Page MenuHomeHEPForge

No OneTemporary

diff --git a/examples/Test_Dpipi.cc b/examples/Test_Dpipi.cc
index e625aa0..dd58295 100755
--- a/examples/Test_Dpipi.cc
+++ b/examples/Test_Dpipi.cc
@@ -1,388 +1,392 @@
#include <iostream>
using std::cout;
using std::cerr;
using std::endl;
#include <vector>
#include <map>
#include "TFile.h"
#include "TH2.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(const int argc, 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;
LauFlavTag* flavTag = new LauFlavTag(params, kTRUE, "tagFlv", "tagCat");
+
+ // Use alternative tagging calibration parameters?
+ //flavTag->useAveOmegaDeltaOmega();
+
TFile* etafile(0);
TH1* etahist(0);
Lau1DHistPdf* etahistpdf(0);
if (command == "gen"){
etafile = TFile::Open("/Users/mark/analysis/DpipiLaura/laura/examples/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);
}
fitModel->setCPEigenvalue( eigenvalue );
fitModel->setPhiMix( 2.0*LauConstants::beta, fixPhiMix, useSinCos );
int tagCat(-1);
// Tag cat fractions, dilutions and Delta dilutions
if (dtype=="CPEven"){
flavTag->addValidTagCat(63);
- flavTag->setSignalTagCatPars(63, 0.5, 1.0, 0.0, kTRUE, kTRUE,"PerEvtMistag",0.5,1.0,1.0);
+ flavTag->setSignalTagCatPars(63, 0.5, 1.0, 0.0, kTRUE, kTRUE,"PerEvtMistag",0.5,0.5,1.0,1.0,1.0);
tagCat=63;
} else {
flavTag->addValidTagCat(0);
- flavTag->setSignalTagCatPars(0, 1.0, 0.0, 0.0, kTRUE, kTRUE,"PerEvtMistag",0.5,1.0,1.0);
+ flavTag->setSignalTagCatPars(0, 1.0, 0.0, 0.0, kTRUE, kTRUE,"PerEvtMistag",0.5,0.5,1.0,1.0,1.0);
}
if (command == "gen" && dtype=="CPEven"){
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(2.5); dtvals.push_back(5.0); dtvals.push_back(10.0); dtvals.push_back(20.0);
std::vector<Double_t> effvals;
effvals.push_back(0.05); effvals.push_back(0.3); effvals.push_back(0.9); effvals.push_back(0.95); effvals.push_back(0.99);
Lau1DCubicSpline* dtEffSpline = new Lau1DCubicSpline(dtvals,effvals);
//LauParameters to float Spline y values
//Test by floating knot 2 for both tagcats
LauParameter* knot_0_0 = new LauParameter("knot_0_0",0.05,0.0,1.0,kTRUE);
LauParameter* knot_0_1 = new LauParameter("knot_0_1",0.30,0.0,1.0,kTRUE);
LauParameter* knot_0_2 = new LauParameter("knot_0_2",0.90,0.0,1.0,kFALSE);
LauParameter* knot_0_3 = new LauParameter("knot_0_3",0.95,0.0,1.0,kTRUE);
LauParameter* knot_0_4 = new LauParameter("knot_0_4",0.99,0.0,1.0,kTRUE);
LauParameter* knot_63_0 = new LauParameter("knot_63_0",0.05,0.0,1.0,kTRUE);
LauParameter* knot_63_1 = new LauParameter("knot_63_1",0.30,0.0,1.0,kTRUE);
LauParameter* knot_63_2 = new LauParameter("knot_63_2",0.90,0.0,1.0,kFALSE);
LauParameter* knot_63_3 = new LauParameter("knot_63_3",0.95,0.0,1.0,kTRUE);
LauParameter* knot_63_4 = new LauParameter("knot_63_4",0.99,0.0,1.0,kTRUE);
std::vector<LauParameter*> effPars0;
effPars0.reserve(5);
effPars0.push_back(knot_0_0); effPars0.push_back(knot_0_1); effPars0.push_back(knot_0_2); effPars0.push_back(knot_0_3); effPars0.push_back(knot_0_4);
std::vector<LauParameter*> effPars63;
effPars63.reserve(5);
effPars63.push_back(knot_63_0); effPars63.push_back(knot_63_1); effPars63.push_back(knot_63_2); effPars63.push_back(knot_63_3); effPars63.push_back(knot_63_4);
if (dtype=="CPEven"){
LauDecayTimePdf * dtPdf = new LauDecayTimePdf( "deltaTAvg", "deltaTAvgErr", dtPars, minDt, maxDt, minDtErr, maxDtErr, LauDecayTimePdf::ExpTrig, nGauss, scale, LauDecayTimePdf::DecayTime );
dtPdf->doSmearing(kFALSE);
dtPdf->setEffiSpline(dtEffSpline, effPars0);
//dtPdf->setEffiSpline(dtEffSpline);
fitModel->setSignalDtPdf( 0, dtPdf );
} else {
LauDecayTimePdf * dtPdf = new LauDecayTimePdf( "deltaTAvg", "deltaTAvgErr", dtPars, minDt, maxDt, minDtErr, maxDtErr, LauDecayTimePdf::ExpTrig, nGauss, scale, LauDecayTimePdf::DecayTime );
dtPdf->doSmearing(kFALSE);
dtPdf->setEffiSpline(dtEffSpline, effPars0);
//dtPdf->setEffiSpline(dtEffSpline);
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 );
dtPdf->doSmearing(kFALSE);
dtPdf->setEffiSpline(dtEffSpline, effPars63);
//dtPdf->setEffiSpline(dtEffSpline);
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_"; 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(10, 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 );
- //}
+// 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/inc/LauFlavTag.hh b/inc/LauFlavTag.hh
index c34f669..c6b54aa 100644
--- a/inc/LauFlavTag.hh
+++ b/inc/LauFlavTag.hh
@@ -1,233 +1,265 @@
/*
Copyright 2017 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 LauFlavTag.hh
\brief File containing declaration of LauFlavTag class.
*/
/*! \class LauFlavTag
\brief Class for defining the flavour tagging approach.
Define the flavour tagging categories and all associated parameters
to be passed to the relevant fit models.
*/
#ifndef LAU_FLAVTAG
#define LAU_FLAVTAG
#include <vector>
#include <map>
#include <set>
#include <iostream>
#include "TString.h"
#include "TStopwatch.h"
#include "TSystem.h"
#include "LauConstants.hh"
#include "LauParameter.hh"
#include "LauFitDataTree.hh"
#include "LauAbsFitModel.hh"
#include "LauDecayTimePdf.hh"
class LauFlavTag {
public:
//! Constructor
/*!
\param [in] modelB0bar DP model for the antiparticle
\param [in] modelB0 DP model for the particle
\param [in] useUntaggedEvents should the untagged sample be used or excluded?
\param [in] tagVarName the variable name in the data tree that specifies the event tag
\param [in] tagCatVarName the variable name in the data tree that specifies the event tagging category
*/
LauFlavTag(const std::vector<LauParameter*>& params, const Bool_t useUntaggedEvents = kTRUE, const TString& tagVarName = "tagFlv", const TString& tagCatVarName = "tagCat");
//! Destructor
virtual ~LauFlavTag();
void initialise();
//! Add a tagging category to the list of valid categories
/*!
NB category 0 is always valid and corresponds to untagged events.
Whether untagged events are used in the fit or note is controlled by a constructor argument.
\param [in] tagCat the tagging category ID
*/
void addValidTagCat(const Int_t tagCat);
//! Add several tagging categories to the list of valid categories
/*!
NB category 0 is always valid and corresponds to untagged events.
Whether untagged events are used in the fit or note is controlled by a constructor argument.
\param [in] tagCats the list of tagging category IDs
*/
void addValidTagCats(const std::vector<Int_t>& tagCats);
//! Check the validity of the given tagging category
/*!
\param [in] tagCat the tagging category ID
*/
Bool_t validTagCat(const Int_t tagCat) const;
//! Return the set of valid tagging categories
std::set<Int_t> getValidTagCats();
//! Change the dilutions, delta dilutions and tagCatFrac for signal if needed
/*!
\param [in] tagCat the tagging category to adjust
\param [in] tagCatFrac the tagging category fraction
\param [in] dilution the tagging category average dilution = (1 - 2 * avg_mistag_fraction)
\param [in] deltaDilution the tagging category dilution difference TODO - check sign convention
\param [in] fixTCFrac whether to fix or float the tagging category fraction
\param [in] usePerEvtMistag whether to use per event mistag information or not
\param [in] mistagVarName the name of the branch in the tree containing per event mistag information
- \param [in] calib_p0 the calibration parameter p0 when using per event mistags
- \param [in] calib_p1 the calibration parameter p1 when using per event mistags
+ \param [in] calib_p0_B0 the calibration parameter p0 for B0 decays when using per event mistags
+ \param [in] calib_p0_B0bar the calibration parameter p0 for B0bar decays when using per event mistags
+ \param [in] calib_p1_B0 the calibration parameter p1 for B0 decays when using per event mistags
+ \param [in] calib_p1_B0bar the calibration parameter p1 for B0bar decays when using per event mistags
*/
void setSignalTagCatPars(const Int_t tagCat, const Double_t tagCatFrac, const Double_t dilution, const Double_t deltaDilution,
const Bool_t fixTCFrac = kTRUE, const Bool_t usePerEvtMistag = kFALSE, const TString& mistagVarName = "tagMistag",
- const Double_t calib_p0=0.25, const Double_t calib_p1=1.0, const Double_t tagAsym=1.0);
+ const Double_t calib_p0_b0=0.25, const Double_t calib_p0_b0bar=0.25, const Double_t calib_p1_b0=1.0, const Double_t calib_p1_b0bar=1.0, const Double_t tagAsym=1.0);
+
+ //! Set up alternative calibration parameters if requested
+ /*!
+ \param [in] tagCat the tagging catergory
+ */
+ void useAveOmegaDeltaOmegaCalib(Int_t tagCat);
//! Read in the input fit data variables, e.g. m13Sq and m23Sq
void cacheInputFitVars(LauFitDataTree* inputFitData);
Bool_t getUsePerEvtMistag(){return usePerEvtMistag_;};
typedef std::map< Int_t, LauParameter> LauTagCatParamMap;
LauTagCatParamMap getDilution(){return dilution_;};
LauTagCatParamMap getDeltaDilution(){return deltaDilution_;};
LauTagCatParamMap& getSignalTagCatFrac(){return signalTagCatFrac_;};
//! Update the fraction of the first tagging category for all species
void setFirstTagCatFractions();
//std::vector<Int_t> getEvtTagFlvVals(){return evtTagFlvVals_;};
//std::vector<Int_t> getEvtTagCatVals(){return evtTagCatVals_;};
//std::vector<Double_t> getEvtMistagVals(){return evtMistagVals_;};
Int_t getEvtTagFlvVals(UInt_t iEvt){return evtTagFlvVals_[iEvt];};
Int_t getEvtTagCatVals(UInt_t iEvt){return evtTagCatVals_[iEvt];};
Double_t getEvtMistagVals(UInt_t iEvt){return evtMistagVals_[iEvt];};
const TString& getMistagVarName(){return mistagVarName_;};
LauParameter* findParameter(const TString& parName);
//std::vector<LauParameter*> getCalibParameters(Int_t tagCat);
//! Get map of calibration parameters for each tagging category
- LauTagCatParamMap& getCalibP0(){return calib_p0_;};
- LauTagCatParamMap& getCalibP1(){return calib_p1_;};
+ LauTagCatParamMap& getCalibP0B0(){return calib_p0_B0_;};
+ LauTagCatParamMap& getCalibP0B0bar(){return calib_p0_B0bar_;};
+ LauTagCatParamMap& getCalibP1B0(){return calib_p1_B0_;};
+ LauTagCatParamMap& getCalibP1B0bar(){return calib_p1_B0bar_;};
+
+ //! Get map of alternative calibration parameters for each tagging category
+ LauTagCatParamMap& getCalibP0Ave(){return calib_p0_ave_;};
+ LauTagCatParamMap& getCalibP0Delta(){return calib_p0_delta_;};
+ LauTagCatParamMap& getCalibP1Ave(){return calib_p1_ave_;};
+ LauTagCatParamMap& getCalibP1Delta(){return calib_p1_delta_;};
//! Get map of tagging asymmetry parameters for each tagging category
LauTagCatParamMap& getTagAsym(){return tagAsym_;};
std::map< Int_t, Double_t> getPerEvtAvgMistag() const {return perEvtAvgMistag_;};
Double_t getOmega(const UInt_t ievt);// const;
- Double_t getOmegaGen(const Double_t eta);// const;
+ Double_t getOmegaGen(const Double_t eta, const Int_t curEvtTagFlv);// const;
Double_t getEtaGen(LauAbsPdf* hist) const;
+
+ //! Use the alternative tagging calibration parameters
+ void useAveOmegaDeltaOmega(){useAveOmegaDeltaOmega_ = kTRUE;}
+
+ //! Retun the Boolean controlling if we use the alternative tagging calibration parameters
+ Bool_t getUseAveOmegaDeltaOmega(){return useAveOmegaDeltaOmega_;}
+
protected:
//! Check the signal tagging category fractions
void checkSignalTagCatFractions();
//! Check that the background tagging category fractions are all present and sum to unity
/*!
\param [in] theMap the container of tagcat fractions
*/
Bool_t checkTagCatFracMap(const LauTagCatParamMap& theMap) const;
//! Calculates the fraction of the first tagging category based on the others
/*!
\param [in] theMap the container of tagcat fractions
*/
void setFirstTagCatFrac(LauTagCatParamMap& theMap);
private:
//! Whether or not to use untagged events
const Bool_t useUntaggedEvents_;
//! Signal tagging category fractions
LauTagCatParamMap signalTagCatFrac_;
//! Flavour tagging variable name
TString tagVarName_;
//! Tagging category variable name
TString tagCatVarName_;
//! Per event mistag variable name
TString mistagVarName_;
//! The allowed tagging categories
std::set<Int_t> validTagCats_;
//! Flavour tag for current event
Int_t curEvtTagFlv_;
//! Tagging category for current event
Int_t curEvtTagCat_;
//! Per event mistag for current event
Double_t curEvtMistag_;
//! Vector to store event flavour tags
std::vector<Int_t> evtTagFlvVals_;
//! Vector to store event tagging categories
std::vector<Int_t> evtTagCatVals_;
//! Vector to store event mistag values
std::vector<Double_t> evtMistagVals_;
//! Average dilutions
LauTagCatParamMap dilution_;
//! Dilution differences
LauTagCatParamMap deltaDilution_;
//! Use per event mistag
Bool_t usePerEvtMistag_;
//! Per-event average mistag value (eta hat)
//Double_t perEvtAvgMistag_;
std::map< Int_t, Double_t> perEvtAvgMistag_;
//! Calibration parameters
- //LauParameter* calib_p0_;
- //LauParameter* calib_p1_;
- LauTagCatParamMap calib_p0_;
- LauTagCatParamMap calib_p1_;
+ LauTagCatParamMap calib_p0_B0_;
+ LauTagCatParamMap calib_p0_B0bar_;
+ LauTagCatParamMap calib_p1_B0_;
+ LauTagCatParamMap calib_p1_B0bar_;
+
+ //! Alternative calibration parameters
+ LauTagCatParamMap calib_p0_ave_;
+ LauTagCatParamMap calib_p0_delta_;
+ LauTagCatParamMap calib_p1_ave_;
+ LauTagCatParamMap calib_p1_delta_;
+
+ //! Flag to use alternative calibration parameters
+ Bool_t useAveOmegaDeltaOmega_;
//! Tagging asymmetry parameters
LauTagCatParamMap tagAsym_;
//! Input parameters
std::vector<LauParameter*> params_;
ClassDef(LauFlavTag,0) // Flaour tagging set up
};
#endif
diff --git a/inc/LauTimeDepFitModel.hh b/inc/LauTimeDepFitModel.hh
index e42bdc3..20f9959 100644
--- a/inc/LauTimeDepFitModel.hh
+++ b/inc/LauTimeDepFitModel.hh
@@ -1,658 +1,658 @@
/*
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.hh
\brief File containing declaration of LauTimeDepFitModel class.
