightObjects(APEvtWeight::kDiMuon);
  vector<APWeightEntry*> temp_vec_mumo = evt_weight->GetWeightObjects(APEvtWeight::kMuonMO);
  vector<APWeightEntry*> temp_vec_tau = evt_weight->GetWeightObjects(APEvtWeight::kTau);
  vector<APWeightEntry*> temp_vec_ditau = evt_weight->GetWeightObjects(APEvtWeight::kDiTau);
  vector<APWeightEntry*> temp_vec_taumo = evt_weight->GetWeightObjects(APEvtWeight::kTauMO);
  vector<APWeightEntry*> temp_vec_el = evt_weight->GetWeightObjects(APEvtWeight::kElectron);
  vector<APWeightEntry*> temp_vec_diel = evt_weight->GetWeightObjects(APEvtWeight::kDiElectron);
  vector<APWeightEntry*> temp_vec_elmo = evt_weight->GetWeightObjects(APEvtWeight::kElectronMO);
  vector<APWeightEntry*> temp_vec_jet = evt_weight->GetWeightObjects(APEvtWeight::kJet);
  vector<APWeightEntry*> temp_vec_dijet = evt_weight->GetWeightObjects(APEvtWeight::kDiJet);
  vector<APWeightEntry*> temp_vec_jetmo = evt_weight->GetWeightObjects(APEvtWeight::kJetMO);
  
  vector< vector<APWeightEntry*> > temp_vec_all;
  
  temp_vec_all.push_back(temp_vec_mu);
  temp_vec_all.push_back(temp_vec_tau);
  temp_vec_all.push_back(temp_vec_el);
  temp_vec_all.push_back(temp_vec_jet);
  temp_vec_all.push_back(temp_vec_mumo);
  temp_vec_all.push_back(temp_vec_taumo);
  temp_vec_all.push_back(temp_vec_elmo);
  temp_vec_all.push_back(temp_vec_jetmo);
  temp_vec_all.push_back(temp_vec_dimu);
  temp_vec_all.push_back(temp_vec_ditau);
  temp_vec_all.push_back(temp_vec_diel);
  temp_vec_all.push_back(temp_vec_dijet);
 
  /* check if histogram for error propagation is already there; if not, create it */
  for( unsigned int iAll = 0, IAll = temp_vec_all.size(); iAll < IAll; ++iAll ) {
    for( unsigned int i = 0, I = temp_vec_all[iAll].size(); i < I; ++i ) {
      unsigned int ID = temp_vec_all[iAll][i]->GetID();
      if( m_linear_uncert.size() < ID+1 ) m_linear_uncert.resize(ID+1, 0);
      if( m_linear_uncert[ID] == 0 ) {
        vector<int> original_dimensions = temp_vec_all[iAll][i]->GetOriginalDimensions();
        int *bins = new int[original_dimensions.size()];
        double *xmin = new double[original_dimensions.size()];
        double *xmax = new double[original_dimensions.size()];
        for( unsigned int j = 0, J = original_dimensions.size(); j < J; ++j ) {
          bins[j] = original_dimensions[j];
          xmin[j] = 0.;
          xmax[j] = 10.;
        }
        m_linear_uncert[ID] = new THnSparseD("","",original_dimensions.size(), bins, xmin, xmax);
      }
    }
  }
  /* calculate weight and derivatives */
  /* these are the simple weights: kMuon, kTau, kElectron and kJet: single object trigger, OR of all elements */
  if(evt_weight->GetType() <= APEvtWeight::kJet) {
    vector<APWeightEntry*> temp_vec_rel;
    if(evt_weight->GetType() == APEvtWeight::kMuon) temp_vec_rel = temp_vec_mu;
    else if(evt_weight->GetType() == APEvtWeight::kTau) temp_vec_rel = temp_vec_tau;
    else if(evt_weight->GetType() == APEvtWeight::kElectron) temp_vec_rel = temp_vec_el;
    else if(evt_weight->GetType() == APEvtWeight::kJet) temp_vec_rel = temp_vec_jet;
    
    for (unsigned int i = 0, I = temp_vec_rel.size(); i < I; ++i ) {
      vector<int> coord = temp_vec_rel[i]->GetCoords();
      double weight_uncert = sqrt(temp_vec_rel[i]->GetVariance());
      for (unsigned int j = 0; j < I; ++j ) {
        if (j == i) continue;
        weight_uncert *= (1.0 - temp_vec_rel[j]->GetExpectancy());
      }
      m_linear_uncert[temp_vec_rel[i]->GetID()]->SetBinContent(&coord.front(), m_linear_uncert[temp_vec_rel[i]->GetID()]->GetBinContent(&coord.front())+weight_uncert);
      m_variance_nocorr += weight_uncert*weight_uncert;
    }
  }
  
