TagProbeFitter Class Reference

#include <TagProbeFitter.h>

Public Member Functions
bool	addCategory (std::string categoryName, std::string title, std::string expression)
	adds a new category variable to the set of variables describing the data in the tree; "expression" is parsed by factory() More...
bool	addExpression (std::string expressionName, std::string title, std::string expression, const std::vector< std::string > &arguments)
	adds a new category based on a cut More...
void	addFixedVariavles (const std::vector< std::string > &)
	set a list of variables to fix during first fit iteration. If the list is empty, do one iteration. More...
void	addPdf (std::string pdfName, std::vector< std::string > &pdfCommands)
bool	addThresholdCategory (std::string categoryName, std::string title, std::string varName, double cutValue)
	adds a new category based on a cut More...
bool	addVariable (std::string variableName, std::string title, double low, double hi, std::string units)
	adds a new real variable to the set of variables describing the data in the tree More...
std::string	calculateEfficiency (std::string dirName, std::string efficiencyCategory, std::string efficiencyState, std::vector< std::string > &unbinnedVariables, std::map< std::string, std::vector< double > > &binnedReals, std::map< std::string, std::vector< std::string > > &binnedCategories, std::vector< std::string > &binToPDFmap)
	calculate the efficiency for a particular binning of the data; it saves everything in the directory "dirName", uses the previously defined PDF with name "pdfName" More...
std::string	calculateEfficiency (std::string dirName, const std::vector< std::string > &efficiencyCategories, const std::vector< std::string > &efficiencyStates, std::vector< std::string > &unbinnedVariables, std::map< std::string, std::vector< double > > &binnedReals, std::map< std::string, std::vector< std::string > > &binnedCategories, std::vector< std::string > &binToPDFmap)
void	setBinnedFit (bool binned, int bins=0)
	set if to do a binned fit More...
void	setBinsForMassPlots (int bins)
	set number of bins to use when making the plots; 0 = automatic More...
void	setQuiet (bool quiet_=true)
	suppress most of the output from RooFit and Minuit More...
void	setSaveDistributionsPlot (bool saveDistributionsPlot_)
void	setWeightVar (const std::string &weight)
	set a variable to be used as weight for a dataset. empty string means no weights. More...
	TagProbeFitter (const std::vector< std::string > &inputFileNames, std::string inputDirectoryName, std::string inputTreeName, std::string outputFileName, int numCPU=1, bool saveWorkspace_=false, bool floatShapeParameters=true, const std::vector< std::string > &fixVars_=std::vector< std::string >())
	construct the fitter with the inputFileName, inputDirectoryName, inputTreeName, outputFileName and specify wether to save the workspace with data for each bin More...
	~TagProbeFitter ()
	destructor closes the files More...

Protected Member Functions
void	createPdf (RooWorkspace *w, std::vector< std::string > &pdfCommands)
	creates the simultaneous PDF in the workspace according to the "pdfCommands" More...
void	doCntEfficiency (RooWorkspace *w, RooRealVar &efficiency)
	calculate the efficiecny by counting in the dataset found in the workspace More...
void	doFitEfficiency (RooWorkspace *w, std::string pdfName, RooRealVar &efficiency)
	calculate the efficiecny with a simulataneous maximum likelihood fit in the dataset found in the workspace with PDF pdfName More...
void	doSBSEfficiency (RooWorkspace *w, RooRealVar &efficiency)
	calculate the efficiecny with side band substraction in the dataset found in the workspace More...
void	makeEfficiencyPlot1D (RooDataSet &eff, RooRealVar &v, const TString &plotName, const TString &plotTitle, const TString &effName, const char *catName=0, int catIndex=-1)
	makes the 1D plot More...
void	makeEfficiencyPlot2D (RooDataSet &eff, RooRealVar &v1, RooRealVar &v2, const TString &plotName, const TString &plotTitle, const TString &effName, const char *catName=0, int catIndex=-1)
	makes the 2D plot More...
void	saveDistributionsPlot (RooWorkspace *w)
	saves the distributions canvas More...
void	saveEfficiencyPlots (RooDataSet &eff, const TString &effName, RooArgSet &binnedVariables, RooArgSet &mappedCategories)
	saves the efficiency plots More...
void	saveFitPlot (RooWorkspace *w)
	saves the fit canvas More...
void	setInitialValues (RooWorkspace *w)
	sets initial values of the PDF parameters based on the data available in the workspace More...
void	varFixer (RooWorkspace *w, bool fix)
	fix or release variables selected by user More...
void	varRestorer (RooWorkspace *w)
	restore variables's values for fit starting point More...
void	varSaver (RooWorkspace *w)
	store values in the vector More...

Protected Attributes
int	binnedFit
	do binned fit; 0 = automatic, 1 = yes, -1 = no. d More...
bool	doSaveDistributionsPlot
	save distribution plots More...
std::vector< std::pair < std::pair< std::string, std::string >, std::pair < std::string, std::vector < std::string > > > >	expressionVars
	expressions computed almost on the fly More...
std::vector< std::string >	fixVars
	list of variables fo fix (see below) More...
std::vector< double >	fixVarValues
bool	floatShapeParameters
TChain *	inputTree
	pointer to the input TTree Chain of data More...
int	massBins
	number of bins to use in mass shape plots; 0 = automatic More...
int	numCPU
	number of CPUs to use for the fit More...
TDirectory *	outputDirectory
	pointer to the TDirectory in the output file that is the root directory for this fitter More...
TFile *	outputFile
	pointer to the output file More...
RooWorkspace	parameterParser
	a RooWorkspace object to parse input parameters with ".factory()" More...
std::map< std::string, std::vector< std::string > >	pdfs
	the map of pdf names to the vector of commands to build the pdf More...
bool	quiet
	suppress most printout More...
bool	saveWorkspace
	the default option wether to save the workspace for each bin More...
std::vector< std::pair < std::pair< std::string, std::string >, std::pair < std::string, double > > >	thresholdCategories
RooArgSet	variables
	the set of variables describing the data in the input TTree More...
std::string	weightVar
	weight variable (or empy string for no weights) More...