*/
/*! \class LauTimeDepFitModel
\brief Class for defining a time-dependent fit model.
LauTimeDepFitModel is a class that allows the user to define a three-body
Dalitz plot according to the isobar model, i.e. defining a set of
resonances that have complex amplitudes that can interfere with each other.
It extends the LauSimpleFitModel and LauCPFitModel models in that it allows
the fitting of time-dependent particle/antiparticle decays to
flavour-conjugate Dalitz plots, including their interference through mixing.
*/
#ifndef LAU_TIMEDEP_FIT_MODEL
#define LAU_TIMEDEP_FIT_MODEL
#include <vector>
#include <map>
#include <set>
#include <iostream>
#include "TString.h"
#include "TStopwatch.h"
#include "TSystem.h"
#include "LauAbsFitModel.hh"
#include "LauConstants.hh"
#include "LauEmbeddedData.hh"
#include "LauParameter.hh"
#include "LauFlavTag.hh"
class LauAbsBkgndDPModel;
class LauAbsCoeffSet;
class LauAbsPdf;
class LauDecayTimePdf;
class LauIsobarDynamics;
class LauKinematics;
class LauScfMap;
class LauTimeDepFitModel : public LauAbsFitModel {
public:
//! Possible CP eigenvalues (the intrinsic CP of the final state particles)
enum CPEigenvalue {
CPOdd = -1, /*!< CP odd final state */
CPEven = 1 /*!< CP even final state */
};
//! Constructor
/*!
\param [in] modelB0bar DP model for the antiparticle
\param [in] modelB0 DP model for the particle
\param [in] flavTag flavour tagging information
*/
LauTimeDepFitModel(LauIsobarDynamics* modelB0bar, LauIsobarDynamics* modelB0, LauFlavTag* flavTag);
//! Destructor
virtual ~LauTimeDepFitModel();
//! Set the signal event yield
/*!
\param [in] nSigEvents contains the signal yield and option to fix it
*/
virtual void setNSigEvents(LauParameter* nSigEvents);
//! Set the signal event yield and asymmetry
/*!
\param [in] nSigEvents contains the signal yield and option to fix it
\param [in] sigAsym contains the signal asymmetry and option to fix it
*/
virtual void setNSigEvents(LauParameter* nSigEvents, LauParameter* sigAsym);
//! Set the number of background events
/*!
The name of the parameter must be that of the corresponding background category (so that it can be correctly assigned)
\param [in] nBkgndEvents contains the name, yield and option to fix the yield of the background
*/
virtual void setNBkgndEvents(LauAbsRValue* nBkgndEvents);
//! Set the background event yield and asymmetry
/*!
\param [in] nBkgEvents contains the background yield and option to fix it
\param [in] BkgAsym contains the background asymmetry and option to fix it
*/
virtual void setNBkgndEvents(LauAbsRValue* nBkgndEvents, LauAbsRValue* bkgndAsym);
//! Switch on/off storage of amplitude info in generated ntuple
void storeGenAmpInfo(Bool_t storeInfo) { storeGenAmpInfo_ = storeInfo; }
//! Set CP eigenvalue
/*!
The CP eigenvalue can be supplied on an event-by-event
basis, e.g. if the data contains daughters that are D0
mesons that can decay to either K+ K- (CP even) or KS pi0
(CP odd).
This method allows you to set the default value that should
be used if the data does not contain this information as
well as the name of the variable in the data that will
specify this information.
If completely unspecified all events will be assumed to be
CP even.
\param defaultCPEV the default for the eigenvalue
\param evVarName the variable name in the data tree that specifies the CP eigenvalue
*/
inline void setCPEigenvalue( const CPEigenvalue defaultCPEV, const TString& cpevVarName = "" )
{
cpEigenValue_ = defaultCPEV;
cpevVarName_ = cpevVarName;
}
//! Set the DP amplitude coefficients
/*!
\param [in] coeffSet the set of coefficients
*/
void setAmpCoeffSet(LauAbsCoeffSet* coeffSet);
//! Set the decay time PDFs
/*!
\param [in] tagCat the tagging category for which the PDF should be used
\param [in] pdf the signal decay time PDF
*/
void setSignalDtPdf(const Int_t tagCat, LauDecayTimePdf* pdf);
//! Set the signal PDF for a given variable
/*!
\param [in] tagCat the tagging category for which the PDF should be used
\param [in] pdf the PDF to be added to the signal model
*/
void setSignalPdfs(const Int_t tagCat, LauAbsPdf* pdf);
void setSignalFlavTagPdfs( const Int_t tagCat, LauAbsPdf* pdf);
void setBkgdFlavTagPdfs( const TString name, LauAbsPdf* pdf);
//! Embed full simulation events for the signal, rather than generating toy from the PDFs
/*!
\param [in] tagCat the tagging category for which the file should be used
\param [in] fileName the name of the file containing the events
\param [in] treeName the name of the tree
\param [in] reuseEventsWithinEnsemble
\param [in] reuseEventsWithinExperiment
\param [in] useReweighting
*/
void embedSignal(const Int_t tagCat, const TString& fileName, const TString& treeName,
const Bool_t reuseEventsWithinEnsemble, const Bool_t reuseEventsWithinExperiment = kFALSE);
//! Set the value of the mixing phase
/*!
\param [in] phiMix the value of the mixing phase
\param [in] fixPhiMix whether the value should be fixed or floated
\param [in] useSinCos whether to use the sine and cosine as separate parameters or to just use the mixing phase itself
*/
void setPhiMix(const Double_t phiMix, const Bool_t fixPhiMix, const Bool_t useSinCos = kFALSE);
//! Initialise the fit
virtual void initialise();
//! Initialise the signal DP model
virtual void initialiseDPModels();
//! Recalculate Normalization the signal DP models
virtual void recalculateNormalisation();
//! Update the coefficients
virtual void updateCoeffs();
// Toy MC generation and fitting overloaded functions
virtual Bool_t genExpt();
//! Set the maximum value of A squared to be used in the accept/reject
/*!
\param [in] value the new value
*/
inline void setASqMaxValue(const Double_t value) {aSqMaxSet_ = value;}
//! Weight events based on the DP model
/*!
\param [in] dataFileName the name of the data file
\param [in] dataTreeName the name of the data tree
*/
virtual void weightEvents( const TString& dataFileName, const TString& dataTreeName );
//! Calculate things that depend on the fit parameters after they have been updated by Minuit
virtual void propagateParUpdates();
//! Read in the input fit data variables, e.g. m13Sq and m23Sq
virtual void cacheInputFitVars();
//! Check the initial fit parameters
virtual void checkInitFitParams();
//! Get the fit results and store them
/*!
\param [in] tablePrefixName prefix for the name of the output file
*/
virtual void finaliseFitResults(const TString& tablePrefixName);
//! Save the pdf Plots for all the resonances of experiment number fitExp
/*!
TODO - not working in this model!!
\param [in] label prefix for the file name to be saved
*/
virtual void savePDFPlots(const TString& label);
//! Save the pdf Plots for the sum of ressonances correspondint to "sin" of experiment number fitExp
/*!
TODO - not working in this model!!
\param [in] label prefix for the file name to be saved
\param [in] spin spin of the wave to be saved
*/
virtual void savePDFPlotsWave(const TString& label, const Int_t& spin);
//! Print the fit fractions, total DP rate and mean efficiency
/*!
\param [out] output the stream to which to print
*/
virtual void printFitFractions(std::ostream& output);
//! Print the asymmetries
/*!
\param [out] output the stream to which to print
*/
virtual void printAsymmetries(std::ostream& output);
//! Write the fit results in latex table format
/*!
\param [in] outputFile the name of the output file
*/
virtual void writeOutTable(const TString& outputFile);
//! Store the per event likelihood values
virtual void storePerEvtLlhds();
// Methods to do with calculating the likelihood functions
// and manipulating the fitting parameters.
//! Get the total likelihood for each event
/*!
\param [in] iEvt the event number
*/
virtual Double_t getTotEvtLikelihood(const UInt_t iEvt);
//! Calculate the signal and background likelihoods for the DP for a given event
/*!
\param [in] iEvt the event number
*/
virtual void getEvtDPDtLikelihood(const UInt_t iEvt);
//! Determine the signal and background likelihood for the extra variables for a given event
/*!
\param [in] iEvt the event number
*/
virtual void getEvtExtraLikelihoods(const UInt_t iEvt);
virtual void getEvtFlavTagLikelihood(const UInt_t iEvt);
//! Get the total number of events
/*!
\return the total number of events
*/
virtual Double_t getEventSum() const;
//! Set the fit parameters for the DP model
void setSignalDPParameters();
//! Set the fit parameters for the decay time PDFs
void setDecayTimeParameters();
//! Set the fit parameters for the extra PDFs
void setExtraPdfParameters();
//! Set the initial yields
void setFitNEvents();
//! Set the calibration parameters, if floating
void setCalibParams();
//! Set the efficiency parameters, if floating
void setEffiParams();
//! Set-up other parameters that are derived from the fit results, e.g. fit fractions
void setExtraNtupleVars();
//! Set production and detections asymmetries
void setProdDetAsymmetries(const Double_t AProd, const Bool_t AProdFix, const Double_t ADet, const Bool_t ADetFix);
//! Randomise the initial fit parameters
void randomiseInitFitPars();
//! Method to set up the storage for background-related quantities called by setBkgndClassNames
virtual void setupBkgndVectors();
//! Calculate the CP asymmetries
/*!
\param [in] initValues is this before or after the fit
*/
void calcAsymmetries(const Bool_t initValues = kFALSE);
//! Finalise value of mixing phase
void checkMixingPhase();
- //!
+ //! Return the map of signal decay time PDFs
typedef std::map< Int_t, LauDecayTimePdf*> LauTagCatDtPdfMap;
LauTagCatDtPdfMap& getSignalDecayTimePdfs(){return signalDecayTimePdfs_;}
protected:
typedef std::map< Int_t, LauParameter> LauTagCatParamMap;
typedef std::map< Int_t, LauPdfList > LauTagCatPdfListMap;
typedef std::map< Int_t, LauAbsPdf* > LauTagCatPdfMap;
typedef std::map< TString, LauAbsPdf* > LauBkgdPdfMap;
typedef std::map< Int_t, Int_t > LauTagCatEventsMap;
typedef std::map< Int_t, LauEmbeddedData* > LauTagCatEmbDataMap;
typedef std::map< Int_t, std::pair<Int_t,Double_t> > LauTagCatGenInfo;
typedef std::map< std::pair<TString,Int_t>, LauTagCatGenInfo > LauGenInfo;
typedef std::vector<LauTagCatEmbDataMap> LauTagCatEmbDataMapList;
typedef std::vector<LauAbsBkgndDPModel*> LauBkgndDPModelList;
typedef std::vector<LauPdfList> LauBkgndPdfsList;
typedef std::vector<LauAbsRValue*> LauBkgndYieldList;
typedef std::vector<Bool_t> LauBkgndReuseEventsList;
//! Determine the number of events to generate for each hypothesis
LauGenInfo eventsToGenerate();
//! Generate signal event
Bool_t generateSignalEvent();
//! Setup the required ntuple branches
void setupGenNtupleBranches();
//! Store all of the DP and decay time information
void setDPDtBranchValues();
//! Generate from the extra PDFs
/*!
\param [in] extraPdfs the list of extra PDFs
\param [in] embeddedData the embedded data sample
*/
void generateExtraPdfValues(LauPdfList* extraPdfs, LauEmbeddedData* embeddedData);
//! Add sPlot branches for the extra PDFs
/*!
\param [in] extraPdfs the list of extra PDFs
\param [in] prefix the list of prefixes for the branch names
*/
void addSPlotNtupleBranches(const LauPdfList* extraPdfs, const TString& prefix);
//! Set the branches for the sPlot ntuple with extra PDFs
/*!
\param [in] extraPdfs the list of extra PDFs
\param [in] prefix the list of prefixes for the branch names
\param [in] iEvt the event number
*/
Double_t setSPlotNtupleBranchValues(LauPdfList* extraPdfs, const TString& prefix, UInt_t iEvt);
//! Update the signal events after Minuit sets background parameters
void updateSigEvents();
//! Add branches to store experiment number and the event number within the experiment
virtual void setupSPlotNtupleBranches();
//! Returns the names of all variables in the fit
virtual LauSPlot::NameSet variableNames() const;
//! Returns the names and yields of species that are free in the fit
virtual LauSPlot::NumbMap freeSpeciesNames() const;
//! Returns the names and yields of species that are fixed in the fit
virtual LauSPlot::NumbMap fixdSpeciesNames() const;
//! Returns the species and variables for all 2D PDFs in the fit
virtual LauSPlot::TwoDMap twodimPDFs() const;
//! Check if the signal is split into well-reconstructed and mis-reconstructed types
virtual Bool_t splitSignal() const { return kFALSE; }
//! Check if the mis-reconstructed signal is to be smeared in the DP
virtual Bool_t scfDPSmear() const { return kFALSE; }
//! Add the parameters from each PDF into the fit
/*!
\param [in] theMap the container of PDFs
*/
UInt_t addParametersToFitList(LauTagCatPdfListMap& theMap);
//! Add the parameters from each decay time PDF into the fit
/*!
\param [in] theMap the container of PDFs
*/
UInt_t addParametersToFitList(LauTagCatDtPdfMap& theMap);
//! Calculate the component integrals of the interference term
void calcInterferenceTermIntegrals();
//! Calculate the total integral of the interference term
void calcInterTermNorm();
private:
//! Dalitz plot PDF for the antiparticle
LauIsobarDynamics* sigModelB0bar_;
//! Dalitz plot PDF for the particle
LauIsobarDynamics* sigModelB0_;
//! Kinematics object for antiparticle
LauKinematics* kinematicsB0bar_;
//! Kinematics object for particle
LauKinematics* kinematicsB0_;
//! The B0 background Dalitz plot models
LauBkgndDPModelList BkgndDPModelsB0_;
//! The B0-bar background Dalitz plot models
LauBkgndDPModelList BkgndDPModelsB0bar_;
//! The B0 background PDFs
LauBkgndPdfsList BkgndPdfsB0_;
//! The B0bar background PDFs
LauBkgndPdfsList BkgndPdfsB0bar_;
//! LauFlavTag object for flavour tagging
LauFlavTag* flavTag_;
//! Flavour tag for current event
Int_t curEvtTagFlv_;
//! Tagging category for current event
Int_t curEvtTagCat_;
//! Per event mistag for current event
Double_t curEvtMistag_;
//! Number of signal components
UInt_t nSigComp_;
//! Number of signal DP parameters
UInt_t nSigDPPar_;
//! Number of decay time PDF parameters
UInt_t nDecayTimePar_;
//! Number of extra PDF parameters
UInt_t nExtraPdfPar_;
//! Number of normalisation parameters (yields, asymmetries)
UInt_t nNormPar_;
//! Number of calibration parameters (p0, p1)
UInt_t nCalibPar_;
//! Number of efficiency parameters (p0, p1)
UInt_t nEffiPar_;
//! The complex coefficients for antiparticle
std::vector<LauComplex> coeffsB0bar_;
//! The complex coefficients for particle
std::vector<LauComplex> coeffsB0_;
//! Magnitudes and Phases or Real and Imaginary Parts
std::vector<LauAbsCoeffSet*> coeffPars_;
//! The integrals of the efficiency corrected amplitude cross terms for each pair of amplitude components
/*!