  /* these are the DiMuon, DiTau, DiElectron and DiJet weights */
  else if (evt_weight->GetType() >= APEvtWeight::kDiMuon && evt_weight->GetType() <= APEvtWeight::kDiJet) {
    vector<APWeightEntry*> temp_vec_rel;
    if(evt_weight->GetType() == APEvtWeight::kDiMuon) temp_vec_rel = temp_vec_dimu;
    else if(evt_weight->GetType() == APEvtWeight::kDiTau) temp_vec_rel = temp_vec_ditau;
    else if(evt_weight->GetType() == APEvtWeight::kDiElectron) temp_vec_rel = temp_vec_diel;
    else if(evt_weight->GetType() == APEvtWeight::kDiJet) temp_vec_rel = temp_vec_dijet;
    
    bool isAsymTrig = false;
    vector<unsigned int> temp_vec_IDs;
    temp_vec_IDs.push_back(temp_vec_rel[0]->GetID() );
    for( unsigned int i = 1, I = temp_vec_rel.size(); i < I; ++i ) {
      bool knownID = false;
      for( unsigned int j = 0, J = temp_vec_IDs.size(); j < J; ++j ) {
        if( temp_vec_rel[i]->GetID() == temp_vec_IDs[j] ) { knownID = true; break; }
      }
      if( !knownID ) temp_vec_IDs.push_back( temp_vec_rel[i]->GetID() );
    }
    if( temp_vec_IDs.size() != 1 ) isAsymTrig = true;
 
    /* this is for symmetric dilepton triggers */
    if( !isAsymTrig ) {
      for (unsigned int i = 0, I = temp_vec_rel.size(); i < I; ++i ) {
        vector<int> coord = temp_vec_rel[i]->GetCoords();
        double weight_uncert = sqrt(temp_vec_rel[i]->GetVariance());
        double weight_derivative = 0.;
        for (unsigned int j = 0; j < I; ++j ) {
          if (j == i) continue;
          double weight_derivative_temp = temp_vec_rel[j]->GetExpectancy();
          for (unsigned int k = 0; k < I; ++k ) {
            if( k == j || k == i ) continue;
            weight_derivative_temp *= (1.0 - temp_vec_rel[k]->GetExpectancy());
          }
          weight_derivative += weight_derivative_temp;
        }
        weight_uncert *= weight_derivative;
        m_linear_uncert[temp_vec_rel[i]->GetID()]->SetBinContent(&coord.front(), m_linear_uncert[temp_vec_rel[i]->GetID()]->GetBinContent(&coord.front())+weight_uncert);
        m_variance_nocorr += weight_uncert*weight_uncert;
      }
    }
    