Detailed Description

Definition at line 11 of file TagProbeFitter.h.

Constructor & Destructor Documentation

TagProbeFitter::TagProbeFitter	(	const std::vector< std::string > &	inputFileNames,
		std::string	inputDirectoryName,
		std::string	inputTreeName,
		std::string	outputFileName,
		int	numCPU = 1,
		bool	saveWorkspace_ = false,
		bool	floatShapeParameters = true,
		const std::vector< std::string > &	fixVars_ = std::vector<std::string>()
	)

construct the fitter with the inputFileName, inputDirectoryName, inputTreeName, outputFileName and specify wether to save the workspace with data for each bin

Definition at line 51 of file TagProbeFitter.cc.

References gather_cfg::cout, alignCSCRings::e, i, and download_sqlite_cfg::outputFile.

                                                                                                                                                                                                                                                    {
  inputTree = new TChain((inputDirectoryName+"/"+inputTreeName).c_str());
  for(size_t i=0; i<inputFileNames.size(); i++){
    inputTree->Add(inputFileNames[i].c_str());
  }
  outputFile = new TFile(outputFileName.c_str(),"recreate");
  outputDirectory = outputFile->mkdir(inputDirectoryName.c_str());
  numCPU = numCPU_;
  saveWorkspace = saveWorkspace_;
  massBins = 0; // automatic default
  floatShapeParameters = floatShapeParameters_;
  fixVars = fixVars_;
  weightVar = "";
  if(!floatShapeParameters && fixVars.empty()) std::cout << "TagProbeFitter: " << "You wnat to fix some variables but do not specify them!";

  gROOT->SetStyle("Plain");
  gStyle->SetTitleFillColor(0);
  gStyle->SetPalette(1);
  gStyle->SetOptStat(0);
  gStyle->SetPaintTextFormat(".2f");

  quiet = false;

  binnedFit = false;

  doSaveDistributionsPlot = true;
  
  // make integration very precise
  RooAbsReal::defaultIntegratorConfig()->setEpsAbs(1e-13);
  RooAbsReal::defaultIntegratorConfig()->setEpsRel(1e-13);
}

TagProbeFitter::~TagProbeFitter

(

)

destructor closes the files

Definition at line 83 of file TagProbeFitter.cc.

References download_sqlite_cfg::outputFile.

                               {
  if(inputTree)
    delete inputTree;
  if(outputFile)
    outputFile->Close();
}

Member Function Documentation

bool TagProbeFitter::addCategory	(	std::string	categoryName,
		std::string	title,
		std::string	expression
	)

adds a new category variable to the set of variables describing the data in the tree; "expression" is parsed by factory()

Definition at line 105 of file TagProbeFitter.cc.

References EnergyCorrector::c, and makeLayoutFileForGui::variables.

Referenced by TagProbeFitTreeAnalyzer::TagProbeFitTreeAnalyzer().

                                                                            {
  RooCategory* c = (RooCategory*) parameterParser.factory(expression.c_str());
  if(!c)
    return false;
  //set the name of the category to the passed name instead of the one in the expression
  c->SetName(name.c_str());
  c->SetTitle(title.c_str());
  variables.addClone(*c);
  return true;
}

bool TagProbeFitter::addExpression	(	std::string	expressionName,
		std::string	title,
		std::string	expression,
		const std::vector< std::string > &	arguments
	)

adds a new category based on a cut

Definition at line 116 of file TagProbeFitter.cc.

Referenced by TagProbeFitTreeAnalyzer::TagProbeFitTreeAnalyzer().

                                                                                                                             {
  expressionVars.push_back(make_pair(make_pair(expressionName,title), make_pair(expression,arguments)));
  return true;
}

void TagProbeFitter::addFixedVariavles

(

const std::vector< std::string > &

)

set a list of variables to fix during first fit iteration. If the list is empty, do one iteration.

void TagProbeFitter::addPdf	(	std::string	pdfName,
		std::vector< std::string > &	pdfCommands
	)

add a new PDF to the list of available PDFs; "pdfCommands" are parsed by factory(). the user needs to define efficiency[0.9,0,1] for the initial value, "signal" PDF, "backgroundPass" PDF and "backgroundFail" PDF

Definition at line 128 of file TagProbeFitter.cc.

References mergeVDriftHistosByStation::name.

Referenced by TagProbeFitTreeAnalyzer::TagProbeFitTreeAnalyzer().

                                                                   {
  pdfs[name] = pdfCommands;
}

bool TagProbeFitter::addThresholdCategory	(	std::string	categoryName,
		std::string	title,
		std::string	varName,
		double	cutValue
	)

adds a new category based on a cut

Definition at line 122 of file TagProbeFitter.cc.

Referenced by TagProbeFitTreeAnalyzer::TagProbeFitTreeAnalyzer().

                                                                                                           {
  thresholdCategories.push_back(make_pair(make_pair(categoryName,title), make_pair(varName,cutValue)));
  return true;
}

bool TagProbeFitter::addVariable	(	std::string	variableName,
		std::string	title,
		double	low,
		double	hi,
		std::string	units
	)

adds a new real variable to the set of variables describing the data in the tree

Definition at line 98 of file TagProbeFitter.cc.

References groupFilesInBlocks::temp, and makeLayoutFileForGui::variables.

Referenced by TagProbeFitTreeAnalyzer::TagProbeFitTreeAnalyzer().

                                                                                              {
  RooRealVar temp(name.c_str(), title.c_str(), low, hi, units.c_str());
  temp.setBins(5000,"cache");
  variables.addClone(temp);
  return true;
}

std::string TagProbeFitter::calculateEfficiency ( std::string  dirName, std::string  efficiencyCategory, std::string  efficiencyState, std::vector< std::string > &  unbinnedVariables, std::map< std::string, std::vector< double > > &  binnedReals, std::map< std::string, std::vector< std::string > > &  binnedCategories, std::vector< std::string > &  binToPDFmap  )

inline

calculate the efficiency for a particular binning of the data; it saves everything in the directory "dirName", uses the previously defined PDF with name "pdfName"

Definition at line 39 of file TagProbeFitter.h.

