diff --git a/examples/Test_Dpipi_efficiencyHist.cc b/examples/Test_Dpipi_efficiencyHist.cc
index ef4782b..170184f 100755
--- a/examples/Test_Dpipi_efficiencyHist.cc
+++ b/examples/Test_Dpipi_efficiencyHist.cc
@@ -1,397 +1,403 @@
#include <iostream>
using std::cout;
using std::cerr;
using std::endl;
#include <vector>
#include <map>
#include "TFile.h"
#include "TH2.h"
#include "TH1D.h"
#include "TRandom.h"
#include "TString.h"
#include "TSystem.h"
#include "LauDaughters.hh"
#include "LauDecayTimePdf.hh"
#include "LauEffModel.hh"
#include "LauIsobarDynamics.hh"
#include "LauMagPhaseCoeffSet.hh"
#include "LauRandom.hh"
#include "LauRealImagCoeffSet.hh"
#include "LauTimeDepFitModel.hh"
#include "LauVetoes.hh"
#include "LauFlavTag.hh"
#include "Lau1DHistPdf.hh"
#include "Lau1DCubicSpline.hh"
void usage(const TString& progName)
{
cerr<<"Usage:"<<endl;
cerr<<progName<<" gen D_type [firstExptGen] [nExptGen] [CP eigenvalue]"<<endl;
cerr<<"or"<<endl;
cerr<<progName<<" fit D_type [port] [iFit] [firstExpt] [nExpt] [nExptGen]"<<endl;
}
int main([[maybe_unused]] const int argc, [[maybe_unused]] const char ** argv)
{
- //const TString dtype = argv[2];
- //Int_t port = 0;
- //Int_t iFit = 0;
- //Int_t firstExpt = 0;
- //Int_t firstExptGen = 0;
- //Int_t nExpt = 1;
- //Int_t nExptGen = 1;
- //LauTimeDepFitModel::CPEigenvalue eigenvalue = LauTimeDepFitModel::CPEven;
-
- //Bool_t fixPhiMix(kFALSE);
- //Bool_t useSinCos(kTRUE);
-
- //// check the command line arguments
- //if (argc<1) {
- // usage(argv[0]);
- // return EXIT_FAILURE;
- //}
- //TString command = argv[1];
- //if (command != "gen" && command != "fit") {
- // usage(argv[0]);
- // return EXIT_FAILURE;
- //}
- //if (command == "fit") {
- // if (argc>3) {
- // port = atoi(argv[3]);
- // if (argc>4) {
- // iFit = atoi(argv[4]);
- // if (argc>5) {
- // firstExpt = atoi(argv[5]);
- // if (argc>6) {
- // nExpt = atoi(argv[6]);
- // if (argc>7) {
- // nExptGen = atoi(argv[7]);
- // }
- // }
- // }
- // }
- // }
-
- // for (firstExptGen = 0; firstExptGen<(firstExpt+nExpt); firstExptGen+=nExptGen) {
- // }
- // firstExptGen -= nExptGen;
-
- // if ( (nExpt > nExptGen) || (nExptGen%nExpt != 0) ) {
- // cerr<<"Error, nExpt must be a factor of nExptGen."<<endl;
- // return EXIT_FAILURE;
- // }
-
- //} else {
- // if (argc>3) {
- // firstExptGen = atoi(argv[3]);
- // if (argc>4) {
- // nExptGen = atoi(argv[4]);
- // if (argc>5) {
- // Int_t eigval = atoi(argv[5]);
- // if ( eigval == 1 ) {
- // eigenvalue = LauTimeDepFitModel::CPOdd;
- // } else {
- // eigenvalue = LauTimeDepFitModel::CPEven;
- // }
- // }
- // }
- // }
- //}
-
- //cout<<"dtype "<<dtype<<" port "<<port<<" iFit "<<iFit<<" firstExpt "<<firstExpt<<" nExpt "<<nExpt<<endl;
-
- //Double_t nSigEvents(0);
- //if (dtype=="CPEven"){
- // nSigEvents = 15000;
- //} else {
- // nSigEvents = 10000;
- //}
-
- //LauDaughters* daughtersB0bar(0);
- //LauDaughters* daughtersB0(0);
- //LauEffModel* effModelB0bar(0);
- //LauEffModel* effModelB0(0);
- //LauVetoes* vetoes = new LauVetoes();
- ////vetoes->addMassVeto( 2, 2.00776, 2.01276 );
-
- //daughtersB0bar = new LauDaughters("B0_bar", "pi+", "pi-", "D0");
- //daughtersB0 = new LauDaughters("B0", "pi+", "pi-", "D0_bar");
-
- //// efficiency
- //effModelB0bar = new LauEffModel(daughtersB0bar, vetoes);
- //effModelB0 = new LauEffModel(daughtersB0, vetoes);
-
- //LauIsobarDynamics* sigModelB0bar(0);
- //LauIsobarDynamics* sigModelB0(0);
- //LauTimeDepFitModel* fitModel(0);
-
- //std::vector<LauParameter *> params;
+ const TString dtype = argv[2];
+ Int_t port = 0;
+ Int_t iFit = 0;
+ Int_t firstExpt = 0;
+ Int_t firstExptGen = 0;
+ Int_t nExpt = 1;
+ Int_t nExptGen = 1;
+ LauTimeDepFitModel::CPEigenvalue eigenvalue = LauTimeDepFitModel::CPEven;
+
+ Bool_t fixPhiMix(kFALSE);
+ Bool_t useSinCos(kTRUE);
+
+ // check the command line arguments
+ if (argc<1) {
+ usage(argv[0]);
+ return EXIT_FAILURE;
+ }
+ TString command = argv[1];
+ if (command != "gen" && command != "fit") {
+ usage(argv[0]);
+ return EXIT_FAILURE;
+ }
+ if (command == "fit") {
+ if (argc>3) {
+ port = atoi(argv[3]);
+ if (argc>4) {
+ iFit = atoi(argv[4]);
+ if (argc>5) {
+ firstExpt = atoi(argv[5]);
+ if (argc>6) {
+ nExpt = atoi(argv[6]);
+ if (argc>7) {
+ nExptGen = atoi(argv[7]);
+ }
+ }
+ }
+ }
+ }
+
+ for (firstExptGen = 0; firstExptGen<(firstExpt+nExpt); firstExptGen+=nExptGen) {
+ }
+ firstExptGen -= nExptGen;
+
+ if ( (nExpt > nExptGen) || (nExptGen%nExpt != 0) ) {
+ cerr<<"Error, nExpt must be a factor of nExptGen."<<endl;
+ return EXIT_FAILURE;
+ }
+
+ } else {
+ if (argc>3) {
+ firstExptGen = atoi(argv[3]);
+ if (argc>4) {
+ nExptGen = atoi(argv[4]);
+ if (argc>5) {
+ Int_t eigval = atoi(argv[5]);
+ if ( eigval == 1 ) {
+ eigenvalue = LauTimeDepFitModel::CPOdd;
+ } else {
+ eigenvalue = LauTimeDepFitModel::CPEven;
+ }
+ }
+ }
+ }
+ }
+
+ cout<<"dtype "<<dtype<<" port "<<port<<" iFit "<<iFit<<" firstExpt "<<firstExpt<<" nExpt "<<nExpt<<endl;
+
+ Double_t nSigEvents(0);
+ if (dtype=="CPEven"){
+ nSigEvents = 15000;
+ } else {
+ nSigEvents = 10000;
+ }
+
+ LauDaughters* daughtersB0bar(0);
+ LauDaughters* daughtersB0(0);
+ LauEffModel* effModelB0bar(0);
+ LauEffModel* effModelB0(0);
+ LauVetoes* vetoes = new LauVetoes();
+ //vetoes->addMassVeto( 2, 2.00776, 2.01276 );
+
+ daughtersB0bar = new LauDaughters("B0_bar", "pi+", "pi-", "D0");
+ daughtersB0 = new LauDaughters("B0", "pi+", "pi-", "D0_bar");
+
+ // efficiency
+ effModelB0bar = new LauEffModel(daughtersB0bar, vetoes);
+ effModelB0 = new LauEffModel(daughtersB0, vetoes);
+
+ LauIsobarDynamics* sigModelB0bar(0);
+ LauIsobarDynamics* sigModelB0(0);
+ LauTimeDepFitModel* fitModel(0);
+
+ std::vector<LauParameter *> params;
//LauFlavTag* flavTag = new LauFlavTag(params, kTRUE, "tagFlv", "tagCat");
- //flavTag->setTrueTagVarName("trueTag");
- //
- //// Use alternative tagging calibration parameters?
- ////flavTag->useAveOmegaDeltaOmega();
-
- //TFile* etafile(0);
- //TH1* etahist(0);
- //Lau1DHistPdf* etahistpdf(0);
- ////if (command == "gen"){
- // etafile = TFile::Open("histogram.root");
- // etahist = dynamic_cast<TH1*>(etafile->Get("htemp"));
- // etahistpdf = new Lau1DHistPdf("eta",etahist,0,0.54,kFALSE,kFALSE);
- ////}
-
- //// signal dynamics
- //sigModelB0bar = new LauIsobarDynamics(daughtersB0bar, effModelB0bar);
- //sigModelB0bar->setIntFileName("integ_B0bar.dat");
- //sigModelB0bar->addResonance("D*+_2", 2, LauAbsResonance::RelBW);
- //sigModelB0bar->addResonance("D*+_0", 2, LauAbsResonance::RelBW);
- //sigModelB0bar->addResonance("rho0(770)", 3, LauAbsResonance::RelBW);
- //sigModelB0bar->addResonance("f_0(980)", 3, LauAbsResonance::RelBW);
- //sigModelB0bar->addResonance("f_2(1270)", 3, LauAbsResonance::RelBW);
-
- //sigModelB0 = new LauIsobarDynamics(daughtersB0, effModelB0);
- //sigModelB0->setIntFileName("integ_B0.dat");
- //sigModelB0->addResonance("D*-_2", 1, LauAbsResonance::RelBW);
- //sigModelB0->addResonance("D*-_0", 1, LauAbsResonance::RelBW);
- //sigModelB0->addResonance("rho0(770)", 3, LauAbsResonance::RelBW);
- //sigModelB0->addResonance("f_0(980)", 3, LauAbsResonance::RelBW);
- //sigModelB0->addResonance("f_2(1270)", 3, LauAbsResonance::RelBW);
-
- //// fit model
- //fitModel = new LauTimeDepFitModel(sigModelB0bar,sigModelB0,flavTag);
- //fitModel->setASqMaxValue(1.45);
-
- //std::vector<LauAbsCoeffSet*> coeffset;
- //coeffset.push_back( new LauRealImagCoeffSet("D*-_2", 1.00, 0.00, kTRUE, kTRUE) );
- //coeffset.push_back( new LauRealImagCoeffSet("D*-_0", 0.53*TMath::Cos( 3.00), 0.53*TMath::Sin( 3.00), kFALSE, kFALSE) );
- //coeffset.push_back( new LauRealImagCoeffSet("rho0(770)", 1.22*TMath::Cos( 2.25), 1.22*TMath::Sin( 2.25), kFALSE, kFALSE) );
- //coeffset.push_back( new LauRealImagCoeffSet("f_0(980)", 0.19*TMath::Cos(-2.48), 0.19*TMath::Sin(-2.48), kFALSE, kFALSE) );
- //coeffset.push_back( new LauRealImagCoeffSet("f_2(1270)", 0.75*TMath::Cos( 2.97), 0.75*TMath::Sin( 2.97), kFALSE, kFALSE) );
-
- //for (std::vector<LauAbsCoeffSet*>::iterator iter=coeffset.begin(); iter!=coeffset.end(); ++iter) {
- // fitModel->setAmpCoeffSet(*iter);
+ LauFlavTag* flavTag = new LauFlavTag();
+ flavTag->setTrueTagVarName("trueTag");
+
+ // Use alternative tagging calibration parameters?
+ //flavTag->useAveOmegaDeltaOmega();
+
+ TFile* etafile(0);
+ TH1* etahist(0);
+ Lau1DHistPdf* etahistpdf(0);
+ //if (command == "gen"){
+ etafile = TFile::Open("histogram.root");
+ etahist = dynamic_cast<TH1*>(etafile->Get("htemp"));
+ etahistpdf = new Lau1DHistPdf("eta",etahist,0,0.54,kFALSE,kFALSE);
//}
- //fitModel->setCPEigenvalue( eigenvalue );
- //fitModel->setPhiMix( 2.0*LauConstants::beta, fixPhiMix, useSinCos );
-
- //fitModel->setAsymmetries(0.0,kFALSE);
-
- //int tagCat(-1);
- //// Tag cat fractions, dilutions and Delta dilutions
- //if (dtype=="CPEven"){
- // flavTag->addValidTagCat(63);
- // flavTag->setSignalTagCatPars(63, 0.6, 1.0, 0.0, kTRUE, kTRUE,"PerEvtMistag",0.5,0.5,1.0,1.0,0.0);
- // tagCat=63;
- //} else {
- // // Still need tagCat 63 in QFS channels for calibration etc
- // flavTag->addValidTagCat(63);
- // flavTag->setSignalTagCatPars(63, 0.6, 1.0, 0.0, kTRUE, kTRUE,"PerEvtMistag",0.5,0.5,1.0,1.0,0.0);
- // tagCat=63;
- //}
- ////if (command == "gen"){
+ // signal dynamics
+ sigModelB0bar = new LauIsobarDynamics(daughtersB0bar, effModelB0bar);
+ sigModelB0bar->setIntFileName("integ_B0bar.dat");
+ sigModelB0bar->addResonance("D*+_2", 2, LauAbsResonance::RelBW);
+ sigModelB0bar->addResonance("D*+_0", 2, LauAbsResonance::RelBW);
+ sigModelB0bar->addResonance("rho0(770)", 3, LauAbsResonance::RelBW);
+ sigModelB0bar->addResonance("f_0(980)", 3, LauAbsResonance::RelBW);
+ sigModelB0bar->addResonance("f_2(1270)", 3, LauAbsResonance::RelBW);
+
+ sigModelB0 = new LauIsobarDynamics(daughtersB0, effModelB0);
+ sigModelB0->setIntFileName("integ_B0.dat");
+ sigModelB0->addResonance("D*-_2", 1, LauAbsResonance::RelBW);
+ sigModelB0->addResonance("D*-_0", 1, LauAbsResonance::RelBW);
+ sigModelB0->addResonance("rho0(770)", 3, LauAbsResonance::RelBW);
+ sigModelB0->addResonance("f_0(980)", 3, LauAbsResonance::RelBW);
+ sigModelB0->addResonance("f_2(1270)", 3, LauAbsResonance::RelBW);
+
+ // fit model
+ fitModel = new LauTimeDepFitModel(sigModelB0bar,sigModelB0,flavTag);
+ fitModel->setASqMaxValue(1.45);
+
+ std::vector<LauAbsCoeffSet*> coeffset;
+ coeffset.push_back( new LauRealImagCoeffSet("D*-_2", 1.00, 0.00, kTRUE, kTRUE) );
+ coeffset.push_back( new LauRealImagCoeffSet("D*-_0", 0.53*TMath::Cos( 3.00), 0.53*TMath::Sin( 3.00), kFALSE, kFALSE) );
+ coeffset.push_back( new LauRealImagCoeffSet("rho0(770)", 1.22*TMath::Cos( 2.25), 1.22*TMath::Sin( 2.25), kFALSE, kFALSE) );
+ coeffset.push_back( new LauRealImagCoeffSet("f_0(980)", 0.19*TMath::Cos(-2.48), 0.19*TMath::Sin(-2.48), kFALSE, kFALSE) );
+ coeffset.push_back( new LauRealImagCoeffSet("f_2(1270)", 0.75*TMath::Cos( 2.97), 0.75*TMath::Sin( 2.97), kFALSE, kFALSE) );
+
+ for (std::vector<LauAbsCoeffSet*>::iterator iter=coeffset.begin(); iter!=coeffset.end(); ++iter) {
+ fitModel->setAmpCoeffSet(*iter);
+ }
+
+ fitModel->setCPEigenvalue( eigenvalue );
+ fitModel->setPhiMix( 2.0*LauConstants::beta, fixPhiMix, useSinCos );
+
+ fitModel->setAsymmetries(0.0,kFALSE);
+
+ int tagCat(-1);
+ // Tag cat fractions, dilutions and Delta dilutions
+// if (dtype=="CPEven"){
+// flavTag->addValidTagCat(63);
+// flavTag->setSignalTagCatPars(63, 0.6, 1.0, 0.0, kTRUE, kTRUE,"PerEvtMistag",0.5,0.5,1.0,1.0,0.0);
+// tagCat=63;
+// } else {
+// // Still need tagCat 63 in QFS channels for calibration etc
+// flavTag->addValidTagCat(63);
+// flavTag->setSignalTagCatPars(63, 0.6, 1.0, 0.0, kTRUE, kTRUE,"PerEvtMistag",0.5,0.5,1.0,1.0,0.0);
+// tagCat=63;
+// }
+
+ // Tag cat fractions, dilutions and Delta dilutions
+ flavTag->addTagger("OSTagger","tagVal_OS","mistagVal_OS", etahistpdf,0.20,0.5,1.0,0.20,0.5,1.0);
+ flavTag->addTagger("SSTagger","tagVal_SS","mistagVal_SS", etahistpdf,0.30,0.5,1.0,0.30,0.5,1.0);
+
+ //if (command == "gen"){
// fitModel->setSignalFlavTagPdfs(63,etahistpdf);
- ////}
-
-
- //// Delta t PDFs
-
- //const Double_t minDt(0.0);
- //const Double_t maxDt(20.0);
- //const Double_t minDtErr(0.0);
- //const Double_t maxDtErr(2.5);
- //const Int_t nGauss(3);
- //std::vector<Bool_t> scale(nGauss);
- //scale[0] = kTRUE;
- //scale[1] = kTRUE;
- //scale[2] = kFALSE;
-
- //std::vector<LauAbsRValue*> dtPars(10);
- //std::vector<LauAbsRValue*> dtParsExp(9);
- //TString mean0Name("dt_"); mean0Name += "_mean_0";
- //TString mean1Name("dt_"); mean1Name += "_mean_1";
- //TString mean2Name("dt_"); mean2Name += "_mean_2";
- //TString sigma0Name("dt_"); sigma0Name += "_sigma_0";
- //TString sigma1Name("dt_"); sigma1Name += "_sigma_1";
- //TString sigma2Name("dt_"); sigma2Name += "_sigma_2";
- //TString frac1Name("dt_"); frac1Name += "_frac_1";
- //TString frac2Name("dt_"); frac2Name += "_frac_2";
- //TString tauName("dt_"); tauName += "_tau";
- //TString freqName("dt_"); freqName += "_deltaM";
-
- //LauParameter * mean0 = new LauParameter(mean0Name, -0.181);
- //LauParameter * mean1 = new LauParameter(mean1Name, -1.27);
- //LauParameter * mean2 = new LauParameter(mean2Name, 0.0);
- //LauParameter * sigma0 = new LauParameter(sigma0Name, 1.067);
- //LauParameter * sigma1 = new LauParameter(sigma1Name, 3.0);
- //LauParameter * sigma2 = new LauParameter(sigma2Name, 8.0);
- //LauParameter * frac1 = new LauParameter(frac1Name, 0.0930);
- //LauParameter * frac2 = new LauParameter(frac2Name, 0.0036);
- //LauParameter * tau = new LauParameter(tauName, 1.520);
- //LauParameter * freq = new LauParameter(freqName, 0.5064);
-
- //TString mean0tagcat63Name("dt_"); mean0tagcat63Name += 63; mean0tagcat63Name += "_mean_0";
- //TString sigma0tagcat63Name("dt_"); sigma0tagcat63Name += 63; sigma0tagcat63Name += "_sigma_0";
-
- //LauParameter * mean0tagcat63 = new LauParameter(mean0tagcat63Name, -0.031);
- //LauParameter * sigma0tagcat63 = new LauParameter(sigma0tagcat63Name, 0.972);
-
- //dtPars[0] = mean0; dtParsExp[0] = mean0;
- //dtPars[1] = mean1; dtParsExp[1] = mean1;
- //dtPars[2] = mean2; dtParsExp[2] = mean2;
- //dtPars[3] = sigma0; dtParsExp[3] = sigma0;
- //dtPars[4] = sigma1; dtParsExp[4] = sigma1;
- //dtPars[5] = sigma2; dtParsExp[5] = sigma2;
- //dtPars[6] = frac1; dtParsExp[6] = frac1;
- //dtPars[7] = frac2; dtParsExp[7] = frac2;
- //dtPars[8] = tau; dtParsExp[8] = tau;
- //dtPars[9] = freq;
-
- ////Decay time acceptance spline - same for all tag cats (though doesn't have to be)
- //std::vector<Double_t> dtvals;
- //dtvals.push_back(0.0); dtvals.push_back(1.0); dtvals.push_back(2.0); dtvals.push_back(4.0); dtvals.push_back(6.0);
- //dtvals.push_back(8.0); dtvals.push_back(11.0); dtvals.push_back(14.0); dtvals.push_back(17.0); dtvals.push_back(20.0);
- //std::vector<Double_t> effvals;