    /* this is for asymmetric triggers */
    else {
      /* at first the first leg of the trigger */ 
      for( unsigned int k = 0, K = temp_vec_rel.size(); k < K; k += 4 ) {
        vector<int> coord = temp_vec_rel[k]->GetCoords();
        double variance_k = 0.;
        double variance_temp = 1.;
        for( unsigned int i = 0, I = temp_vec_rel.size(); i < I; i += 4 ) {
          if( i == k ) continue;
          variance_temp *= (1. - temp_vec_rel[i]->GetExpectancy());
        }
        variance_k += variance_temp;
        variance_temp = -1.;
        for( unsigned int i = 0, I = temp_vec_rel.size(); i < I; i += 4 ) {
          variance_temp *= (1.0 - temp_vec_rel[i+2]->GetExpectancy());
          if( i == k ) continue;
          variance_temp *= (1.0 - temp_vec_rel[i]->GetExpectancy());
        }
        variance_k += variance_temp;
        variance_temp = -temp_vec_rel[k+3]->GetExpectancy();
        for( unsigned int i = 0, I = temp_vec_rel.size(); i < I; i += 4 ) {
          if( i == k ) continue;
          variance_temp *= (1.0 - temp_vec_rel[i]->GetExpectancy())*(1.0 - temp_vec_rel[i+2]->GetExpectancy());
        }
        variance_k += variance_temp;
        variance_temp = 0.;
        for( unsigned int j = 0, J = temp_vec_rel.size(); j < J; j+= 4 ) {
          if( j == k ) continue;
          double variance_ijk_temp = temp_vec_rel[j]->GetExpectancy()*temp_vec_rel[j+3]->GetExpectancy();
          for( unsigned int i = 0, I = temp_vec_rel.size(); i < I; i += 4 ) {
            if( i == j ) continue;
            variance_ijk_temp *= (1.0 -  temp_vec_rel[i+2]->GetExpectancy());
            if( i == k ) continue;
            variance_ijk_temp *= (1.0 - temp_vec_rel[i]->GetExpectancy());
          }
          variance_temp += variance_ijk_temp;
        }
        variance_k += variance_temp;
        variance_k *= variance_k*temp_vec_rel[k]->GetVariance();
        m_linear_uncert[temp_vec_rel[k]->GetID()]->SetBinContent(&coord.front(), m_linear_uncert[temp_vec_rel[k]->GetID()]->GetBinContent(&coord.front())+sqrt(variance_k));
        m_variance_nocorr += variance_k;
      }
      
      /* second leg */
      for( unsigned int k = 0, K = temp_vec_rel.size(); k < K; k += 4 ) {
        vector<int> coord = temp_vec_rel[k+1]->GetCoords();
        double variance_temp = 1.;
        for( unsigned int i = 0, I = temp_vec_rel.size(); i < I; i += 4 ) {
        if( i == k ) continue;
          variance_temp *= (1. - temp_vec_rel[i+1]->GetExpectancy());
        }
        variance_temp *= variance_temp*temp_vec_rel[k+1]->GetVariance();
        m_linear_uncert[temp_vec_rel[k+1]->GetID()]->SetBinContent(&coord.front(), m_linear_uncert[temp_vec_rel[k+1]->GetID()]->GetBinContent(&coord.front())+sqrt(variance_temp));
        m_variance_nocorr += variance_temp;
      }
      
      /* second leg | condition leg 1 failed */
      for( unsigned int k = 0, K = temp_vec_rel.size(); k < K; k += 4 ) {
        vector<int> coord = temp_vec_rel[k+2]->GetCoords();
        double variance_k = 0.;
        double variance_temp = 1.;
        for( unsigned int i = 0, I = temp_vec_rel.size(); i < I; i += 4 ) {
          variance_temp *= (1. - temp_vec_rel[i]->GetExpectancy());
          if( i == k ) continue;
          variance_temp *= (1. - temp_vec_rel[i+2]->GetExpectancy());
        }
        variance_k += variance_temp;
        variance_temp = 0.;
        for( unsigned int j = 0, J = temp_vec_rel.size(); j < J; j+= 4 ) {
          double variance_ijk_temp = temp_vec_rel[j]->GetExpectancy()*temp_vec_rel[j+3]->GetExpectancy();
          for( unsigned int i = 0, I = temp_vec_rel.size(); i < I; i += 4 ) {
            if( j == i ) continue;
            variance_ijk_temp *= (1.0 - temp_vec_rel[i]->GetExpectancy());
            if( i == k ) continue;
            variance_ijk_temp *= (1.0 -  temp_vec_rel[i+2]->GetExpectancy());
          }
          variance_temp += variance_ijk_temp;
        }
        variance_k += variance_temp;
        variance_k *= variance_k*temp_vec_rel[k+2]->GetVariance();
        m_linear_uncert[temp_vec_rel[k+2]->GetID()]->SetBinContent(&coord.front(), m_linear_uncert[temp_vec_rel[k+2]->GetID()]->GetBinContent(&coord.front())+sqrt(variance_k));
        m_variance_nocorr += variance_k;
      }
      