Referenced by TagProbeFitTreeAnalyzer::calculateEfficiency().

                                                                                                                                                                                                                                                                                                        {
    std::vector<std::string> efficiencyCategories(1,efficiencyCategory);
    std::vector<std::string> efficiencyStates(1,efficiencyState);
    return calculateEfficiency(dirName, efficiencyCategories, efficiencyStates, unbinnedVariables, binnedReals, binnedCategories, binToPDFmap);
  }

std::string TagProbeFitter::calculateEfficiency	(	std::string	dirName,
		const std::vector< std::string > &	efficiencyCategories,
		const std::vector< std::string > &	efficiencyStates,
		std::vector< std::string > &	unbinnedVariables,
		std::map< std::string, std::vector< double > > &	binnedReals,
		std::map< std::string, std::vector< std::string > > &	binnedCategories,
		std::vector< std::string > &	binToPDFmap
	)

void TagProbeFitter::createPdf ( RooWorkspace *  w, std::vector< std::string > &  pdfCommands  )

protected

creates the simultaneous PDF in the workspace according to the "pdfCommands"

Definition at line 535 of file TagProbeFitter.cc.

References edmPickEvents::command, i, and AlCaHLTBitMon_QueryRunRegistry::string.

                                                                          {
  // create the signal and background pdfs defined by the user
  for(unsigned int i=0; i<pdfCommands.size(); i++){
    const std::string & command = pdfCommands[i];
    if (command.find("#import ") == 0) {
        TDirectory *here = gDirectory;
        w->import(command.substr(8).c_str());
        here->cd();
    } else {
      TDirectory *here = gDirectory;
      w->factory(command.c_str());
      here->cd();
    }
  }
  // setup the simultaneous extended pdf

  w->factory("expr::nSignalPass('efficiency*fSigAll*numTot', efficiency, fSigAll[.9,0,1],numTot[1,0,1e10])");
  w->factory("expr::nSignalFail('(1-efficiency)*fSigAll*numTot', efficiency, fSigAll,numTot)");  
  w->factory("expr::nBkgPass('effBkg*(1-fSigAll)*numTot', effBkg[.9,0,1],fSigAll,numTot)");
  w->factory("expr::nBkgFail('(1-effBkg)*(1-fSigAll)*numTot', effBkg,fSigAll,numTot)");  
  TString sPass = "signal", sFail = "signal";
  if (w->pdf("signalPass") != 0 && w->pdf("signalFail") != 0) {
    if (w->pdf("signal") != 0) throw std::logic_error("You must either define one 'signal' PDF or two PDFs ('signalPass', 'signalFail'), not both!"); 
    sPass = "signalPass"; sFail = "signalFail";
  } else if (w->pdf("signal") != 0) {
    if (w->pdf("signalPass") != 0 || w->pdf("signalFail") != 0) {
        throw std::logic_error("You must either define one 'signal' PDF or two PDFs ('signalPass', 'signalFail'), not both!"); 
    }
  } else {
    throw std::logic_error("You must either define one 'signal' PDF or two PDFs ('signalPass', 'signalFail')");
  }
  w->factory("SUM::pdfPass(nSignalPass*"+sPass+", nBkgPass*backgroundPass)"); //fBkgPass*
  w->factory("SUM::pdfFail(nSignalFail*"+sFail+", nBkgFail*backgroundFail)"); //fBkgFail*

  w->factory("SIMUL::simPdf(_efficiencyCategory_, Passed=pdfPass, Failed=pdfFail)");
  // signalFractionInPassing is not used in the fit just to set the initial values
  if (w->pdf("simPdf") == 0) throw std::runtime_error("Could not create simultaneous fit pdf.");
  if(w->var("signalFractionInPassing") == 0)
    w->factory("signalFractionInPassing[0.9]");
}

void TagProbeFitter::doCntEfficiency ( RooWorkspace *  w, RooRealVar &  efficiency  )

protected

calculate the efficiecny by counting in the dataset found in the workspace

Definition at line 828 of file TagProbeFitter.cc.

References alpha, alignCSCRings::e, and cmsPerfPublish::fail().

                                                                           {
  int pass = w->data("data")->sumEntries("_efficiencyCategory_==_efficiencyCategory_::Passed");
  int fail = w->data("data")->sumEntries("_efficiencyCategory_==_efficiencyCategory_::Failed");
  double e = (pass+fail == 0) ? 0 : pass/double(pass+fail);
  // Use Clopper-Pearson
  double alpha = (1.0 - .68540158589942957)/2;
  double lo = (pass == 0) ? 0.0 : ROOT::Math::beta_quantile(   alpha, pass,   fail+1 );
  double hi = (fail == 0) ? 1.0 : ROOT::Math::beta_quantile( 1-alpha, pass+1, fail   );
  //double lob, hib;
  //Efficiency( pass, pass+fail, .68540158589942957, e, lob, hib );
  //std::cerr << "CNT " << pass << "/" << fail << ":  Clopper Pearson [" << lo << ", "  << hi << "], Bayes [" << lob << ", " << hib << "]" << std::endl;
  efficiency.setVal(e);
  efficiency.setAsymError(lo-e, hi-e);
}

void TagProbeFitter::doFitEfficiency ( RooWorkspace *  w, std::string  pdfName, RooRealVar &  efficiency  )

protected

calculate the efficiecny with a simulataneous maximum likelihood fit in the dataset found in the workspace with PDF pdfName

—> if "floatShapeParameters==false" && "fixVars is NOT empty" : Perform a global fit to the whole sample, save the fitted values of the user specified parameters, and fix them for bin-by-bin fit.

Definition at line 375 of file TagProbeFitter.cc.

References ecal_dqm_sourceclient-live_cfg::cerr, data, and alignCSCRings::e.