- //effvals.push_back(0.0); effvals.push_back(0.15); effvals.push_back(0.25); effvals.push_back(0.33); effvals.push_back(0.38);
- //effvals.push_back(0.4); effvals.push_back(0.43); effvals.push_back(0.45); effvals.push_back(0.47); effvals.push_back(0.50);
- //
- ////Lau1DCubicSpline* dtEffSpline = new Lau1DCubicSpline(dtvals,effvals);
-// //Lau1DCubicSpline* dtEffSpline = new Lau1DCubicSpline(dtvals,effvals,Lau1DCubicSpline::StandardSpline,Lau1DCubicSpline::Natural,Lau1DCubicSpline::Natural);
-
- //const Int_t nBins = 9;
- //const Double_t edges[nBins + 1] = {0,1,2,4,6,8,11,14,17,20};
- //const Double_t binFilling[nBins] = {0.0075,0.02,0.029,0.655,0.69,0.715,0.74,0.76,0.785};
- //TH1D effHist("effHist","Histogram of efficiencies", nBins, edges);
-
- //for( Int_t i = 1 ; i <= nBins ; ++i ){ effHist.SetBinContent(i, binFilling[i-1]); }
-
- //if (dtype=="CPEven"){
- // LauDecayTimePdf * dtPdf = new LauDecayTimePdf( "deltaTAvg", "deltaTAvgErr", dtPars, minDt, maxDt, minDtErr, maxDtErr, LauDecayTimePdf::ExpTrig, nGauss, scale, LauDecayTimePdf::DecayTime, LauDecayTimePdf::Flat );
- // dtPdf->doSmearing(kFALSE);
- // dtPdf->setEffiHist(&effHist);
-// // dtPdf->setEffiSpline(dtEffSpline, effPars0);
- // fitModel->setSignalDtPdf( 0, dtPdf );
- //} else {
- // LauDecayTimePdf * dtPdf = new LauDecayTimePdf( "deltaTAvg", "deltaTAvgErr", dtPars, minDt, maxDt, minDtErr, maxDtErr, LauDecayTimePdf::ExpTrig, nGauss, scale, LauDecayTimePdf::DecayTime, LauDecayTimePdf::Flat );
- // dtPdf->doSmearing(kFALSE);
- // dtPdf->setEffiHist(&effHist);
-// // dtPdf->setEffiSpline(dtEffSpline, effPars0);
- // fitModel->setSignalDtPdf( 0, dtPdf );
- //}
-
- ////if (tagCat==63){
- // dtPars[0] = mean0tagcat63;
- // dtPars[1] = mean1->createClone();
- // dtPars[2] = mean2->createClone();
- // dtPars[3] = sigma0tagcat63;
- // dtPars[4] = sigma1->createClone();
- // dtPars[5] = sigma2->createClone();
- // dtPars[6] = frac1->createClone();
- // dtPars[7] = frac2->createClone();
- // dtPars[8] = tau->createClone();
- // dtPars[9] = freq->createClone();
-
- // //LauDecayTimePdf * dtPdf = new LauDecayTimePdf( "deltaTAvg", "deltaTAvgErr", dtPars, minDt, maxDt, minDtErr, maxDtErr, LauDecayTimePdf::ExpTrig, nGauss, scale, LauDecayTimePdf::DecayTime );
- // if (dtype=="CPEven"){
- // LauDecayTimePdf * dtPdf = new LauDecayTimePdf( "deltaTAvg", "deltaTAvgErr", dtPars, minDt, maxDt, minDtErr, maxDtErr, LauDecayTimePdf::SimFitSigBd, nGauss, scale, LauDecayTimePdf::DecayTime , LauDecayTimePdf::Flat );
- // dtPdf->doSmearing(kFALSE);
-// // dtPdf->setEffiSpline(dtEffSpline, effPars63);
- // dtPdf->setEffiHist(&effHist);
- // fitModel->setSignalDtPdf( tagCat, dtPdf );
- // } else {
- // LauDecayTimePdf * dtPdf = new LauDecayTimePdf( "deltaTAvg", "deltaTAvgErr", dtPars, minDt, maxDt, minDtErr, maxDtErr, LauDecayTimePdf::SimFitNormBd, nGauss, scale, LauDecayTimePdf::DecayTime , LauDecayTimePdf::Flat);
- // dtPdf->doSmearing(kFALSE);
-// // dtPdf->setEffiSpline(dtEffSpline, effPars63);
- // dtPdf->setEffiHist(&effHist);
- // fitModel->setSignalDtPdf( tagCat, dtPdf );
- // }
-
- ////}
-
- //// set the number of signal events
- //cout<<"nSigEvents = "<<nSigEvents<<endl;
- //LauParameter* nSigPar = new LauParameter("signalEvents", nSigEvents, -2.0*nSigEvents, 2.0*nSigEvents, kTRUE);
-
- //fitModel->setNSigEvents(nSigPar);
-
- //// set the number of experiments
- //if (command == "fit") {
- // fitModel->setNExpts(nExpt, firstExpt);
- //} else {
- // fitModel->setNExpts(nExptGen, firstExptGen);
- //}
-
- //fitModel->useAsymmFitErrors(kFALSE);
- ////fitModel->useRandomInitFitPars(kTRUE);
- //fitModel->useRandomInitFitPars(kFALSE);
- //fitModel->doPoissonSmearing(kFALSE);
- //fitModel->doEMLFit(kFALSE);
- //fitModel->writeLatexTable(kFALSE);
-
-
- //TString dataFile("");
- //TString treeName("fitTree");
- //TString rootFileName("");
- //TString tableFileName("");
- //TString fitToyFileName("");
- //TString splotFileName("");
- //if (command == "fit") {
- // dataFile = "TEST-Dpipi_"+dtype;
- // dataFile += "_expts"; dataFile += firstExptGen; dataFile += "-"; dataFile += firstExptGen+nExptGen-1;
- // dataFile += "_CP";
- // if ( eigenvalue == LauTimeDepFitModel::CPEven ) {
- // dataFile += "even";
- // } else {
- // dataFile += "odd";
- // }
- // dataFile += ".root";
-
- // rootFileName = "fits/fit"; rootFileName += iFit;
- // rootFileName += "_expts"; rootFileName += firstExpt; rootFileName += "-"; rootFileName += firstExpt+nExpt-1;
- // rootFileName += ".root";
-
- // tableFileName = "fitResults_"; tableFileName += iFit;
- // tableFileName += "_expts"; tableFileName += firstExpt; tableFileName += "-"; tableFileName += firstExpt+nExpt-1;
-
- // fitToyFileName = "fitToyMC_"+dtype; fitToyFileName += iFit;
- // fitToyFileName += "_expts"; fitToyFileName += firstExpt; fitToyFileName += "-"; fitToyFileName += firstExpt+nExpt-1;
- // fitToyFileName += ".root";
-
- // splotFileName = "splot_"; splotFileName += iFit;
- // splotFileName += "_expts"; splotFileName += firstExpt; splotFileName += "-"; splotFileName += firstExpt+nExpt-1;
- // splotFileName += ".root";
- //} else {
- // dataFile = "TEST-Dpipi_"+dtype;
- // dataFile += "_expts"; dataFile += firstExptGen; dataFile += "-"; dataFile += firstExptGen+nExptGen-1; dataFile += "_CP";
- // if ( eigenvalue == LauTimeDepFitModel::CPEven ) {
- // dataFile += "even";
- // } else {
- // dataFile += "odd";
- // }
- // dataFile += ".root";
-
- // rootFileName = "dummy.root";
- // tableFileName = "genResults";
//}
- //// Generate toy from the fitted parameters
- //fitModel->compareFitData(1, fitToyFileName);
- //// Write out per-event likelihoods and sWeights
- ////fitModel->writeSPlotData(splotFileName, "splot", kFALSE);
+ // Delta t PDFs
+
+ const Double_t minDt(0.0);
+ const Double_t maxDt(20.0);
+ const Double_t minDtErr(0.0);
+ const Double_t maxDtErr(2.5);
+ const Int_t nGauss(3);
+ std::vector<Bool_t> scale(nGauss);
+ scale[0] = kTRUE;
+ scale[1] = kTRUE;
+ scale[2] = kFALSE;
+
+ std::vector<LauAbsRValue*> dtPars(10);
+ std::vector<LauAbsRValue*> dtParsExp(9);
+ TString mean0Name("dt_"); mean0Name += "_mean_0";
+ TString mean1Name("dt_"); mean1Name += "_mean_1";
+ TString mean2Name("dt_"); mean2Name += "_mean_2";
+ TString sigma0Name("dt_"); sigma0Name += "_sigma_0";
+ TString sigma1Name("dt_"); sigma1Name += "_sigma_1";
+ TString sigma2Name("dt_"); sigma2Name += "_sigma_2";
+ TString frac1Name("dt_"); frac1Name += "_frac_1";
+ TString frac2Name("dt_"); frac2Name += "_frac_2";
+ TString tauName("dt_"); tauName += "_tau";
+ TString freqName("dt_"); freqName += "_deltaM";
+
+ LauParameter * mean0 = new LauParameter(mean0Name, -0.181);
+ LauParameter * mean1 = new LauParameter(mean1Name, -1.27);
+ LauParameter * mean2 = new LauParameter(mean2Name, 0.0);
+ LauParameter * sigma0 = new LauParameter(sigma0Name, 1.067);
+ LauParameter * sigma1 = new LauParameter(sigma1Name, 3.0);
+ LauParameter * sigma2 = new LauParameter(sigma2Name, 8.0);
+ LauParameter * frac1 = new LauParameter(frac1Name, 0.0930);
+ LauParameter * frac2 = new LauParameter(frac2Name, 0.0036);
+ LauParameter * tau = new LauParameter(tauName, 1.520);
+ LauParameter * freq = new LauParameter(freqName, 0.5064);
+
+ TString mean0tagcat63Name("dt_"); mean0tagcat63Name += 63; mean0tagcat63Name += "_mean_0";
+ TString sigma0tagcat63Name("dt_"); sigma0tagcat63Name += 63; sigma0tagcat63Name += "_sigma_0";
+
+ LauParameter * mean0tagcat63 = new LauParameter(mean0tagcat63Name, -0.031);
+ LauParameter * sigma0tagcat63 = new LauParameter(sigma0tagcat63Name, 0.972);
+
+ dtPars[0] = mean0; dtParsExp[0] = mean0;
+ dtPars[1] = mean1; dtParsExp[1] = mean1;
+ dtPars[2] = mean2; dtParsExp[2] = mean2;
+ dtPars[3] = sigma0; dtParsExp[3] = sigma0;
+ dtPars[4] = sigma1; dtParsExp[4] = sigma1;
+ dtPars[5] = sigma2; dtParsExp[5] = sigma2;
+ dtPars[6] = frac1; dtParsExp[6] = frac1;
+ dtPars[7] = frac2; dtParsExp[7] = frac2;
+ dtPars[8] = tau; dtParsExp[8] = tau;
+ dtPars[9] = freq;
+
+ //Decay time acceptance spline - same for all tag cats (though doesn't have to be)
+ std::vector<Double_t> dtvals;
+ dtvals.push_back(0.0); dtvals.push_back(1.0); dtvals.push_back(2.0); dtvals.push_back(4.0); dtvals.push_back(6.0);
+ dtvals.push_back(8.0); dtvals.push_back(11.0); dtvals.push_back(14.0); dtvals.push_back(17.0); dtvals.push_back(20.0);
+ std::vector<Double_t> effvals;
+ effvals.push_back(0.0); effvals.push_back(0.15); effvals.push_back(0.25); effvals.push_back(0.33); effvals.push_back(0.38);
+ effvals.push_back(0.4); effvals.push_back(0.43); effvals.push_back(0.45); effvals.push_back(0.47); effvals.push_back(0.50);
+
+ //Lau1DCubicSpline* dtEffSpline = new Lau1DCubicSpline(dtvals,effvals);
+// Lau1DCubicSpline* dtEffSpline = new Lau1DCubicSpline(dtvals,effvals,Lau1DCubicSpline::StandardSpline,Lau1DCubicSpline::Natural,Lau1DCubicSpline::Natural);
+
+ const Int_t nBins = 9;
+ const Double_t edges[nBins + 1] = {0,1,2,4,6,8,11,14,17,20};
+ const Double_t binFilling[nBins] = {0.0075,0.02,0.029,0.655,0.69,0.715,0.74,0.76,0.785};
+ TH1D effHist("effHist","Histogram of efficiencies", nBins, edges);
+
+ for( Int_t i = 1 ; i <= nBins ; ++i ){ effHist.SetBinContent(i, binFilling[i-1]); }
+
+ if (dtype=="CPEven"){
+ LauDecayTimePdf * dtPdf = new LauDecayTimePdf( "deltaTAvg", "deltaTAvgErr", dtPars, minDt, maxDt, minDtErr, maxDtErr, LauDecayTimePdf::ExpTrig, nGauss, scale, LauDecayTimePdf::DecayTime, LauDecayTimePdf::Flat );
+ dtPdf->doSmearing(kFALSE);
+ dtPdf->setEffiHist(&effHist);
+// dtPdf->setEffiSpline(dtEffSpline, effPars0);
+ fitModel->setSignalDtPdf( dtPdf );
+ } else {
+ LauDecayTimePdf * dtPdf = new LauDecayTimePdf( "deltaTAvg", "deltaTAvgErr", dtPars, minDt, maxDt, minDtErr, maxDtErr, LauDecayTimePdf::ExpTrig, nGauss, scale, LauDecayTimePdf::DecayTime, LauDecayTimePdf::Flat );
+ dtPdf->doSmearing(kFALSE);
+ dtPdf->setEffiHist(&effHist);
+// dtPdf->setEffiSpline(dtEffSpline, effPars0);
+ fitModel->setSignalDtPdf( dtPdf );
+ }
+
+ //if (tagCat==63){
+ dtPars[0] = mean0tagcat63;
+ dtPars[1] = mean1->createClone();
+ dtPars[2] = mean2->createClone();
+ dtPars[3] = sigma0tagcat63;
+ dtPars[4] = sigma1->createClone();
+ dtPars[5] = sigma2->createClone();
+ dtPars[6] = frac1->createClone();
+ dtPars[7] = frac2->createClone();
+ dtPars[8] = tau->createClone();
+ dtPars[9] = freq->createClone();
+
+ //LauDecayTimePdf * dtPdf = new LauDecayTimePdf( "deltaTAvg", "deltaTAvgErr", dtPars, minDt, maxDt, minDtErr, maxDtErr, LauDecayTimePdf::ExpTrig, nGauss, scale, LauDecayTimePdf::DecayTime );
+ if (dtype=="CPEven"){
+ LauDecayTimePdf * dtPdf = new LauDecayTimePdf( "deltaTAvg", "deltaTAvgErr", dtPars, minDt, maxDt, minDtErr, maxDtErr, LauDecayTimePdf::SimFitSigBd, nGauss, scale, LauDecayTimePdf::DecayTime , LauDecayTimePdf::Flat );
+ dtPdf->doSmearing(kFALSE);
+// dtPdf->setEffiSpline(dtEffSpline, effPars63);
+ dtPdf->setEffiHist(&effHist);
+ fitModel->setSignalDtPdf( dtPdf );
+ } else {
+ LauDecayTimePdf * dtPdf = new LauDecayTimePdf( "deltaTAvg", "deltaTAvgErr", dtPars, minDt, maxDt, minDtErr, maxDtErr, LauDecayTimePdf::SimFitNormBd, nGauss, scale, LauDecayTimePdf::DecayTime , LauDecayTimePdf::Flat);
+ dtPdf->doSmearing(kFALSE);
+// dtPdf->setEffiSpline(dtEffSpline, effPars63);
+ dtPdf->setEffiHist(&effHist);
+ fitModel->setSignalDtPdf( dtPdf );
+ }
- //// Execute the generation/fit
- //if ( command == "fit" ){
- // fitModel->runSlave( dataFile, treeName, rootFileName, tableFileName, "localhost", port );
- //} else {
- // fitModel->run( command, dataFile, treeName, rootFileName, tableFileName );
//}
+ // set the number of signal events
+ cout<<"nSigEvents = "<<nSigEvents<<endl;
+ LauParameter* nSigPar = new LauParameter("signalEvents", nSigEvents, -2.0*nSigEvents, 2.0*nSigEvents, kTRUE);
+
+ fitModel->setNSigEvents(nSigPar);
+
+ // set the number of experiments
+ if (command == "fit") {
+ fitModel->setNExpts(nExpt, firstExpt);
+ } else {
+ fitModel->setNExpts(nExptGen, firstExptGen);
+ }
+
+ fitModel->useAsymmFitErrors(kFALSE);
+ //fitModel->useRandomInitFitPars(kTRUE);
+ fitModel->useRandomInitFitPars(kFALSE);
+ fitModel->doPoissonSmearing(kFALSE);
+ fitModel->doEMLFit(kFALSE);
+ fitModel->writeLatexTable(kFALSE);
+
+
+ TString dataFile("");
+ TString treeName("fitTree");
+ TString rootFileName("");
+ TString tableFileName("");
+ TString fitToyFileName("");
+ TString splotFileName("");
+ if (command == "fit") {
+ dataFile = "TEST-Dpipi_"+dtype;
+ dataFile += "_expts"; dataFile += firstExptGen; dataFile += "-"; dataFile += firstExptGen+nExptGen-1;
+ dataFile += "_CP";
+ if ( eigenvalue == LauTimeDepFitModel::CPEven ) {
+ dataFile += "even";
+ } else {
+ dataFile += "odd";
+ }
+ dataFile += ".root";
+
+ rootFileName = "fits/fit"; rootFileName += iFit;
+ rootFileName += "_expts"; rootFileName += firstExpt; rootFileName += "-"; rootFileName += firstExpt+nExpt-1;
+ rootFileName += ".root";
+
+ tableFileName = "fitResults_"; tableFileName += iFit;
+ tableFileName += "_expts"; tableFileName += firstExpt; tableFileName += "-"; tableFileName += firstExpt+nExpt-1;
+
+ fitToyFileName = "fitToyMC_"+dtype; fitToyFileName += iFit;
+ fitToyFileName += "_expts"; fitToyFileName += firstExpt; fitToyFileName += "-"; fitToyFileName += firstExpt+nExpt-1;
+ fitToyFileName += ".root";
+
+ splotFileName = "splot_"; splotFileName += iFit;
+ splotFileName += "_expts"; splotFileName += firstExpt; splotFileName += "-"; splotFileName += firstExpt+nExpt-1;
+ splotFileName += ".root";
+ } else {
+ dataFile = "TEST-Dpipi_"+dtype;
+ dataFile += "_expts"; dataFile += firstExptGen; dataFile += "-"; dataFile += firstExptGen+nExptGen-1; dataFile += "_CP";
+ if ( eigenvalue == LauTimeDepFitModel::CPEven ) {
+ dataFile += "even";
+ } else {
+ dataFile += "odd";
+ }
+ dataFile += ".root";
+
+ rootFileName = "dummy.root";
+ tableFileName = "genResults";
+ }
+
+ // Generate toy from the fitted parameters
+ fitModel->compareFitData(1, fitToyFileName);
+
+ // Write out per-event likelihoods and sWeights
+ //fitModel->writeSPlotData(splotFileName, "splot", kFALSE);
+
+ // Execute the generation/fit
+ if ( command == "fit" ){
+ fitModel->runSlave( dataFile, treeName, rootFileName, tableFileName, "localhost", port );
+ } else {
+ fitModel->run( command, dataFile, treeName, rootFileName, tableFileName );
+ }
+
return EXIT_SUCCESS;
}
diff --git a/src/LauTimeDepFitModel.cc b/src/LauTimeDepFitModel.cc
index 23d03d3..396ec8a 100644
--- a/src/LauTimeDepFitModel.cc
+++ b/src/LauTimeDepFitModel.cc
@@ -1,2871 +1,2871 @@
/*
Copyright 2006 University of Warwick
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
/*
Laura++ package authors:
John Back
Paul Harrison
Thomas Latham
*/
/*! \file LauTimeDepFitModel.cc
\brief File containing implementation of LauTimeDepFitModel class.