      /* second leg | condition leg 1 passed */
      for( unsigned int k = 0, K = temp_vec_rel.size(); k < K; k += 4 ) {
        vector<int> coord = temp_vec_rel[k+3]->GetCoords();
        double variance_k = - temp_vec_rel[k]->GetExpectancy();
        for( unsigned int i = 0, I = temp_vec_rel.size(); i < I; i += 4 ) {
          if( i == k ) continue;
          variance_k *= (1.0 - temp_vec_rel[i]->GetExpectancy())*(1.0 - temp_vec_rel[i+3]->GetExpectancy());
        }
        variance_k *= variance_k*temp_vec_rel[k+3]->GetVariance();
        m_linear_uncert[temp_vec_rel[k+3]->GetID()]->SetBinContent(&coord.front(), m_linear_uncert[temp_vec_rel[k+3]->GetID()]->GetBinContent(&coord.front())+sqrt(variance_k));
        m_variance_nocorr += variance_k;
      }
    } 
    
  }
   
  /* these are the weights for ANDed triggers. Shouldn't be used but for examples. This will treat everything as ANDed. */
  else if (evt_weight->GetType() == APEvtWeight::kANDed ) {
    for (unsigned int iAll = 0, IAll = temp_vec_all.size(); iAll < IAll; ++iAll ) {
      for (unsigned int i = 0, I = temp_vec_all[iAll].size(); i < I; ++i ) {
        vector<int> coord = temp_vec_all[iAll][i]->GetCoords();
        double weight_uncert = sqrt(temp_vec_all[iAll][i]->GetVariance());
        weight_uncert *= (temp_vec_all[iAll][i]->GetExpectancy() <= numeric_limits<double>::epsilon() ) ? 0. : evt_weight->GetWeight()/temp_vec_all[iAll][i]->GetExpectancy();
        m_linear_uncert[temp_vec_all[iAll][i]->GetID()]->SetBinContent(&coord.front(), m_linear_uncert[temp_vec_all[iAll][i]->GetID()]->GetBinContent(&coord.front())+weight_uncert); 
        m_variance_nocorr += weight_uncert*weight_uncert;
      }
    }
  }
 
  /* these are weights for ORed triggers, for instance dimuon OR single muon */
  /* treat everything as ORed: calculate weight for each type, then combine weights */
  /* objects of same type are ORed: kMuon, kTau, kElectron, kJet, kMuonMO, kTauMO, kElectronMO, kJetMo */
  /* objects of different type are handled differently */
  /* if type is kMOANDed, everything is ANDed.*/
  /* if type is kMOORed, kMuonMO, kTauMO, kElectronMO, kJetMO are ANDed; all others are ORed with each other! */
  else if (evt_weight->GetType() >= APEvtWeight::kORed ) {
    
    vector<double> temp_weight_rel(12,1.);
    
    /* calculate single object trigger weights: OR of all objects of same type: kMuon, kTau, kElectron, kJet, kMuonMO, kTauMO, kElectronMO, kJetMO */
    for (unsigned int j = 0; j < 8; ++j) {
      for (unsigned int i = 0, I = temp_vec_all[j].size(); i < I; ++i ) temp_weight_rel[j] *= (1.0 - temp_vec_all[j][i]->GetExpectancy());
      // for triggers intended to be used in ORing, set weight to 1. if there is no object and an AND is require: (if no object is added, assume none is required)
      if( j < 4 ) temp_weight_rel[j] = (temp_vec_all[j].size() > 0 || evt_weight->GetType() == APEvtWeight::kORed || evt_weight->GetType() == APEvtWeight::kMOORed) ? (1.0 - temp_weight_rel[j]) : 1.;
      // for triggers inteded to be used in ANDing, set weight to 1. if there is no object added (if none is added assume none is required)
      else temp_weight_rel[j] = (temp_vec_all[j].size() > 0) ? (1.0 - temp_weight_rel[j]) : 1.;
    }
 