Calculated as the sum of A* x Abar x efficiency
*/
std::vector< std::vector<LauComplex> > fifjEffSum_;
//! The normalisation for the term 2.0*Re(A*Abar*phiMix)
Double_t interTermReNorm_;
//! The normalisation for the term 2.0*Im(A*Abar*phiMix)
Double_t interTermImNorm_;
//! The antiparticle fit fractions
LauParArray fitFracB0bar_;
//! The particle fit fractions
LauParArray fitFracB0_;
//! The fit fraction asymmetries
std::vector<LauParameter> fitFracAsymm_;
//! A_CP parameter
std::vector<LauParameter> acp_;
//! The mean efficiency for the antiparticle
LauParameter meanEffB0bar_;
//! The mean efficiency for the particle
LauParameter meanEffB0_;
//! The average DP rate for the antiparticle
LauParameter DPRateB0bar_;
//! The average DP rate for the particle
LauParameter DPRateB0_;
//! Signal yields
LauParameter* signalEvents_;
//! Signal asymmetry
LauParameter* signalAsym_;
//! Background yield(s)
LauBkgndYieldList bkgndEvents_;
//! Background asymmetries(s)
LauBkgndYieldList bkgndAsym_;
//! CP eigenvalue variable name
TString cpevVarName_;
//! CP eigenvalue for current event
CPEigenvalue cpEigenValue_;
//! Vector to store event CP eigenvalues
std::vector<CPEigenvalue> evtCPEigenVals_;
//! The mass difference between the neutral mass eigenstates
LauParameter deltaM_;
//! The width difference between the neutral mass eigenstates
LauParameter deltaGamma_;
//! The lifetime
LauParameter tau_;
//! The mixing phase
LauParameter phiMix_;
//! The sine of the mixing phase
LauParameter sinPhiMix_;
//! The cosine of the mixing phase
LauParameter cosPhiMix_;
//! Flag whether to use the sine and cosine of the mixing phase or the phase itself as the fit parameters
Bool_t useSinCos_;
//! e^{-i*phiMix}
LauComplex phiMixComplex_;
//! Decay time PDFs (one per tagging category)
LauTagCatDtPdfMap signalDecayTimePdfs_;
//! Decay time for the current event
Double_t curEvtDecayTime_;
//! Decay time error for the current event
Double_t curEvtDecayTimeErr_;
//! PDFs for other variables
LauTagCatPdfListMap sigExtraPdf_;
//! eta PDFs for each TagCat
LauTagCatPdfMap sigFlavTagPdf_;
//! eta PDFs for each background
LauBkgdPdfMap bkgdFlavTagPdf_;
//! Production asymmetry between B0 and B0bar
LauParameter AProd_;
//! Detection asymmetry between B0 and B0bar
LauParameter ADet_;
// Toy generation stuff
//! The maximum allowed number of attempts when generating an event
Int_t iterationsMax_;
//! The number of unsucessful attempts to generate an event so far
Int_t nGenLoop_;
//! The value of A squared for the current event
Double_t ASq_;
//! The maximum value of A squared that has been seen so far while generating
Double_t aSqMaxVar_;
//! The maximum allowed value of A squared
Double_t aSqMaxSet_;
//! Flag for storage of amplitude info in generated ntuple
Bool_t storeGenAmpInfo_;
//! The signal event tree for embedding fully simulated events
LauTagCatEmbDataMap signalTree_;
//! The background event tree for embedding fully simulated events
LauTagCatEmbDataMapList bkgndTree_;
//! Boolean to control reuse of embedded signal events
Bool_t reuseSignal_;
//! Vector of booleans to reuse background events
LauBkgndReuseEventsList reuseBkgnd_;
// Likelihood values
//! Signal DP likelihood value
Double_t sigDPLike_;
//! Signal likelihood from extra PDFs
Double_t sigExtraLike_;
Double_t sigFlavTagLike_;
Double_t bkgdFlavTagLike_;
//! Total signal likelihood
Double_t sigTotalLike_;
//! Background DP likelihood value(s)
std::vector<Double_t> bkgndDPLike_;
//! Background likelihood value(s) from extra PDFs
std::vector<Double_t> bkgndExtraLike_;
//! Total background likelihood(s)
std::vector<Double_t> bkgndTotalLike_;
ClassDef(LauTimeDepFitModel,0) // Time-dependent neutral model
};
#endif
diff --git a/src/LauDecayTimePdf.cc b/src/LauDecayTimePdf.cc
index 55b3059..e600a62 100644
--- a/src/LauDecayTimePdf.cc
+++ b/src/LauDecayTimePdf.cc
@@ -1,1035 +1,1032 @@
/*
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 LauDecayTimePdf.cc
\brief File containing implementation of LauDecayTimePdf class.
*/
#include <iostream>
#include <vector>
using std::cout;
using std::cerr;
using std::endl;
#include <complex>
using std::complex;
#include "TMath.h"
#include "TRandom.h"
#include "TSystem.h"
#include "Lau1DCubicSpline.hh"
#include "Lau1DHistPdf.hh"
#include "LauConstants.hh"
#include "LauComplex.hh"
#include "LauDecayTimePdf.hh"
#include "LauFitDataTree.hh"
#include "LauParameter.hh"
#include "LauRandom.hh"
ClassImp(LauDecayTimePdf)
LauDecayTimePdf::LauDecayTimePdf(const TString& theVarName, const TString& theVarErrName, const std::vector<LauAbsRValue*>& params,
Double_t minAbscissaVal, Double_t maxAbscissaVal,
Double_t minAbscissaErr, Double_t maxAbscissaErr,
FuncType type, UInt_t nGauss, const std::vector<Bool_t>& scale, TimeMeasurementMethod method) :
varName_(theVarName),
varErrName_(theVarErrName),
param_(params),
smear_(kTRUE),
minAbscissa_(minAbscissaVal),
maxAbscissa_(maxAbscissaVal),
minAbscissaError_(minAbscissaErr),
maxAbscissaError_(maxAbscissaErr),
abscissaError_(0.0),
abscissaErrorGenerated_(kFALSE),
errorDistMPV_(0.230), // for signal 0.234, for qqbar 0.286
errorDistSigma_(0.075), // for signal 0.073, for qqbar 0.102
nGauss_(nGauss),
mean_(nGauss_,0),
sigma_(nGauss_,0),
frac_(nGauss_-1,0),
tau_(0),
deltaM_(0),
deltaGamma_(0),
fracPrompt_(0),
type_(type),
method_(method),
scaleMeans_(scale),
scaleWidths_(scale),
expTerm_(0.0),
cosTerm_(0.0),
sinTerm_(0.0),
coshTerm_(0.0),
sinhTerm_(0.0),
normTermExp_(0.0),
normTermCosh_(0.0),
normTermSinh_(0.0),
errTerm_(0.0),
pdfTerm_(0.0),
effiTerm_(0.0),
state_(Good),
errHist_(0),
pdfHist_(0),
effiFun_(0),
effiPars_(0)
{
this->initialise();
// Calculate the integrals of the decay time independent of the t
this->storeIntegralTimeDep(minAbscissa_, maxAbscissa_);
}
LauDecayTimePdf::LauDecayTimePdf(const TString& theVarName, const TString& theVarErrName, const std::vector<LauAbsRValue*>& params,
Double_t minAbscissaVal, Double_t maxAbscissaVal,
Double_t minAbscissaErr, Double_t maxAbscissaErr,
FuncType type, UInt_t nGauss, const std::vector<Bool_t>& scaleMeans, const std::vector<Bool_t>& scaleWidths, TimeMeasurementMethod method) :
varName_(theVarName),
varErrName_(theVarErrName),
param_(params),
smear_(kTRUE),
minAbscissa_(minAbscissaVal),
maxAbscissa_(maxAbscissaVal),
minAbscissaError_(minAbscissaErr),
maxAbscissaError_(maxAbscissaErr),
abscissaError_(0.0),
abscissaErrorGenerated_(kFALSE),
errorDistMPV_(0.230), // for signal 0.234, for qqbar 0.286
errorDistSigma_(0.075), // for signal 0.073, for qqbar 0.102
nGauss_(nGauss),
mean_(nGauss_,0),
sigma_(nGauss_,0),
frac_(nGauss_-1,0),
tau_(0),
deltaM_(0),
deltaGamma_(0),
fracPrompt_(0),
type_(type),
method_(method),
scaleMeans_(scaleMeans),
scaleWidths_(scaleWidths),
expTerm_(0.0),
cosTerm_(0.0),
sinTerm_(0.0),
coshTerm_(0.0),
sinhTerm_(0.0),
normTermExp_(0.0),
normTermCosh_(0.0),
normTermSinh_(0.0),
errTerm_(0.0),
pdfTerm_(0.0),
effiTerm_(0.0),
- state_(Good),
+ state_(Good),
errHist_(0),
pdfHist_(0),
effiFun_(0),
effiPars_(0)
{
this->initialise();
// Calculate the integrals of the decay time independent of the t
this->storeIntegralTimeDep(minAbscissa_, maxAbscissa_);
}
LauDecayTimePdf::~LauDecayTimePdf()
{
// Destructor
delete errHist_; errHist_ = 0;
delete pdfHist_; pdfHist_ = 0;
delete effiFun_; effiFun_ = 0;
}
void LauDecayTimePdf::initialise()
{
// The parameters are:
// - the mean and the sigma (bias and spread in resolution) of the gaussian(s)
// - the mean lifetime, denoted tau, of the exponential decay
// - the frequency of oscillation, denoted Delta m, of the cosine and sine terms
// - the decay width difference, denoted Delta Gamma, of the hyperbolic cosine and sine terms
//
// The next two arguments specify the range in which the PDF is defined,
// and the PDF will be normalised w.r.t. these limits.
//
// The final three arguments define the type of Delta t PDF (Delta, Exp, ExpTrig or ExpHypTrig ), the number of gaussians
// and whether or not the gaussian parameters should be scaled by the per-event errors on Delta t
// First check whether the scale vector is nGauss in size
if (nGauss_ != scaleMeans_.size() || nGauss_ != scaleWidths_.size()) {
cerr<<"ERROR in LauDecayTimePdf::initialise : scale vector size not the same as nGauss."<<endl;
gSystem->Exit(EXIT_FAILURE);
}
if (type_ == Hist){
if (this->nParameters() != 0){
cerr<<"ERROR in LauDecayTimePdf::initialise : Hist PDF should have 0 parameters"<<endl;
gSystem->Exit(EXIT_FAILURE);
}
}else{
TString meanName("mean_");
TString sigmaName("sigma_");
TString fracName("frac_");
Bool_t foundParams(kTRUE);
for (UInt_t i(0); i<nGauss_; ++i) {
TString tempName(meanName); tempName += i;
TString tempName2(sigmaName); tempName2 += i;
TString tempName3(fracName); tempName3 += i;
mean_[i] = this->findParameter(tempName);
foundParams &= (mean_[i] != 0);
sigma_[i] = this->findParameter(tempName2);
foundParams &= (sigma_[i] != 0);
if (i!=0) {
frac_[i-1] = this->findParameter(tempName3);
foundParams &= (frac_[i-1] != 0);
}
}
if (type_ == Delta) {
if ((this->nParameters() != (3*nGauss_-1)) || (!foundParams)) {
cerr<<"ERROR in LauDecayTimePdf::initialise : Delta type PDF requires:"<<endl;
cerr<<" - 2 parameters per Gaussian (i): \"mean_i\" and \"sigma_i\""<<endl;
cerr<<" - nGauss-1 fractions: \"frac_i\", where i!=0"<<endl;
gSystem->Exit(EXIT_FAILURE);
}
} else if (type_ == Exp) {
tau_ = this->findParameter("tau");
foundParams &= (tau_ != 0);
if ((this->nParameters() != (3*nGauss_-1+1)) || (!foundParams)) {
cerr<<"ERROR in LauDecayTimePdf::initialise : Exp type PDF requires:"<<endl;
cerr<<" - 2 parameters per Gaussian (i): \"mean_i\" and \"sigma_i\""<<endl;
cerr<<" - nGauss-1 fractions: \"frac_i\", where i!=0"<<endl;
cerr<<" - the lifetime of the exponential decay: \"tau\"."<<endl;
gSystem->Exit(EXIT_FAILURE);
}
} else if (type_ == ExpTrig) {
tau_ = this->findParameter("tau");
deltaM_ = this->findParameter("deltaM");
foundParams &= (tau_ != 0);
foundParams &= (deltaM_ != 0);
if ((this->nParameters() != (3*nGauss_-1+2)) || (!foundParams)) {
cerr<<"ERROR in LauDecayTimePdf::initialise : ExpTrig type PDF requires:"<<endl;
cerr<<" - 2 parameters per Gaussian (i): \"mean_i\" and \"sigma_i\""<<endl;
cerr<<" - nGauss-1 fractions: \"frac_i\", where i!=0"<<endl;
cerr<<" - the lifetime of the exponential decay: \"tau\""<<endl;
cerr<<" - the oscillation frequency: \"deltaM\"."<<endl;
gSystem->Exit(EXIT_FAILURE);
}
} else if (type_ == ExpHypTrig) {
tau_ = this->findParameter("tau");
deltaM_ = this->findParameter("deltaM");
deltaGamma_ = this->findParameter("deltaGamma");
foundParams &= (tau_ != 0);
foundParams &= (deltaM_ != 0);
foundParams &= (deltaGamma_ != 0);
if ((this->nParameters() != (3*nGauss_-1+3)) || (!foundParams)) {
cerr<<"ERROR in LauDecayTimePdf::initialise : ExpHypTrig type PDF requires:"<<endl;
cerr<<" - 2 parameters per Gaussian (i): \"mean_i\" and \"sigma_i\""<<endl;
cerr<<" - nGauss-1 fractions: \"frac_i\", where i!=0"<<endl;
cerr<<" - the lifetime of the exponential decay: \"tau\""<<endl;
cerr<<" - the oscillation frequency: \"deltaM\"."<<endl;
cerr<<" - the width difference: \"deltaGamma\"."<<endl;
gSystem->Exit(EXIT_FAILURE);
}
} else if (type_ == DeltaExp) {
tau_ = this->findParameter("tau");
fracPrompt_ = this->findParameter("frac_prompt");
foundParams &= (tau_ != 0);
foundParams &= (fracPrompt_ != 0);
if ((this->nParameters() != (3*nGauss_-1+2)) || (!foundParams)) {
cerr<<"ERROR in LauDecayTimePdf::initialise : DeltaExp type PDF requires:"<<endl;
cerr<<" - 2 parameters per Gaussian (i): \"mean_i\" and \"sigma_i\""<<endl;
cerr<<" - nGauss-1 fractions: \"frac_i\", where i!=0"<<endl;
cerr<<" - the lifetime of the exponential decay: \"tau\""<<endl;
cerr<<" - the fraction of the prompt part: \"frac_prompt\"."<<endl;
gSystem->Exit(EXIT_FAILURE);
}
}
}
// Cache the normalisation factor
//this->calcNorm();
}
void LauDecayTimePdf::cacheInfo(const LauFitDataTree& inputData)
{
Bool_t hasBranch = inputData.haveBranch(this->varName());
if (!hasBranch) {
cerr<<"ERROR in LauDecayTimePdf::cacheInfo : Input data does not contain variable \""<<this->varName()<<"\"."<<endl;
return;
}
hasBranch = inputData.haveBranch(this->varErrName());
if (!hasBranch) {
cerr<<"ERROR in LauDecayTimePdf::cacheInfo : Input data does not contain variable \""<<this->varErrName()<<"\"."<<endl;
return;
}
// Pass the data to the decay-time error PDF for caching
if ( errHist_ ) {
errHist_->cacheInfo(inputData);
}
if (type_ == Hist){
// Pass the data to the decay-time PDF for caching
if ( pdfHist_ ) {
pdfHist_->cacheInfo(inputData);
}
}else{
- // determine whether we are caching our PDF value
- //TODO
- //Bool_t doCaching( this->nFixedParameters() == this->nParameters() );