*/
#include <iostream>
#include <iomanip>
#include <fstream>
#include <map>
#include <vector>
#include "TFile.h"
#include "TMinuit.h"
#include "TRandom.h"
#include "TSystem.h"
#include "TVirtualFitter.h"
#include "LauAbsBkgndDPModel.hh"
#include "LauAbsCoeffSet.hh"
#include "LauAbsPdf.hh"
#include "LauAsymmCalc.hh"
#include "LauComplex.hh"
#include "LauConstants.hh"
#include "LauDPPartialIntegralInfo.hh"
#include "LauDaughters.hh"
#include "LauDecayTimePdf.hh"
#include "LauFitNtuple.hh"
#include "LauGenNtuple.hh"
#include "LauIsobarDynamics.hh"
#include "LauKinematics.hh"
#include "LauPrint.hh"
#include "LauRandom.hh"
#include "LauScfMap.hh"
#include "LauTimeDepFitModel.hh"
#include "LauFlavTag.hh"
ClassImp(LauTimeDepFitModel)
LauTimeDepFitModel::LauTimeDepFitModel(LauIsobarDynamics* modelB0bar, LauIsobarDynamics* modelB0, LauFlavTag* flavTag) : LauAbsFitModel(),
sigModelB0bar_(modelB0bar),
sigModelB0_(modelB0),
kinematicsB0bar_(modelB0bar ? modelB0bar->getKinematics() : 0),
kinematicsB0_(modelB0 ? modelB0->getKinematics() : 0),
usingBkgnd_(kFALSE),
flavTag_(flavTag),
nSigComp_(0),
nSigDPPar_(0),
nDecayTimePar_(0),
nExtraPdfPar_(0),
nNormPar_(0),
nCalibPar_(0),
nTagEffPar_(0),
nEffiPar_(0),
nAsymPar_(0),
coeffsB0bar_(0),
coeffsB0_(0),
coeffPars_(0),
fitFracB0bar_(0),
fitFracB0_(0),
fitFracAsymm_(0),
acp_(0),
meanEffB0bar_("meanEffB0bar",0.0,0.0,1.0),
meanEffB0_("meanEffB0",0.0,0.0,1.0),
DPRateB0bar_("DPRateB0bar",0.0,0.0,100.0),
DPRateB0_("DPRateB0",0.0,0.0,100.0),
signalEvents_(0),
signalAsym_(0),
cpevVarName_(""),
cpEigenValue_(CPEven),
evtCPEigenVals_(0),
deltaM_("deltaM",0.0),
deltaGamma_("deltaGamma",0.0),
tau_("tau",LauConstants::tauB0),
phiMix_("phiMix", 2.0*LauConstants::beta, -LauConstants::threePi, LauConstants::threePi, kFALSE),
sinPhiMix_("sinPhiMix", TMath::Sin(2.0*LauConstants::beta), -1.0, 1.0, kFALSE),
cosPhiMix_("cosPhiMix", TMath::Cos(2.0*LauConstants::beta), -1.0, 1.0, kFALSE),
useSinCos_(kFALSE),
phiMixComplex_(TMath::Cos(-2.0*LauConstants::beta),TMath::Sin(-2.0*LauConstants::beta)),
signalDecayTimePdf_(),
backgroundDecayTimePdfs_(),
curEvtDecayTime_(0.0),
curEvtDecayTimeErr_(0.0),
sigExtraPdf_(),
sigFlavTagPdf_(),
bkgdFlavTagPdf_(),
AProd_("AProd",0.0,-1.0,1.0,kTRUE),
iterationsMax_(500000),
nGenLoop_(0),
ASq_(0.0),
aSqMaxVar_(0.0),
aSqMaxSet_(1.25),
storeGenAmpInfo_(kFALSE),
signalTree_(),
reuseSignal_(kFALSE),
sigDPLike_(0.0),
sigExtraLike_(0.0),
sigFlavTagLike_(0.0),
bkgdFlavTagLike_(0.0),
sigTotalLike_(0.0)
{
// Set up ftag here?
// Make sure that the integration scheme will be symmetrised
sigModelB0bar_->forceSymmetriseIntegration(kTRUE);
sigModelB0_->forceSymmetriseIntegration(kTRUE);
}
LauTimeDepFitModel::~LauTimeDepFitModel()
{
for (LauPdfList::iterator pdf_iter = sigExtraPdf_->begin(); pdf_iter != sigExtraPdf_->end(); ++pdf_iter) {
delete *(pdf_iter);
}
for (std::vector<LauEmbeddedData*>::iterator iter = bkgndTree_.begin(); iter != bkgndTree_.end(); ++iter){
delete *(iter);
}
}
void LauTimeDepFitModel::setupBkgndVectors()
{
UInt_t nBkgnds = this->nBkgndClasses();
BkgndDPModels_.resize( nBkgnds );
BkgndPdfs_.resize( nBkgnds );
bkgndEvents_.resize( nBkgnds );
bkgndAsym_.resize( nBkgnds );
bkgndTree_.resize( nBkgnds );
reuseBkgnd_.resize( nBkgnds );
bkgndDPLike_.resize( nBkgnds );
bkgndExtraLike_.resize( nBkgnds );
bkgndTotalLike_.resize( nBkgnds );
}
void LauTimeDepFitModel::setNSigEvents(LauParameter* nSigEvents)
{
if ( nSigEvents == 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : The LauParameter pointer is null." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
if ( signalEvents_ != 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : You are trying to overwrite the signal yield." << std::endl;
return;
}
if ( signalAsym_ != 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : You are trying to overwrite the signal asymmetry." << std::endl;
return;
}
signalEvents_ = nSigEvents;
signalEvents_->name("signalEvents");
Double_t value = nSigEvents->value();
signalEvents_->range(-2.0*(TMath::Abs(value)+1.0),2.0*(TMath::Abs(value)+1.0));
signalAsym_ = new LauParameter("signalAsym",0.0,-1.0,1.0,kTRUE);
}
void LauTimeDepFitModel::setNSigEvents(LauParameter* nSigEvents, LauParameter* sigAsym)
{
if ( nSigEvents == 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : The event LauParameter pointer is null." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
if ( sigAsym == 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : The asym LauParameter pointer is null." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
if ( signalEvents_ != 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : You are trying to overwrite the signal yield." << std::endl;
return;
}
if ( signalAsym_ != 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : You are trying to overwrite the signal asymmetry." << std::endl;
return;
}
signalEvents_ = nSigEvents;
signalEvents_->name("signalEvents");
Double_t value = nSigEvents->value();
signalEvents_->range(-2.0*(TMath::Abs(value)+1.0), 2.0*(TMath::Abs(value)+1.0));
signalAsym_ = sigAsym;
signalAsym_->name("signalAsym");
signalAsym_->range(-1.0,1.0);
}
void LauTimeDepFitModel::setNBkgndEvents(LauAbsRValue* nBkgndEvents)
{
if ( nBkgndEvents == 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNBgkndEvents : The background yield LauParameter pointer is null." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
if ( ! this->validBkgndClass( nBkgndEvents->name() ) ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : Invalid background class \"" << nBkgndEvents->name() << "\"." << std::endl;
std::cerr << " : Background class names must be provided in \"setBkgndClassNames\" before any other background-related actions can be performed." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
UInt_t bkgndID = this->bkgndClassID( nBkgndEvents->name() );
if ( bkgndEvents_[bkgndID] != 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : You are trying to overwrite the background yield." << std::endl;
return;
}
if ( bkgndAsym_[bkgndID] != 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : You are trying to overwrite the background asymmetry." << std::endl;
return;
}
nBkgndEvents->name( nBkgndEvents->name()+"Events" );
if ( nBkgndEvents->isLValue() ) {
Double_t value = nBkgndEvents->value();
LauParameter* yield = dynamic_cast<LauParameter*>( nBkgndEvents );
yield->range(-2.0*(TMath::Abs(value)+1.0), 2.0*(TMath::Abs(value)+1.0));
}
bkgndEvents_[bkgndID] = nBkgndEvents;
bkgndAsym_[bkgndID] = new LauParameter(nBkgndEvents->name()+"Asym",0.0,-1.0,1.0,kTRUE);
}
void LauTimeDepFitModel::setNBkgndEvents(LauAbsRValue* nBkgndEvents, LauAbsRValue* bkgndAsym)
{
if ( nBkgndEvents == 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : The background yield LauParameter pointer is null." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
if ( bkgndAsym == 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : The background asym LauParameter pointer is null." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
if ( ! this->validBkgndClass( nBkgndEvents->name() ) ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : Invalid background class \"" << nBkgndEvents->name() << "\"." << std::endl;
std::cerr << " : Background class names must be provided in \"setBkgndClassNames\" before any other background-related actions can be performed." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
UInt_t bkgndID = this->bkgndClassID( nBkgndEvents->name() );
if ( bkgndEvents_[bkgndID] != 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : You are trying to overwrite the background yield." << std::endl;
return;
}
if ( bkgndAsym_[bkgndID] != 0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : You are trying to overwrite the background asymmetry." << std::endl;
return;
}
bkgndEvents_[bkgndID]->name( nBkgndEvents->name()+"Events" );
if ( nBkgndEvents->isLValue() ) {
Double_t value = nBkgndEvents->value();
LauParameter* yield = dynamic_cast<LauParameter*>( nBkgndEvents );
yield->range(-2.0*(TMath::Abs(value)+1.0), 2.0*(TMath::Abs(value)+1.0));
}
bkgndEvents_[bkgndID] = nBkgndEvents;
bkgndAsym_[bkgndID]->name( nBkgndEvents->name()+"Asym" );
if ( bkgndAsym->isLValue() ) {
LauParameter* asym = dynamic_cast<LauParameter*>( bkgndAsym );
asym->range(-1.0, 1.0);
}
bkgndAsym_[bkgndID] = bkgndAsym;
}
void LauTimeDepFitModel::setSignalDtPdf(LauDecayTimePdf* pdf)
{
if (pdf==0) {
std::cerr<<"ERROR in LauTimeDepFitModel::setSignalDtPdf : The PDF pointer is null, not adding it."<<std::endl;
return;
}
signalDecayTimePdf_ = pdf;
}
void LauTimeDepFitModel::setBackgroundDtPdf(LauDecayTimePdf* pdf)
{
// TODO If these are all histograms shouldn't need to add much more code in other functions
if (pdf==0) {
std::cerr<<"ERROR in LauTimeDepFitModel::setBackgroundDtPdf : The PDF pointer is null, not adding it."<<std::endl;
return;
}
backgroundDecayTimePdfs_.push_back(pdf);
usingBkgnd_ = kTRUE;
}
void LauTimeDepFitModel::setBkgndDPModels(const TString& bkgndClass, LauAbsBkgndDPModel* model)
{
if (model==0) {
std::cerr << "ERROR in LauTimeDepFitModel::setBkgndDPModels : the model pointer is null." << std::endl;
return;
}
// check that this background name is valid
if ( ! this->validBkgndClass( bkgndClass) ) {
std::cerr << "ERROR in LauTimeDepFitModel::setBkgndDPModel : Invalid background class \"" << bkgndClass << "\"." << std::endl;
std::cerr << " : Background class names must be provided in \"setBkgndClassNames\" before any other background-related actions can be performed." << std::endl;
return;
}
UInt_t bkgndID = this->bkgndClassID( bkgndClass );
BkgndDPModels_[bkgndID] = model;
usingBkgnd_ = kTRUE;
}
void LauTimeDepFitModel::setSignalPdfs(LauAbsPdf* pdf)
{
// These "extra variables" are assumed to be purely kinematical, like mES and DeltaE
//or making use of Rest of Event information, and therefore independent of whether
//the parent is a B0 or a B0bar. If this assupmtion doesn't hold, do modify this part!
if (pdf==0) {
std::cerr<<"ERROR in LauTimeDepFitModel::setSignalPdfs : The PDF pointer is null."<<std::endl;
return;
}
sigExtraPdf_->push_back(pdf);
}
void LauTimeDepFitModel::setBkgndPdf(const TString& bkgndClass, LauAbsPdf* pdf)
{
if (pdf==0) {
std::cerr << "ERROR in LauTimeDepFitModel::setBkgndPdf : PDF pointer is null." << std::endl;
return;
}
// check that this background name is valid
if ( ! this->validBkgndClass( bkgndClass ) ) {
std::cerr << "ERROR in LauTimeDepFitModel::setBkgndPdf : Invalid background class \"" << bkgndClass << "\"." << std::endl;
std::cerr << " : Background class names must be provided in \"setBkgndClassNames\" before any other background-related actions can be performed." << std::endl;
return;
}
UInt_t bkgndID = this->bkgndClassID( bkgndClass );
BkgndPdfs_[bkgndID].push_back(pdf);
usingBkgnd_ = kTRUE;
}
void LauTimeDepFitModel::setPhiMix(const Double_t phiMix, const Bool_t fixPhiMix, const Bool_t useSinCos)
{
phiMix_.value(phiMix); phiMix_.initValue(phiMix); phiMix_.genValue(phiMix); phiMix_.fixed(fixPhiMix);
const Double_t sinPhiMix = TMath::Sin(phiMix);
sinPhiMix_.value(sinPhiMix); sinPhiMix_.initValue(sinPhiMix); sinPhiMix_.genValue(sinPhiMix); sinPhiMix_.fixed(fixPhiMix);
const Double_t cosPhiMix = TMath::Cos(phiMix);
cosPhiMix_.value(cosPhiMix); cosPhiMix_.initValue(cosPhiMix); cosPhiMix_.genValue(cosPhiMix); cosPhiMix_.fixed(fixPhiMix);
useSinCos_ = useSinCos;
phiMixComplex_.setRealPart(cosPhiMix);
phiMixComplex_.setImagPart(-1.0*sinPhiMix);
}
void LauTimeDepFitModel::initialise()
{
// From the initial parameter values calculate the coefficients
// so they can be passed to the signal model
this->updateCoeffs();
// Initialisation
if (this->useDP() == kTRUE) {
this->initialiseDPModels();
}
//Flavour tagging
flavTag_->initialise();
if (!this->useDP() && sigExtraPdf_->empty()) {
std::cerr<<"ERROR in LauTimeDepFitModel::initialise : Signal model doesn't exist for any variable."<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
if (this->useDP() == kTRUE) {
// Check that we have all the Dalitz-plot models
if ((sigModelB0bar_ == 0) || (sigModelB0_ == 0)) {
std::cerr<<"ERROR in LauTimeDepFitModel::initialise : the pointer to one (particle or anti-particle) of the signal DP models is null."<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
}
// Next check that, if a given component is being used we've got the
// right number of PDFs for all the variables involved
// TODO - should probably check variable names and so on as well
//UInt_t nsigpdfvars(0);
//for ( LauPdfList::const_iterator pdf_iter = sigExtraPdf_.begin(); pdf_iter != sigExtraPdf_.end(); ++pdf_iter ) {
// std::vector<TString> varNames = (*pdf_iter)->varNames();
// for ( std::vector<TString>::const_iterator var_iter = varNames.begin(); var_iter != varNames.end(); ++var_iter ) {
// if ( (*var_iter) != "m13Sq" && (*var_iter) != "m23Sq" ) {
// ++nsigpdfvars;
// }
// }
//}
//if (usingBkgnd_) {
// for (LauBkgndPdfsList::const_iterator bgclass_iter = BkgndPdfsB0_.begin(); bgclass_iter != BkgndPdfsB0_.end(); ++bgclass_iter) {
// UInt_t nbkgndpdfvars(0);
// const LauPdfList& pdfList = (*bgclass_iter);
// for ( LauPdfList::const_iterator pdf_iter = pdfList.begin(); pdf_iter != pdfList.end(); ++pdf_iter ) {
// std::vector<TString> varNames = (*pdf_iter)->varNames();
// for ( std::vector<TString>::const_iterator var_iter = varNames.begin(); var_iter != varNames.end(); ++var_iter ) {
// if ( (*var_iter) != "m13Sq" && (*var_iter) != "m23Sq" ) {
// ++nbkgndpdfvars;
// }
// }
// }
// if (nbkgndpdfvars != nsigpdfvars) {
// std::cerr << "ERROR in LauTimeDepFitModel::initialise : There are " << nsigpdfvars << " signal PDF variables but " << nbkgndpdfvars << " bkgnd PDF variables." << std::endl;
// gSystem->Exit(EXIT_FAILURE);
// }
// }
//}
// Clear the vectors of parameter information so we can start from scratch
this->clearFitParVectors();
// Set the fit parameters for signal and background models
this->setSignalDPParameters();
// Set the fit parameters for the decay time models
this->setDecayTimeParameters();
// Set the fit parameters for the extra PDFs
this->setExtraPdfParameters();
// Set the initial bg and signal events
this->setFitNEvents();
// Handle flavour-tagging calibration parameters
this->setCalibParams();
// Add tagging efficiency parameters
this->setTagEffParams();
// Add the efficiency parameters
this->setEffiParams();
//Asymmetry terms AProd and in setAsymmetries()?