    
    /* calculate diobject trigger weights: OR of all objects of same type but require at least 2: kDiMuon, kDiTau, kDiElectron, kDiJet */
    for (unsigned int j = 8; j < 12; ++j) {
      if( temp_vec_all[j].size() >= 2 ) {
        for (unsigned int i = 0, I = temp_vec_all[j].size(); i < I; ++i) temp_weight_rel[j] *= (1.0 - temp_vec_all[j][i]->GetExpectancy());
        for (unsigned int i = 0, I = temp_vec_all[j].size(); i < I; ++i) {
          double temp_weight = temp_vec_all[j][i]->GetExpectancy();
          for (unsigned int k = 0; k < I; ++k ) {
            if( k == i ) continue;
            temp_weight *= (1.0 - temp_vec_all[j][k]->GetExpectancy());
          }
          temp_weight_rel[j] += temp_weight;
        }
      }
      temp_weight_rel[j] = (temp_vec_all[j].size() > 0 || evt_weight->GetType() == APEvtWeight::kORed || evt_weight->GetType() == APEvtWeight::kMOORed) ? (1.0 - temp_weight_rel[j]) : 1.;
    }
   
    /* calculat weight for multiobject trigger (AND of all MO objects) */
    double temp_weight_MO = 1.;
    int n_noObject_MO = 0;
    for (unsigned int l = 4; l < 8; ++l ) {
      temp_weight_MO *= temp_weight_rel[l];
      if( temp_vec_all[l].size() == 0 ) n_noObject_MO += 1;
    }
    if( /*(evt_weight->GetType() == APEvtWeight::kORed || evt_weight->GetType() == APEvtWeight::kMOORed) &&*/ n_noObject_MO >= 2 ) temp_weight_MO = 0.; 
 
    /* all partial weights calculated; now calculate uncertainties */
    /* single object triggers */
    for (unsigned int j = 0; j < 8; ++j) {
      for (unsigned int i = 0, I = temp_vec_all[j].size(); i < I; ++i ) {
        vector<int> coord = temp_vec_all[j][i]->GetCoords();
        double weight_uncert = sqrt(temp_vec_all[j][i]->GetVariance());
        for (unsigned int k = 0; k < I; ++k ) {
          if( k == i ) continue;
          weight_uncert *= (1.0 - temp_vec_all[j][k]->GetExpectancy());
        }
        for( unsigned int l = 0; l < 4; ++l ) {
          if( l == j ) continue;
          if( evt_weight->GetType() == APEvtWeight::kMOANDed ) weight_uncert *= temp_weight_rel[l];
          else if( evt_weight->GetType() == APEvtWeight::kORed || evt_weight->GetType() == APEvtWeight::kMOORed ) weight_uncert *= (1.0 - temp_weight_rel[l]); 
          else cout << "WARNING: handling for this weight type is unknown! uncertainties will be incorrect" << endl;
        }
        for( unsigned int l = 8; l < 12; ++l ) {
          if( l == j ) continue;
          if( evt_weight->GetType() == APEvtWeight::kMOANDed ) weight_uncert *= temp_weight_rel[l];
          else if( evt_weight->GetType() == APEvtWeight::kORed || evt_weight->GetType() == APEvtWeight::kMOORed ) weight_uncert *= (1.0 - temp_weight_rel[l]);
          else cout << "WARNING: handling for this weight type is unknown! uncertainties will be incorrect" << endl;
        }
 
        if( j < 4 || j > 7 ) {
          if( evt_weight->GetType() == APEvtWeight::kMOANDed ) weight_uncert *= temp_weight_MO;
          else if( evt_weight->GetType() == APEvtWeight::kORed || evt_weight->GetType() == APEvtWeight::kMOORed ) weight_uncert *= (1.0 - temp_weight_MO);
          else cout << "WARNING: handling for this weight type is unknown! uncertainties will be incorrect" << endl;
        }
        else if( j >= 4 && j <= 7 && temp_weight_rel[j] > numeric_limits<double>::epsilon() ) weight_uncert = weight_uncert*temp_weight_MO/temp_weight_rel[j];
        m_linear_uncert[temp_vec_all[j][i]->GetID()]->SetBinContent(&coord.front(), m_linear_uncert[temp_vec_all[j][i]->GetID()]->GetBinContent(&coord.front())+weight_uncert);
        m_variance_nocorr += weight_uncert*weight_uncert;
      }
    }
    