- //this->cachePDF( doCaching );
-
- // clear the vectors and reserve enough space
- const UInt_t nEvents = inputData.nEvents();
- abscissas_.clear(); abscissas_.reserve(nEvents);
- abscissaErrors_.clear(); abscissaErrors_.reserve(nEvents);
- expTerms_.clear(); expTerms_.reserve(nEvents);
- cosTerms_.clear(); cosTerms_.reserve(nEvents);
- sinTerms_.clear(); sinTerms_.reserve(nEvents);
- coshTerms_.clear(); coshTerms_.reserve(nEvents);
- sinhTerms_.clear(); sinhTerms_.reserve(nEvents);
- normTermsExp_.clear(); normTermsExp_.reserve(nEvents);
- normTermsCosh_.clear(); normTermsCosh_.reserve(nEvents);
- normTermsSinh_.clear(); normTermsSinh_.reserve(nEvents);
- effiTerms_.clear(); effiTerms_.reserve(nEvents);
-
- for (UInt_t iEvt = 0; iEvt < nEvents; iEvt++) {
-
- const LauFitData& dataValues = inputData.getData(iEvt);
-
- LauFitData::const_iterator iter = dataValues.find(this->varName());
- const Double_t abscissa = iter->second;
-
- if (abscissa > this->maxAbscissa() || abscissa < this->minAbscissa()) {
- cerr<<"ERROR in LauDecayTimePdf::cacheInfo : Given value of the decay time: "<<abscissa<<
- " outside allowed range: ["<<this->minAbscissa()<<","<<this->maxAbscissa()<<"]."<<endl;
- gSystem->Exit(EXIT_FAILURE);
- }
+ // determine whether we are caching our PDF value
+ //TODO
+ //Bool_t doCaching( this->nFixedParameters() == this->nParameters() );
+ //this->cachePDF( doCaching );
+
+ // clear the vectors and reserve enough space
+ const UInt_t nEvents = inputData.nEvents();
+ abscissas_.clear(); abscissas_.reserve(nEvents);
+ abscissaErrors_.clear(); abscissaErrors_.reserve(nEvents);
+ expTerms_.clear(); expTerms_.reserve(nEvents);
+ cosTerms_.clear(); cosTerms_.reserve(nEvents);
+ sinTerms_.clear(); sinTerms_.reserve(nEvents);
+ coshTerms_.clear(); coshTerms_.reserve(nEvents);
+ sinhTerms_.clear(); sinhTerms_.reserve(nEvents);
+ normTermsExp_.clear(); normTermsExp_.reserve(nEvents);
+ normTermsCosh_.clear(); normTermsCosh_.reserve(nEvents);
+ normTermsSinh_.clear(); normTermsSinh_.reserve(nEvents);
+ effiTerms_.clear(); effiTerms_.reserve(nEvents);
+
+ for (UInt_t iEvt = 0; iEvt < nEvents; iEvt++) {
+
+ const LauFitData& dataValues = inputData.getData(iEvt);
+
+ LauFitData::const_iterator iter = dataValues.find(this->varName());
+ const Double_t abscissa = iter->second;
+
+ if (abscissa > this->maxAbscissa() || abscissa < this->minAbscissa()) {
+ cerr<<"ERROR in LauDecayTimePdf::cacheInfo : Given value of the decay time: "<<abscissa<<
+ " outside allowed range: ["<<this->minAbscissa()<<","<<this->maxAbscissa()<<"]."<<endl;
+ gSystem->Exit(EXIT_FAILURE);
+ }
- abscissas_.push_back( abscissa );
+ abscissas_.push_back( abscissa );
- iter = dataValues.find(this->varErrName());
- Double_t abscissaErr = iter->second;
+ iter = dataValues.find(this->varErrName());
+ Double_t abscissaErr = iter->second;
- if (abscissaErr > this->maxAbscissaError() || abscissaErr < this->minAbscissaError()) {
- cerr<<"ERROR in LauDecayTimePdf::cacheInfo : Given value of the decay-time error: "<<abscissaErr<<
- " outside allowed range: ["<<this->minAbscissaError()<<","<<this->maxAbscissaError()<<"]."<<endl;
- gSystem->Exit(EXIT_FAILURE);
- }
-
- abscissaErrors_.push_back(abscissaErr);
+ if (abscissaErr > this->maxAbscissaError() || abscissaErr < this->minAbscissaError()) {
+ cerr<<"ERROR in LauDecayTimePdf::cacheInfo : Given value of the decay-time error: "<<abscissaErr<<
+ " outside allowed range: ["<<this->minAbscissaError()<<","<<this->maxAbscissaError()<<"]."<<endl;
+ gSystem->Exit(EXIT_FAILURE);
+ }
- this->calcLikelihoodInfo(abscissa, abscissaErr);
- expTerms_.push_back(expTerm_);
- cosTerms_.push_back(cosTerm_);
- sinTerms_.push_back(sinTerm_);
- coshTerms_.push_back(coshTerm_);
- sinhTerms_.push_back(sinhTerm_);
- normTermsExp_.push_back(normTermExp_);
- normTermsCosh_.push_back(normTermCosh_);
- normTermsSinh_.push_back(normTermSinh_);
-
- if(effiFun_) effiTerms_.push_back(effiFun_->evaluate(abscissa));
- else effiTerms_.push_back(1.0);
- }
+ abscissaErrors_.push_back(abscissaErr);
+
+ this->calcLikelihoodInfo(abscissa, abscissaErr);
+ expTerms_.push_back(expTerm_);
+ cosTerms_.push_back(cosTerm_);
+ sinTerms_.push_back(sinTerm_);
+ coshTerms_.push_back(coshTerm_);
+ sinhTerms_.push_back(sinhTerm_);
+ normTermsExp_.push_back(normTermExp_);
+ normTermsCosh_.push_back(normTermCosh_);
+ normTermsSinh_.push_back(normTermSinh_);
+
+ if(effiFun_) effiTerms_.push_back(effiFun_->evaluate(abscissa));
+ else effiTerms_.push_back(1.0);
+ }
}
}
void LauDecayTimePdf::calcLikelihoodInfo(UInt_t iEvt)
{
if (type_ == Hist){
if ( pdfHist_ ) {
pdfHist_->calcLikelihoodInfo(iEvt);
pdfTerm_ = pdfHist_->getLikelihood();
} else {
pdfTerm_ = 1.0;
}
}else{
expTerm_ = expTerms_[iEvt];
cosTerm_ = cosTerms_[iEvt];
sinTerm_ = sinTerms_[iEvt];
coshTerm_ = coshTerms_[iEvt];
sinhTerm_ = sinhTerms_[iEvt];
normTermExp_ = normTermsExp_[iEvt];
normTermCosh_ = normTermsCosh_[iEvt];
normTermSinh_ = normTermsSinh_[iEvt];
}
if ( errHist_ ) {
errHist_->calcLikelihoodInfo(iEvt);
errTerm_ = errHist_->getLikelihood();
} else {
errTerm_ = 1.0;
}
const Double_t abscissa = abscissas_[iEvt];
- if ( effiFun_ ) {
+ if ( effiFun_ ) {
this->updateEffiSpline(effiPars_);
- effiTerm_ = effiFun_->evaluate(abscissa);
+ effiTerm_ = effiFun_->evaluate(abscissa);
if (effiTerm_>1.0){effiTerm_=1.0;}
if (effiTerm_<0.0){effiTerm_=0.0;}
- } else {
- effiTerm_ = 1.0;
- }
+ } else {
+ effiTerm_ = 1.0;
+ }
// TODO need a check in here that none of the floating parameter values have changed
// If they have, then we need to recalculate all or some of the terms
/*
if ( parsChanged ) {
const Double_t abscissa = abscissas_[iEvt][0];
const Double_t abscissaErr = abscissaErrors_[iEvt];
this->calcLikelihoodInfo(abscissa, abscissaErr);
}
*/
}
void LauDecayTimePdf::calcLikelihoodInfo(Double_t abscissa)
{
// Check whether any of the gaussians should be scaled - if any of them should we need the per-event error
Bool_t scale(kFALSE);
for (std::vector<Bool_t>::const_iterator iter = scaleMeans_.begin(); iter != scaleMeans_.end(); ++iter) {
scale |= (*iter);
}
for (std::vector<Bool_t>::const_iterator iter = scaleWidths_.begin(); iter != scaleWidths_.end(); ++iter) {
scale |= (*iter);
}
if (scale) {
cerr<<"ERROR in LauDecayTimePdf::calcLikelihoodInfo : Per-event error on Delta t not provided, cannot calculate anything."<<endl;
return;
} else {
this->calcLikelihoodInfo(abscissa, 0.0);
}
}
void LauDecayTimePdf::calcLikelihoodInfo(Double_t abscissa, Double_t abscissaErr)
{
if (abscissa > this->maxAbscissa() || abscissa < this->minAbscissa()) {
cerr<<"ERROR in LauDecayTimePdf::calcLikelihoodInfo : Given value of the decay time: "<<abscissa<<
" outside allowed range: ["<<this->minAbscissa()<<","<<this->maxAbscissa()<<"]."<<endl;
gSystem->Exit(EXIT_FAILURE);
}
if (abscissaErr > this->maxAbscissaError() || abscissaErr < this->minAbscissaError()) {
cerr<<"ERROR in LauDecayTimePdf::calcLikelihoodInfo : Given value of Delta t error: "<<abscissaErr<<
" outside allowed range: ["<<this->minAbscissaError()<<","<<this->maxAbscissaError()<<"]."<<endl;
gSystem->Exit(EXIT_FAILURE);
}
// Initialise the various terms to zero
if (type_ == Hist){
if ( pdfHist_ ) {
pdfHist_->calcLikelihoodInfo(abscissa);
pdfTerm_ = pdfHist_->getLikelihood();
} else {
pdfTerm_ = 1.0;
}
}else{
// Reset the state to Good
this->state(Good);
// If we're not using the resolution function calculate the simple terms and return
if (!this->doSmearing()) {
this->calcNonSmearedTerms(abscissa);
return;
}
// Get all the up to date parameter values
std::vector<Double_t> frac(nGauss_);
std::vector<Double_t> mean(nGauss_);
std::vector<Double_t> sigma(nGauss_);
Double_t tau(0.0);
Double_t deltaM(0.0);
Double_t fracPrompt(0.0);
Double_t Delta_gamma(0.0);
frac[0] = 1.0;
for (UInt_t i(0); i<nGauss_; ++i) {
mean[i] = mean_[i]->value();
sigma[i] = sigma_[i]->value();
if (i != 0) {
frac[i] = frac_[i-1]->value();
frac[0] -= frac[i];
}
}
if (type_ != Delta) {
tau = tau_->value();
if (type_ == ExpTrig) {
deltaM = deltaM_->value();
}
if (type_ == DeltaExp) {
fracPrompt = fracPrompt_->value();
}
if (type_ == ExpHypTrig){
Delta_gamma = deltaGamma_->value();
}
}
// Scale the gaussian parameters by the per-event error on Delta t (if appropriate)
for (UInt_t i(0); i<nGauss_; ++i) {
if (scaleMeans_[i]) {
mean[i] *= abscissaErr;
}
if (scaleWidths_[i]) {
sigma[i] *= abscissaErr;
}
}
// Calculate term needed by every type
std::vector<Double_t> x(nGauss_);
const Double_t xMax = this->maxAbscissa();
const Double_t xMin = this->minAbscissa();
for (UInt_t i(0); i<nGauss_; ++i) {
x[i] = abscissa - mean[i];
}
// TODO, what to do with this
Double_t value(0.0);
if (type_ == Delta || type_ == DeltaExp) {
// Calculate the gaussian function(s)
for (UInt_t i(0); i<nGauss_; ++i) {
if (TMath::Abs(sigma[i]) > 1e-10) {
Double_t exponent(0.0);
Double_t norm(0.0);
Double_t scale = LauConstants::root2*sigma[i];
Double_t scale2 = LauConstants::rootPiBy2*sigma[i];
exponent = -0.5*x[i]*x[i]/(sigma[i]*sigma[i]);
norm = scale2*(TMath::Erf((xMax - mean[i])/scale)
- TMath::Erf((xMin - mean[i])/scale));
value += frac[i]*TMath::Exp(exponent)/norm;
}
}
}
if (type_ != Delta) {
std::vector<Double_t> expTerms(nGauss_);
std::vector<Double_t> cosTerms(nGauss_);
std::vector<Double_t> sinTerms(nGauss_);
std::vector<Double_t> coshTerms(nGauss_);
std::vector<Double_t> sinhTerms(nGauss_);
std::vector<Double_t> expTermsNorm(nGauss_);
// TODO - TEL changed this name to make it compile - please check!
std::vector<Double_t> SinhTermsNorm(nGauss_);
// Calculate values of the PDF convoluated with each Gaussian for a given value of the abscsissa
for (UInt_t i(0); i<nGauss_; ++i) {
// Typical case (1): B0/B0bar
if (type_ == ExpTrig) {
// LHCb convention, i.e. convolution evaluate between 0 and inf
if (method_ == DecayTime) {
// Exponential term
Double_t termExponent = (pow(sigma[i], 2) - 2.0 * tau * x[i])/(2.0 * pow(tau, 2));
Double_t termErfc = (pow(sigma[i], 2) - tau * x[i])/(LauConstants::root2 * tau * sigma[i]);
expTerms[i] = (1.0/2.0) * TMath::Exp(termExponent) * TMath::Erfc(termErfc);
Double_t exponentTermRe, exponentTermIm;
this->calcTrigExponent(deltaM, tau, x[i], sigma[i], exponentTermRe, exponentTermIm);
// Elements related to the trigonometric function, i.e. convolution of Exp*Sin or Cos with Gauss
Double_t sinTrigTermRe, sinTrigTermIm, cosTrigTermRe, cosTrigTermIm;
this->calcTrigConv(deltaM, tau, x[i], sigma[i], sinTrigTermRe, sinTrigTermIm, kFALSE);
this->calcTrigConv(deltaM, tau, x[i], sigma[i], cosTrigTermRe, cosTrigTermIm, kTRUE);
// Combining elements of the full pdf
LauComplex zExp(exponentTermRe, exponentTermIm);
LauComplex zTrigSin(sinTrigTermRe, sinTrigTermIm);
LauComplex zTrigCos(cosTrigTermRe, cosTrigTermIm);
LauComplex sinConv = zExp * zTrigSin;
LauComplex cosConv = zExp * zTrigCos;
sinConv.scale(1.0/4.0);
cosConv.scale(1.0/4.0);
// Cosine*Exp and Sine*Exp terms
cosTerms[i] = cosConv.re();
sinTerms[i] = sinConv.im();
// Normalisation
Double_t umax = xMax - mean[i];
Double_t umin = xMin - mean[i];
expTermsNorm[i] = (1.0/2.0) * tau * (-1.0 + TMath::Erf(umax/(LauConstants::root2 * sigma[i])) + TMath::Erfc(umin/(LauConstants::root2 * sigma[i])) +
TMath::Exp((pow(sigma[i], 2) - 2.0 * tau * (xMax + xMin - mean[i]))/(2.0 * pow(tau, 2))) *
(TMath::Exp(xMax/tau) * TMath::Erfc((pow(sigma[i], 2) - xMin)/(LauConstants::root2 * tau))) +
(TMath::Exp(xMin/tau) * TMath::Erfc((pow(sigma[i], 2) - xMax)/(LauConstants::root2 * tau))));
} else {
}
}
// Typical case (2): B0s/B0sbar
if (type_ == ExpHypTrig) {
// LHCb convention
if (method_ == DecayTime) {
// Convolution of Exp*cosh (Exp*sinh) with a gaussian
//Double_t OverallExpFactor = 0.25*TMath::Exp(-(x[i]-mean[i])*(x[i]-mean[i])/(2*sigma[i]*sigma[i]));
//Double_t ExpFirstTerm = TMath::Exp((2*(x[i]-mean[i])*tau+sigma[i]*sigma[i]*(-2+Delta_gamma*tau))*(2*(x[i]-mean[i])*tau+sigma[i]*sigma[i]*(-2+Delta_gamma*tau))/(8*sigma[i]*sigma[i]*tau*tau));
//Double_t ExpSecondTerm = TMath::Exp((2*(-x[i]+mean[i])*tau+sigma[i]*sigma[i]*(2+Delta_gamma*tau))*(2*(-x[i]+mean[i])*tau+sigma[i]*sigma[i]*(2+Delta_gamma*tau))/(8*sigma[i]*sigma[i]*tau*tau));
//Double_t ErfFirstTerm = TMath::Erf((2*(x[i]-mean[i])*tau+sigma[i]*sigma[i]*(-2+Delta_gamma*tau))/(2*TMath::Sqrt(2)*sigma[i]*tau));
//Double_t ErfSecondTerm = TMath::Erf((2*(-x[i]+mean[i])*tau+sigma[i]*sigma[i]*(2+Delta_gamma*tau))/(2*TMath::Sqrt(2)*sigma[i]*tau));
//Double_t sinhConv = OverallExpFactor*(ExpFirstTerm*(1+ErfFirstTerm) + ExpSecondTerm*(-1+ErfSecondTerm));
//Double_t coshConv = OverallExpFactor*(ExpFirstTerm*(1+ErfFirstTerm) - ExpSecondTerm*(-1+ErfSecondTerm));
//cosTerms[i] = sinhConv;
// sinTerms[i] = coshConv;
//TODO: check this formula and try to simplify it!