                                                                                           {
  //if pdfName is empty skip the fit
  if(pdfName == "all"){
    return;
  }
  //create the simultaneous pdf of name pdfName
  createPdf(w, pdfs[pdfName]);
  //set the initial values for the yields of signal and background
  setInitialValues(w);  
  std::auto_ptr<RooFitResult> res(0);
  
  RooAbsData *data = w->data("data");
  std::auto_ptr<RooDataHist> bdata;
  if (binnedFit) { 
    // get variables from data, which contain also other binning or expression variables
    const RooArgSet *dataObs = data->get(0); 
    // remove everything which is not a dependency of the pdf
    RooArgSet *obs = w->pdf("simPdf")->getObservables(dataObs);
    bdata.reset(new RooDataHist("data_binned", "data_binned", *obs, *data)); 
    w->import(*bdata);
    data = w->data("data_binned");
    delete obs;
  }

  double totPassing = data->sumEntries("_efficiencyCategory_==_efficiencyCategory_::Passed");
  double totFailing = data->sumEntries("_efficiencyCategory_==_efficiencyCategory_::Failed");

  RooAbsReal* simNLL = w->pdf("simPdf")->createNLL(*data,Extended(true),NumCPU(numCPU));
  
  RooMinimizer minimizer(*simNLL); // we are going to use this for 'scan'
  RooMinuit minuit(*simNLL);
  minuit.setStrategy(1);
  minuit.setProfile(true);
  RooProfileLL profileLL("simPdfNLL","",*simNLL,*w->var("efficiency"));
  

  //******* The block of code below is to make the fit converge faster.
  // ****** This part is OPTIONAL, i.e., off be default. User can activate this
  // ****** by setting the following parameters: "fixVars" and "floatShapeParameters"
  // ****** Here is the full logic:

      
  if(!fixVars.empty()){
    // calculate initial values for parameters user want to fix
    if(!floatShapeParameters && fixVarValues.empty()){
      // we want to fix these parameters for each bin.
      // the following sequence fixes them, fits, releases and fits again
      // to get reasonable values. 
      // ----------------------------------------------------------------------
      // This procedure works only once with a whole dataset (without binning)
      // ----------------------------------------------------------------------

      // fix them
      varFixer(w,true);
      //do fit 
      minimizer.minimize("Minuit2","Scan");
      minuit.migrad();
      minuit.hesse();
      //minuit.minos();
      //w->pdf("simPdf")->fitTo(*data, Save(true), Extended(true), NumCPU(numCPU), Strategy(2),
      //PrintLevel(quiet?-1:1), PrintEvalErrors(quiet?-1:1), Warnings(!quiet));
      //release vars
      varFixer(w,false);
      //do fit 
      minimizer.minimize("Minuit2","Scan");      
      minuit.migrad();
      minuit.hesse();
      //minuit.minos();
      //w->pdf("simPdf")->fitTo(*data, Save(true), Extended(true), NumCPU(numCPU), Strategy(2),
      //PrintLevel(quiet?-1:1), PrintEvalErrors(quiet?-1:1), Warnings(!quiet));
      //save vars
      varSaver(w);
      // now we have a starting point. Fit will converge faster.
    }
    
    // here we can use initial values if we want (this works for each bin)
    if(!floatShapeParameters) varRestorer(w);  //restore vars

    //do fit
    minimizer.minimize("Minuit2","Scan");
    minuit.migrad();
    minuit.hesse();
    // initialize the profile likelihood
    profileLL.getVal();
    RooMinimizer* profMinuit = profileLL.minimizer();
    profMinuit->setProfile(true);
    profMinuit->setStrategy(2);     
    profMinuit->setPrintLevel(1);
    profMinuit->minos(*w->var("efficiency"));
    res.reset( profMinuit->save() );
    //res = w->pdf("simPdf")->fitTo(*data, Save(true), Extended(true), NumCPU(numCPU), Strategy(2),
    //Minos(*w->var("efficiency")), PrintLevel(quiet?-1:1), 
    //PrintEvalErrors(quiet?-1:1), Warnings(!quiet));
  }//if(!fixVars.empty())
      
  // (default = true) if we don't want to fix any parameters or want to fit each bin with all parameters floating
  if(floatShapeParameters){
    //release vars
    varFixer(w,false);
    
    //do fit
    minimizer.minimize("Minuit2","Scan");
    minuit.migrad();
    minuit.hesse();
    res.reset( w->pdf("simPdf")->fitTo(*data, Save(true), Extended(true), NumCPU(numCPU), Strategy(2),
                                    Minos(*w->var("efficiency")), PrintLevel(quiet?-1:1), 
                      PrintEvalErrors(quiet?-1:1), Warnings(!quiet)) );
   }



  // save everything
  res->Write("fitresults");
  w->saveSnapshot("finalState",w->components());
  saveFitPlot(w);
  //extract the efficiency parameter from the results
  RooRealVar* e = (RooRealVar*) res->floatParsFinal().find("efficiency");
  //What's wrong with this? and why don't they copy the errors!
  //efficiency = *e;
  efficiency.setVal(e->getVal());
  Double_t errLo = e->getErrorLo(), errHi = e->getErrorHi();
  if (errLo == 0 && e->getVal() < 0.5) errLo = e->getMin()-e->getVal();
  if (errHi == 0 && e->getVal() > 0.5) errHi = e->getMax()-e->getVal();
  efficiency.setAsymError(errLo, errHi);

  if (totPassing * totFailing == 0) {
   RooRealVar* nTot = (RooRealVar*) res->floatParsFinal().find("numTot");
   RooRealVar* fSig = (RooRealVar*) res->floatParsFinal().find("fSigAll");
   double cerr = ROOT::Math::beta_quantile( 1-(1.0-.68540158589942957)/2, 1, nTot->getVal() * fSig->getVal() ); 
    /*
    std::cout << "======================================================================================" << std::endl;
    std::cout << "======= totPassing "  << totPassing << ", totFailing " << totFailing << std::endl;
    std::cout << "======= FIT: e  "  <<  e->getVal() << ",  e Lo " << e->getErrorLo()  << ",  e Hi " <<  e->getErrorHi() << std::endl;
    std::cout << "======= FIT:nS  "  << nS->getVal() << ", nS Lo " << nS->getErrorLo() << ", nS Hi " << nS->getErrorHi() << std::endl;
    std::cout << "======= FIT:nB  "  << nB->getVal() << ", nB Lo " << nB->getErrorLo() << ", nB Hi " << nB->getErrorHi() << std::endl;
    std::cout << "======= CNT:    "  << cerr << std::endl;
    std::cout << "======================================================================================" << std::endl;
    */
    if (totPassing == 0) {
      efficiency.setVal(0);
      efficiency.setAsymError(0,cerr);
    } else {
      efficiency.setVal(1);
      efficiency.setAsymError(-cerr,0);
    }
  }

  delete simNLL;
}

void TagProbeFitter::doSBSEfficiency ( RooWorkspace *  w, RooRealVar &  efficiency  )

protected

calculate the efficiecny with side band substraction in the dataset found in the workspace

Definition at line 825 of file TagProbeFitter.cc.