//this->setAsymParams();
// Check that we have the expected number of fit variables
const LauParameterPList& fitVars = this->fitPars();
if (fitVars.size() != (nSigDPPar_ + nDecayTimePar_ + nExtraPdfPar_ + nNormPar_ + nCalibPar_ + nTagEffPar_ + nEffiPar_)) {
std::cerr<<"ERROR in LauTimeDepFitModel::initialise : Number of fit parameters not of expected size."<<std::endl;
std::cout<< fitVars.size() << " != " << nSigDPPar_ << nDecayTimePar_ << nExtraPdfPar_ << nNormPar_ << nCalibPar_ << nTagEffPar_ << nEffiPar_ << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
this->setExtraNtupleVars();
}
void LauTimeDepFitModel::recalculateNormalisation()
{
sigModelB0bar_->recalculateNormalisation();
sigModelB0_->recalculateNormalisation();
sigModelB0bar_->modifyDataTree();
sigModelB0_->modifyDataTree();
this->calcInterferenceTermIntegrals();
}
void LauTimeDepFitModel::initialiseDPModels()
{
if (sigModelB0bar_ == 0) {
std::cerr<<"ERROR in LauTimeDepFitModel::initialiseDPModels : B0bar signal DP model doesn't exist"<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
if (sigModelB0_ == 0) {
std::cerr<<"ERROR in LauTimeDepFitModel::initialiseDPModels : B0 signal DP model doesn't exist"<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
// Need to check that the number of components we have and that the dynamics has matches up
const UInt_t nAmpB0bar = sigModelB0bar_->getnTotAmp();
const UInt_t nAmpB0 = sigModelB0_->getnTotAmp();
if ( nAmpB0bar != nAmpB0 ) {
std::cerr << "ERROR in LauTimeDepFitModel::initialiseDPModels : Unequal number of signal DP components in the particle and anti-particle models: " << nAmpB0bar << " != " << nAmpB0 << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
if ( nAmpB0bar != nSigComp_ ) {
std::cerr << "ERROR in LauTimeDepFitModel::initialiseDPModels : Number of signal DP components in the model (" << nAmpB0bar << ") not equal to number of coefficients supplied (" << nSigComp_ << ")." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
std::cout<<"INFO in LauTimeDepFitModel::initialiseDPModels : Initialising signal DP model"<<std::endl;
sigModelB0bar_->initialise(coeffsB0bar_);
sigModelB0_->initialise(coeffsB0_);
fifjEffSum_.clear();
fifjEffSum_.resize(nSigComp_);
for (UInt_t iAmp = 0; iAmp < nSigComp_; ++iAmp) {
fifjEffSum_[iAmp].resize(nSigComp_);
}
// calculate the integrals of the A*Abar terms
this->calcInterferenceTermIntegrals();
this->calcInterTermNorm();
// Add backgrounds
if (usingBkgnd_ == kTRUE) {
for (LauBkgndDPModelList::iterator iter = BkgndDPModels_.begin(); iter != BkgndDPModels_.end(); ++iter) {
(*iter)->initialise();
}
}
}
void LauTimeDepFitModel::calcInterferenceTermIntegrals()
{
const std::vector<LauDPPartialIntegralInfo*>& integralInfoListB0bar = sigModelB0bar_->getIntegralInfos();
const std::vector<LauDPPartialIntegralInfo*>& integralInfoListB0 = sigModelB0_->getIntegralInfos();
// TODO should check (first time) that they match in terms of number of entries in the vectors and that each entry has the same number of points, ranges, weights etc.
LauComplex A, Abar, fifjEffSumTerm;
for (UInt_t iAmp = 0; iAmp < nSigComp_; ++iAmp) {
for (UInt_t jAmp = 0; jAmp < nSigComp_; ++jAmp) {
fifjEffSum_[iAmp][jAmp].zero();
}
}
const UInt_t nIntegralRegions = integralInfoListB0bar.size();
for ( UInt_t iRegion(0); iRegion < nIntegralRegions; ++iRegion ) {
const LauDPPartialIntegralInfo* integralInfoB0bar = integralInfoListB0bar[iRegion];
const LauDPPartialIntegralInfo* integralInfoB0 = integralInfoListB0[iRegion];
const UInt_t nm13Points = integralInfoB0bar->getnm13Points();
const UInt_t nm23Points = integralInfoB0bar->getnm23Points();
for (UInt_t m13 = 0; m13 < nm13Points; ++m13) {
for (UInt_t m23 = 0; m23 < nm23Points; ++m23) {
const Double_t weight = integralInfoB0bar->getWeight(m13,m23);
const Double_t eff = integralInfoB0bar->getEfficiency(m13,m23);
const Double_t effWeight = eff*weight;
for (UInt_t iAmp = 0; iAmp < nSigComp_; ++iAmp) {
A = integralInfoB0->getAmplitude(m13, m23, iAmp);
for (UInt_t jAmp = 0; jAmp < nSigComp_; ++jAmp) {
Abar = integralInfoB0bar->getAmplitude(m13, m23, jAmp);
fifjEffSumTerm = Abar*A.conj();
fifjEffSumTerm.rescale(effWeight);
fifjEffSum_[iAmp][jAmp] += fifjEffSumTerm;
}
}
}
}
}
}
void LauTimeDepFitModel::calcInterTermNorm()
{
const std::vector<Double_t>& fNormB0bar = sigModelB0bar_->getFNorm();
const std::vector<Double_t>& fNormB0 = sigModelB0_->getFNorm();
LauComplex norm;
for (UInt_t iAmp = 0; iAmp < nSigComp_; ++iAmp) {
for (UInt_t jAmp = 0; jAmp < nSigComp_; ++jAmp) {
LauComplex coeffTerm = coeffsB0bar_[jAmp]*coeffsB0_[iAmp].conj();
coeffTerm *= fifjEffSum_[iAmp][jAmp];
coeffTerm.rescale(fNormB0bar[jAmp] * fNormB0[iAmp]);
norm += coeffTerm;
}
}
norm *= phiMixComplex_;
interTermReNorm_ = 2.0*norm.re();
interTermImNorm_ = 2.0*norm.im();
}
void LauTimeDepFitModel::setAmpCoeffSet(LauAbsCoeffSet* coeffSet)
{
// Is there a component called compName in the signal models?
TString compName = coeffSet->name();
TString conjName = sigModelB0bar_->getConjResName(compName);
const LauDaughters* daughtersB0bar = sigModelB0bar_->getDaughters();
const LauDaughters* daughtersB0 = sigModelB0_->getDaughters();
const Bool_t conjugate = daughtersB0bar->isConjugate( daughtersB0 );
if ( ! sigModelB0bar_->hasResonance(compName) ) {
if ( ! sigModelB0bar_->hasResonance(conjName) ) {
std::cerr<<"ERROR in LauTimeDepFitModel::setAmpCoeffSet : B0bar signal DP model doesn't contain component \""<<compName<<"\"."<<std::endl;
return;
}
std::cerr<<"WARNING in LauTimeDepFitModel::setAmpCoeffSet : B0bar signal DP model doesn't contain component \""<<compName<<"\" but does contain the conjugate \""<<conjName<<"\", resetting name to use the conjugate."<<std::endl;
TString tmp = compName;
compName = conjName;
conjName = tmp;
coeffSet->name( compName );
}
if ( conjugate ) {
if ( ! sigModelB0_->hasResonance(conjName) ) {
std::cerr<<"ERROR in LauTimeDepFitModel::setAmpCoeffSet : B0 signal DP model doesn't contain component \""<<conjName<<"\"."<<std::endl;
return;
}
} else {
if ( ! sigModelB0_->hasResonance(compName) ) {
std::cerr<<"ERROR in LauTimeDepFitModel::setAmpCoeffSet : B0 signal DP model doesn't contain component \""<<compName<<"\"."<<std::endl;
return;
}
}
// Do we already have it in our list of names?
for (std::vector<LauAbsCoeffSet*>::const_iterator iter=coeffPars_.begin(); iter!=coeffPars_.end(); ++iter) {
if ((*iter)->name() == compName) {
std::cerr<<"ERROR in LauTimeDepFitModel::setAmpCoeffSet : Have already set coefficients for \""<<compName<<"\"."<<std::endl;
return;
}
}
coeffSet->index(nSigComp_);
coeffPars_.push_back(coeffSet);
TString parName = coeffSet->baseName(); parName += "FitFracAsym";
fitFracAsymm_.push_back(LauParameter(parName, 0.0, -1.0, 1.0));
acp_.push_back(coeffSet->acp());
++nSigComp_;
std::cout<<"INFO in LauTimeDepFitModel::setAmpCoeffSet : Added coefficients for component \""<<compName<<"\" to the fit model."<<std::endl;
}
void LauTimeDepFitModel::calcAsymmetries(Bool_t initValues)
{
// Calculate the CP asymmetries
// Also calculate the fit fraction asymmetries
for (UInt_t i = 0; i < nSigComp_; i++) {
acp_[i] = coeffPars_[i]->acp();
LauAsymmCalc asymmCalc(fitFracB0bar_[i][i].value(), fitFracB0_[i][i].value());
Double_t asym = asymmCalc.getAsymmetry();
fitFracAsymm_[i].value(asym);
if (initValues) {
fitFracAsymm_[i].genValue(asym);
fitFracAsymm_[i].initValue(asym);
}
}
}
void LauTimeDepFitModel::setSignalDPParameters()
{
// Set the fit parameters for the signal model.
nSigDPPar_ = 0;
if ( ! this->useDP() ) {
return;
}
std::cout << "INFO in LauTimeDepFitModel::setSignalDPParameters : Setting the initial fit parameters for the signal DP model." << std::endl;
// Place isobar coefficient parameters in vector of fit variables
LauParameterPList& fitVars = this->fitPars();
for (UInt_t i = 0; i < nSigComp_; ++i) {
LauParameterPList pars = coeffPars_[i]->getParameters();
for (LauParameterPList::iterator iter = pars.begin(); iter != pars.end(); ++iter) {
if ( !(*iter)->clone() ) {
fitVars.push_back(*iter);
++nSigDPPar_;
}
}
}
// Obtain the resonance parameters and place them in the vector of fit variables and in a separate vector
// Need to make sure that they are unique because some might appear in both DP models
LauParameterPSet& resVars = this->resPars();
resVars.clear();
LauParameterPList& sigDPParsB0bar = sigModelB0bar_->getFloatingParameters();
LauParameterPList& sigDPParsB0 = sigModelB0_->getFloatingParameters();
for ( LauParameterPList::iterator iter = sigDPParsB0bar.begin(); iter != sigDPParsB0bar.end(); ++iter ) {
if ( resVars.insert(*iter).second ) {
fitVars.push_back(*iter);
++nSigDPPar_;
}
}
for ( LauParameterPList::iterator iter = sigDPParsB0.begin(); iter != sigDPParsB0.end(); ++iter ) {
if ( resVars.insert(*iter).second ) {
fitVars.push_back(*iter);
++nSigDPPar_;
}
}
}
UInt_t LauTimeDepFitModel::addParametersToFitList(std::vector<LauDecayTimePdf*> theVector)
{
UInt_t counter(0);
LauParameterPList& fitVars = this->fitPars();
// loop through the map
for (std::vector<LauDecayTimePdf*>::iterator iter = theVector.begin(); iter != theVector.end(); ++iter) {
// grab the pdf and then its parameters
LauDecayTimePdf* thePdf = *iter; // The first one is the tagging category
LauAbsRValuePList& rvalues = thePdf->getParameters();
// loop through the parameters
for (LauAbsRValuePList::iterator pars_iter = rvalues.begin(); pars_iter != rvalues.end(); ++pars_iter) {
LauParameterPList params = (*pars_iter)->getPars();
for (LauParameterPList::iterator params_iter = params.begin(); params_iter != params.end(); ++params_iter) {
// for each "original" parameter add it to the list of fit parameters and increment the counter
if ( !(*params_iter)->clone() && ( !(*params_iter)->fixed() ||
(this->twoStageFit() && (*params_iter)->secondStage()) ) ) {
fitVars.push_back(*params_iter);
++counter;
}
}
}
}
return counter;
}
UInt_t LauTimeDepFitModel::addParametersToFitList(LauPdfList* theList)
{
UInt_t counter(0);
counter += this->addFitParameters(*(theList));
return counter;
}
void LauTimeDepFitModel::setDecayTimeParameters()
{
nDecayTimePar_ = 0;
std::cout << "INFO in LauTimeDepFitModel::setDecayTimeParameters : Setting the initial fit parameters of the DecayTime Pdfs." << std::endl;
LauParameterPList& fitVars = this->fitPars();
// Loop over the Dt PDFs
LauAbsRValuePList& rvalues = signalDecayTimePdf_->getParameters();
// loop through the parameters
for (LauAbsRValuePList::iterator pars_iter = rvalues.begin(); pars_iter != rvalues.end(); ++pars_iter) {
LauParameterPList params = (*pars_iter)->getPars();
for (LauParameterPList::iterator params_iter = params.begin(); params_iter != params.end(); ++params_iter) {
// for each "original" parameter add it to the list of fit parameters and increment the counter
if ( !(*params_iter)->clone() && ( !(*params_iter)->fixed() ||
(this->twoStageFit() && (*params_iter)->secondStage()) ) ) {
fitVars.push_back(*params_iter);
++nDecayTimePar_;
}
}
}
if (usingBkgnd_){
nDecayTimePar_ += this->addParametersToFitList(backgroundDecayTimePdfs_);
}
if (useSinCos_) {
fitVars.push_back(&sinPhiMix_);
fitVars.push_back(&cosPhiMix_);
nDecayTimePar_ += 2;
} else {
fitVars.push_back(&phiMix_);
++nDecayTimePar_;
}
}
void LauTimeDepFitModel::setExtraPdfParameters()
{
// Include the parameters of the PDF for each tagging category in the fit
// NB all of them are passed to the fit, even though some have been fixed through parameter.fixed(kTRUE)
// With the new "cloned parameter" scheme only "original" parameters are passed to the fit.
// Their clones are updated automatically when the originals are updated.
nExtraPdfPar_ = 0;
std::cout << "INFO in LauTimeDepFitModel::setExtraPdfParameters : Setting the initial fit parameters of the extra Pdfs." << std::endl;
if (sigExtraPdf_){
nExtraPdfPar_ += this->addFitParameters((*sigExtraPdf_));
}
if (usingBkgnd_ == kTRUE) {
for (LauBkgndPdfsList::iterator iter = BkgndPdfs_.begin(); iter != BkgndPdfs_.end(); ++iter) {
nExtraPdfPar_ += this->addFitParameters(*iter);
}
}
}
void LauTimeDepFitModel::setFitNEvents()
{
nNormPar_ = 0;
std::cout << "INFO in LauTimeDepFitModel::setFitNEvents : Setting the initial fit parameters of the signal and ackground yields." << std::endl;
// Initialise the total number of events to be the sum of all the hypotheses
Double_t nTotEvts = signalEvents_->value();
this->eventsPerExpt(TMath::FloorNint(nTotEvts));
LauParameterPList& fitVars = this->fitPars();
// if doing an extended ML fit add the signal fraction into the fit parameters
if (this->doEMLFit()) {
std::cout<<"INFO in LauTimeDepFitModel::setFitNEvents : Initialising number of events for signal and background components..."<<std::endl;
fitVars.push_back(signalEvents_);
++nNormPar_;
} else {
std::cout<<"INFO in LauTimeDepFitModel::setFitNEvents : Initialising number of events for background components (and hence signal)..."<<std::endl;
}
// if not using the DP in the model we need an explicit signal asymmetry parameter
if (this->useDP() == kFALSE) {
fitVars.push_back(signalAsym_);
++nNormPar_;
}
// TODO arguably should delegate this
//LauTagCatParamMap& signalTagCatFrac = flavTag_->getSignalTagCatFrac();
// tagging-category fractions for signal events
//for (LauTagCatParamMap::iterator iter = signalTagCatFrac.begin(); iter != signalTagCatFrac.end(); ++iter) {
// if (iter == signalTagCatFrac.begin()) {
// continue;
// }
// LauParameter* par = &((*iter).second);
// fitVars.push_back(par);
// ++nNormPar_;
//}
// Backgrounds
if (usingBkgnd_ == kTRUE) {
for (LauBkgndYieldList::iterator iter = bkgndEvents_.begin(); iter != bkgndEvents_.end(); ++iter) {
std::vector<LauParameter*> parameters = (*iter)->getPars();
for ( LauParameter* parameter : parameters ) {
if(!parameter->clone()) {
fitVars.push_back(parameter);
++nNormPar_;
}
}
}
for (LauBkgndYieldList::iterator iter = bkgndAsym_.begin(); iter != bkgndAsym_.end(); ++iter) {
std::vector<LauParameter*> parameters = (*iter)->getPars();
for ( LauParameter* parameter : parameters ) {
if(!parameter->clone()) {
fitVars.push_back(parameter);
++nNormPar_;
}
}
}
}
}
void LauTimeDepFitModel::setAsymParams()
{
nAsymPar_ = 0;
LauParameterPList& fitVars = this->fitPars();
if (!AProd_.fixed()){
fitVars.push_back(&AProd_);
nAsymPar_+=1;
}
}
void LauTimeDepFitModel::setTagEffParams()
{
nTagEffPar_ = 0;
Bool_t useAltPars = flavTag_->getUseAveDelta();
std::cout << "INFO in LauTimeDepFitModel::setTagEffParams : Setting the initial fit parameters for flavour tagging efficiencies." << std::endl;
if (useAltPars){
std::vector<LauParameter*> tageff_ave = flavTag_->getTagEffAve();
std::vector<LauParameter*> tageff_delta = flavTag_->getTagEffDelta();
LauParameterPList& fitVars = this->fitPars();
for(std::vector<LauParameter*>::iterator iter = tageff_ave.begin(); iter != tageff_ave.end(); ++iter){
LauParameter* eff = *iter;
if (eff->fixed()){continue;}
fitVars.push_back(eff);
++nTagEffPar_;
}
for(std::vector<LauParameter*>::iterator iter = tageff_delta.begin(); iter != tageff_delta.end(); ++iter){
LauParameter* eff = *iter;
if (eff->fixed()){continue;}
fitVars.push_back(eff);
++nTagEffPar_;
}
} else {
std::vector<LauParameter*> tageff_b0 = flavTag_->getTagEffB0();
std::vector<LauParameter*> tageff_b0bar = flavTag_->getTagEffB0bar();
LauParameterPList& fitVars = this->fitPars();
for(std::vector<LauParameter*>::iterator iter = tageff_b0.begin(); iter != tageff_b0.end(); ++iter){
LauParameter* eff = *iter;
if (eff->fixed()){continue;}
fitVars.push_back(eff);
++nTagEffPar_;
}
for(std::vector<LauParameter*>::iterator iter = tageff_b0bar.begin(); iter != tageff_b0bar.end(); ++iter){
LauParameter* eff = *iter;
if (eff->fixed()){continue;}
fitVars.push_back(eff);
++nTagEffPar_;
}
}
}
void LauTimeDepFitModel::setCalibParams()
{
Bool_t useAltPars = flavTag_->getUseAveDelta();
std::cout << "INFO in LauTimeDepFitModel::setCalibParams : Setting the initial fit parameters of the flavour tagging calibration parameters." << std::endl;
if (useAltPars){
std::vector<LauParameter*> p0pars_ave = flavTag_->getCalibP0Ave();
std::vector<LauParameter*> p0pars_delta = flavTag_->getCalibP0Delta();
std::vector<LauParameter*> p1pars_ave = flavTag_->getCalibP1Ave();
std::vector<LauParameter*> p1pars_delta = flavTag_->getCalibP1Delta();
LauParameterPList& fitVars = this->fitPars();
for(std::vector<LauParameter*>::iterator iter = p0pars_ave.begin(); iter != p0pars_ave.end(); ++iter){
LauParameter* p0 = *iter;
if (p0->fixed()){continue;}
fitVars.push_back(p0);
++nCalibPar_;
}
for(std::vector<LauParameter*>::iterator iter = p0pars_delta.begin(); iter != p0pars_delta.end(); ++iter){
LauParameter* p0 = *iter;
if (p0->fixed()){continue;}
fitVars.push_back(p0);
++nCalibPar_;
}
for(std::vector<LauParameter*>::iterator iter = p1pars_ave.begin(); iter != p1pars_ave.end(); ++iter){
LauParameter* p1 = *iter;
if (p1->fixed()){continue;}
fitVars.push_back(p1);
++nCalibPar_;
}
for(std::vector<LauParameter*>::iterator iter = p1pars_delta.begin(); iter != p1pars_delta.end(); ++iter){
LauParameter* p1 = *iter;
if (p1->fixed()){continue;}
fitVars.push_back(p1);
++nCalibPar_;
}
} else {
std::vector<LauParameter*> p0pars_b0 = flavTag_->getCalibP0B0();
std::vector<LauParameter*> p0pars_b0bar = flavTag_->getCalibP0B0bar();
std::vector<LauParameter*> p1pars_b0 = flavTag_->getCalibP1B0();
std::vector<LauParameter*> p1pars_b0bar = flavTag_->getCalibP1B0bar();
LauParameterPList& fitVars = this->fitPars();
for(std::vector<LauParameter*>::iterator iter = p0pars_b0.begin(); iter != p0pars_b0.end(); ++iter){
LauParameter* p0 = *iter;
if (p0->fixed()){continue;}
fitVars.push_back(p0);
++nCalibPar_;
}
for(std::vector<LauParameter*>::iterator iter = p0pars_b0bar.begin(); iter != p0pars_b0bar.end(); ++iter){
LauParameter* p0 = *iter;
if (p0->fixed()){continue;}
fitVars.push_back(p0);
++nCalibPar_;
}
for(std::vector<LauParameter*>::iterator iter = p1pars_b0.begin(); iter != p1pars_b0.end(); ++iter){
LauParameter* p1 = *iter;
if (p1->fixed()){continue;}
fitVars.push_back(p1);
++nCalibPar_;
}
for(std::vector<LauParameter*>::iterator iter = p1pars_b0bar.begin(); iter != p1pars_b0bar.end(); ++iter){
LauParameter* p1 = *iter;
if (p1->fixed()){continue;}
fitVars.push_back(p1);
++nCalibPar_;
}
}
}
void LauTimeDepFitModel::setEffiParams()
{
nEffiPar_ = 0;
LauParameterPList& fitVars = this->fitPars();
std::vector<LauParameter*>& effiPars = signalDecayTimePdf_->getEffiPars();
for(std::vector<LauParameter*>::iterator iter = effiPars.begin(); iter != effiPars.end(); ++iter){
LauParameter* par = *iter;
if (par->fixed()){continue;}
fitVars.push_back(par);
++nEffiPar_;
}
}
void LauTimeDepFitModel::setExtraNtupleVars()
{
// Set-up other parameters derived from the fit results, e.g. fit fractions.