double OverallExpTerm_max = (1/(2*(-4 + Delta_gamma*Delta_gamma*tau*tau)))*tau*TMath::Exp(-0.5*Delta_gamma*(xMax + mean[i]) - xMax/tau);
double ErfTerm_max = -2*Delta_gamma*tau*TMath::Exp(0.5*Delta_gamma*(xMax+mean[i])+xMax/tau)*TMath::Erf((xMax-mean[i])/(TMath::Sqrt(2)*sigma[i]));
double ExpFirstTerm_max = TMath::Exp(xMax*Delta_gamma+(sigma[i]*sigma[i]*(-2 + Delta_gamma*tau)*(-2 + Delta_gamma*tau))/(8*tau*tau));
double ErfcFirstTerm_max = TMath::Erfc((2*(-xMax + mean[i])*tau + sigma[i]*sigma[i]*(2 - Delta_gamma*tau))/(2*TMath::Sqrt(2)*sigma[i]*tau));
double ExpSecondTerm_max = TMath::Exp(Delta_gamma*mean[i] + (sigma[i]*sigma[i]*(2 + Delta_gamma*tau)*(2 + Delta_gamma*tau))/(8*tau*tau));
double ErfcSecondTerm_max = TMath::Erfc((2*(-xMax + mean[i])*tau + sigma[i]*sigma[i]*(2 + Delta_gamma*tau))/(2*TMath::Sqrt(2)*sigma[i]*tau));
double MaxVal= OverallExpTerm_max*(ErfTerm_max + TMath::Exp(mean[i]/tau)*(ExpFirstTerm_max*(2+Delta_gamma*tau)* ErfcFirstTerm_max + ExpSecondTerm_max*(-2+Delta_gamma*tau)* ErfcSecondTerm_max));
double OverallExpTerm_min = (1/(2*(-4 + Delta_gamma*Delta_gamma*tau*tau)))*tau*TMath::Exp(-0.5*Delta_gamma*(xMin + mean[i]) - xMin/tau);
double ErfTerm_min = -2*Delta_gamma*tau*TMath::Exp(0.5*Delta_gamma*(xMin+mean[i])+xMin/tau)*TMath::Erf((xMin-mean[i])/(TMath::Sqrt(2)*sigma[i]));
double ExpFirstTerm_min = TMath::Exp(xMin*Delta_gamma+(sigma[i]*sigma[i]*(-2 + Delta_gamma*tau)*(-2 + Delta_gamma*tau))/(8*tau*tau));
double ErfcFirstTerm_min = TMath::Erfc((2*(-xMin + mean[i])*tau + sigma[i]*sigma[i]*(2 - Delta_gamma*tau))/(2*TMath::Sqrt(2)*sigma[i]*tau));
// TODO - TEL added this (currently identical to ExpSecondTerm_max) to get this to compile - please check!!
double ExpSecondTerm_min = TMath::Exp(Delta_gamma*mean[i] + (sigma[i]*sigma[i]*(2 + Delta_gamma*tau)*(2 + Delta_gamma*tau))/(8*tau*tau));
double ErfcSecondTerm_min = TMath::Erfc((2*(-xMin + mean[i])*tau + sigma[i]*sigma[i]*(2 + Delta_gamma*tau))/(2*TMath::Sqrt(2)*sigma[i]*tau));
double minVal= OverallExpTerm_min*(ErfTerm_min + TMath::Exp(mean[i]/tau)*(ExpFirstTerm_min*(2+Delta_gamma*tau)* ErfcFirstTerm_min + ExpSecondTerm_min*(-2+Delta_gamma*tau)* ErfcSecondTerm_min));
SinhTermsNorm[i] = MaxVal - minVal;
} else {
}
}
}
for (UInt_t i(0); i<nGauss_; ++i) {
expTerm_ += frac[i]*expTerms[i];
cosTerm_ += frac[i]*cosTerms[i];
sinTerm_ += frac[i]*sinTerms[i];
coshTerm_ += frac[i]*coshTerms[i];
sinhTerm_ += frac[i]*sinhTerms[i];
normTermExp_ += frac[i]*expTermsNorm[i];
//normTermSinh_ += frac[i]*SinhTermsNorm[i];
}
if (type_ == DeltaExp) {
value *= fracPrompt;
value += (1.0-fracPrompt)*expTerm_;
} else {
value = expTerm_;
}
}
}
if ( errHist_ ) {
errHist_->calcLikelihoodInfo(abscissaErr);
errTerm_ = errHist_->getLikelihood();
} else {
errTerm_ = 1.0;
}
- if ( effiFun_ ) {
+ if ( effiFun_ ) {
this->updateEffiSpline(effiPars_);
- effiTerm_ = effiFun_->evaluate(abscissa);
+ effiTerm_ = effiFun_->evaluate(abscissa);
if (effiTerm_>1.0){effiTerm_=1.0;}
if (effiTerm_<0.0){effiTerm_=0.0;}
- } else {
- effiTerm_ = 1.0;
- }
+ } else {
+ effiTerm_ = 1.0;
+ }
}
void LauDecayTimePdf::calcTrigExponent(Double_t deltaM, Double_t tau, Double_t x, Double_t sigma, Double_t& reTerm, Double_t& imTerm)
{
Double_t exponentTerm = TMath::Exp(-(2.0 * tau * x + pow(sigma, 2) * (pow(deltaM, 2) * pow(tau, 2) - 1.0))/(2.0 * pow(tau,2)));
reTerm = exponentTerm * TMath::Cos(deltaM * (x - pow(sigma,2)/tau));
imTerm = - exponentTerm * TMath::Sin(deltaM * (x - pow(sigma,2)/tau));
}
void LauDecayTimePdf::calcTrigConv(Double_t deltaM, Double_t tau, Double_t x, Double_t sigma, Double_t& reOutTerm, Double_t& imOutTerm, Bool_t trig)
{
Double_t reExpTerm, imExpTerm;
LauComplex zExp;
LauComplex zTrig1;
LauComplex zTrig2;
// Calculation for the sine or cosine term
if (!trig) {
reExpTerm = TMath::Sin(2.0 * deltaM * (x + pow(sigma,2)/tau));
imExpTerm = 2.0 * TMath::Sin(pow(deltaM * (x + pow(sigma,2)/tau), 2));
} else {
reExpTerm = TMath::Cos(2.0 * deltaM * (x + pow(sigma,2)/tau));
imExpTerm = TMath::Sin(2.0 * deltaM * (x + pow(sigma,2)/tau));
}
// Exponential term in front of Erfc/Erfi terms
zExp.setRealPart(reExpTerm);
zExp.setImagPart(imExpTerm);
// Nominal Erfc term (common to both sine and cosine expressions
zTrig1.setRealPart(-(tau * x - pow(sigma,2))/(LauConstants::root2 * tau * sigma));
zTrig1.setImagPart(-(deltaM * sigma)/ LauConstants::root2);
// Second term for sine (Erfi) or cosine (Erfc) - notice the re-im swap and sign change
zTrig2.setRealPart(-zTrig1.im());
zTrig2.setImagPart(-zTrig1.re());
// Calculation of Erfc and Erfi (if necessary)
LauComplex term1 = ComplexErfc(zTrig1.re(), zTrig1.im());
LauComplex term2;
if (!trig) {
term2 = Erfi(zTrig2.re(), zTrig2.im());
} else {
term2 = ComplexErfc(zTrig2.re(), zTrig2.im());
}
// Multiplying all elemnets of the convolution
LauComplex output = zExp * term1 + term2;
reOutTerm = output.re();
imOutTerm = output.im();
}
LauComplex LauDecayTimePdf::ComplexErf(Double_t x, Double_t y)
{
// Evaluate Erf(x + iy) using an infinite series approximation
// From Abramowitz & Stegun (http://people.math.sfu.ca/~cbm/aands/page_299.htm)
if (x==0){
// cout << "WARNING: Set x value to 1e-100 to avoid division by 0." << endl;
x = 1e-100;
}
int n = 20; // this cotrols the number of iterations of the sum
LauComplex ErfTerm(TMath::Erf(x),0.);
LauComplex CosSineTerm(1-cos(2*x*y), sin(2*x*y));
CosSineTerm.rescale(TMath::Exp(-x*x)/(2*TMath::Pi()*x));
LauComplex firstPart = ErfTerm + CosSineTerm;
LauComplex SumTerm(0,0);
for (int k = 1; k<=n; k++){
Double_t f_k = 2*x*(1 - cos(2*x*y)*cosh(k*y)) + k*sin(2*x*y)*sinh(k*y);
Double_t g_k = 2*x*sin(2*x*y)*cosh(k*y) + k*cos(2*x*y)*sinh(k*y);
LauComplex fgTerm(f_k, g_k);
fgTerm.rescale(TMath::Exp(-0.25*k*k)/(k*k + 4*x*x));
SumTerm += fgTerm;
}
SumTerm.rescale((2/TMath::Pi())*TMath::Exp(-x*x));
LauComplex result = firstPart + SumTerm;
return result;
}
LauComplex LauDecayTimePdf::Erfi(Double_t x, Double_t y)
{
// Erfi(z) = -I*Erf(I*z) where z = x + iy
double x_prime = -y;
double y_prime = x;
LauComplex a = ComplexErf(x_prime, y_prime);
LauComplex result(a.im(), -a.re());
return result;
}
LauComplex LauDecayTimePdf::ComplexErfc(Double_t x, Double_t y)
{
// Erfc(z) = 1 - Erf(z) (z = x + iy)
LauComplex one(1., 0.);
LauComplex result = one - ComplexErf(x,y);
return result;
}
void LauDecayTimePdf::calcNonSmearedTerms(Double_t abscissa)
{
if (type_ == Hist ){
cerr << "It is a histogrammed PDF" << endl;
return;
}
if (type_ == Delta) {
return;
}
Double_t tau = tau_->value();
// Calculate the terms related to cosine and sine not normalised
if (type_ == ExpTrig) {
Double_t deltaM = deltaM_->value();
if (method_ == DecayTime) {
expTerm_ = TMath::Exp(-abscissa/tau)/(2.0*tau);
}
if (method_ == DecayTimeDiff) {
expTerm_ = TMath::Exp(-TMath::Abs(abscissa)/tau)/(2.0*tau);
}
cosTerm_ = TMath::Cos(deltaM*abscissa)*expTerm_;
sinTerm_ = TMath::Sin(deltaM*abscissa)*expTerm_;
coshTerm_ = expTerm_;
sinhTerm_ = 0.0;
}
// Calculate the terms related to cosine, sine, cosh and sinh not normalised (no decayTimeDiff implemented
if (type_ == ExpHypTrig) {
Double_t deltaM = deltaM_->value();
Double_t deltaGamma = deltaGamma_->value();
expTerm_ = TMath::Exp(-abscissa/tau)/(2.0*tau);
cosTerm_ = TMath::Cos(deltaM*abscissa)*expTerm_;
sinTerm_ = TMath::Sin(deltaM*abscissa)*expTerm_;
coshTerm_ = TMath::CosH(deltaGamma*abscissa/2.0)*expTerm_;
sinhTerm_ = TMath::SinH(deltaGamma*abscissa/2.0)*expTerm_;
}
- if ( effiFun_ ) {
+ if ( effiFun_ ) {
this->updateEffiSpline(effiPars_);
- effiTerm_ = effiFun_->evaluate(abscissa);
+ effiTerm_ = effiFun_->evaluate(abscissa);
if (effiTerm_>1.0){effiTerm_=1.0;}
if (effiTerm_<0.0){effiTerm_=0.0;}
- } else {
- effiTerm_ = 1.0;
- }
+ } else {
+ effiTerm_ = 1.0;
+ }
}
Double_t LauDecayTimePdf::normExpHypTerm(Double_t Abs)
{
Double_t tau = tau_->value();
Double_t deltaGamma = deltaGamma_->value();
Double_t y = tau*deltaGamma/2;
Double_t nonTrigTerm = -(TMath::Exp(-Abs/tau))/(1 - y*y);
Double_t cosHTerm = TMath::CosH(deltaGamma*Abs/2);
Double_t sinHTerm = TMath::SinH(deltaGamma*Abs/2);
Double_t normTerm = nonTrigTerm*(cosHTerm + y*sinHTerm);
return normTerm;
}
Double_t LauDecayTimePdf::normExpHypTermDep(Double_t Abs)
{
Double_t tau = tau_->value();
Double_t deltaGamma = deltaGamma_->value();
Double_t y = tau*deltaGamma/2;
Double_t nonTrigTerm = -(TMath::Exp(-Abs/tau))/(1 - y*y);
Double_t cosHTerm = TMath::CosH(deltaGamma*Abs/2);
Double_t sinHTerm = TMath::SinH(deltaGamma*Abs/2);
Double_t normTerm = nonTrigTerm*(sinHTerm + y*cosHTerm);
return normTerm;
}
void LauDecayTimePdf::storeIntegralTimeDep(Double_t minAbs, Double_t maxAbs)
{
Double_t tau = tau_->value();
// Normalisation factor for B0 decays
if (type_ == ExpTrig) {
if (method_ == DecayTime) {
normTermExp_ = tau * (TMath::Exp(-minAbs/tau) - TMath::Exp(-maxAbs/tau));
}
if (method_ == DecayTimeDiff) {
normTermExp_ = tau * (2.0 - TMath::Exp(-maxAbs/tau) - TMath::Exp(-minAbs/tau));
}
}
// Normalisation factor for Bs decays
if (type_ == ExpHypTrig) {
normTermCosh_ = normExpHypTerm(maxAbs) - normExpHypTerm(minAbs);
normTermSinh_ = normExpHypTermDep( maxAbs) - normExpHypTermDep( minAbs);
}
}
Double_t LauDecayTimePdf::generateError(Bool_t forceNew)
{
if (errHist_ && (forceNew || !abscissaErrorGenerated_)) {
LauFitData errData = errHist_->generate(0);
abscissaError_ = errData.find(this->varErrName())->second;
abscissaErrorGenerated_ = kTRUE;
} else {
while (forceNew || !abscissaErrorGenerated_) {
abscissaError_ = LauRandom::randomFun()->Landau(errorDistMPV_,errorDistSigma_);
if (abscissaError_ < maxAbscissaError_ && abscissaError_ > minAbscissaError_) {
abscissaErrorGenerated_ = kTRUE;
forceNew = kFALSE;
}
}
}
return abscissaError_;
}
/*
LauFitData LauDecayTimePdf::generate(const LauKinematics* kinematics)
{
// generateError SHOULD have been called before this
// function but will call it here just to make sure
// (has ns effect if has already been called)
abscissaError_ = this->generateError();
// If the PDF is scaled by the per-event error then need to update the PDF height for each event
Bool_t scale(kFALSE);
for (std::vector<Bool_t>::const_iterator iter = scaleMeans_.begin(); iter != scaleMeans_.end(); ++iter) {
scale |= (*iter);
}
for (std::vector<Bool_t>::const_iterator iter = scaleWidths_.begin(); iter != scaleWidths_.end(); ++iter) {
scale |= (*iter);
}
if (scale || (!this->heightUpToDate() && !this->cachePDF())) {
this->calcPDFHeight(kinematics);
this->heightUpToDate(kTRUE);
}
// Generate the value of the abscissa.