    /* diobject triggers */
    for (unsigned int j = 8; j < 12; ++j) {
      if( temp_vec_all[j].size() >= 2 ) {
        for (unsigned int i = 0, I = temp_vec_all[j].size(); i < I; ++i ) {
          vector<int> coord = temp_vec_all[j][i]->GetCoords();
          double weight_uncert = sqrt(temp_vec_all[j][i]->GetVariance());
          double weight_derivative = 0.;
          for (unsigned int k = 0; k < I; ++k ) {
            if( k == i ) continue;
            double weight_derivative_temp = temp_vec_all[j][k]->GetExpectancy();
            for (unsigned int l = 0; l < I; ++l ) {
              if( l == k || l == i ) continue;
              weight_derivative_temp *= (1.0 - temp_vec_all[j][l]->GetExpectancy());
            }
            weight_derivative += weight_derivative_temp;
          }
          weight_uncert *= weight_derivative;
          for( unsigned int l = 0; l < 4; ++l ) {
            if( l == j ) continue;
            if( evt_weight->GetType() == APEvtWeight::kMOANDed ) weight_uncert *= temp_weight_rel[l];
            else if( evt_weight->GetType() == APEvtWeight::kORed || evt_weight->GetType() == APEvtWeight::kMOORed ) weight_uncert *= (1.0 - temp_weight_rel[l]);
            else cout << "WARNING: handling for this weight type is unknown! uncertainties will be incorrect" << endl;
          }
          for( unsigned int l = 8; l < 12; ++l ) {
            if( l == j ) continue;
            if( evt_weight->GetType() == APEvtWeight::kMOANDed ) weight_uncert *= temp_weight_rel[l];
            else if( evt_weight->GetType() == APEvtWeight::kORed || evt_weight->GetType() == APEvtWeight::kMOORed ) weight_uncert *= (1.0 - temp_weight_rel[l]);
            else cout << "WARNING: handling for this weight type is unknown! uncertainties will be incorrect" << endl;
          }
          if( evt_weight->GetType() == APEvtWeight::kMOANDed ) weight_uncert *= temp_weight_MO;
          else if( evt_weight->GetType() == APEvtWeight::kORed || evt_weight->GetType() == APEvtWeight::kMOORed ) weight_uncert *= (1.0 - temp_weight_MO);
          else cout << "WARNING: handling for this weight type is unknown! uncertainties will be incorrect" << endl;
          
          if( j >= 4 && j <= 7 && temp_weight_rel[j] > numeric_limits<double>::epsilon() ) weight_uncert /= temp_weight_rel[j];
          
          m_linear_uncert[temp_vec_all[j][i]->GetID()]->SetBinContent(&coord.front(), m_linear_uncert[temp_vec_all[j][i]->GetID()]->GetBinContent(&coord.front())+weight_uncert);
          m_variance_nocorr += weight_uncert*weight_uncert; 
        }
      }
    }
  }
 
  m_variance_sys += ext_weight * evt_weight->GetSysVariance();
  
  m_isComputed = false;
}

AddWeightToEvt()

void APWeightSumEnsemble::AddWeightToEvt

(

APWeightEntry *

weight

)

Adds a weight to the sum of weights.

Definition at line 31 of file APWeightSumEnsemble.cxx.

                                                              {
  APWeightSum::AddWeightToEvt(weight);
  m_current_evt_pdfs.push_back(weight);
  m_ensembleTest_done = false;
}

FinishEvt()

void APWeightSumEnsemble::FinishEvt

(

double

ext_weight = 1.0

)

Finishes the current event and calculates the event weight.

Takes an optional external weight factor (e.g. mc weight).

Definition at line 65 of file APWeightSumEnsemble.cxx.

                                                     {
  APWeightSum::FinishEvt(ext_weight);
  m_weight_vector.push_back(m_current_evt_pdfs);
  m_ext_weights.push_back(ext_weight);
  m_current_evt_pdfs.clear();
}

GetAllUncertHistograms()

vector< THnSparse * > APWeightSum::GetAllUncertHistograms ( )

inherited

Returns vector of THnSparses holding the uncertainties for all APReweight IDs.

Definition at line 480 of file APWeightSum.cxx.

                                                        {
  return m_linear_uncert;
}

GetEnsemblePDFMode()

double APWeightSumEnsemble::GetEnsemblePDFMode

(

)

Returns the Mode (= sum of weights from PDF).

(Invokes Ensemble Test)

Definition at line 50 of file APWeightSumEnsemble.cxx.

                                               {
  if (!m_ensembleTest_done) Compute();
  return m_ensemble_mode;
}

GetEnsemblePDFStdDev()

double APWeightSumEnsemble::GetEnsemblePDFStdDev

(

)

Returns the standard deviation from PDF .