if (this->useDP() != kTRUE) {
return;
}
// First clear the vectors so we start from scratch
this->clearExtraVarVectors();
LauParameterList& extraVars = this->extraPars();
// Add the B0 and B0bar fit fractions for each signal component
fitFracB0bar_ = sigModelB0bar_->getFitFractions();
if (fitFracB0bar_.size() != nSigComp_) {
std::cerr<<"ERROR in LauTimeDepFitModel::setExtraNtupleVars : Initial Fit Fraction array of unexpected dimension: "<<fitFracB0bar_.size()<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
for (UInt_t i(0); i<nSigComp_; ++i) {
if (fitFracB0bar_[i].size() != nSigComp_) {
std::cerr<<"ERROR in LauTimeDepFitModel::setExtraNtupleVars : Initial Fit Fraction array of unexpected dimension: "<<fitFracB0bar_[i].size()<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
}
for (UInt_t i(0); i<nSigComp_; ++i) {
for (UInt_t j = i; j < nSigComp_; j++) {
TString name = fitFracB0bar_[i][j].name();
name.Insert( name.Index("FitFrac"), "B0bar" );
fitFracB0bar_[i][j].name(name);
extraVars.push_back(fitFracB0bar_[i][j]);
}
}
fitFracB0_ = sigModelB0_->getFitFractions();
if (fitFracB0_.size() != nSigComp_) {
std::cerr<<"ERROR in LauTimeDepFitModel::setExtraNtupleVars : Initial Fit Fraction array of unexpected dimension: "<<fitFracB0_.size()<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
for (UInt_t i(0); i<nSigComp_; ++i) {
if (fitFracB0_[i].size() != nSigComp_) {
std::cerr<<"ERROR in LauTimeDepFitModel::setExtraNtupleVars : Initial Fit Fraction array of unexpected dimension: "<<fitFracB0_[i].size()<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
}
for (UInt_t i(0); i<nSigComp_; ++i) {
for (UInt_t j = i; j < nSigComp_; j++) {
TString name = fitFracB0_[i][j].name();
name.Insert( name.Index("FitFrac"), "B0" );
fitFracB0_[i][j].name(name);
extraVars.push_back(fitFracB0_[i][j]);
}
}
// Calculate the ACPs and FitFrac asymmetries
this->calcAsymmetries(kTRUE);
// Add the Fit Fraction asymmetry for each signal component
for (UInt_t i = 0; i < nSigComp_; i++) {
extraVars.push_back(fitFracAsymm_[i]);
}
// Add the calculated CP asymmetry for each signal component
for (UInt_t i = 0; i < nSigComp_; i++) {
extraVars.push_back(acp_[i]);
}
// Now add in the DP efficiency values
Double_t initMeanEffB0bar = sigModelB0bar_->getMeanEff().initValue();
meanEffB0bar_.value(initMeanEffB0bar); meanEffB0bar_.initValue(initMeanEffB0bar); meanEffB0bar_.genValue(initMeanEffB0bar);
extraVars.push_back(meanEffB0bar_);
Double_t initMeanEffB0 = sigModelB0_->getMeanEff().initValue();
meanEffB0_.value(initMeanEffB0); meanEffB0_.initValue(initMeanEffB0); meanEffB0_.genValue(initMeanEffB0);
extraVars.push_back(meanEffB0_);
// Also add in the DP rates
Double_t initDPRateB0bar = sigModelB0bar_->getDPRate().initValue();
DPRateB0bar_.value(initDPRateB0bar); DPRateB0bar_.initValue(initDPRateB0bar); DPRateB0bar_.genValue(initDPRateB0bar);
extraVars.push_back(DPRateB0bar_);
Double_t initDPRateB0 = sigModelB0_->getDPRate().initValue();
DPRateB0_.value(initDPRateB0); DPRateB0_.initValue(initDPRateB0); DPRateB0_.genValue(initDPRateB0);
extraVars.push_back(DPRateB0_);
}
void LauTimeDepFitModel::setAsymmetries(const Double_t AProd, const Bool_t AProdFix){
AProd_.value(AProd);
AProd_.fixed(AProdFix);
}
void LauTimeDepFitModel::finaliseFitResults(const TString& tablePrefixName)
{
// Retrieve parameters from the fit results for calculations and toy generation
// and eventually store these in output root ntuples/text files
// Now take the fit parameters and update them as necessary
// i.e. to make mag > 0.0, phase in the right range.
// This function will also calculate any other values, such as the
// fit fractions, using any errors provided by fitParErrors as appropriate.
// Also obtain the pull values: (measured - generated)/(average error)
if (this->useDP() == kTRUE) {
for (UInt_t i = 0; i < nSigComp_; ++i) {
// Check whether we have "a > 0.0", and phases in the right range
coeffPars_[i]->finaliseValues();
}
}
// update the pulls on the event fractions and asymmetries
if (this->doEMLFit()) {
signalEvents_->updatePull();
}
if (this->useDP() == kFALSE) {
signalAsym_->updatePull();
}
// Finalise the pulls on the decay time parameters
signalDecayTimePdf_->updatePulls();
// and for backgrounds if required
if (usingBkgnd_){
for (std::vector<LauDecayTimePdf*>::iterator iter = backgroundDecayTimePdfs_.begin(); iter != backgroundDecayTimePdfs_.end(); ++iter) {
LauDecayTimePdf* pdf = *iter;
pdf->updatePulls();
}
}
if (useSinCos_) {
cosPhiMix_.updatePull();
sinPhiMix_.updatePull();
} else {
this->checkMixingPhase();
}
if (usingBkgnd_ == kTRUE) {
for (LauBkgndYieldList::iterator iter = bkgndEvents_.begin(); iter != bkgndEvents_.end(); ++iter) {
std::vector<LauParameter*> parameters = (*iter)->getPars();
for ( LauParameter* parameter : parameters ) {
parameter->updatePull();
}
}
for (LauBkgndYieldList::iterator iter = bkgndAsym_.begin(); iter != bkgndAsym_.end(); ++iter) {
std::vector<LauParameter*> parameters = (*iter)->getPars();
for ( LauParameter* parameter : parameters ) {
parameter->updatePull();
}
}
}
// Update the pulls on all the extra PDFs' parameters
if (sigExtraPdf_){
this->updateFitParameters(*(sigExtraPdf_));
}
if (usingBkgnd_ == kTRUE) {
for (LauBkgndPdfsList::iterator iter = BkgndPdfs_.begin(); iter != BkgndPdfs_.end(); ++iter) {
this->updateFitParameters(*iter);
}
}
// Fill the fit results to the ntuple
// update the coefficients and then calculate the fit fractions and ACP's
if (this->useDP() == kTRUE) {
this->updateCoeffs();
sigModelB0bar_->updateCoeffs(coeffsB0bar_); sigModelB0bar_->calcExtraInfo();
sigModelB0_->updateCoeffs(coeffsB0_); sigModelB0_->calcExtraInfo();
LauParArray fitFracB0bar = sigModelB0bar_->getFitFractions();
if (fitFracB0bar.size() != nSigComp_) {
std::cerr<<"ERROR in LauTimeDepFitModel::finaliseFitResults : Fit Fraction array of unexpected dimension: "<<fitFracB0bar.size()<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
for (UInt_t i(0); i<nSigComp_; ++i) {
if (fitFracB0bar[i].size() != nSigComp_) {
std::cerr<<"ERROR in LauTimeDepFitModel::finaliseFitResults : Fit Fraction array of unexpected dimension: "<<fitFracB0bar[i].size()<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
}
LauParArray fitFracB0 = sigModelB0_->getFitFractions();
if (fitFracB0.size() != nSigComp_) {
std::cerr<<"ERROR in LauTimeDepFitModel::finaliseFitResults : Fit Fraction array of unexpected dimension: "<<fitFracB0.size()<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
for (UInt_t i(0); i<nSigComp_; ++i) {
if (fitFracB0[i].size() != nSigComp_) {
std::cerr<<"ERROR in LauTimeDepFitModel::finaliseFitResults : Fit Fraction array of unexpected dimension: "<<fitFracB0[i].size()<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
}
for (UInt_t i(0); i<nSigComp_; ++i) {
for (UInt_t j(i); j<nSigComp_; ++j) {
fitFracB0bar_[i][j].value(fitFracB0bar[i][j].value());
fitFracB0_[i][j].value(fitFracB0[i][j].value());
}
}
meanEffB0bar_.value(sigModelB0bar_->getMeanEff().value());
meanEffB0_.value(sigModelB0_->getMeanEff().value());
DPRateB0bar_.value(sigModelB0bar_->getDPRate().value());
DPRateB0_.value(sigModelB0_->getDPRate().value());
this->calcAsymmetries();
// Then store the final fit parameters, and any extra parameters for
// the signal model (e.g. fit fractions, FF asymmetries, ACPs, mean efficiency and DP rate)
this->clearExtraVarVectors();
LauParameterList& extraVars = this->extraPars();
for (UInt_t i(0); i<nSigComp_; ++i) {
for (UInt_t j(i); j<nSigComp_; ++j) {
extraVars.push_back(fitFracB0bar_[i][j]);
}
}
for (UInt_t i(0); i<nSigComp_; ++i) {
for (UInt_t j(i); j<nSigComp_; ++j) {
extraVars.push_back(fitFracB0_[i][j]);
}
}
for (UInt_t i(0); i<nSigComp_; ++i) {
extraVars.push_back(fitFracAsymm_[i]);
}
for (UInt_t i(0); i<nSigComp_; ++i) {
extraVars.push_back(acp_[i]);
}
extraVars.push_back(meanEffB0bar_);
extraVars.push_back(meanEffB0_);
extraVars.push_back(DPRateB0bar_);
extraVars.push_back(DPRateB0_);
this->printFitFractions(std::cout);
this->printAsymmetries(std::cout);
}
const LauParameterPList& fitVars = this->fitPars();
const LauParameterList& extraVars = this->extraPars();
LauFitNtuple* ntuple = this->fitNtuple();
ntuple->storeParsAndErrors(fitVars, extraVars);
// find out the correlation matrix for the parameters
ntuple->storeCorrMatrix(this->iExpt(), this->fitStatus(), this->covarianceMatrix());
// Fill the data into ntuple
ntuple->updateFitNtuple();
// Print out the partial fit fractions, phases and the
// averaged efficiency, reweighted by the dynamics (and anything else)
if (this->writeLatexTable()) {
TString sigOutFileName(tablePrefixName);
sigOutFileName += "_"; sigOutFileName += this->iExpt(); sigOutFileName += "Expt.tex";
this->writeOutTable(sigOutFileName);
}
}
void LauTimeDepFitModel::printFitFractions(std::ostream& output)
{
// Print out Fit Fractions, total DP rate and mean efficiency
// First for the B0bar events
for (UInt_t i = 0; i < nSigComp_; i++) {
const TString compName(coeffPars_[i]->name());
output<<"B0bar FitFraction for component "<<i<<" ("<<compName<<") = "<<fitFracB0bar_[i][i]<<std::endl;
}
output<<"B0bar overall DP rate (integral of matrix element squared) = "<<DPRateB0bar_<<std::endl;
output<<"B0bar average efficiency weighted by whole DP dynamics = "<<meanEffB0bar_<<std::endl;
// Then for the B0 sample
for (UInt_t i = 0; i < nSigComp_; i++) {
const TString compName(coeffPars_[i]->name());
const TString conjName(sigModelB0bar_->getConjResName(compName));
output<<"B0 FitFraction for component "<<i<<" ("<<conjName<<") = "<<fitFracB0_[i][i]<<std::endl;
}
output<<"B0 overall DP rate (integral of matrix element squared) = "<<DPRateB0_<<std::endl;
output<<"B0 average efficiency weighted by whole DP dynamics = "<<meanEffB0_<<std::endl;
}
void LauTimeDepFitModel::printAsymmetries(std::ostream& output)
{
for (UInt_t i = 0; i < nSigComp_; i++) {
const TString compName(coeffPars_[i]->name());
output<<"Fit Fraction asymmetry for component "<<i<<" ("<<compName<<") = "<<fitFracAsymm_[i]<<std::endl;
}
for (UInt_t i = 0; i < nSigComp_; i++) {
const TString compName(coeffPars_[i]->name());
output<<"ACP for component "<<i<<" ("<<compName<<") = "<<acp_[i].value()<<" +- "<<acp_[i].error()<<std::endl;
}
}
void LauTimeDepFitModel::writeOutTable(const TString& outputFile)
{
// Write out the results of the fit to a tex-readable table
std::ofstream fout(outputFile);
LauPrint print;
std::cout<<"INFO in LauTimeDepFitModel::writeOutTable : Writing out results of the fit to the tex file "<<outputFile<<std::endl;
if (this->useDP() == kTRUE) {
// print the fit coefficients in one table
coeffPars_.front()->printTableHeading(fout);
for (UInt_t i = 0; i < nSigComp_; i++) {
coeffPars_[i]->printTableRow(fout);
}
fout<<"\\hline"<<std::endl;
fout<<"\\end{tabular}"<<std::endl<<std::endl;
// print the fit fractions in another
fout<<"\\begin{tabular}{|l|c|c|c|c|}"<<std::endl;
fout<<"\\hline"<<std::endl;
fout<<"Component & \\Bzb\\ Fit Fraction & \\Bz\\ Fit Fraction & Fit Fraction Asymmetry & $A_{\\CP}$ \\\\"<<std::endl;
fout<<"\\hline"<<std::endl;
Double_t fitFracSumB0bar(0.0);
Double_t fitFracSumB0(0.0);
for (UInt_t i = 0; i < nSigComp_; i++) {
TString resName = coeffPars_[i]->name();
resName = resName.ReplaceAll("_", "\\_");
fout<<resName<<" & $";
Double_t fitFracB0bar = fitFracB0bar_[i][i].value();
fitFracSumB0bar += fitFracB0bar;
print.printFormat(fout, fitFracB0bar);
fout << "$ & $" << std::endl;
Double_t fitFracB0 = fitFracB0_[i][i].value();
fitFracSumB0 += fitFracB0;
print.printFormat(fout, fitFracB0);
fout << "$ & $" << std::endl;
Double_t fitFracAsymm = fitFracAsymm_[i].value();
print.printFormat(fout, fitFracAsymm);
fout << "$ & $" << std::endl;
Double_t acp = acp_[i].value();
Double_t acpErr = acp_[i].error();
print.printFormat(fout, acp);
fout<<" \\pm ";
print.printFormat(fout, acpErr);
fout<<"$ \\\\"<<std::endl;
}
fout<<"\\hline"<<std::endl;
// Also print out sum of fit fractions
fout << "Fit Fraction Sum = & $";
print.printFormat(fout, fitFracSumB0bar);
fout << "$ & $";
print.printFormat(fout, fitFracSumB0);
fout << "$ & & \\\\" << std::endl;
fout << "\\hline \n\\hline" << std::endl;
fout << "DP rate = & $";
print.printFormat(fout, DPRateB0bar_.value());
fout << "$ & $";
print.printFormat(fout, DPRateB0_.value());
fout << "$ & & \\\\" << std::endl;
fout << "$< \\varepsilon > =$ & $";
print.printFormat(fout, meanEffB0bar_.value());
fout << "$ & $";
print.printFormat(fout, meanEffB0_.value());
fout << "$ & & \\\\" << std::endl;
if (useSinCos_) {
fout << "$\\sinPhiMix =$ & $";
print.printFormat(fout, sinPhiMix_.value());
fout << " \\pm ";
print.printFormat(fout, sinPhiMix_.error());
fout << "$ & & & & & & & \\\\" << std::endl;
fout << "$\\cosPhiMix =$ & $";
print.printFormat(fout, cosPhiMix_.value());
fout << " \\pm ";
print.printFormat(fout, cosPhiMix_.error());
fout << "$ & & & & & & & \\\\" << std::endl;
} else {
fout << "$\\phiMix =$ & $";
print.printFormat(fout, phiMix_.value());
fout << " \\pm ";
print.printFormat(fout, phiMix_.error());
fout << "$ & & & & & & & \\\\" << std::endl;
}
fout << "\\hline \n\\end{tabular}" << std::endl;
}
if (!sigExtraPdf_->empty()) {
fout<<"\\begin{tabular}{|l|c|}"<<std::endl;
fout<<"\\hline"<<std::endl;
fout<<"\\Extra Signal PDFs' Parameters: & \\\\"<<std::endl;
this->printFitParameters(*(sigExtraPdf_), fout);
if (usingBkgnd_ == kTRUE && !BkgndPdfs_.empty()) {
fout << "\\hline" << std::endl;
fout << "\\Extra Background PDFs' Parameters: & \\\\" << std::endl;
for (LauBkgndPdfsList::const_iterator iter = BkgndPdfs_.begin(); iter != BkgndPdfs_.end(); ++iter) {
this->printFitParameters(*iter, fout);
}
}
fout<<"\\hline \n\\end{tabular}"<<std::endl<<std::endl;
}
}
void LauTimeDepFitModel::checkInitFitParams()
{
// Update the number of signal events to be total-sum(background events)
this->updateSigEvents();
// Check whether we want to have randomised initial fit parameters for the signal model
if (this->useRandomInitFitPars() == kTRUE) {
this->randomiseInitFitPars();
}
}
void LauTimeDepFitModel::randomiseInitFitPars()
{
// Only randomise those parameters that are not fixed!
std::cout<<"INFO in LauTimeDepFitModel::randomiseInitFitPars : Randomising the initial values of the coefficients of the DP components (and phiMix)..."<<std::endl;
for (UInt_t i = 0; i < nSigComp_; i++) {
coeffPars_[i]->randomiseInitValues();
}
phiMix_.randomiseValue(-LauConstants::pi, LauConstants::pi);
if (useSinCos_) {
sinPhiMix_.initValue(TMath::Sin(phiMix_.initValue()));
cosPhiMix_.initValue(TMath::Cos(phiMix_.initValue()));
}
}
LauTimeDepFitModel::LauGenInfo LauTimeDepFitModel::eventsToGenerate()
{
// Determine the number of events to generate for each hypothesis
// If we're smearing then smear each one individually
// NB this individual smearing has to be done individually per tagging category as well
LauGenInfo nEvtsGen;
// Signal
// If we're including the DP and decay time we can't decide on the tag
// yet, since it depends on the whole DP+dt PDF, however, if
// we're not then we need to decide.