Bool_t gotAbscissa(kFALSE);
Double_t genVal(0.0);
Double_t genPDFVal(0.0);
LauFitData genAbscissa;
const Double_t xMin = this->minAbscissa();
const Double_t xMax = this->maxAbscissa();
const Double_t xRange = xMax - xMin;
while (!gotAbscissa) {
genVal = LauRandom::randomFun()->Rndm()*xRange + xMin;
this->calcLikelihoodInfo(genVal, abscissaError_);
genPDFVal = this->getUnNormLikelihood();
if (LauRandom::randomFun()->Rndm() <= genPDFVal/this->getMaxHeight()) {gotAbscissa = kTRUE;}
if (genPDFVal > this->getMaxHeight()) {
cerr<<"Warning in LauDecayTimePdf::generate()."
<<" genPDFVal = "<<genPDFVal<<" is larger than the specified PDF height "
<<this->getMaxHeight()<<" for the abscissa = "<<genVal<<". Need to reset height to be larger than "
<<genPDFVal<<" by using the setMaxHeight(Double_t) function"
<<" and re-run the Monte Carlo generation!"<<endl;
}
}
genAbscissa[this->varName()] = genVal;
// mark that we need a new error to be generated next time
abscissaErrorGenerated_ = kFALSE;
return genAbscissa;
}
*/
void LauDecayTimePdf::setErrorHisto(const TH1* hist)
{
if ( errHist_ != 0 ) {
cerr<<"WARNING in LauDecayTimePdf::setErrorHisto : Error histogram already set, not doing it again."<<endl;
return;
}
errHist_ = new Lau1DHistPdf(this->varErrName(), hist, this->minAbscissaError(), this->maxAbscissaError());
}
void LauDecayTimePdf::setHistoPdf(const TH1* hist)
{
if ( pdfHist_ != 0 ) {
cerr<<"WARNING in LauDecayTimePdf::setHistoPdf : PDF histogram already set, not doing it again."<<endl;
return;
}
pdfHist_ = new Lau1DHistPdf(this->varName(), hist, this->minAbscissa(), this->maxAbscissa());
}
void LauDecayTimePdf::setEffiSpline(Lau1DCubicSpline* spline)
{
if ( effiFun_ != 0 ) {
cerr<<"WARNING in LauDecayTimePdf::setEffiPdf : efficiency function already set, not doing it again."<<endl;
return;
}
effiFun_ = spline;
}
void LauDecayTimePdf::setEffiSpline(Lau1DCubicSpline* spline, std::vector<LauParameter*> effiPars)
{
- if ( effiFun_ != 0 ) {
- cerr<<"WARNING in LauDecayTimePdf::setEffiPdf : efficiency function already set, not doing it again."<<endl;
- return;
- }
+ if ( effiFun_ != 0 ) {
+ cerr<<"WARNING in LauDecayTimePdf::setEffiPdf : efficiency function already set, not doing it again."<<endl;
+ return;
+ }
effiFun_ = spline;
if (effiPars.size() != spline->getnKnots()){
cerr<<"ERROR in LauDecayTimePdf::setEffiPdf : number of efficiency parameters is not equal to the number of spline knots."<<endl;
gSystem->Exit(EXIT_FAILURE);
}
effiPars_ = effiPars;
}
LauAbsRValue* LauDecayTimePdf::findParameter(const TString& parName)
{
for ( std::vector<LauAbsRValue*>::iterator iter = param_.begin(); iter != param_.end(); ++iter ) {
if ((*iter)->name().Contains(parName)) {
return (*iter);
}
}
std::cerr << "ERROR in LauDecayTimePdf::findParameter : Parameter \"" << parName << "\" not found." << std::endl;
return 0;
}
const LauAbsRValue* LauDecayTimePdf::findParameter(const TString& parName) const
{
for ( std::vector<LauAbsRValue*>::const_iterator iter = param_.begin(); iter != param_.end(); ++iter ) {
if ((*iter)->name().Contains(parName)) {
return (*iter);
}
}
std::cerr << "ERROR in LauDecayTimePdf::findParameter : Parameter \"" << parName << "\" not found." << std::endl;
return 0;
}
void LauDecayTimePdf::updatePulls()
{
for ( std::vector<LauAbsRValue*>::iterator iter = param_.begin(); iter != param_.end(); ++iter ) {
std::vector<LauParameter*> params = (*iter)->getPars();
for (std::vector<LauParameter*>::iterator params_iter = params.begin(); params_iter != params.end(); ++params_iter ) {
if (!(*iter)->fixed()) {
(*params_iter)->updatePull();
}
}
}
}
void LauDecayTimePdf::updateEffiSpline(std::vector<LauParameter*> params)
{
- //if (params[4]->unblindValue()!=current_yvals[4]){
- // std::cout<< "params[4]->unblindValue() "<<params[4]->unblindValue()<<std::endl;
- //}
if (!params.empty()){
std::vector<Double_t> yvals;
yvals.reserve(params.size());
for (ULong_t i(0); i<params.size(); ++i){
yvals.push_back(params[i]->unblindValue());
}
effiFun_->updateYValues(yvals);
}
}
diff --git a/src/LauFlavTag.cc b/src/LauFlavTag.cc
index d807e3a..f5c6dc7 100644
--- a/src/LauFlavTag.cc
+++ b/src/LauFlavTag.cc
@@ -1,420 +1,494 @@
/*
Copyright 2017 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 LauFlavTag.cc
\brief File containing implementation of LauFlavTag 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 "LauFlavTag.hh"
ClassImp(LauFlavTag)
LauFlavTag::LauFlavTag(const std::vector<LauParameter*>& params, const Bool_t useUntaggedEvents, const TString& tagVarName, const TString& tagCatVarName) :
useUntaggedEvents_(useUntaggedEvents),
signalTagCatFrac_(),
tagVarName_(tagVarName),
tagCatVarName_(tagCatVarName),
mistagVarName_("tagMistag"),
validTagCats_(),
curEvtTagFlv_(0),
curEvtTagCat_(0),
curEvtMistag_(0.),
evtTagFlvVals_(0),
evtTagCatVals_(0),
evtMistagVals_(0),
dilution_(),
deltaDilution_(),
usePerEvtMistag_(kFALSE),
perEvtAvgMistag_(),
- calib_p0_(),
- calib_p1_(),
+ calib_p0_B0_(),
+ calib_p0_B0bar_(),
+ calib_p1_B0_(),
+ calib_p1_B0bar_(),
+ calib_p0_ave_(),
+ calib_p0_delta_(),
+ calib_p1_ave_(),
+ calib_p1_delta_(),
+ useAveOmegaDeltaOmega_(kFALSE),
tagAsym_(),
params_(params)
{
// Add the untagged category as a valid category
this->addValidTagCat(0);
// Set the fraction, average dilution and dilution difference for the untagged category
- this->setSignalTagCatPars(0, 1.0, 0.0, 0.0, kTRUE,kTRUE,"PerEvtMistag",0.5,1.0,1.0);
+ this->setSignalTagCatPars(0, 1.0, 0.0, 0.0, kTRUE,kTRUE,"PerEvtMistag",0.5,1.0,0.5,1.0,1.0);
}
LauFlavTag::~LauFlavTag()
{
}
void LauFlavTag::initialise()
{
this->checkSignalTagCatFractions();
}
void LauFlavTag::addValidTagCats(const std::vector<Int_t>& tagCats)
{
for (std::vector<Int_t>::const_iterator iter = tagCats.begin(); iter != tagCats.end(); ++iter) {
this->addValidTagCat(*iter);
}
}
void LauFlavTag::addValidTagCat(const Int_t tagCat)
{
validTagCats_.insert(tagCat);
}
-void LauFlavTag::setSignalTagCatPars(const Int_t tagCat, const Double_t tagCatFrac, const Double_t dilution, const Double_t deltaDilution, const Bool_t fixTCFrac, const Bool_t usePerEvtMistag, const TString& mistagVarName, const Double_t calib_p0, const Double_t calib_p1, const Double_t tagAsym)
+void LauFlavTag::setSignalTagCatPars(const Int_t tagCat, const Double_t tagCatFrac, const Double_t dilution, const Double_t deltaDilution, const Bool_t fixTCFrac, const Bool_t usePerEvtMistag, const TString& mistagVarName, const Double_t calib_p0_b0, const Double_t calib_p0_b0bar, const Double_t calib_p1_b0, const Double_t calib_p1_b0bar, const Double_t tagAsym)
{
if (!this->validTagCat(tagCat)) {
std::cerr<<"ERROR in LauFlavTag::setSignalTagCatPars : Tagging category \""<<tagCat<<"\" not valid, not changing the parameters."<<std::endl;
return;
}
TString tagCatFracName("signalTagCatFrac");
tagCatFracName += tagCat;
signalTagCatFrac_[tagCat].name(tagCatFracName);
signalTagCatFrac_[tagCat].range(0.0,1.0);
signalTagCatFrac_[tagCat].value(tagCatFrac); signalTagCatFrac_[tagCat].initValue(tagCatFrac); signalTagCatFrac_[tagCat].genValue(tagCatFrac);
signalTagCatFrac_[tagCat].fixed(fixTCFrac);
TString dilutionName("dilution");
dilutionName += tagCat;
dilution_[tagCat].name(dilutionName);
dilution_[tagCat].range(0.0,1.0);
dilution_[tagCat].value(dilution); dilution_[tagCat].initValue(dilution); dilution_[tagCat].genValue(dilution);
dilution_[tagCat].fixed(kTRUE);
TString deltaDilutionName("deltaDilution");
deltaDilutionName += tagCat;
deltaDilution_[tagCat].name(deltaDilutionName);
deltaDilution_[tagCat].range(-2.0,2.0);
deltaDilution_[tagCat].value(deltaDilution); deltaDilution_[tagCat].initValue(deltaDilution); deltaDilution_[tagCat].genValue(deltaDilution);
deltaDilution_[tagCat].fixed(kTRUE);
TString tagAsymName("tagAsym");
tagAsymName += tagCat;
tagAsym_[tagCat].name(tagAsymName);
tagAsym_[tagCat].range(0.0,2.0);
tagAsym_[tagCat].value(tagAsym); tagAsym_[tagCat].initValue(tagAsym); tagAsym_[tagCat].genValue(tagAsym);
tagAsym_[tagCat].fixed(kTRUE); //Default should be fixed to 1.0
if (usePerEvtMistag){
usePerEvtMistag_ = kTRUE;
mistagVarName_ = mistagVarName;
std::cout<<"INFO in LauFlavTag::setSignalTagCatPars : Using per event mistag information from branch "<<mistagVarName_<<" ."<<std::endl;
perEvtAvgMistag_[tagCat]=0;
- TString calib_p0Name("calib_p0_");
- TString calib_p1Name("calib_p1_");
- calib_p0Name += tagCat;
- calib_p1Name += tagCat;
+ TString calib_p0_B0Name("calib_p0_B0_");
+ TString calib_p0_B0barName("calib_p0_B0bar_");
+ TString calib_p1_B0Name("calib_p1_B0_");
+ TString calib_p1_B0barName("calib_p1_B0bar_");
+ calib_p0_B0Name += tagCat;
+ calib_p0_B0barName += tagCat;
+ calib_p1_B0Name += tagCat;
+ calib_p1_B0barName += tagCat;
+
+ calib_p0_B0_[tagCat].name(calib_p0_B0Name);
+ calib_p0_B0_[tagCat].range(0.0,1.0);
+ calib_p0_B0_[tagCat].value(calib_p0_b0); calib_p0_B0_[tagCat].initValue(calib_p0_b0); calib_p0_B0_[tagCat].genValue(calib_p0_b0); //Ideally would use perEvtAvgMistag_[tagCat]
+ calib_p0_B0_[tagCat].fixed(kTRUE); //Update once full code in place
+
+ calib_p0_B0bar_[tagCat].name(calib_p0_B0barName);
+ calib_p0_B0bar_[tagCat].range(0.0,1.0);
+ calib_p0_B0bar_[tagCat].value(calib_p0_b0bar); calib_p0_B0bar_[tagCat].initValue(calib_p0_b0bar); calib_p0_B0bar_[tagCat].genValue(calib_p0_b0bar); //Ideally would use perEvtAvgMistag_[tagCat]
+ calib_p0_B0bar_[tagCat].fixed(kTRUE); //Update once full code in place
+
+ calib_p1_B0_[tagCat].name(calib_p1_B0Name);
+ calib_p1_B0_[tagCat].range(0.0,1.5);
+ calib_p1_B0_[tagCat].value(calib_p1_b0); calib_p1_B0_[tagCat].initValue(calib_p1_b0); calib_p1_B0_[tagCat].genValue(calib_p1_b0); //Ideally would use perEvtAvgMistag_[tagCat]
+ calib_p1_B0_[tagCat].fixed(kTRUE); //Update once full code in place
+
+ calib_p1_B0bar_[tagCat].name(calib_p1_B0barName);
+ calib_p1_B0bar_[tagCat].range(0.0,1.5);
+ calib_p1_B0bar_[tagCat].value(calib_p1_b0bar); calib_p1_B0bar_[tagCat].initValue(calib_p1_b0bar); calib_p1_B0bar_[tagCat].genValue(calib_p1_b0bar); //Ideally would use perEvtAvgMistag_[tagCat]
+ calib_p1_B0bar_[tagCat].fixed(kTRUE); //Update once full code in place
+
+ //If requested, set up the alternative option to float average omega and delta omega instead
+ if (useAveOmegaDeltaOmega_){
+ this->useAveOmegaDeltaOmegaCalib(tagCat);
+ }
+
+ //Fix this later - add alternate params for tagCat 0 as it is called before the user can specify the flag
+ if (tagCat==0){
+ this->useAveOmegaDeltaOmegaCalib(tagCat);
+ }
- calib_p0_[tagCat].name(calib_p0Name);
- calib_p0_[tagCat].range(0.0,1.0);
- calib_p0_[tagCat].value(calib_p0); calib_p0_[tagCat].initValue(calib_p0); calib_p0_[tagCat].genValue(calib_p0); //Ideally would use perEvtAvgMistag_[tagCat]
- calib_p0_[tagCat].fixed(kTRUE); //Update once full code in place
- calib_p1_[tagCat].name(calib_p1Name);
- calib_p1_[tagCat].range(0.0,1.5);
- calib_p1_[tagCat].value(calib_p1); calib_p1_[tagCat].initValue(calib_p1); calib_p1_[tagCat].genValue(calib_p1); //Ideally would use perEvtAvgMistag_[tagCat]
- calib_p1_[tagCat].fixed(kTRUE); //Update once full code in place
}
// We check they're set up correctly with checkSignalTagCatFractions()
// only when the user has set them all up, see initialise()
}
+void LauFlavTag::useAveOmegaDeltaOmegaCalib(Int_t tagCat)
+{
+ TString calib_p0_ave("calib_p0_ave_");
+ TString calib_p0_delta("calib_p0_delta_");
+ TString calib_p1_ave("calib_p1_ave_");
+ TString calib_p1_delta("calib_p1_delta_");
+ calib_p0_ave += tagCat;
+ calib_p0_delta += tagCat;
+ calib_p1_ave += tagCat;
+ calib_p1_delta += tagCat;
+
+ calib_p0_ave_[tagCat].name(calib_p0_ave);
+ calib_p0_ave_[tagCat].range(0.0,1.0);
+ Double_t ave_p0 = ((calib_p0_B0_[tagCat].unblindValue() + calib_p0_B0bar_[tagCat].unblindValue())/2);
+ calib_p0_ave_[tagCat].value(ave_p0); calib_p0_ave_[tagCat].initValue(ave_p0); calib_p0_ave_[tagCat].genValue(ave_p0);
+ calib_p0_ave_[tagCat].fixed(kTRUE); //Update once full code in place
+
+ calib_p0_delta_[tagCat].name(calib_p0_delta);
+ calib_p0_delta_[tagCat].range(-1.0,1.0);
+ Double_t delta_p0 = (calib_p0_B0_[tagCat].unblindValue() - calib_p0_B0bar_[tagCat].unblindValue());