                                                                           {
}

void TagProbeFitter::makeEfficiencyPlot1D ( RooDataSet &  eff, RooRealVar &  v, const TString &  plotName, const TString &  plotTitle, const TString &  effName, const char *  catName = 0, int  catIndex = -1  )

protected

makes the 1D plot

Definition at line 771 of file TagProbeFitter.cc.

References svgfig::canvas(), i, j, gen::n, and AlCaHLTBitMon_ParallelJobs::p.

                                                                                                                                                                                     {
 TGraphAsymmErrors *p = new TGraphAsymmErrors();
  const RooArgSet *entry = eff.get();
  const RooRealVar &vi = dynamic_cast<const RooRealVar &>(*entry->find(v.GetName()));
  const RooRealVar &ei = dynamic_cast<const RooRealVar &>(*entry->find("efficiency"));
  for (unsigned int i = 0, n = eff.numEntries(); i < n; ++i) {
    entry = eff.get(i); 
    if (catName != 0 && entry->getCatIndex(catName) != catIndex) continue;
    int j = p->GetN(); p->Set(j+1);
    p->SetPoint(j, vi.getVal(), ei.getVal() );
    p->SetPointError(j, -vi.getAsymErrorLo(), vi.getAsymErrorHi(), -ei.getAsymErrorLo(), ei.getAsymErrorHi() );
  }
  TCanvas canvas(plotName);
  TH1F *frame = new TH1F("frame", "Efficiency of "+effName, 1, v.getMin(), v.getMax()); frame->SetDirectory(0);
  p->SetNameTitle(Form("hxy_%s", eff.GetName()), "Efficiency of "+effName);
  p->GetXaxis()->SetTitle(strlen(v.getUnit()) ? Form("%s (%s)", v.GetName(), v.getUnit()) : v.GetName());
  p->GetYaxis()->SetTitle("Efficiency of "+effName);
  frame->GetXaxis()->SetTitle(strlen(v.getUnit()) ? Form("%s (%s)", v.GetName(), v.getUnit()) : v.GetName());
  frame->GetYaxis()->SetTitle("Efficiency of "+effName);
  frame->GetYaxis()->SetRangeUser(0,1);
  frame->Draw();
  p->SetLineWidth(2); p->SetMarkerStyle(kFullCircle); p->SetMarkerSize(1.2);
  p->Draw("P SAME");
  canvas.Write();
  delete frame;
  delete p;  
}

void TagProbeFitter::makeEfficiencyPlot2D ( RooDataSet &  eff, RooRealVar &  v1, RooRealVar &  v2, const TString &  plotName, const TString &  plotTitle, const TString &  effName, const char *  catName = 0, int  catIndex = -1  )

protected

makes the 2D plot

Definition at line 799 of file TagProbeFitter.cc.

References svgfig::canvas(), Data::Data(), alignCSCRings::e, h, and i.

                                                                                                                                                                                                      {
 TCanvas canvas(plotName);
  canvas.SetRightMargin(0.15);
  TH2F* h = new TH2F(plotName, plotName, v1.getBinning().numBins(), v1.getBinning().array(), v2.getBinning().numBins(), v2.getBinning().array());
  const RooArgSet* set = eff.get();
  RooRealVar* e = (RooRealVar*) set->find("efficiency");
  RooRealVar* v1_ = (RooRealVar*) set->find(v1.GetName());
  RooRealVar* v2_ = (RooRealVar*) set->find(v2.GetName());
  h->SetTitle(TString::Format("%s;%s%s;%s%s;Efficiency of %s", plotTitle.Data(),
    v1.GetTitle(), TString(v1.getUnit()).Length()==0?"":TString::Format(" (%s)", v1.getUnit()).Data(),
    v2.GetTitle(), TString(v2.getUnit()).Length()==0?"":TString::Format(" (%s)", v2.getUnit()).Data(), effName.Data()));
  h->SetOption("colztexte");
  h->GetZaxis()->SetRangeUser(-0.001,1.001);
  h->SetStats(kFALSE);
  for(int i=0; i<eff.numEntries(); i++){
    const RooArgSet *entry = eff.get(i); 
    if (catName != 0 && entry->getCatIndex(catName) != catIndex) continue;
    h->SetBinContent(h->FindBin(v1_->getVal(), v2_->getVal()), e->getVal());
    h->SetBinError(h->FindBin(v1_->getVal(), v2_->getVal()), (e->getErrorHi()-e->getErrorLo())/2.);
  }
  h->Draw();
  canvas.Draw();
  canvas.Write();
  delete h;
}

void TagProbeFitter::saveDistributionsPlot ( RooWorkspace *  w )

protected

saves the distributions canvas

Definition at line 676 of file TagProbeFitter.cc.

References svgfig::canvas(), i, and findQualityFiles::v.