(Invokes Ensemble Test)

Definition at line 55 of file APWeightSumEnsemble.cxx.

                                                 {
  if (!m_ensembleTest_done) Compute();
  return m_ensemble_sigma;
}

GetKUnweighted()

unsigned long APWeightSum::GetKUnweighted ( ) const

inherited

Returns the unweighted sum of entries.

Definition at line 74 of file APWeightSum.cxx.

                                                {
  return m_k_evt_orig;
}

GetPDF()

TH1F * APWeightSumEnsemble::GetPDF

(

)

Returns the calculated PDF.

(Invokes Ensemble Test)

Definition at line 60 of file APWeightSumEnsemble.cxx.

                                  {
  if (!m_ensembleTest_done) Compute();
  return m_pdf;
}

GetQuantile()

double APWeightSumEnsemble::GetQuantile

(

const double

prob

)

Returns the quantlile for p=prob for the distribution.

(Invokes Ensemble Test)

Definition at line 37 of file APWeightSumEnsemble.cxx.

                                                         {
  if (!m_ensembleTest_done) Compute();
  double prob_in[1] = {prob};
  double quant[1];
  m_pdf->GetQuantiles(1, quant, prob_in);
  return quant[0];
}

GetRandom()

double APWeightSumEnsemble::GetRandom

(

)

Returns a random value according to the pdf.

(Invokes Ensemble Test)

Definition at line 45 of file APWeightSumEnsemble.cxx.

                                      {
  if (!m_ensembleTest_done) Compute();
  return m_pdf->GetRandom();
}

GetStdDev()

double APWeightSum::GetStdDev ( )

inherited

Returns the standard deviation.

Definition at line 51 of file APWeightSum.cxx.

                              {
  if ( !m_isComputed ) Compute();
  return sqrt(m_variance);
}

GetSumW()

double APWeightSum::GetSumW ( ) const

inherited

Returns the sum of weights.

Definition at line 39 of file APWeightSum.cxx.

                                  {
  return m_k_evt_weight;
}

GetSumW2()

double APWeightSum::GetSumW2 ( ) const

inherited

Returns sum of (weights^2).

Definition at line 43 of file APWeightSum.cxx.

                                   {
  return m_k_evt_weight2;
}

GetSumWExternal()

double APWeightSum::GetSumWExternal ( ) const

inherited

Returns the sum of weights without taking into account the trigger weighting (external weights only) to allow switching trigger weighting on/off.

Definition at line 47 of file APWeightSum.cxx.

                                          {
  return m_k_evt_weight_external;
}

GetSysUncert()

double APWeightSum::GetSysUncert ( ) const

inherited

Returns the systematic uncertainty (from systematics assigned to weights).

Definition at line 70 of file APWeightSum.cxx.

                                       {
  return sqrt(m_variance_sys);
}

GetUncertHistogram()

THnSparse * APWeightSum::GetUncertHistogram ( APReweightBase *  weighter )

inherited

Returns THnSparse holding the uncertainties for given APReweightBase instance.

Definition at line 471 of file APWeightSum.cxx.

                                                                     {
  unsigned int temp_ID = weighter->GetID();
  if( temp_ID > m_linear_uncert.size()-1 ) {
    cout << "WARNING: ID unknown. Returning 0-pointer!" << endl;
    return 0;
  }
  else return m_linear_uncert[temp_ID];
}

GetVariance()

double APWeightSum::GetVariance ( )

inherited

Returns the variance.

Definition at line 56 of file APWeightSum.cxx.

                                {
  if ( !m_isComputed ) Compute();
  return m_variance;
}

GetVarianceFullCorr()

double APWeightSum::GetVarianceFullCorr ( )

inherited

Returns the variance, assuming full correlation amongst objects.

Definition at line 65 of file APWeightSum.cxx.

                                        {
  if ( !m_isComputed ) Compute();
  return m_variance_fullcorr;
}

GetVarianceNoCorr()

double APWeightSum::GetVarianceNoCorr ( )

inherited

Returns the variance, assuming no correlations.

Definition at line 61 of file APWeightSum.cxx.