+ calib_p0_delta_[tagCat].value(delta_p0); calib_p0_delta_[tagCat].initValue(delta_p0); calib_p0_delta_[tagCat].genValue(delta_p0);
+ calib_p0_delta_[tagCat].fixed(kTRUE); //Update once full code in place
+
+ calib_p1_ave_[tagCat].name(calib_p1_ave);
+ calib_p1_ave_[tagCat].range(0.0,1.0);
+ Double_t ave_p1 = ((calib_p1_B0_[tagCat].unblindValue() + calib_p1_B0bar_[tagCat].unblindValue())/2);
+ calib_p1_ave_[tagCat].value(ave_p1); calib_p1_ave_[tagCat].initValue(ave_p1); calib_p1_ave_[tagCat].genValue(ave_p1);
+ calib_p1_ave_[tagCat].fixed(kTRUE); //Update once full code in place
+
+ calib_p1_delta_[tagCat].name(calib_p1_delta);
+ calib_p1_delta_[tagCat].range(-1.0,1.0);
+ Double_t delta_p1 = (calib_p1_B0_[tagCat].unblindValue() - calib_p1_B0bar_[tagCat].unblindValue());
+ calib_p1_delta_[tagCat].value(delta_p1); calib_p1_delta_[tagCat].initValue(delta_p1); calib_p1_delta_[tagCat].genValue(delta_p1);
+ calib_p1_delta_[tagCat].fixed(kTRUE); //Update once full code in place
+}
+
void LauFlavTag::checkSignalTagCatFractions()
{
Double_t totalTaggedFrac(0.0);
for (LauTagCatParamMap::const_iterator iter=signalTagCatFrac_.begin(); iter!=signalTagCatFrac_.end(); ++iter) {
if (iter->first != 0) {
const LauParameter& par = iter->second;
totalTaggedFrac += par.value();
}
}
if ( ((totalTaggedFrac < (1.0-1.0e-8))&&!useUntaggedEvents_) || (totalTaggedFrac > (1.0+1.0e-8)) ) {
std::cerr<<"WARNING in LauFlavTag::checkSignalTagCatFractions : Tagging category fractions add up to "<<totalTaggedFrac<<", not 1.0; normalizing them."<<std::endl;
for (LauTagCatParamMap::iterator iter=signalTagCatFrac_.begin(); iter!=signalTagCatFrac_.end(); ++iter) {
LauParameter& par = iter->second;
Double_t newVal = par.value() / totalTaggedFrac;
par.value(newVal); par.initValue(newVal); par.genValue(newVal);
}
} else if (useUntaggedEvents_) {
Double_t tagCatFrac = 1.0 - totalTaggedFrac;
TString tagCatFracName("signalTagCatFrac0");
signalTagCatFrac_[0].name(tagCatFracName);
signalTagCatFrac_[0].range(0.0,1.0);
signalTagCatFrac_[0].value(tagCatFrac); signalTagCatFrac_[0].initValue(tagCatFrac); signalTagCatFrac_[0].genValue(tagCatFrac);
signalTagCatFrac_[0].fixed(kTRUE);
TString dilutionName("dilution0");
dilution_[0].name(dilutionName);
dilution_[0].range(0.0,1.0);
dilution_[0].value(0.0); dilution_[0].initValue(0.0); dilution_[0].genValue(0.0);
dilution_[0].fixed(kTRUE);
TString deltaDilutionName("deltaDilution0");
deltaDilution_[0].name(deltaDilutionName);
deltaDilution_[0].range(-2.0,2.0);
deltaDilution_[0].value(0.0); deltaDilution_[0].initValue(0.0); deltaDilution_[0].genValue(0.0);
deltaDilution_[0].fixed(kTRUE);
}
for (LauTagCatParamMap::const_iterator iter=dilution_.begin(); iter!=dilution_.end(); ++iter) {
std::cout<<"INFO in LauFlavTag::checkSignalTagCatFractions : Setting dilution for tagging category "<<(*iter).first<<" to "<<(*iter).second<<std::endl;
}
for (LauTagCatParamMap::const_iterator iter=deltaDilution_.begin(); iter!=deltaDilution_.end(); ++iter) {
std::cout<<"INFO in LauFlavTag::checkSignalTagCatFractions : Setting Delta(dilution) for tagging category "<<(*iter).first<<" to "<<(*iter).second<<std::endl;
}
for (LauTagCatParamMap::const_iterator iter=signalTagCatFrac_.begin(); iter!=signalTagCatFrac_.end(); ++iter) {
std::cout<<"INFO in LauFlavTag::checkSignalTagCatFractions : Setting (signal) fraction for tagging category "<<(*iter).first<<" to "<<(*iter).second<<std::endl;
}
}
void LauFlavTag::setFirstTagCatFractions()
{
this->setFirstTagCatFrac(signalTagCatFrac_);
// TODO - add background maps
}
void LauFlavTag::setFirstTagCatFrac(LauTagCatParamMap& theMap)
{
Double_t firstCatFrac = 1.0;
Int_t firstCat(0);
for (LauTagCatParamMap::iterator iter = theMap.begin(); iter != theMap.end(); ++iter) {
if (iter == theMap.begin()) {
firstCat = iter->first;
continue;
}
LauParameter& par = iter->second;
firstCatFrac -= par.unblindValue();
}
theMap[firstCat].value(firstCatFrac);
}
Bool_t LauFlavTag::validTagCat(Int_t tagCat) const
{
return (validTagCats_.find(tagCat) != validTagCats_.end());
}
std::set<Int_t> LauFlavTag::getValidTagCats()
{
return validTagCats_;
}
Bool_t LauFlavTag::checkTagCatFracMap(const LauTagCatParamMap& theMap) const
{
// TODO - this is for checking the the background maps are OK (so it is unused at the moment)
// First check that there is an entry for each tagging category.
// NB an entry won't have been added if it isn't a valid category
// so don't need to check for that here.
if (theMap.size() != signalTagCatFrac_.size()) {
std::cerr<<"ERROR in LauFlavTag::checkTagCatFracMap : Not all tagging categories present."<<std::endl;
return kFALSE;
}
// Now check that the fractions sum up to unity.
Double_t tagCatFracSum(0.0);
for (LauTagCatParamMap::const_iterator iter = theMap.begin(); iter != theMap.end(); ++iter) {
const LauParameter& par = (*iter).second;
tagCatFracSum += par.unblindValue();
}
if ((tagCatFracSum - 1.0) > 1E-10) {
std::cerr<<"ERROR in LauFlavTag::checkTagCatFracMap : Tagging category event fractions do not sum to unity."<<std::endl;
return kFALSE;
}
// If we've got to here then all is OK.
return kTRUE;
}
void LauFlavTag::cacheInputFitVars(LauFitDataTree* inputFitData)
{
// Fill event by event data
// Start by caching the tagging information
evtTagCatVals_.clear();
evtTagFlvVals_.clear();
evtMistagVals_.clear();
if ( ! inputFitData->haveBranch( tagCatVarName_ ) ) {
std::cerr << "ERROR in LauFlavTag::cacheInputFitVars : Input data does not contain branch \"" << tagCatVarName_ << "\"." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
if ( ! inputFitData->haveBranch( tagVarName_ ) ) {
std::cerr << "ERROR in LauFlavTag::cacheInputFitVars : Input data does not contain branch \"" << tagVarName_ << "\"." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
if ( ! inputFitData->haveBranch( mistagVarName_ ) ) {
std::cerr << "ERROR in LauFlavTag::cacheInputFitVars : Input data does not contain branch \"" << mistagVarName_ << "\"." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
UInt_t nEvents = inputFitData->nEvents();
evtTagCatVals_.reserve( nEvents );
evtTagFlvVals_.reserve( nEvents );
evtMistagVals_.reserve( nEvents );
//Running total to calc average mistag per tagCat
//Double_t tot_mistag(0.);
std::map< Int_t, Double_t> tot_mistag;
//Int_t totalTagged = 0;
std::map< Int_t, Int_t> totalTagged;
LauFitData::const_iterator fitdata_iter;
for (UInt_t iEvt = 0; iEvt < nEvents; iEvt++) {
const LauFitData& dataValues = inputFitData->getData(iEvt);
fitdata_iter = dataValues.find( tagCatVarName_ );
curEvtTagCat_ = static_cast<Int_t>( fitdata_iter->second );
if ( ! this->validTagCat( curEvtTagCat_ ) ) {
std::cerr << "WARNING in LauFlavTag::cacheInputFitVars : Invalid tagging category " << curEvtTagCat_ << " for event " << iEvt << ", setting it to untagged" << std::endl;
curEvtTagCat_ = 0;
}
evtTagCatVals_.push_back( curEvtTagCat_ );
fitdata_iter = dataValues.find( tagVarName_ );
curEvtTagFlv_ = static_cast<Int_t>( fitdata_iter->second );
if ( TMath::Abs( curEvtTagFlv_ ) != 1 ) {
if ( curEvtTagFlv_ > 0 ) {
std::cerr << "WARNING in LauFlavTag::cacheInputFitVars : Invalid tagging output " << curEvtTagFlv_ << " for event " << iEvt << ", setting it to +1" << std::endl;
curEvtTagFlv_ = +1;
} else {
std::cerr << "WARNING in LauFlavTag::cacheInputFitVars : Invalid tagging output " << curEvtTagFlv_ << " for event " << iEvt << ", setting it to -1" << std::endl;
curEvtTagFlv_ = -1;
}
}
evtTagFlvVals_.push_back( curEvtTagFlv_ );
// TODO - surely this part should only be done if we have per-event mistagging
fitdata_iter = dataValues.find( mistagVarName_);
curEvtMistag_ = static_cast<Double_t>( fitdata_iter->second );
if (curEvtMistag_ > 0.5){
std::cerr<<"WARNING in LauFlavTag::cacheInputFitVars : Mistag value "<<curEvtMistag_<<" is larger than 0.5, setting to 0.5"<<std::endl;
curEvtMistag_ = 0.5;
}
if (curEvtMistag_ < 0.0){
std::cerr<<"WARNING in LauFlavTag::cacheInputFitVars : Mistag value "<<curEvtMistag_<<" is less than 0.0, setting to 0.0"<<std::endl;
curEvtMistag_ = 0.0;
}
// Only those with tags (cat != 0) contribute to the average
if (curEvtTagCat_ != 0) {
tot_mistag[curEvtTagCat_] += curEvtMistag_;
totalTagged[curEvtTagCat_] += 1;
}
evtMistagVals_.push_back( curEvtMistag_ );
}
// Store average per event mistag for calibration
for (std::map< Int_t, Double_t>::iterator iter = perEvtAvgMistag_.begin(); iter != perEvtAvgMistag_.end(); ++iter) {
if (totalTagged[iter->first]!=0){
perEvtAvgMistag_[iter->first] = tot_mistag[iter->first]/totalTagged[iter->first];
}
else {
std::cout<<"INFO in LauFlavTag::cacheInputFitVars : average per event mistag set to 0.5 for tagCat "<<iter->first<<std::endl;
perEvtAvgMistag_[iter->first] = 0.5;
}
}
}
LauParameter* LauFlavTag::findParameter(const TString& parName)
{
for ( std::vector<LauParameter*>::iterator iter = params_.begin(); iter != params_.end(); ++iter ) {
if ((*iter)->name().Contains(parName)) {
return (*iter);
}
}
std::cerr << "ERROR in LauFlavTag::findParameter : Parameter \"" << parName << "\" not found." << std::endl;
return 0;
}
Double_t LauFlavTag::getOmega(const UInt_t iEvt) //const
{
- return calib_p0_[curEvtTagCat_].unblindValue() + calib_p1_[curEvtTagCat_].unblindValue() * (evtMistagVals_[iEvt] - perEvtAvgMistag_[curEvtTagCat_]);
+ //If we are floating average omega and delta omega we need to use those parameters instead
+ if (useAveOmegaDeltaOmega_){
+ calib_p0_B0_[curEvtTagCat_].value( calib_p0_ave_[curEvtTagCat_].unblindValue() + 0.5*calib_p0_delta_[curEvtTagCat_].unblindValue() );
+ calib_p0_B0bar_[curEvtTagCat_].value( calib_p0_ave_[curEvtTagCat_].unblindValue() - 0.5*calib_p0_delta_[curEvtTagCat_].unblindValue() );
+ calib_p1_B0_[curEvtTagCat_].value( calib_p1_ave_[curEvtTagCat_].unblindValue() + 0.5*calib_p1_delta_[curEvtTagCat_].unblindValue() );
+ calib_p1_B0bar_[curEvtTagCat_].value( calib_p1_ave_[curEvtTagCat_].unblindValue() - 0.5*calib_p1_delta_[curEvtTagCat_].unblindValue() );
+ }
+ if (curEvtTagFlv_ == -1){
+ return calib_p0_B0_[curEvtTagCat_].unblindValue() + calib_p1_B0_[curEvtTagCat_].unblindValue() * (evtMistagVals_[iEvt] - perEvtAvgMistag_[curEvtTagCat_]);
+ }
+ if (curEvtTagFlv_ == +1){
+ return calib_p0_B0bar_[curEvtTagCat_].unblindValue() + calib_p1_B0bar_[curEvtTagCat_].unblindValue() * (evtMistagVals_[iEvt] - perEvtAvgMistag_[curEvtTagCat_]);
+ }
+ std::cerr << "ERROR in LauFlavTag::getOmega : Current event flavour tag not defined" << std::endl;
+ return 0.0;
}
-Double_t LauFlavTag::getOmegaGen(const Double_t eta) //const
+Double_t LauFlavTag::getOmegaGen(const Double_t eta, const Int_t curEvtTagFlv) //const
{
- return calib_p0_[curEvtTagCat_].unblindValue() + calib_p1_[curEvtTagCat_].unblindValue() * (eta - perEvtAvgMistag_[curEvtTagCat_]);
+ //If we are floating average omega and delta omega we need to use those parameters instead
+ if (useAveOmegaDeltaOmega_){
+ calib_p0_B0_[curEvtTagCat_].value( calib_p0_ave_[curEvtTagCat_].unblindValue() + 0.5*calib_p0_delta_[curEvtTagCat_].unblindValue() );
+ calib_p0_B0bar_[curEvtTagCat_].value( calib_p0_ave_[curEvtTagCat_].unblindValue() - 0.5*calib_p0_delta_[curEvtTagCat_].unblindValue() );
+ calib_p1_B0_[curEvtTagCat_].value( calib_p1_ave_[curEvtTagCat_].unblindValue() + 0.5*calib_p1_delta_[curEvtTagCat_].unblindValue() );
+ calib_p1_B0bar_[curEvtTagCat_].value( calib_p1_ave_[curEvtTagCat_].unblindValue() - 0.5*calib_p1_delta_[curEvtTagCat_].unblindValue() );
+ }
+ if (curEvtTagFlv == -1){
+ return calib_p0_B0_[curEvtTagCat_].unblindValue() + calib_p1_B0_[curEvtTagCat_].unblindValue() * (eta - perEvtAvgMistag_[curEvtTagCat_]);
+ }
+ if (curEvtTagFlv == +1){
+ return calib_p0_B0bar_[curEvtTagCat_].unblindValue() + calib_p1_B0bar_[curEvtTagCat_].unblindValue() * (eta - perEvtAvgMistag_[curEvtTagCat_]);
+ }
+ std::cerr << "ERROR in LauFlavTag::getOmegaGen : Current event flavour tag not defined" << std::endl;
+ return 0.0;
}
Double_t LauFlavTag::getEtaGen(LauAbsPdf* hist) const
{
if (hist==0){
std::cout << "Error in LauFlavTag::getEtaGen : Supplied LauAbsPdf is a null pointer" << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
LauFitData data = hist->generate(0); //TODO Add DP dependence?