                                                         {
  // save pointers to datasets to manage memory
  RooAbsData* dataAll = w->data("data");
  RooAbsData* dataPass = dataAll->reduce(Cut("_efficiencyCategory_==_efficiencyCategory_::Passed")); 
  RooAbsData* dataFail = dataAll->reduce(Cut("_efficiencyCategory_==_efficiencyCategory_::Failed")); 

  const RooArgSet* vars = dataAll->get();
  vector<RooRealVar*> reals;
  RooLinkedListIter it = vars->iterator();
  for(RooAbsArg* v = (RooAbsArg*)it.Next(); v!=0; v = (RooAbsArg*)it.Next() ){
    if(!v->InheritsFrom("RooRealVar")) continue;
    reals.push_back((RooRealVar*)v);
  }
  TCanvas canvas("distributions_canvas");
  canvas.Divide(3,reals.size());
  vector<RooPlot*> frames;
  for(unsigned int i=0; i<reals.size(); i++){
    // plot the Passing Probes
    canvas.cd(3*i+1);
    frames.push_back(reals[i]->frame(Name("Passing"), Title("Passing Probes"), Bins(100)));
    dataPass->plotOn(frames.back(), LineColor(kGreen));
    dataPass->statOn(frames.back());
    frames.back()->Draw();
    // plot the Failing Probes
    canvas.cd(3*i+2);
    frames.push_back(reals[i]->frame(Name("Failing"), Title("Failing Probes"), Bins(100)));
    dataFail->plotOn(frames.back(), LineColor(kRed));
    dataFail->statOn(frames.back());
    frames.back()->Draw();
    // plot the All Probes
    canvas.cd(3*i+3);
    frames.push_back(reals[i]->frame(Name("All"), Title("All Probes"), Bins(100)));
    dataAll->plotOn(frames.back(), LineColor(kBlue));
    dataAll->statOn(frames.back());
    frames.back()->Draw();
  }
  canvas.Draw();
  canvas.Write();
  for (size_t i=0; i<frames.size(); i++) {
    delete frames[i];
  }
  delete dataPass;
  delete dataFail;
}

void TagProbeFitter::saveEfficiencyPlots ( RooDataSet &  eff, const TString &  effName, RooArgSet &  binnedVariables, RooArgSet &  mappedCategories  )

protected

saves the efficiency plots

Definition at line 721 of file TagProbeFitter.cc.

References lumiQTWidget::t.

                                                                                                                                       {
  RooLinkedListIter v1it = binnedVariables.iterator();
  bool isOnePoint = (eff.numEntries() == 1); // for datasets with > 1 entry, we don't make plots for variables with just one bin
  for(RooRealVar* v1 = (RooRealVar*)v1it.Next(); v1!=0; v1 = (RooRealVar*)v1it.Next() ){
    RooArgSet binCategories1D;
    if (v1->numBins() == 1 && !isOnePoint) continue;
    RooLinkedListIter v2it = binnedVariables.iterator();
    for(RooRealVar* v2 = (RooRealVar*)v2it.Next(); v2!=0; v2 = (RooRealVar*)v2it.Next() ){
      if(v2 == v1) continue;
      if (v2->numBins() == 1 && !isOnePoint) continue;
      binCategories1D.addClone( RooBinningCategory(TString(v2->GetName())+"_bins", TString(v2->GetName())+"_bins", *v2) );

      RooArgSet binCategories2D;
      RooLinkedListIter v3it = binnedVariables.iterator();
      for(RooRealVar* v3 = (RooRealVar*)v3it.Next(); v3!=0; v3 = (RooRealVar*)v3it.Next() ){
        if(v3 == v1 || v3 == v2) continue;
        binCategories2D.addClone( RooBinningCategory(TString(v3->GetName())+"_bins", TString(v3->GetName())+"_bins", *v3) );
      }  
      RooMultiCategory allCats2D("allCats2D", "allCats2D", RooArgSet(binCategories2D, mappedCategories));
      if(allCats2D.numTypes()==0){
        makeEfficiencyPlot2D(eff, *v1, *v2, TString::Format("%s_%s_PLOT", v1->GetName(), v2->GetName()), "", effName);
      }else{
        RooDataSet myEff(eff);
        myEff.addColumn(allCats2D);
        std::auto_ptr<TIterator> catIt(allCats2D.typeIterator());
        for(RooCatType* t = (RooCatType*)catIt->Next(); t!=0; t = (RooCatType*)catIt->Next() ){
          TString catName = t->GetName();
          if(catName.Contains("NotMapped")) continue;
          catName.ReplaceAll("{","").ReplaceAll("}","").ReplaceAll(";","_&_");
          makeEfficiencyPlot2D(myEff, *v1, *v2, TString::Format("%s_%s_PLOT_%s",v1->GetName(), v2->GetName(), catName.Data()), catName, effName, "allCats1D", t->getVal());
        }        
      }
    }
    RooMultiCategory allCats1D("allCats1D", "allCats1D", RooArgSet(binCategories1D, mappedCategories));
    if(allCats1D.numTypes()==0){
      makeEfficiencyPlot1D(eff, *v1, TString::Format("%s_PLOT", v1->GetName()), "", effName);
    }else{
      RooDataSet myEff(eff);
      myEff.addColumn(allCats1D);
      std::auto_ptr<TIterator> catIt(allCats1D.typeIterator());
      for(RooCatType* t = (RooCatType*)catIt->Next(); t!=0; t = (RooCatType*)catIt->Next() ){
        TString catName = t->GetName();
        if(catName.Contains("NotMapped")) continue;
        catName.ReplaceAll("{","").ReplaceAll("}","").ReplaceAll(";","_&_");
        makeEfficiencyPlot1D(myEff, *v1, TString::Format("%s_PLOT_%s", v1->GetName(), catName.Data()), catName, effName, "allCats1D", t->getVal());
      }
    }
  }
}

void TagProbeFitter::saveFitPlot ( RooWorkspace *  w )

protected

saves the fit canvas

Definition at line 613 of file TagProbeFitter.cc.

References svgfig::canvas(), i, and findQualityFiles::v.