                                      {
  return m_variance_nocorr;
}

SetRelPrecision()

void APWeightSumEnsemble::SetRelPrecision

(

double

rel_prec

)

Sets the relative precision of the gaussian fit to stop the ensemble test at.

Definition at line 26 of file APWeightSumEnsemble.cxx.

                                                         {
  m_rel_prec = rel_prec;
  m_ensembleTest_done = false;
}

Member Data Documentation

m_current_evt_pdfs

std::vector< APWeightEntry* > APWeightSumEnsemble::m_current_evt_pdfs

Holds the weight objects for the current event.

Definition at line 50 of file APWeightSumEnsemble.h.

m_current_evt_weights

ClassDef (APWeightSum,1) protected std::vector< APWeightEntry* > APWeightSum::m_current_evt_weights

inherited

< Calculates the final uncertainties including correlations.

Holds the expectancy values of the weights in the current event.

Definition at line 57 of file APWeightSum.h.

m_ensemble_mode

double APWeightSumEnsemble::m_ensemble_mode

Holds the Mode (= sum of weights from PDF) from ensemble test.

Definition at line 54 of file APWeightSumEnsemble.h.

m_ensemble_sigma

double APWeightSumEnsemble::m_ensemble_sigma

Holds the standard deviation from ensemble test.

Definition at line 55 of file APWeightSumEnsemble.h.

m_ensembleTest_done

bool APWeightSumEnsemble::m_ensembleTest_done

Flag if the ensemble test has been performed with the current set of weights.

Definition at line 56 of file APWeightSumEnsemble.h.

m_ext_weights

std::vector< double > APWeightSumEnsemble::m_ext_weights

Holds the external event weight provided when finishing the respective events.

Definition at line 51 of file APWeightSumEnsemble.h.

m_isComputed

bool APWeightSum::m_isComputed

inherited

Definition at line 67 of file APWeightSum.h.

m_k_evt_orig

unsigned long int APWeightSum::m_k_evt_orig

inherited

Holds the original amount of unweighted counts ("sum of 1's").

Definition at line 59 of file APWeightSum.h.

m_k_evt_weight

double APWeightSum::m_k_evt_weight

inherited

Holds the sum of weights.

Definition at line 60 of file APWeightSum.h.

m_k_evt_weight2

double APWeightSum::m_k_evt_weight2

inherited

Holds the sum of squared weights.

Definition at line 61 of file APWeightSum.h.

m_k_evt_weight_external

double APWeightSum::m_k_evt_weight_external

inherited

Holds the sum of external weights (no trigger weighting).

Definition at line 62 of file APWeightSum.h.

m_linear_uncert

std::vector< THnSparse* > APWeightSum::m_linear_uncert

inherited

Holds all histograms for uncertainties.

Definition at line 58 of file APWeightSum.h.

m_pdf

TH1F* APWeightSumEnsemble::m_pdf

Holds the TH1F instance from the arrays if computed.

Definition at line 53 of file APWeightSumEnsemble.h.

m_rel_prec

double APWeightSumEnsemble::m_rel_prec

Holds the relative precision of the gaussian fit to stop the ensemble test at.

Definition at line 52 of file APWeightSumEnsemble.h.

m_variance

double APWeightSum::m_variance

inherited

Holds the variance.

Definition at line 63 of file APWeightSum.h.

m_variance_fullcorr

double APWeightSum::m_variance_fullcorr

inherited

Holds the variance, assuming full correlation amongst objects.

Definition at line 65 of file APWeightSum.h.

m_variance_nocorr

double APWeightSum::m_variance_nocorr

inherited

Holds the variance, assuming no correlations.

Definition at line 64 of file APWeightSum.h.

m_variance_sys

double APWeightSum::m_variance_sys

inherited

Holds the systematic variance (from systematics assigned to weights).

Definition at line 66 of file APWeightSum.h.

m_weight_vector

ClassDef (APWeightSumEnsemble,1) private std::vector< std::vector< APWeightEntry* > > APWeightSumEnsemble::m_weight_vector

< Performs the ensemble test to model final PDF.

Holds the weight objects (dim2) for each event (dim1).

Definition at line 49 of file APWeightSumEnsemble.h.

---

The documentation for this class was generated from the following files:

• APWeightSumEnsemble.h
• APWeightSumEnsemble.cxx