Double_t evtWeight(1.0);
Double_t nEvts = signalEvents_->genValue();
if ( nEvts < 0.0 ) {
evtWeight = -1.0;
nEvts = TMath::Abs( nEvts );
}
Double_t sigAsym(0.0);
if (this->useDP() == kFALSE) {
sigAsym = signalAsym_->genValue();
//TODO fill in here if we care
} else {
Double_t rateB0bar = sigModelB0bar_->getDPRate().value();
Double_t rateB0 = sigModelB0_->getDPRate().value();
if ( rateB0bar+rateB0 > 1e-30) {
sigAsym = (rateB0bar-rateB0)/(rateB0bar+rateB0);
}
//for (LauTagCatParamMap::const_iterator iter = signalTagCatFrac.begin(); iter != signalTagCatFrac.end(); ++iter) {
// const LauParameter& par = iter->second;
// Double_t eventsbyTagCat = par.value() * nEvts;
// if (this->doPoissonSmearing()) {
// eventsbyTagCat = LauRandom::randomFun()->Poisson(eventsbyTagCat);
// }
// eventsB0[iter->first] = std::make_pair( TMath::Nint(eventsbyTagCat), evtWeight );
//}
//nEvtsGen[std::make_pair("signal",0)] = eventsB0; // generate signal event, decide tag later.
nEvtsGen["signal"] = std::make_pair( nEvts, evtWeight );
}
std::cout<<"INFO in LauTimeDepFitModel::eventsToGenerate : Generating toy MC with:"<<std::endl;
std::cout<<" : Signal asymmetry = "<<sigAsym<<" and number of signal events = "<<signalEvents_->genValue()<<std::endl;
return nEvtsGen;
}
Bool_t LauTimeDepFitModel::genExpt()
{
// Routine to generate toy Monte Carlo events according to the various models we have defined.
// Determine the number of events to generate for each hypothesis
LauGenInfo nEvts = this->eventsToGenerate();
Bool_t genOK(kTRUE);
Int_t evtNum(0);
const UInt_t nBkgnds = this->nBkgndClasses();
std::vector<TString> bkgndClassNames(nBkgnds);
std::vector<TString> bkgndClassNamesGen(nBkgnds);
for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
TString name( this->bkgndClassName(iBkgnd) );
bkgndClassNames[iBkgnd] = name;
bkgndClassNamesGen[iBkgnd] = "gen"+name;
}
// Loop over the hypotheses and generate the appropriate number of
// events for each one
for (LauGenInfo::const_iterator iter = nEvts.begin(); iter != nEvts.end(); ++iter) {
// find the category of events (e.g. signal)
const TString& evtCategory(iter->first);
// Type
const TString& type(iter->first);
// Number of events
Int_t nEvtsGen( iter->second.first );
// get the event weight for this category
const Double_t evtWeight( iter->second.second );
for (Int_t iEvt(0); iEvt<nEvtsGen; ++iEvt) {
this->setGenNtupleDoubleBranchValue( "evtWeight", evtWeight );
if (evtCategory == "signal") {
this->setGenNtupleIntegerBranchValue("genSig",1);
for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
this->setGenNtupleIntegerBranchValue( bkgndClassNamesGen[iBkgnd], 0 );
}
// All the generate*Event() methods have to fill in curEvtDecayTime_ and curEvtDecayTimeErr_
// In addition, generateSignalEvent has to decide on the tag and fill in curEvtTagFlv_
genOK = this->generateSignalEvent();
} else {
this->setGenNtupleIntegerBranchValue("genSig",0);
UInt_t bkgndID(0);
for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
Int_t gen(0);
if ( bkgndClassNames[iBkgnd] == type ) {
gen = 1;
bkgndID = iBkgnd;
}
this->setGenNtupleIntegerBranchValue( bkgndClassNamesGen[iBkgnd], gen );
}
genOK = this->generateBkgndEvent(bkgndID);
}
if (!genOK) {
// If there was a problem with the generation then break out and return.
// The problem model will have adjusted itself so that all should be OK next time.
break;
}
if (this->useDP() == kTRUE) {
this->setDPDtBranchValues(); // store DP, decay time and tagging variables in the ntuple
}
// Store the event's tag and tagging category
this->setGenNtupleIntegerBranchValue("cpEigenvalue", cpEigenValue_);
this->setGenNtupleDoubleBranchValue(flavTag_->getTrueTagVarName(),curEvtTrueTagFlv_);
std::vector<TString> tagVarName = flavTag_->getTagVarNames();
std::vector<TString> mistagVarName = flavTag_->getMistagVarNames();
// Loop over the taggers - values set via generateSignalEvent
for (Int_t i=0; i<flavTag_->getNTaggers(); ++i){
this->setGenNtupleIntegerBranchValue(tagVarName[i],curEvtTagFlv_[i]);
this->setGenNtupleDoubleBranchValue(mistagVarName[i],curEvtMistag_[i]);
}
// Store the event number (within this experiment)
// and then increment it
this->setGenNtupleIntegerBranchValue("iEvtWithinExpt",evtNum);
++evtNum;
// Write the values into the tree
this->fillGenNtupleBranches();
// Print an occasional progress message
if (iEvt%1000 == 0) {std::cout<<"INFO in LauTimeDepFitModel::genExpt : Generated event number "<<iEvt<<" out of "<<nEvtsGen<<" "<<evtCategory<<" events."<<std::endl;}
}
} //end of loop over species and tagFlv.
if (this->useDP() && genOK) {
sigModelB0bar_->checkToyMC(kTRUE);
sigModelB0_->checkToyMC(kTRUE);
std::cout<<"aSqMaxSet = "<<aSqMaxSet_<<" and aSqMaxVar = "<<aSqMaxVar_<<std::endl;
// Get the fit fractions if they're to be written into the latex table
if (this->writeLatexTable()) {
LauParArray fitFracB0bar = sigModelB0bar_->getFitFractions();
if (fitFracB0bar.size() != nSigComp_) {
std::cerr<<"ERROR in LauTimeDepFitModel::generate : Fit Fraction array of unexpected dimension: "<<fitFracB0bar.size()<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
for (UInt_t i(0); i<nSigComp_; ++i) {
if (fitFracB0bar[i].size() != nSigComp_) {
std::cerr<<"ERROR in LauTimeDepFitModel::generate : Fit Fraction array of unexpected dimension: "<<fitFracB0bar[i].size()<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
}
LauParArray fitFracB0 = sigModelB0_->getFitFractions();
if (fitFracB0.size() != nSigComp_) {
std::cerr<<"ERROR in LauTimeDepFitModel::generate : Fit Fraction array of unexpected dimension: "<<fitFracB0.size()<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
for (UInt_t i(0); i<nSigComp_; ++i) {
if (fitFracB0[i].size() != nSigComp_) {
std::cerr<<"ERROR in LauTimeDepFitModel::generate : Fit Fraction array of unexpected dimension: "<<fitFracB0[i].size()<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
}
for (UInt_t i(0); i<nSigComp_; ++i) {
for (UInt_t j(i); j<nSigComp_; ++j) {
fitFracB0bar_[i][j].value(fitFracB0bar[i][j].value());
fitFracB0_[i][j].value(fitFracB0[i][j].value());
}
}
meanEffB0bar_.value(sigModelB0bar_->getMeanEff().value());
meanEffB0_.value(sigModelB0_->getMeanEff().value());
DPRateB0bar_.value(sigModelB0bar_->getDPRate().value());
DPRateB0_.value(sigModelB0_->getDPRate().value());
}
}
// If we're reusing embedded events or if the generation is being
// reset then clear the lists of used events
if (reuseSignal_ || !genOK) {
- signalTree_->clearUsedList();
+ if (signalTree_) {
+ signalTree_->clearUsedList();
+ }
}
for ( UInt_t bkgndID(0); bkgndID < nBkgnds; ++bkgndID ) {
+ LauEmbeddedData* data = bkgndTree_[bkgndID];
if (reuseBkgnd_[bkgndID] || !genOK) {
- for (std::vector<LauEmbeddedData*>::iterator iter = bkgndTree_.begin(); iter != bkgndTree_.end(); ++iter){
- LauEmbeddedData* temp = *(iter);
- temp->clearUsedList();
- //*(iter)->clearUsedList();
+ if (data) {
+ data->clearUsedList();
}
}
}
-
return genOK;
}
Bool_t LauTimeDepFitModel::generateSignalEvent()
{
// Generate signal event, including SCF if necessary.
// DP:DecayTime generation follows.
// If it's ok, we then generate mES, DeltaE, Fisher/NN...
Bool_t genOK(kTRUE);
Bool_t generatedEvent(kFALSE);
Bool_t doSquareDP = kinematicsB0bar_->squareDP();
doSquareDP &= kinematicsB0_->squareDP();
LauKinematics* kinematics(kinematicsB0bar_);
if (this->useDP()) {
if (signalTree_) {
signalTree_->getEmbeddedEvent(kinematics);
//curEvtTagFlv_ = TMath::Nint(signalTree_->getValue("tagFlv"));
curEvtDecayTimeErr_ = signalTree_->getValue(signalDecayTimePdf_->varErrName());
curEvtDecayTime_ = signalTree_->getValue(signalDecayTimePdf_->varName());
if (signalTree_->haveBranch("mcMatch")) {
Int_t match = TMath::Nint(signalTree_->getValue("mcMatch"));
if (match) {
this->setGenNtupleIntegerBranchValue("genTMSig",1);
this->setGenNtupleIntegerBranchValue("genSCFSig",0);
} else {
this->setGenNtupleIntegerBranchValue("genTMSig",0);
this->setGenNtupleIntegerBranchValue("genSCFSig",1);
}
}
} else {
nGenLoop_ = 0;
// generate the decay time error (NB the kTRUE forces the generation of a new value)
curEvtDecayTimeErr_ = signalDecayTimePdf_->generateError(kTRUE);
// clear vectors
curEvtTagFlv_.clear();
Int_t ntaggers = flavTag_->getNTaggers();
std::vector<LauParameter*> tageffB0 = flavTag_->getTagEffB0();
std::vector<LauParameter*> tageffB0bar = flavTag_->getTagEffB0bar();
for(Int_t position=0; position<ntaggers; ++position){
// First let define the tag flavour CONVENTION WARNING
Double_t randNo = LauRandom::randomFun()->Rndm();
if (randNo <= tageffB0[position]->unblindValue()) {
curEvtTagFlv_.push_back(1); // B0 tag
} else if (randNo <= (tageffB0[position]->unblindValue() + tageffB0bar[position]->unblindValue())){
curEvtTagFlv_.push_back(-1); // B0bar tag
} else {
curEvtTagFlv_.push_back(0); // Untagged
}
}
while (generatedEvent == kFALSE && nGenLoop_ < iterationsMax_) {
curEvtMistag_.clear();
curEvtTrueTagFlv_ = 0;
// Should we be smarter about this? Should match the Flavour tag X% of the time?
if (signalDecayTimePdf_->getFuncType() == LauDecayTimePdf::SimFitNormBd || signalDecayTimePdf_->getFuncType() == LauDecayTimePdf::SimFitNormBs){
// First let define the tag flavour CONVENTION WARNING
Double_t random = LauRandom::randomFun()->Rndm();
if (random < 0.5) {
curEvtTrueTagFlv_ = 1; // B0bar tag
} else {
curEvtTrueTagFlv_ = -1; // B0 tag
}
}
// Generate the DP position
Double_t m13Sq(0.0), m23Sq(0.0);
kinematicsB0bar_->genFlatPhaseSpace(m13Sq, m23Sq);
// Next, calculate the total A and Abar for the given DP position
sigModelB0_->calcLikelihoodInfo(m13Sq, m23Sq);
sigModelB0bar_->calcLikelihoodInfo(m13Sq, m23Sq);
// Retrieve the amplitudes and efficiency from the dynamics
const LauComplex& Abar = sigModelB0bar_->getEvtDPAmp();
const LauComplex& A = sigModelB0_->getEvtDPAmp();
Double_t eff = sigModelB0bar_->getEvtEff();
// Next calculate the DP terms
Double_t aSqSum = A.abs2() + Abar.abs2();
Double_t aSqDif = A.abs2() - Abar.abs2();
LauComplex inter = Abar * A.conj() * phiMixComplex_;
Double_t interTermIm = 2.0 * inter.im();
Double_t interTermRe = 2.0 * inter.re();
// Generate decay time
const Double_t tMin = signalDecayTimePdf_->minAbscissa();
const Double_t tMax = signalDecayTimePdf_->maxAbscissa();
curEvtDecayTime_ = LauRandom::randomFun()->Rndm()*(tMax-tMin) + tMin;
// Calculate all the decay time info
signalDecayTimePdf_->calcLikelihoodInfo(curEvtDecayTime_,curEvtDecayTimeErr_);
// ...and check that the calculation went ok, otherwise loop again
if (signalDecayTimePdf_->state() != LauDecayTimePdf::Good) {
std::cout<<"signalDecayTimePdf_ state is bad"<<std::endl;
++nGenLoop_;
continue;
}
// Get the decay time acceptance
Double_t dtEff = signalDecayTimePdf_->getEffiTerm();
// First get all the decay time terms
Double_t dtCos = signalDecayTimePdf_->getCosTerm();
Double_t dtSin = signalDecayTimePdf_->getSinTerm();
Double_t dtCosh = signalDecayTimePdf_->getCoshTerm();
Double_t dtSinh = signalDecayTimePdf_->getSinhTerm();
// Get flavour tagging terms with per event mistag
Double_t ftOmegaTrig(1.);
Double_t ftOmegaHyp(1.);
for (Int_t position=0; position<ntaggers; ++position){
// Calculate event quantities that depend only on the tagFlv
curEvtMistag_.push_back(flavTag_->getEtaGen(position));
Double_t omega(0);
Double_t omegabar(0);
omega = flavTag_->getCapitalOmegaGen(position,curEvtMistag_[position],curEvtTagFlv_[position],1);
omegabar = flavTag_->getCapitalOmegaGen(position,curEvtMistag_[position],curEvtTagFlv_[position],-1);
ftOmegaTrig *= ((1 - AProd_.unblindValue())*omega - (1 + AProd_.unblindValue())*omegabar);
ftOmegaHyp *= ((1 - AProd_.unblindValue())*omega + (1 + AProd_.unblindValue())*omegabar);
}
// Combine all terms
Double_t cosTerm = dtCos * ftOmegaTrig * aSqDif;
Double_t sinTerm = dtSin * ftOmegaTrig * interTermIm;
Double_t coshTerm = dtCosh * ftOmegaHyp * aSqSum;
Double_t sinhTerm = dtSinh * ftOmegaHyp * interTermRe;
if (curEvtTrueTagFlv_!=0 && (signalDecayTimePdf_->getFuncType() == LauDecayTimePdf::SimFitNormBd || signalDecayTimePdf_->getFuncType() == LauDecayTimePdf::SimFitNormBs)){
cosTerm *= curEvtTrueTagFlv_;
sinTerm *= curEvtTrueTagFlv_;
}
if ( cpEigenValue_ == CPOdd ) {
sinTerm *= -1.0;
sinhTerm *= -1.0;
}
// ... to get the total and multiply by the efficiency
Double_t ASq = coshTerm + cosTerm - sinTerm + sinhTerm;
//if (curEvtTrueTagFlv_ !=0 && curEvtTagCat_>0 && curEvtTagFlv_==-1){
// std::cout<<"##### Event details #####"<<std::endl;
// std::cout<< "dtCos dtSin dtCosh dtSinh " << dtCos << " " << dtSin << " " << dtCosh << " " << dtSinh << std::endl;
// std::cout<< "qD aSqDif dtSin interTermIm " << qD << " " << aSqDif << " " << dtSin << " " << interTermIm << std::endl;
// std::cout<<"Cosh Cos Sin Sinh "<< coshTerm<< " " << cosTerm << " " << sinTerm << " " << sinhTerm << std::endl;
// std::cout<< "Total Amplitude : " << ASq << std::endl;
//}
//ASq /= decayTimePdf->getNormTerm();
ASq *= eff;
ASq *= dtEff;
//std::cout << "Total Amplitude Eff: " << ASq << std::endl;
//Finally we throw the dice to see whether this event should be generated
//We make a distinction between the likelihood of TM and SCF to tag the SCF events as such
Double_t randNum = LauRandom::randomFun()->Rndm();
if (randNum <= ASq/aSqMaxSet_ ) {
generatedEvent = kTRUE;
nGenLoop_ = 0;
if (ASq > aSqMaxVar_) {aSqMaxVar_ = ASq;}
} else {
nGenLoop_++;
}
} // end of while !generatedEvent loop
} // end of if (signalTree_) else control
} else {
if ( signalTree_ ) {
signalTree_->getEmbeddedEvent(0);
//curEvtTagFlv_ = TMath::Nint(signalTree_->getValue("tagFlv"));
curEvtDecayTimeErr_ = signalTree_->getValue(signalDecayTimePdf_->varErrName());
curEvtDecayTime_ = signalTree_->getValue(signalDecayTimePdf_->varName());
}
}
// Check whether we have generated the toy MC OK.