                                               {
  // save refferences for convenience
  RooCategory& efficiencyCategory = *w->cat("_efficiencyCategory_");
  RooAbsData* dataAll = (binnedFit ? w->data("data_binned") : w->data("data") );
  RooAbsData* dataPass = dataAll->reduce(Cut("_efficiencyCategory_==_efficiencyCategory_::Passed")); 
  RooAbsData* dataFail = dataAll->reduce(Cut("_efficiencyCategory_==_efficiencyCategory_::Failed")); 
  RooAbsPdf& pdf = *w->pdf("simPdf");
  std::auto_ptr<RooArgSet> obs(pdf.getObservables(*dataAll));
  RooRealVar* mass = 0;
  RooLinkedListIter it = obs->iterator();
  for(RooAbsArg* v = (RooAbsArg*)it.Next(); v!=0; v = (RooAbsArg*)it.Next() ){
    if(!v->InheritsFrom("RooRealVar")) continue;
    mass = (RooRealVar*)v;
    break;
  }
  if(!mass) return;
  // make a 2x2 canvas
  TCanvas canvas("fit_canvas");
  canvas.Divide(2,2);
  vector<RooPlot*> frames;
  // plot the Passing Probes
  canvas.cd(1);
  if (massBins == 0) {
      frames.push_back(mass->frame(Name("Passing"), Title("Passing Probes")));
      frames.push_back(mass->frame(Name("Failing"), Title("Failing Probes")));
      frames.push_back(mass->frame(Name("All"),     Title("All Probes")));
  } else {
      frames.push_back(mass->frame(Name("Passing"), Title("Passing Probes"), Bins(massBins)));
      frames.push_back(mass->frame(Name("Failing"), Title("Failing Probes"), Bins(massBins)));
      frames.push_back(mass->frame(Name("All"),     Title("All Probes"), Bins(massBins)));
  }
  dataPass->plotOn(frames[0]);
  pdf.plotOn(frames[0], Slice(efficiencyCategory, "Passed"), ProjWData(*dataPass), LineColor(kGreen));
  pdf.plotOn(frames[0], Slice(efficiencyCategory, "Passed"), ProjWData(*dataPass), LineColor(kGreen), Components("backgroundPass"), LineStyle(kDashed));
  frames[0]->Draw();
  // plot the Failing Probes
  canvas.cd(2);
  dataFail->plotOn(frames[1]);
  pdf.plotOn(frames[1], Slice(efficiencyCategory, "Failed"), ProjWData(*dataFail), LineColor(kRed));
  pdf.plotOn(frames[1], Slice(efficiencyCategory, "Failed"), ProjWData(*dataFail), LineColor(kRed), Components("backgroundFail"), LineStyle(kDashed));
  frames[1]->Draw();
  // plot the All Probes
  canvas.cd(3);
  dataAll->plotOn(frames.back());
  pdf.plotOn(frames.back(), ProjWData(*dataAll), LineColor(kBlue));
  pdf.plotOn(frames.back(), ProjWData(*dataAll), LineColor(kBlue), Components("backgroundPass,backgroundFail"), LineStyle(kDashed));
  frames.back()->Draw();
  // plot the Fit Results
  canvas.cd(4);
  frames.push_back(mass->frame(Name("Fit Results"), Title("Fit Results")));
  pdf.paramOn(frames.back(), dataAll, "", 0, "NELU", 0.1, 0.9, 0.9);
  // draw only the parameter box not the whole frame
  frames.back()->findObject(Form("%s_paramBox",pdf.GetName()))->Draw();
  //save and clean up
  canvas.Draw();
  canvas.Write();
  for (size_t i=0; i<frames.size(); i++) {
    delete frames[i];
  }
  delete dataPass;
  delete dataFail;
}

void TagProbeFitter::setBinnedFit ( bool  binned, int  bins = 0  )

inline

set if to do a binned fit

Definition at line 48 of file TagProbeFitter.h.

References binnedFit, and massBins.

Referenced by TagProbeFitTreeAnalyzer::TagProbeFitTreeAnalyzer().

{ binnedFit = binned; massBins = bins; }

void TagProbeFitter::setBinsForMassPlots

(

int

bins

)

set number of bins to use when making the plots; 0 = automatic

Definition at line 132 of file TagProbeFitter.cc.

Referenced by TagProbeFitTreeAnalyzer::TagProbeFitTreeAnalyzer().

                                                {
  massBins = bins;
}

void TagProbeFitter::setInitialValues ( RooWorkspace *  w )

protected

sets initial values of the PDF parameters based on the data available in the workspace

Definition at line 576 of file TagProbeFitter.cc.

                                                    {
  // calculate initial values
  double signalEfficiency = w->var("efficiency")->getVal();
  double signalFractionInPassing = w->var("signalFractionInPassing")->getVal();
  double totPassing = w->data("data")->sumEntries("_efficiencyCategory_==_efficiencyCategory_::Passed");
  double totFailinging = w->data("data")->sumEntries("_efficiencyCategory_==_efficiencyCategory_::Failed");
  double numSignalAll = totPassing*signalFractionInPassing/signalEfficiency;

  //std::cout << "Number of probes: " << totPassing+totFailinging << std::endl;

  // check if this value is inconsistent on the failing side
  if(numSignalAll*(1-signalEfficiency) > totFailinging)
    numSignalAll = totFailinging;
  // now set the values
  w->var("numTot")->setVal(totPassing+totFailinging);
  w->var("numTot")->setMax(2.0*(totPassing+totFailinging)+10); //wiggle room in case of 0 events in bin

  if (totPassing == 0) {
    w->var("efficiency")->setVal(0.0);
    w->var("efficiency")->setAsymError(0,1);
    w->var("efficiency")->setConstant(false);
  } else if (totFailinging == 0) {
    w->var("efficiency")->setVal(1.0);
    w->var("efficiency")->setAsymError(-1,0);
    w->var("efficiency")->setConstant(false);
  } else {
    w->var("efficiency")->setConstant(false);
  }

  // if signal fraction is 1 then set the number of background events to 0.
  //RooRealVar* fBkgPass = w->var("numBackgroundPass");
  //if(signalFractionInPassing==1.0) { fBkgPass->setVal(0.0); fBkgPass->setConstant(true); }

  // save initial state for reference
  w->saveSnapshot("initialState",w->components());
}

void TagProbeFitter::setQuiet

(

bool

quiet_ = true

)

suppress most of the output from RooFit and Minuit

Definition at line 90 of file TagProbeFitter.cc.

