/***************************************************************************** * Project: RooFit * * Package: RooFitCore * * @(#)root/roofitcore:$Id: RooExtendPdf.cxx 24278 2008-06-15 15:21:16Z wouter $ * Authors: * * WV, Wouter Verkerke, UC Santa Barbara, verkerke@slac.stanford.edu * * DK, David Kirkby, UC Irvine, dkirkby@uci.edu * * * * Copyright (c) 2000-2005, Regents of the University of California * * and Stanford University. All rights reserved. * * * * Redistribution and use in source and binary forms, * * with or without modification, are permitted according to the terms * * listed in LICENSE (http://roofit.sourceforge.net/license.txt) * *****************************************************************************/ /////////////////////////////////////////////////////////////////////////// // RooExtendPdf is a wrappper around an existing PDF that adds a // parameteric extended likelihood term to the PDF, optionally multiplied by a // fractional term from a partial normalization of the PDF: // // nExpected = N _or Expected = N * frac // // where N is supplied as a RooAbsReal to RooExtendPdf. // The fractional term is defined as // _ _ _ _ _ // Int(cutRegion[x]) pdf(x,y) dx dy // frac = ---------------_-------_-_---_--_ // Int(normRegion[x]) pdf(x,y) dx dy // // _ _ // where x is the set of dependents involved in the selection region and y // is the set of remaining dependents. // _ // cutRegion[x] is an limited integration range that is contained in // the nominal integration range normRegion[x[] // #include "RooFit.h" #include "Riostream.h" #include "RooExtendPdf.h" #include "RooExtendPdf.h" #include "RooArgList.h" #include "RooRealVar.h" #include "RooFormulaVar.h" #include "RooNameReg.h" #include "RooMsgService.h" ClassImp(RooExtendPdf) ; RooExtendPdf::RooExtendPdf() { // Default constructor } RooExtendPdf::RooExtendPdf(const char *name, const char *title, const RooAbsPdf& pdf, const RooAbsReal& norm, const char* rangeName) : RooAbsPdf(name,title), _pdf("pdf","PDF",this,(RooAbsReal&)pdf), _n("n","Normalization",this,(RooAbsReal&)norm), _rangeName(RooNameReg::ptr(rangeName)) { // Constructor. The ExtendedPdf behaves identical to the supplied input pdf, // but adds an extended likelihood term. The expected number of events return // is 'norm'. If a rangename is given, the number of events is interpreted as # // the number of events in the given range // Copy various setting from pdf setUnit(_pdf.arg().getUnit()) ; setPlotLabel(_pdf.arg().getPlotLabel()) ; } RooExtendPdf::RooExtendPdf(const RooExtendPdf& other, const char* name) : RooAbsPdf(other,name), _pdf("pdf",this,other._pdf), _n("n",this,other._n), _rangeName(other._rangeName) { // Copy constructor } RooExtendPdf::~RooExtendPdf() { // Destructor } Double_t RooExtendPdf::expectedEvents(const RooArgSet* nset) const { // Return the number of expected events, which is // // n / [ Int(xC,yF) pdf(x,y) / Int(xF,yF) pdf(x,y) ] // // Where x is the set of dependents with cuts defined // and y are the other dependents. xC is the integration // of x over the cut range, xF is the integration of // x over the full range. RooAbsPdf& pdf = (RooAbsPdf&)_pdf.arg() ; if (_rangeName && (!nset || nset->getSize()==0)) { coutW(InputArguments) << "RooExtendPdf::expectedEvents(" << GetName() << ") WARNING: RooExtendPdf needs non-null normalization set to calculate fraction in range " << _rangeName << ". Results may be nonsensical" << endl ; } Double_t nExp = _n ; // Optionally multiply with fractional normalization if (_rangeName) { globalSelectComp(kTRUE) ; Double_t fracInt = pdf.getNormObj(nset,nset,_rangeName)->getVal() ; globalSelectComp(kFALSE) ; if ( fracInt == 0. || _n == 0.) { coutW(Eval) << "RooExtendPdf(" << GetName() << ") WARNING: nExpected = " << _n << " / " << fracInt << " for nset = " << (nset?*nset:RooArgSet()) << endl ; } nExp /= fracInt ; // cout << "RooExtendPdf::expectedEvents(" << GetName() << ") fracInt = " << fracInt << " _n = " << _n << " nExpect = " << nExp << endl ; } // Multiply with original Nexpected, if defined if (pdf.canBeExtended()) nExp *= pdf.expectedEvents(nset) ; return nExp ; }