if (nGenLoop_ >= iterationsMax_) {
aSqMaxSet_ = 1.01 * aSqMaxVar_;
genOK = kFALSE;
std::cerr<<"WARNING in LauTimeDepFitModel::generateSignalEvent : Hit max iterations: setting aSqMaxSet_ to "<<aSqMaxSet_<<std::endl;
} else if (aSqMaxVar_ > aSqMaxSet_) {
aSqMaxSet_ = 1.01 * aSqMaxVar_;
genOK = kFALSE;
std::cerr<<"WARNING in LauTimeDepFitModel::generateSignalEvent : Found a larger ASq value: setting aSqMaxSet_ to "<<aSqMaxSet_<<std::endl;
}
if (genOK) {
//Some variables, like Fisher or NN, might use m13Sq and m23Sq from the kinematics
//kinematicsB0bar_ is up to date, update kinematicsB0_
kinematicsB0_->updateKinematics(kinematicsB0bar_->getm13Sq(), kinematicsB0bar_->getm23Sq() );
this->generateExtraPdfValues(sigExtraPdf_, signalTree_);
}
// Check for problems with the embedding
if (signalTree_ && (signalTree_->nEvents() == signalTree_->nUsedEvents())) {
std::cerr<<"WARNING in LauTimeDepFitModel::generateSignalEvent : Source of embedded signal events used up, clearing the list of used events."<<std::endl;
signalTree_->clearUsedList();
}
return genOK;
}
Bool_t LauTimeDepFitModel::generateBkgndEvent(UInt_t bkgndID)
{
// Generate Bkgnd event
Bool_t genOK(kTRUE);
//LauAbsBkgndDPModel* model(0);
//LauEmbeddedData* embeddedData(0);
//LauPdfList* extraPdfs(0);
//LauKinematics* kinematics(0);
//model = BkgndDPModels_[bkgndID];
//if (this->enableEmbedding()) {
// // find the right embedded data for the current tagging category
// LauTagCatEmbDataMap::const_iterator emb_iter = bkgndTree_[bkgndID].find(curEvtTagCat_);
// embeddedData = (emb_iter != bkgndTree_[bkgndID].end()) ? emb_iter->second : 0;
//}
//extraPdfs = &BkgndPdfs_[bkgndID];
//kinematics = kinematicsB0bar_;
//if (this->useDP()) {
// if (embeddedData) {
// embeddedData->getEmbeddedEvent(kinematics);
// } else {
// if (model == 0) {
// const TString& bkgndClass = this->bkgndClassName(bkgndID);
// std::cerr << "ERROR in LauCPFitModel::generateBkgndEvent : Can't find the DP model for background class \"" << bkgndClass << "\"." << std::endl;
// gSystem->Exit(EXIT_FAILURE);
// }
// genOK = model->generate();
// }
//} else {
// if (embeddedData) {
// embeddedData->getEmbeddedEvent(0);
// }
//}
//if (genOK) {
// this->generateExtraPdfValues(extraPdfs, embeddedData);
//}
//// Check for problems with the embedding
//if (embeddedData && (embeddedData->nEvents() == embeddedData->nUsedEvents())) {
// const TString& bkgndClass = this->bkgndClassName(bkgndID);
// std::cerr << "WARNING in LauCPFitModel::generateBkgndEvent : Source of embedded " << bkgndClass << " events used up, clearing the list of used events." << std::endl;
// embeddedData->clearUsedList();
//}
return genOK;
}
void LauTimeDepFitModel::setupGenNtupleBranches()
{
// Setup the required ntuple branches
this->addGenNtupleDoubleBranch("evtWeight");
this->addGenNtupleIntegerBranch("genSig");
this->addGenNtupleIntegerBranch("cpEigenvalue");
std::vector<TString> tagVarName = flavTag_->getTagVarNames();
for (Int_t position=0; position<flavTag_->getNTaggers(); ++position){
this->addGenNtupleIntegerBranch(tagVarName[position]);
}
if (this->useDP() == kTRUE) {
// Let's add the decay time variables.
this->addGenNtupleDoubleBranch(signalDecayTimePdf_->varName());
this->addGenNtupleDoubleBranch(signalDecayTimePdf_->varErrName());
this->addGenNtupleDoubleBranch("m12");
this->addGenNtupleDoubleBranch("m23");
this->addGenNtupleDoubleBranch("m13");
this->addGenNtupleDoubleBranch("m12Sq");
this->addGenNtupleDoubleBranch("m23Sq");
this->addGenNtupleDoubleBranch("m13Sq");
this->addGenNtupleDoubleBranch("cosHel12");
this->addGenNtupleDoubleBranch("cosHel23");
this->addGenNtupleDoubleBranch("cosHel13");
if (kinematicsB0bar_->squareDP() && kinematicsB0_->squareDP()) {
this->addGenNtupleDoubleBranch("mPrime");
this->addGenNtupleDoubleBranch("thPrime");
}
// Can add the real and imaginary parts of the B0 and B0bar total
// amplitudes seen in the generation (restrict this with a flag
// that defaults to false)
if ( storeGenAmpInfo_ ) {
this->addGenNtupleDoubleBranch("reB0Amp");
this->addGenNtupleDoubleBranch("imB0Amp");
this->addGenNtupleDoubleBranch("reB0barAmp");
this->addGenNtupleDoubleBranch("imB0barAmp");
}
}
// Let's look at the extra variables for signal in one of the tagging categories
if ( sigExtraPdf_ ) {
for (LauPdfList::const_iterator pdf_iter = sigExtraPdf_->begin(); pdf_iter != sigExtraPdf_->end(); ++pdf_iter) {
for ( std::vector<TString>::const_iterator var_iter = (*pdf_iter)->varNames().begin(); var_iter != (*pdf_iter)->varNames().end(); ++var_iter ) {
if ( (*var_iter) != "m13Sq" && (*var_iter) != "m23Sq" ) {
this->addGenNtupleDoubleBranch( (*var_iter) );
}
}
}
}
}
void LauTimeDepFitModel::setDPDtBranchValues()
{
// Store the decay time variables.
this->setGenNtupleDoubleBranchValue(signalDecayTimePdf_->varName(),curEvtDecayTime_);
this->setGenNtupleDoubleBranchValue(signalDecayTimePdf_->varErrName(),curEvtDecayTimeErr_);
// CONVENTION WARNING
// TODO check - for now use B0 for any tags
//LauKinematics* kinematics(0);
//if (curEvtTagFlv_[position]<0) {
LauKinematics* kinematics = kinematicsB0_;
//} else {
// kinematics = kinematicsB0bar_;
//}
// Store all the DP information
this->setGenNtupleDoubleBranchValue("m12", kinematics->getm12());
this->setGenNtupleDoubleBranchValue("m23", kinematics->getm23());
this->setGenNtupleDoubleBranchValue("m13", kinematics->getm13());
this->setGenNtupleDoubleBranchValue("m12Sq", kinematics->getm12Sq());
this->setGenNtupleDoubleBranchValue("m23Sq", kinematics->getm23Sq());
this->setGenNtupleDoubleBranchValue("m13Sq", kinematics->getm13Sq());
this->setGenNtupleDoubleBranchValue("cosHel12", kinematics->getc12());
this->setGenNtupleDoubleBranchValue("cosHel23", kinematics->getc23());
this->setGenNtupleDoubleBranchValue("cosHel13", kinematics->getc13());
if (kinematics->squareDP()) {
this->setGenNtupleDoubleBranchValue("mPrime", kinematics->getmPrime());
this->setGenNtupleDoubleBranchValue("thPrime", kinematics->getThetaPrime());
}
// Can add the real and imaginary parts of the B0 and B0bar total
// amplitudes seen in the generation (restrict this with a flag
// that defaults to false)
if ( storeGenAmpInfo_ ) {
if ( this->getGenNtupleIntegerBranchValue("genSig")==1 ) {
LauComplex Abar = sigModelB0bar_->getEvtDPAmp();
LauComplex A = sigModelB0_->getEvtDPAmp();
this->setGenNtupleDoubleBranchValue("reB0Amp", A.re());
this->setGenNtupleDoubleBranchValue("imB0Amp", A.im());
this->setGenNtupleDoubleBranchValue("reB0barAmp", Abar.re());
this->setGenNtupleDoubleBranchValue("imB0barAmp", Abar.im());
} else {
this->setGenNtupleDoubleBranchValue("reB0Amp", 0.0);
this->setGenNtupleDoubleBranchValue("imB0Amp", 0.0);
this->setGenNtupleDoubleBranchValue("reB0barAmp", 0.0);
this->setGenNtupleDoubleBranchValue("imB0barAmp", 0.0);
}
}
}
void LauTimeDepFitModel::generateExtraPdfValues(LauPdfList* extraPdfs, LauEmbeddedData* embeddedData)
{
// CONVENTION WARNING
LauKinematics* kinematics = kinematicsB0_;
//LauKinematics* kinematics(0);
//if (curEvtTagFlv_<0) {
// kinematics = kinematicsB0_;
//} else {
// kinematics = kinematicsB0bar_;
//}
// Generate from the extra PDFs
if (extraPdfs) {
for (LauPdfList::iterator pdf_iter = extraPdfs->begin(); pdf_iter != extraPdfs->end(); ++pdf_iter) {
LauFitData genValues;
if (embeddedData) {
genValues = embeddedData->getValues( (*pdf_iter)->varNames() );
} else {
genValues = (*pdf_iter)->generate(kinematics);
}
for ( LauFitData::const_iterator var_iter = genValues.begin(); var_iter != genValues.end(); ++var_iter ) {
TString varName = var_iter->first;
if ( varName != "m13Sq" && varName != "m23Sq" ) {
Double_t value = var_iter->second;
this->setGenNtupleDoubleBranchValue(varName,value);
}
}
}
}
}
void LauTimeDepFitModel::propagateParUpdates()
{
// Update the complex mixing phase
if (useSinCos_) {
phiMixComplex_.setRealPart(cosPhiMix_.unblindValue());
phiMixComplex_.setImagPart(-1.0*sinPhiMix_.unblindValue());
} else {
phiMixComplex_.setRealPart(TMath::Cos(-1.0*phiMix_.unblindValue()));
phiMixComplex_.setImagPart(TMath::Sin(-1.0*phiMix_.unblindValue()));
}
// Update the total normalisation for the signal likelihood
if (this->useDP() == kTRUE) {
this->updateCoeffs();
sigModelB0bar_->updateCoeffs(coeffsB0bar_);
sigModelB0_->updateCoeffs(coeffsB0_);
this->calcInterTermNorm();
}
// Update the signal events from the background numbers if not doing an extended fit
// And update the tagging category fractions
this->updateSigEvents();
}
void LauTimeDepFitModel::updateSigEvents()
{
// The background parameters will have been set from Minuit.
// We need to update the signal events using these.
if (!this->doEMLFit()) {
Double_t nTotEvts = this->eventsPerExpt();
Double_t signalEvents = nTotEvts;
signalEvents_->range(-2.0*nTotEvts,2.0*nTotEvts);
for (LauBkgndYieldList::iterator iter = bkgndEvents_.begin(); iter != bkgndEvents_.end(); ++iter) {
LauAbsRValue* nBkgndEvents = (*iter);
if ( nBkgndEvents->isLValue() ) {
LauParameter* yield = dynamic_cast<LauParameter*>( nBkgndEvents );
yield->range(-2.0*nTotEvts,2.0*nTotEvts);
}
}
// Subtract background events (if any) from signal.
if (usingBkgnd_ == kTRUE) {
for (LauBkgndYieldList::const_iterator iter = bkgndEvents_.begin(); iter != bkgndEvents_.end(); ++iter) {
signalEvents -= (*iter)->value();
}
}
if ( ! signalEvents_->fixed() ) {
signalEvents_->value(signalEvents);
}
}
}
void LauTimeDepFitModel::cacheInputFitVars()
{
// Fill the internal data trees of the signal and background models.
// Note that we store the events of both charges in both the
// negative and the positive models. It's only later, at the stage
// when the likelihood is being calculated, that we separate them.
LauFitDataTree* inputFitData = this->fitData();
evtCPEigenVals_.clear();
const Bool_t hasCPEV = ( (cpevVarName_ != "") && inputFitData->haveBranch( cpevVarName_ ) );
UInt_t nEvents = inputFitData->nEvents();
evtCPEigenVals_.reserve( nEvents );
LauFitData::const_iterator fitdata_iter;
for (UInt_t iEvt = 0; iEvt < nEvents; iEvt++) {
const LauFitData& dataValues = inputFitData->getData(iEvt);
// if the CP-eigenvalue is in the data use those, otherwise use the default
if ( hasCPEV ) {
fitdata_iter = dataValues.find( cpevVarName_ );
const Int_t cpEV = static_cast<Int_t>( fitdata_iter->second );
if ( cpEV == 1 ) {
cpEigenValue_ = CPEven;
} else if ( cpEV == -1 ) {
cpEigenValue_ = CPOdd;
} else {
std::cerr<<"WARNING in LauTimeDepFitModel::cacheInputFitVars : Unknown value: "<<cpEV<<" for CP eigenvalue, setting to CP-even"<<std::endl;
cpEigenValue_ = CPEven;
}
}
evtCPEigenVals_.push_back( cpEigenValue_ );
}
// We'll cache the DP amplitudes at the end because we'll
// append some points that the other PDFs won't deal with.
// Flavour tagging information
flavTag_->cacheInputFitVars(inputFitData);
if (this->useDP() == kTRUE) {
// DecayTime and SigmaDecayTime
signalDecayTimePdf_->cacheInfo(*inputFitData);
}
// ...and then the extra PDFs
if (sigExtraPdf_){
this->cacheInfo((*sigExtraPdf_), *inputFitData);
}
if(usingBkgnd_ == kTRUE){
for (LauBkgndPdfsList::iterator iter = BkgndPdfs_.begin(); iter != BkgndPdfs_.end(); ++iter) {
this->cacheInfo((*iter), *inputFitData);
}
}
if (this->useDP() == kTRUE) {
sigModelB0bar_->fillDataTree(*inputFitData);
sigModelB0_->fillDataTree(*inputFitData);
if (usingBkgnd_ == kTRUE) {
for (LauBkgndDPModelList::iterator iter = BkgndDPModels_.begin(); iter != BkgndDPModels_.end(); ++iter) {
(*iter)->fillDataTree(*inputFitData);
}
}
}
}
Double_t LauTimeDepFitModel::getTotEvtLikelihood(const UInt_t iEvt)
{
// Find out whether the tag-side B was a B0 or a B0bar.
curEvtTagFlv_ = flavTag_->getCurEvtTagFlv();
// Get the CP eigenvalue of the current event
cpEigenValue_ = evtCPEigenVals_[iEvt];
// Get the DP and DecayTime likelihood for signal (TODO and eventually backgrounds)
this->getEvtDPDtLikelihood(iEvt);
// Get the flavour tagging likelihood from eta PDFs (per tagging category - TODO backgrounds to come later)
sigFlavTagLike_ = 1.0;
//this->getEvtFlavTagLikelihood(iEvt);
// Get the combined extra PDFs likelihood for signal (TODO and eventually backgrounds)
this->getEvtExtraLikelihoods(iEvt);
// Construct the total likelihood for signal, qqbar and BBbar backgrounds
Double_t sigLike = sigDPLike_ * sigFlavTagLike_ * sigExtraLike_;
//std::cout << "DP like = " << sigDPLike_ << std::endl;
//std::cout << "flav tag like = " << sigFlavTagLike_ << std::endl;
//std::cout << "extra like = " << sigExtraLike_ << std::endl;
// TODO
Double_t signalEvents = signalEvents_->unblindValue();
if (this->useDP() == kFALSE) {
//signalEvents *= 0.5 * (1.0 + curEvtTagFlv_ * signalAsym_->unblindValue());
}
if ( ! signalEvents_->fixed() ) {
sigLike *= signalEvents;
}
return sigLike;
}
Double_t LauTimeDepFitModel::getEventSum() const
{
Double_t eventSum(0.0);
eventSum += signalEvents_->unblindValue();
return eventSum;
}
void LauTimeDepFitModel::getEvtDPDtLikelihood(const UInt_t iEvt)
{
// Function to return the signal and background likelihoods for the
// Dalitz plot for the given event evtNo.
if ( ! this->useDP() ) {
// There's always going to be a term in the likelihood for the
// signal, so we'd better not zero it.
sigDPLike_ = 1.0;
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t bkgndID(0); bkgndID < nBkgnds; ++bkgndID ) {
if (usingBkgnd_ == kTRUE) {
bkgndDPLike_[bkgndID] = 1.0;
} else {
bkgndDPLike_[bkgndID] = 0.0;
}
}
return;
}
// Calculate event quantities
// Get the dynamics to calculate everything required for the likelihood calculation
sigModelB0bar_->calcLikelihoodInfo(iEvt);
sigModelB0_->calcLikelihoodInfo(iEvt);
// Background part
// TODO add them into the actual Likelihood calculations
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t bkgndID(0); bkgndID < nBkgnds; ++bkgndID ) {
if (usingBkgnd_ == kTRUE) {
bkgndDPLike_[bkgndID] = BkgndDPModels_[bkgndID]->getLikelihood(iEvt);
} else {
bkgndDPLike_[bkgndID] = 0.0;
}
}
// Retrieve the amplitudes and efficiency from the dynamics
const LauComplex& Abar = sigModelB0bar_->getEvtDPAmp();
const LauComplex& A = sigModelB0_->getEvtDPAmp();
Double_t eff = sigModelB0bar_->getEvtEff();
// Next calculate the DP terms
Double_t aSqSum = A.abs2() + Abar.abs2();
Double_t aSqDif = A.abs2() - Abar.abs2();
LauComplex inter = Abar * A.conj() * phiMixComplex_;
Double_t interTermIm = 2.0 * inter.im();
Double_t interTermRe = 2.0 * inter.re();
// First get all the decay time terms
signalDecayTimePdf_->calcLikelihoodInfo(iEvt);
// TODO Backgrounds
// Get the decay time acceptance
Double_t dtEff = signalDecayTimePdf_->getEffiTerm();
// First get all the decay time terms
Double_t dtCos = signalDecayTimePdf_->getCosTerm();
Double_t dtSin = signalDecayTimePdf_->getSinTerm();
Double_t dtCosh = signalDecayTimePdf_->getCoshTerm();
Double_t dtSinh = signalDecayTimePdf_->getSinhTerm();
// Get flavour tagging terms
flavTag_->updateEventInfo(iEvt);
Double_t ftOmegaTrig(1.);
Double_t ftOmegaHyp(1.);
Int_t ntaggers = flavTag_->getNTaggers();
for (Int_t position=0; position<ntaggers; ++position){
Double_t omega(0);
Double_t omegabar(0);
omega = flavTag_->getCapitalOmega(position,1);
omegabar = flavTag_->getCapitalOmega(position,-1);
ftOmegaTrig *= ((1 - AProd_.unblindValue())*omega - (1 + AProd_.unblindValue())*omegabar);
ftOmegaHyp *= ((1 - AProd_.unblindValue())*omega + (1 + AProd_.unblindValue())*omegabar);
}
Double_t cosTerm = dtCos * ftOmegaTrig * aSqDif;
Double_t sinTerm = dtSin * ftOmegaTrig * interTermIm;
Double_t coshTerm = dtCosh * ftOmegaHyp * aSqSum;
Double_t sinhTerm = dtSinh * ftOmegaHyp * interTermRe;
curEvtTrueTagFlv_ = flavTag_->getCurEvtTrueTagFlv();
if (curEvtTrueTagFlv_!=0 && (signalDecayTimePdf_->getFuncType() == LauDecayTimePdf::SimFitNormBd || signalDecayTimePdf_->getFuncType() == LauDecayTimePdf::SimFitNormBs)){
cosTerm *= curEvtTrueTagFlv_;
sinTerm *= curEvtTrueTagFlv_;
}
if ( cpEigenValue_ == CPOdd ) {
sinTerm *= -1.0;
sinhTerm *= -1.0;
}
// ... to get the total and multiply by the efficiency (DP and decay time)
Double_t ASq = coshTerm + cosTerm - sinTerm + sinhTerm;
ASq *= eff;
ASq *= dtEff;
//std::cout<<"Cosh Cos Sin Sinh "<< coshTerm<< " " << cosTerm << " " << sinTerm << " " << sinhTerm << std::endl;
//std::cout << "Total Amplitude : " << ASq << std::endl;
// Calculate the DP and time normalisation
Double_t normTermIndep = sigModelB0bar_->getDPNorm() + sigModelB0_->getDPNorm();
Double_t normTermCosh(0.0);
Double_t norm(0.0);
if (signalDecayTimePdf_->getFuncType() == LauDecayTimePdf::ExpTrig || signalDecayTimePdf_->getFuncType() == LauDecayTimePdf::SimFitNormBd || signalDecayTimePdf_->getFuncType() == LauDecayTimePdf::SimFitSigBd){
normTermCosh = signalDecayTimePdf_->getNormTermExp();
norm = normTermIndep*normTermCosh;
//Test
// norm *= dtEffN;
}
if (signalDecayTimePdf_->getFuncType() == LauDecayTimePdf::ExpHypTrig){
normTermCosh = signalDecayTimePdf_->getNormTermCosh();
Double_t normTermDep = interTermReNorm_;
Double_t normTermSinh = signalDecayTimePdf_->getNormTermSinh();
norm = normTermIndep*normTermCosh + normTermDep*normTermSinh;
}
// Calculate the normalised signal likelihood
//std::cout << "ASq = " << ASq << std::endl;
//std::cout << "norm = " << norm << std::endl;
sigDPLike_ = ASq / norm;
}
void LauTimeDepFitModel::getEvtExtraLikelihoods(const UInt_t iEvt)
{
// Function to return the signal and background likelihoods for the
// extra variables for the given event evtNo.
sigExtraLike_ = 1.0; //There's always a likelihood term for signal, so we better not zero it.