References cond::ERROR, instance, and dqm::qstatus::WARNING.

Referenced by TagProbeFitTreeAnalyzer::TagProbeFitTreeAnalyzer().

                                         { 
    quiet = quiet_; 
    if (quiet) {
        RooMsgService::instance().setGlobalKillBelow(RooFit::ERROR);
    } else {
        RooMsgService::instance().setGlobalKillBelow(RooFit::WARNING);
    }
}

void TagProbeFitter::setSaveDistributionsPlot ( bool  saveDistributionsPlot_ )

inline

Definition at line 54 of file TagProbeFitter.h.

References doSaveDistributionsPlot.

Referenced by TagProbeFitTreeAnalyzer::TagProbeFitTreeAnalyzer().

{ doSaveDistributionsPlot = saveDistributionsPlot_; }

void TagProbeFitter::setWeightVar

(

const std::string &

weight

)

set a variable to be used as weight for a dataset. empty string means no weights.

Definition at line 136 of file TagProbeFitter.cc.

References MetTreeProducer::var().

Referenced by TagProbeFitTreeAnalyzer::TagProbeFitTreeAnalyzer().

                                                      {
  weightVar = var;
}

void TagProbeFitter::varFixer ( RooWorkspace *  w, bool  fix  )

protected

fix or release variables selected by user

Definition at line 844 of file TagProbeFitter.cc.

References gather_cfg::cout.

                                                      {
  std::vector<std::string>::const_iterator it;
  for(it=fixVars.begin(); it<fixVars.end(); it++){    
    if(w->var((*it).c_str()))
      w->var((*it).c_str())->setAttribute("Constant",fix);
    else{
      std::cout << "TagProbeFitter: " << "Can't find a variable to fix: " << *it;
    }
  }
}

void TagProbeFitter::varRestorer ( RooWorkspace *  w )

protected

restore variables's values for fit starting point

Definition at line 867 of file TagProbeFitter.cc.

References gather_cfg::cout, and i.

                                               {
  if(fixVarValues.size()==fixVars.size())
    for(unsigned int i=0; i< fixVars.size(); i++){
      std::cout << "setting variable " << fixVars[i].c_str() << std::endl;
      w->var(fixVars[i].c_str())->setVal(fixVarValues[i]);
    }
  else{
    std::cout << "fixVars and fixVarValues are not of the same size!" << std::endl; 
  }
}

void TagProbeFitter::varSaver ( RooWorkspace *  w )

protected

store values in the vector

Definition at line 855 of file TagProbeFitter.cc.

References gather_cfg::cout.

                                            {
  if(!fixVarValues.empty()){
    std::cout << "attempt to save variables more than once!" << std::endl;
    return;
  }
  std::vector<std::string>::const_iterator it;
  for(it=fixVars.begin(); it<fixVars.end(); it++){
    fixVarValues.push_back(w->var((*it).c_str())->getVal());
  }
  
}

Member Data Documentation

int TagProbeFitter::binnedFit

protected

do binned fit; 0 = automatic, 1 = yes, -1 = no. d

Definition at line 82 of file TagProbeFitter.h.

Referenced by setBinnedFit().

bool TagProbeFitter::doSaveDistributionsPlot

protected

save distribution plots

Definition at line 76 of file TagProbeFitter.h.

Referenced by setSaveDistributionsPlot().

std::vector<std::pair<std::pair<std::string,std::string>, std::pair<std::string, std::vector<std::string> > > > TagProbeFitter::expressionVars

protected

expressions computed almost on the fly

Definition at line 98 of file TagProbeFitter.h.

std::vector<std::string> TagProbeFitter::fixVars

protected

list of variables fo fix (see below)

Definition at line 105 of file TagProbeFitter.h.

std::vector<double> TagProbeFitter::fixVarValues

protected

Definition at line 106 of file TagProbeFitter.h.

bool TagProbeFitter::floatShapeParameters

protected

release some variables before the fit in each bin if set to "false" will fit all dataset to get values of specified variables and then fit all bins having them fixed if set to "true" (default) will not fit all dataset, just each bin with fixed and then released variables

Definition at line 111 of file TagProbeFitter.h.

TChain* TagProbeFitter::inputTree

protected

pointer to the input TTree Chain of data

Definition at line 64 of file TagProbeFitter.h.

int TagProbeFitter::massBins

protected

number of bins to use in mass shape plots; 0 = automatic

Definition at line 85 of file TagProbeFitter.h.

Referenced by setBinnedFit().

int TagProbeFitter::numCPU

protected

number of CPUs to use for the fit

Definition at line 73 of file TagProbeFitter.h.

TDirectory* TagProbeFitter::outputDirectory

protected

pointer to the TDirectory in the output file that is the root directory for this fitter

Definition at line 70 of file TagProbeFitter.h.

TFile* TagProbeFitter::outputFile

protected

pointer to the output file

Definition at line 67 of file TagProbeFitter.h.

RooWorkspace TagProbeFitter::parameterParser

protected

a RooWorkspace object to parse input parameters with ".factory()"

Definition at line 114 of file TagProbeFitter.h.

std::map<std::string, std::vector<std::string> > TagProbeFitter::pdfs

protected

the map of pdf names to the vector of commands to build the pdf

Definition at line 88 of file TagProbeFitter.h.

bool TagProbeFitter::quiet

protected

suppress most printout

Definition at line 117 of file TagProbeFitter.h.

bool TagProbeFitter::saveWorkspace

protected

the default option wether to save the workspace for each bin

Definition at line 79 of file TagProbeFitter.h.

std::vector<std::pair<std::pair<std::string,std::string>, std::pair<std::string, double> > > TagProbeFitter::thresholdCategories

protected

Definition at line 102 of file TagProbeFitter.h.

RooArgSet TagProbeFitter::variables

protected

the set of variables describing the data in the input TTree

Definition at line 91 of file TagProbeFitter.h.

std::string TagProbeFitter::weightVar

protected

weight variable (or empy string for no weights)

Definition at line 94 of file TagProbeFitter.h.