// First, those independent of the tagging of the event:
// signal
if (sigExtraPdf_) {
sigExtraLike_ = this->prodPdfValue( (*sigExtraPdf_), iEvt );
}
// Background
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t bkgndID(0); bkgndID < nBkgnds; ++bkgndID ) {
if (usingBkgnd_) {
bkgndExtraLike_[bkgndID] = this->prodPdfValue( BkgndPdfs_[bkgndID], iEvt );
} else {
bkgndExtraLike_[bkgndID] = 0.0;
}
}
}
void LauTimeDepFitModel::getEvtFlavTagLikelihood(const UInt_t iEvt)
{
// Function to return the signal and background likelihoods for the
// extra variables for the given event evtNo.
sigFlavTagLike_ = 1.0; //There's always a likelihood term for signal, so we better not zero it.
// Loop over taggers
Int_t ntaggers = flavTag_->getNTaggers();
for (Int_t position=0; position<ntaggers; ++position){
if (sigFlavTagPdf_[position]) {
sigFlavTagPdf_[position]->calcLikelihoodInfo(iEvt);
sigFlavTagLike_ = sigFlavTagPdf_[position]->getLikelihood();
}
}
if (sigFlavTagLike_<=0){
std::cout<<"INFO in LauTimeDepFitModel::getEvtFlavTagLikelihood : Event with 0 FlavTag Liklihood"<<std::endl;
}
// TODO Add in the background components too
}
void LauTimeDepFitModel::updateCoeffs()
{
coeffsB0bar_.clear(); coeffsB0_.clear();
coeffsB0bar_.reserve(nSigComp_); coeffsB0_.reserve(nSigComp_);
for (UInt_t i = 0; i < nSigComp_; ++i) {
coeffsB0bar_.push_back(coeffPars_[i]->antiparticleCoeff());
coeffsB0_.push_back(coeffPars_[i]->particleCoeff());
}
}
void LauTimeDepFitModel::checkMixingPhase()
{
Double_t phase = phiMix_.value();
Double_t genPhase = phiMix_.genValue();
// Check now whether the phase lies in the right range (-pi to pi).
Bool_t withinRange(kFALSE);
while (withinRange == kFALSE) {
if (phase > -LauConstants::pi && phase < LauConstants::pi) {
withinRange = kTRUE;
} else {
// Not within the specified range
if (phase > LauConstants::pi) {
phase -= LauConstants::twoPi;
} else if (phase < -LauConstants::pi) {
phase += LauConstants::twoPi;
}
}
}
// A further problem can occur when the generated phase is close to -pi or pi.
// The phase can wrap over to the other end of the scale -
// this leads to artificially large pulls so we wrap it back.
Double_t diff = phase - genPhase;
if (diff > LauConstants::pi) {
phase -= LauConstants::twoPi;
} else if (diff < -LauConstants::pi) {
phase += LauConstants::twoPi;
}
// finally store the new value in the parameter
// and update the pull
phiMix_.value(phase);
phiMix_.updatePull();
}
void LauTimeDepFitModel::embedSignal(const TString& fileName, const TString& treeName,
Bool_t reuseEventsWithinEnsemble, Bool_t reuseEventsWithinExperiment)
{
if (signalTree_) {
std::cerr<<"ERROR in LauTimeDepFitModel::embedSignal : Already embedding signal from file."<<std::endl;
return;
}
if (!reuseEventsWithinEnsemble && reuseEventsWithinExperiment) {
std::cerr<<"WARNING in LauTimeDepFitModel::embedSignal : Conflicting options provided, will not reuse events at all."<<std::endl;
reuseEventsWithinExperiment = kFALSE;
}
signalTree_ = new LauEmbeddedData(fileName,treeName,reuseEventsWithinExperiment);
Bool_t dataOK = signalTree_->findBranches();
if (!dataOK) {
delete signalTree_; signalTree_ = 0;
std::cerr<<"ERROR in LauTimeDepFitModel::embedSignal : Problem creating data tree for embedding."<<std::endl;
return;
}
reuseSignal_ = reuseEventsWithinEnsemble;
}
void LauTimeDepFitModel::embedBkgnd(const TString& bkgndClass, const TString& fileName, const TString& treeName,
Bool_t reuseEventsWithinEnsemble, Bool_t reuseEventsWithinExperiment)
{
if ( ! this->validBkgndClass( bkgndClass ) ) {
std::cerr << "ERROR in LauSimpleFitModel::embedBkgnd : Invalid background class \"" << bkgndClass << "\"." << std::endl;
std::cerr << " : Background class names must be provided in \"setBkgndClassNames\" before any other background-related actions can be performed." << std::endl;
return;
}
UInt_t bkgndID = this->bkgndClassID( bkgndClass );
LauEmbeddedData* bkgTree = bkgndTree_[bkgndID];
if (bkgTree) {
std::cerr << "ERROR in LauSimpleFitModel::embedBkgnd : Already embedding background from a file." << std::endl;
return;
}
bkgTree = new LauEmbeddedData(fileName,treeName,reuseEventsWithinExperiment);
Bool_t dataOK = bkgTree->findBranches();
if (!dataOK) {
delete bkgTree; bkgTree = 0;
std::cerr << "ERROR in LauSimpleFitModel::embedBkgnd : Problem creating data tree for embedding." << std::endl;
return;
}
reuseBkgnd_[bkgndID] = reuseEventsWithinEnsemble;
if (this->enableEmbedding() == kFALSE) {
this->enableEmbedding(kTRUE);
}
}
void LauTimeDepFitModel::setupSPlotNtupleBranches()
{
// add branches for storing the experiment number and the number of
// the event within the current experiment
this->addSPlotNtupleIntegerBranch("iExpt");
this->addSPlotNtupleIntegerBranch("iEvtWithinExpt");
// Store the efficiency of the event (for inclusive BF calculations).
if (this->storeDPEff()) {
this->addSPlotNtupleDoubleBranch("efficiency");
}
// Store the total event likelihood for each species.
this->addSPlotNtupleDoubleBranch("sigTotalLike");
if (usingBkgnd_) {
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
TString name( this->bkgndClassName(iBkgnd) );
name += "TotalLike";
this->addSPlotNtupleDoubleBranch(name);
}
}
// Store the DP likelihoods
if (this->useDP()) {
this->addSPlotNtupleDoubleBranch("sigDPLike");
if (usingBkgnd_) {
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
TString name( this->bkgndClassName(iBkgnd) );
name += "DPLike";
this->addSPlotNtupleDoubleBranch(name);
}
}
}
// Store the likelihoods for each extra PDF
const LauPdfList* pdfList( sigExtraPdf_ );
this->addSPlotNtupleBranches(pdfList, "sig");
if (usingBkgnd_) {
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
const TString& bkgndClass = this->bkgndClassName(iBkgnd);
const LauPdfList* pdfList2 = &(BkgndPdfs_[iBkgnd]);
this->addSPlotNtupleBranches(pdfList2, bkgndClass);
}
}
}
void LauTimeDepFitModel::addSPlotNtupleBranches(const LauPdfList* extraPdfs, const TString& prefix)
{
if (!extraPdfs) {
return;
}
// Loop through each of the PDFs
for (LauPdfList::const_iterator pdf_iter = extraPdfs->begin(); pdf_iter != extraPdfs->end(); ++pdf_iter) {
// Count the number of input variables that are not
// DP variables (used in the case where there is DP
// dependence for e.g. MVA)
UInt_t nVars(0);
for ( std::vector<TString>::const_iterator var_iter = (*pdf_iter)->varNames().begin(); var_iter != (*pdf_iter)->varNames().end(); ++var_iter ) {
if ( (*var_iter) != "m13Sq" && (*var_iter) != "m23Sq" ) {
++nVars;
}
}
if ( nVars == 1 ) {
// If the PDF only has one variable then
// simply add one branch for that variable
TString varName = (*pdf_iter)->varName();
TString name(prefix);
name += varName;
name += "Like";
this->addSPlotNtupleDoubleBranch(name);
} else if ( nVars == 2 ) {
// If the PDF has two variables then we
// need a branch for them both together and
// branches for each
TString allVars("");
for ( std::vector<TString>::const_iterator var_iter = (*pdf_iter)->varNames().begin(); var_iter != (*pdf_iter)->varNames().end(); ++var_iter ) {
allVars += (*var_iter);
TString name(prefix);
name += (*var_iter);
name += "Like";
this->addSPlotNtupleDoubleBranch(name);
}
TString name(prefix);
name += allVars;
name += "Like";
this->addSPlotNtupleDoubleBranch(name);
} else {
std::cerr<<"WARNING in LauTimeDepFitModel::addSPlotNtupleBranches : Can't yet deal with 3D PDFs."<<std::endl;
}
}
}
Double_t LauTimeDepFitModel::setSPlotNtupleBranchValues(LauPdfList* extraPdfs, const TString& prefix, UInt_t iEvt)
{
// Store the PDF value for each variable in the list
Double_t totalLike(1.0);
Double_t extraLike(0.0);
if ( !extraPdfs ) {
return totalLike;
}
for (LauPdfList::iterator pdf_iter = extraPdfs->begin(); pdf_iter != extraPdfs->end(); ++pdf_iter) {
// calculate the likelihood for this event
(*pdf_iter)->calcLikelihoodInfo(iEvt);
extraLike = (*pdf_iter)->getLikelihood();
totalLike *= extraLike;
// Count the number of input variables that are not
// DP variables (used in the case where there is DP
// dependence for e.g. MVA)
UInt_t nVars(0);
for ( std::vector<TString>::const_iterator var_iter = (*pdf_iter)->varNames().begin(); var_iter != (*pdf_iter)->varNames().end(); ++var_iter ) {
if ( (*var_iter) != "m13Sq" && (*var_iter) != "m23Sq" ) {
++nVars;
}
}
if ( nVars == 1 ) {
// If the PDF only has one variable then
// simply store the value for that variable
TString varName = (*pdf_iter)->varName();
TString name(prefix);
name += varName;
name += "Like";
this->setSPlotNtupleDoubleBranchValue(name, extraLike);
} else if ( nVars == 2 ) {
// If the PDF has two variables then we
// store the value for them both together
// and for each on their own
TString allVars("");
for ( std::vector<TString>::const_iterator var_iter = (*pdf_iter)->varNames().begin(); var_iter != (*pdf_iter)->varNames().end(); ++var_iter ) {
allVars += (*var_iter);
TString name(prefix);
name += (*var_iter);
name += "Like";
Double_t indivLike = (*pdf_iter)->getLikelihood( (*var_iter) );
this->setSPlotNtupleDoubleBranchValue(name, indivLike);
}
TString name(prefix);
name += allVars;
name += "Like";
this->setSPlotNtupleDoubleBranchValue(name, extraLike);
} else {
std::cerr<<"WARNING in LauAllFitModel::setSPlotNtupleBranchValues : Can't yet deal with 3D PDFs."<<std::endl;
}
}
return totalLike;
}
LauSPlot::NameSet LauTimeDepFitModel::variableNames() const
{
LauSPlot::NameSet nameSet;
if (this->useDP()) {
nameSet.insert("DP");
}
for (LauPdfList::const_iterator pdf_iter = sigExtraPdf_->begin(); pdf_iter != sigExtraPdf_->end(); ++pdf_iter) {
// Loop over the variables involved in each PDF
for ( std::vector<TString>::const_iterator var_iter = (*pdf_iter)->varNames().begin(); var_iter != (*pdf_iter)->varNames().end(); ++var_iter ) {
// If they are not DP coordinates then add them
if ( (*var_iter) != "m13Sq" && (*var_iter) != "m23Sq" ) {
nameSet.insert( (*var_iter) );
}
}
}
return nameSet;
}
LauSPlot::NumbMap LauTimeDepFitModel::freeSpeciesNames() const
{
LauSPlot::NumbMap numbMap;
if (!signalEvents_->fixed() && this->doEMLFit()) {
numbMap["sig"] = signalEvents_->genValue();
}
if ( usingBkgnd_ ) {
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
const TString& bkgndClass = this->bkgndClassName(iBkgnd);
const LauAbsRValue* par = bkgndEvents_[iBkgnd];
if (!par->fixed()) {
numbMap[bkgndClass] = par->genValue();
if ( ! par->isLValue() ) {
std::cerr << "WARNING in LauTimeDepFitModel::freeSpeciesNames : \"" << par->name() << "\" is a LauFormulaPar, which implies it is perhaps not entirely free to float in the fit, so the sWeight calculation may not be reliable" << std::endl;
}
}
}
}
return numbMap;
}
LauSPlot::NumbMap LauTimeDepFitModel::fixdSpeciesNames() const
{
LauSPlot::NumbMap numbMap;
if (signalEvents_->fixed() && this->doEMLFit()) {
numbMap["sig"] = signalEvents_->genValue();
}
if ( usingBkgnd_ ) {
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
const TString& bkgndClass = this->bkgndClassName(iBkgnd);
const LauAbsRValue* par = bkgndEvents_[iBkgnd];
if (par->fixed()) {
numbMap[bkgndClass] = par->genValue();
}
}
}
return numbMap;
}
LauSPlot::TwoDMap LauTimeDepFitModel::twodimPDFs() const
{
LauSPlot::TwoDMap twodimMap;
const LauPdfList* pdfList = sigExtraPdf_;
for (LauPdfList::const_iterator pdf_iter = pdfList->begin(); pdf_iter != pdfList->end(); ++pdf_iter) {
// Count the number of input variables that are not DP variables
UInt_t nVars(0);
for ( std::vector<TString>::const_iterator var_iter = (*pdf_iter)->varNames().begin(); var_iter != (*pdf_iter)->varNames().end(); ++var_iter ) {
if ( (*var_iter) != "m13Sq" && (*var_iter) != "m23Sq" ) {
++nVars;
}
}
if ( nVars == 2 ) {
twodimMap.insert( std::make_pair( "sig", std::make_pair( (*pdf_iter)->varNames()[0], (*pdf_iter)->varNames()[1] ) ) );
}
}
if (usingBkgnd_) {
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
const TString& bkgndClass = this->bkgndClassName(iBkgnd);
const LauPdfList& pdfList2 = BkgndPdfs_[iBkgnd];
for (LauPdfList::const_iterator pdf_iter = pdfList2.begin(); pdf_iter != pdfList2.end(); ++pdf_iter) {
// Count the number of input variables that are not DP variables
UInt_t nVars(0);
std::vector<TString> varNames = (*pdf_iter)->varNames();
for ( std::vector<TString>::const_iterator var_iter = varNames.begin(); var_iter != varNames.end(); ++var_iter ) {
if ( (*var_iter) != "m13Sq" && (*var_iter) != "m23Sq" ) {
++nVars;
}
}
if ( nVars == 2 ) {
twodimMap.insert( std::make_pair( bkgndClass, std::make_pair( varNames[0], varNames[1] ) ) );
}
}
}
}
return twodimMap;
}
void LauTimeDepFitModel::storePerEvtLlhds()
{
std::cout<<"INFO in LauTimeDepFitModel::storePerEvtLlhds : Storing per-event likelihood values..."<<std::endl;
LauFitDataTree* inputFitData = this->fitData();
// if we've not been using the DP model then we need to cache all
// the info here so that we can get the efficiency from it
if (!this->useDP() && this->storeDPEff()) {
sigModelB0bar_->initialise(coeffsB0bar_);
sigModelB0_->initialise(coeffsB0_);
sigModelB0bar_->fillDataTree(*inputFitData);
sigModelB0_->fillDataTree(*inputFitData);
}
UInt_t evtsPerExpt(this->eventsPerExpt());
LauIsobarDynamics* sigModel(sigModelB0bar_);
for (UInt_t iEvt = 0; iEvt < evtsPerExpt; ++iEvt) {
// Find out whether we have B0bar or B0
flavTag_->updateEventInfo(iEvt);
curEvtTagFlv_ = flavTag_->getCurEvtTagFlv();
curEvtMistag_ = flavTag_->getCurEvtMistag();
// the DP information
this->getEvtDPDtLikelihood(iEvt);
if (this->storeDPEff()) {
if (!this->useDP()) {
sigModel->calcLikelihoodInfo(iEvt);
}
this->setSPlotNtupleDoubleBranchValue("efficiency",sigModel->getEvtEff());
}
if (this->useDP()) {
sigTotalLike_ = sigDPLike_;
this->setSPlotNtupleDoubleBranchValue("sigDPLike",sigDPLike_);
if (usingBkgnd_) {
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
TString name = this->bkgndClassName(iBkgnd);
name += "DPLike";
this->setSPlotNtupleDoubleBranchValue(name,bkgndDPLike_[iBkgnd]);
}
}
} else {
sigTotalLike_ = 1.0;
}
// the signal PDF values
sigTotalLike_ *= this->setSPlotNtupleBranchValues(sigExtraPdf_, "sig", iEvt);
// the background PDF values
LauBkgndPdfsList* bkgndPdfs(0);
if (usingBkgnd_) {
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
const TString& bkgndClass = this->bkgndClassName(iBkgnd);
LauPdfList& pdfs = (*bkgndPdfs)[iBkgnd];
bkgndTotalLike_[iBkgnd] *= this->setSPlotNtupleBranchValues(&(pdfs), bkgndClass, iEvt);
}
}
// the total likelihoods
this->setSPlotNtupleDoubleBranchValue("sigTotalLike",sigTotalLike_);
if (usingBkgnd_) {
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
TString name = this->bkgndClassName(iBkgnd);
name += "TotalLike";
this->setSPlotNtupleDoubleBranchValue(name,bkgndTotalLike_[iBkgnd]);
}
}
// fill the tree
this->fillSPlotNtupleBranches();
}
std::cout<<"INFO in LauTimeDepFitModel::storePerEvtLlhds : Finished storing per-event likelihood values."<<std::endl;
}
void LauTimeDepFitModel::weightEvents( const TString& /*dataFileName*/, const TString& /*dataTreeName*/ )
{
std::cerr << "ERROR in LauTimeDepFitModel::weightEvents : Method not available for this fit model." << std::endl;
return;
}
void LauTimeDepFitModel::savePDFPlots(const TString& /*label*/)
{
}
void LauTimeDepFitModel::savePDFPlotsWave(const TString& /*label*/, const Int_t& /*spin*/)
{
}
void LauTimeDepFitModel::setBkgdFlavTagPdfs(const TString name, LauAbsPdf* pdf)
{
// TODO - when backgrounds are added - implement a check that "name" really is the name of a background category
if (pdf==0) {
std::cerr<<"ERROR in LauTimeDepFitModel::setBkgdFlavTagPdfs : The PDF pointer is null."<<std::endl;
return;
}
bkgdFlavTagPdf_[name] = pdf;
}