return data.find(hist->varName())->second;
}
-
-//std::vector<LauParameter*> LauFlavTag::getCalibParameters(Int_t tagCat)
-//{
-// if (!this->validTagCat(tagCat)){
-// std::cout << "FATAL in LauFlavTag::setCalibParams : Invalid tagging category, number " << tagCat << "." << std::endl;
-// gSystem->Exit(EXIT_FAILURE);
-// }
-// std::vector<LauParameter*> calibParams;
-// calib_p0_[tagCat] = this->findParameter("calib_p0");
-// calib_p1_[tagCat] = this->findParameter("calib_p1");
-//
-// // calib_p0_->value(perEvtAvgMistag_); // WOULD BE NICE TO DO THIS
-//
-// calibParams.push_back( calib_p0_[tagCat] );
-// calibParams.push_back( calib_p1_[tagCat] );
-// if (calibParams.size() != 2) {
-// std::cout << "FATAL in LauFlavTag::setCalibParams : Expected two calibration parameters, received " << calibParams.size() << "." << std::endl;
-// gSystem->Exit(EXIT_FAILURE);
-// }
-// return calibParams;
-//
-//}
-
diff --git a/src/LauTimeDepFitModel.cc b/src/LauTimeDepFitModel.cc
index 60e5acb..a7b6683 100644
--- a/src/LauTimeDepFitModel.cc
+++ b/src/LauTimeDepFitModel.cc
@@ -1,2385 +1,2429 @@
/*
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),
flavTag_(flavTag),
nSigComp_(0),
nSigDPPar_(0),
nDecayTimePar_(0),
nExtraPdfPar_(0),
nNormPar_(0),
nCalibPar_(0),
nEffiPar_(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)),
signalDecayTimePdfs_(),
curEvtDecayTime_(0.0),
curEvtDecayTimeErr_(0.0),
sigExtraPdf_(),
sigFlavTagPdf_(),
bkgdFlavTagPdf_(),
AProd_("AProd",1.0,0.0,2.0,kTRUE),
ADet_("ADet",1.0,0.0,2.0,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 (LauTagCatEmbDataMap::iterator iter = signalTree_.begin(); iter != signalTree_.end(); ++iter){
delete iter->second;
}
for (LauTagCatEmbDataMapList::iterator iterlist = bkgndTree_.begin(); iterlist != bkgndTree_.end(); ++iterlist){
for (LauTagCatEmbDataMap::iterator iter = (*iterlist).begin(); iter != (*iterlist).end(); ++iter){
delete iter->second;
}
}
}
void LauTimeDepFitModel::setupBkgndVectors()
{
UInt_t nBkgnds = this->nBkgndClasses();
BkgndDPModelsB0_.resize( nBkgnds );
BkgndDPModelsB0bar_.resize( nBkgnds );
BkgndPdfsB0_.resize( nBkgnds );
BkgndPdfsB0bar_.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(Int_t tagCat, LauDecayTimePdf* pdf)
{
if (!flavTag_->validTagCat(tagCat)) {
std::cerr<<"ERROR in LauTimeDepFitModel::setSignalDtPdf : Tagging category \""<<tagCat<<"\" not valid, not adding PDF."<<std::endl;
return;
}
if (pdf==0) {
std::cerr<<"ERROR in LauTimeDepFitModel::setSignalDtPdf : The PDF pointer is null, not adding it."<<std::endl;
return;
}
signalDecayTimePdfs_[tagCat] = pdf;
}
void LauTimeDepFitModel::setSignalPdfs(Int_t tagCat, 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 (!flavTag_->validTagCat(tagCat)) {
std::cerr<<"ERROR in LauTimeDepFitModel::setSignalPdfs : Tagging category \""<<tagCat<<"\" not valid, not adding models."<<std::endl;
return;
}
if (pdf==0) {
std::cerr<<"ERROR in LauTimeDepFitModel::setSignalPdfs : The PDF pointer is null."<<std::endl;
return;
}
sigExtraPdf_[tagCat].push_back(pdf);
}
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);
}
}
// 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 the efficiency parameters
this->setEffiParams();
// Check that we have the expected number of fit variables
const LauParameterPList& fitVars = this->fitPars();
if (fitVars.size() != (nSigDPPar_ + nDecayTimePar_ + nExtraPdfPar_ + nNormPar_ + nCalibPar_ + nEffiPar_)) {
std::cerr<<"ERROR in LauTimeDepFitModel::initialise : Number of fit parameters not of expected size."<<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();
}
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<<"\", restting 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(LauTagCatDtPdfMap& theMap)
{
UInt_t counter(0);
LauParameterPList& fitVars = this->fitPars();
// loop through the map
for (LauTagCatDtPdfMap::iterator iter = theMap.begin(); iter != theMap.end(); ++iter) {
// grab the pdf and then its parameters
LauDecayTimePdf* thePdf = (*iter).second; // 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(LauTagCatPdfListMap& theMap)
{
UInt_t counter(0);
// loop through the map
for (LauTagCatPdfListMap::iterator iter = theMap.begin(); iter != theMap.end(); ++iter) {
counter += this->addFitParameters(iter->second); // first is the tagging category
}
return counter;
}
void LauTimeDepFitModel::setDecayTimeParameters()
{
nDecayTimePar_ = 0;
// Loop over the Dt PDFs
nDecayTimePar_ += this->addParametersToFitList(signalDecayTimePdfs_);
LauParameterPList& fitVars = this->fitPars();
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;
nExtraPdfPar_ += this->addParametersToFitList(sigExtraPdf_);
}
void LauTimeDepFitModel::setFitNEvents()
{
nNormPar_ = 0;
// 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_;
}
}
void LauTimeDepFitModel::setCalibParams()
{
- LauTagCatParamMap& p0pars = flavTag_->getCalibP0();
- LauTagCatParamMap& p1pars = flavTag_->getCalibP1();
+ Bool_t useAltPars = flavTag_->getUseAveOmegaDeltaOmega();
- LauParameterPList& fitVars = this->fitPars();
+ if (useAltPars){
+ LauTagCatParamMap& p0pars_ave = flavTag_->getCalibP0Ave();
+ LauTagCatParamMap& p0pars_delta = flavTag_->getCalibP0Delta();
+ LauTagCatParamMap& p1pars_ave = flavTag_->getCalibP1Ave();
+ LauTagCatParamMap& p1pars_delta = flavTag_->getCalibP1Delta();
- for(LauTagCatParamMap::iterator iter = p0pars.begin(); iter != p0pars.end(); ++iter){
- LauParameter* p0 = &((*iter).second);
- fitVars.push_back(p0);
- ++nCalibPar_;
- }
- for(LauTagCatParamMap::iterator iter = p1pars.begin(); iter != p1pars.end(); ++iter){
- LauParameter* p1 = &((*iter).second);
- fitVars.push_back(p1);
- ++nCalibPar_;
+ LauParameterPList& fitVars = this->fitPars();
+
+ for(LauTagCatParamMap::iterator iter = p0pars_ave.begin(); iter != p0pars_ave.end(); ++iter){
+ LauParameter* p0 = &((*iter).second);
+ fitVars.push_back(p0);
+ ++nCalibPar_;
+ }
+ for(LauTagCatParamMap::iterator iter = p0pars_delta.begin(); iter != p0pars_delta.end(); ++iter){
+ LauParameter* p0 = &((*iter).second);
+ fitVars.push_back(p0);
+ ++nCalibPar_;
+ }
+ for(LauTagCatParamMap::iterator iter = p1pars_ave.begin(); iter != p1pars_ave.end(); ++iter){
+ LauParameter* p1 = &((*iter).second);
+ fitVars.push_back(p1);
+ ++nCalibPar_;
+ }
+ for(LauTagCatParamMap::iterator iter = p1pars_delta.begin(); iter != p1pars_delta.end(); ++iter){
+ LauParameter* p1 = &((*iter).second);
+ fitVars.push_back(p1);
+ ++nCalibPar_;
+ }
+ } else {
+ LauTagCatParamMap& p0pars_b0 = flavTag_->getCalibP0B0();
+ LauTagCatParamMap& p0pars_b0bar = flavTag_->getCalibP0B0bar();
+ LauTagCatParamMap& p1pars_b0 = flavTag_->getCalibP1B0();
+ LauTagCatParamMap& p1pars_b0bar = flavTag_->getCalibP1B0bar();
+
+ LauParameterPList& fitVars = this->fitPars();
+
+ for(LauTagCatParamMap::iterator iter = p0pars_b0.begin(); iter != p0pars_b0.end(); ++iter){
+ LauParameter* p0 = &((*iter).second);
+ fitVars.push_back(p0);
+ ++nCalibPar_;
+ }
+ for(LauTagCatParamMap::iterator iter = p0pars_b0bar.begin(); iter != p0pars_b0bar.end(); ++iter){
+ LauParameter* p0 = &((*iter).second);
+ fitVars.push_back(p0);
+ ++nCalibPar_;
+ }
+ for(LauTagCatParamMap::iterator iter = p1pars_b0.begin(); iter != p1pars_b0.end(); ++iter){
+ LauParameter* p1 = &((*iter).second);
+ fitVars.push_back(p1);
+ ++nCalibPar_;
+ }
+ for(LauTagCatParamMap::iterator iter = p1pars_b0bar.begin(); iter != p1pars_b0bar.end(); ++iter){
+ LauParameter* p1 = &((*iter).second);
+ fitVars.push_back(p1);
+ ++nCalibPar_;
+ }
}
}
void LauTimeDepFitModel::setEffiParams()
{
LauParameterPList& fitVars = this->fitPars();
LauTagCatDtPdfMap& signalDecayTimePdfs = this->getSignalDecayTimePdfs();
// Loop over DecayTimePdfs
for (LauTagCatDtPdfMap::iterator iter = signalDecayTimePdfs.begin(); iter != signalDecayTimePdfs.end(); ++iter){
LauDecayTimePdf* pdf = (*iter).second;
std::vector<LauParameter*>& effiPars = pdf->getEffiPars();
for(std::vector<LauParameter*>::iterator iter2 = effiPars.begin(); iter2 != effiPars.end(); ++iter2){
LauParameter* par = *iter2;
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::setProdDetAsymmetries(const Double_t AProd, const Bool_t AProdFix, const Double_t ADet, const Bool_t ADetFix){
AProd_.value(AProd);
AProd_.fixed(AProdFix);
ADet_.value(ADet);
ADet_.fixed(ADetFix);
}
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
for (LauTagCatDtPdfMap::iterator iter = signalDecayTimePdfs_.begin(); iter != signalDecayTimePdfs_.end(); ++iter) {
LauDecayTimePdf* pdf = (*iter).second;
pdf->updatePulls();
}
if (useSinCos_) {
cosPhiMix_.updatePull();
sinPhiMix_.updatePull();
} else {
this->checkMixingPhase();
}
// Update the pulls on all the extra PDFs' parameters
for (LauTagCatPdfListMap::iterator iter = sigExtraPdf_.begin(); iter != sigExtraPdf_.end(); ++iter) {
this->updateFitParameters(iter->second);
}
LauTagCatParamMap& signalTagCatFrac = flavTag_->getSignalTagCatFrac();
// Tagging-category fractions for signal and background events
Double_t firstCatFrac(1.0);
Int_t firstCat(0);
for (LauTagCatParamMap::iterator iter = signalTagCatFrac.begin(); iter != signalTagCatFrac.end(); ++iter) {
if (iter == signalTagCatFrac.begin()) {
firstCat = iter->first;
continue;
}
LauParameter& par = (*iter).second;
firstCatFrac -= par.value();
// update the parameter pull
par.updatePull();
}
signalTagCatFrac[firstCat].value(firstCatFrac);
signalTagCatFrac[firstCat].updatePull();
// 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;
for (LauTagCatPdfListMap::const_iterator iter = sigExtraPdf_.begin(); iter != sigExtraPdf_.end(); ++iter) {
this->printFitParameters(iter->second, 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;
LauTagCatGenInfo eventsB0, eventsB0bar;
// 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 );
}
LauTagCatParamMap& signalTagCatFrac = flavTag_->getSignalTagCatFrac();
Double_t sigAsym(0.0);
if (this->useDP() == kFALSE) {
sigAsym = signalAsym_->genValue();
for (LauTagCatParamMap::const_iterator iter = signalTagCatFrac.begin(); iter != signalTagCatFrac.end(); ++iter) {
const LauParameter& par = iter->second;
Double_t eventsbyTagCat = par.value() * nEvts;
Double_t eventsB0byTagCat = TMath::Nint(eventsbyTagCat/2.0 * (1.0 - sigAsym));
Double_t eventsB0barbyTagCat = TMath::Nint(eventsbyTagCat/2.0 * (1.0 + sigAsym));
if (this->doPoissonSmearing()) {
eventsB0byTagCat = LauRandom::randomFun()->Poisson(eventsB0byTagCat);
eventsB0barbyTagCat = LauRandom::randomFun()->Poisson(eventsB0barbyTagCat);
}
eventsB0[iter->first] = std::make_pair( TMath::Nint(eventsB0byTagCat), evtWeight );
eventsB0bar[iter->first] = std::make_pair( TMath::Nint(eventsB0barbyTagCat), evtWeight );
}
// CONVENTION WARNING
nEvtsGen[std::make_pair("signal",-1)] = eventsB0;
nEvtsGen[std::make_pair("signal",+1)] = eventsB0bar;
} 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.
}
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);
// 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.first);
// find the true flavour
curEvtTagFlv_ = iter->first.second;
// loop through each tagging category
const LauTagCatGenInfo& eventsByTagCat = iter->second;
for (LauTagCatGenInfo::const_iterator tagCatIter = eventsByTagCat.begin(); tagCatIter != eventsByTagCat.end(); ++tagCatIter) {
// get the tagging category
curEvtTagCat_ = tagCatIter->first;
// get the event weight for this category
const Double_t evtWeight( tagCatIter->second.second );
// get the number of events to generate in this configuration
const Int_t nEvtsGen( tagCatIter->second.first );
for (Int_t iEvt(0); iEvt<nEvtsGen; ++iEvt) {
this->setGenNtupleDoubleBranchValue( "evtWeight", evtWeight );
if (evtCategory == "signal") {
this->setGenNtupleIntegerBranchValue("genSig",1);
// 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 {
genOK = kFALSE;
}
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->setGenNtupleIntegerBranchValue("tagCat",curEvtTagCat_);
this->setGenNtupleIntegerBranchValue("tagFlv",curEvtTagFlv_);
this->setGenNtupleDoubleBranchValue(flavTag_->getMistagVarName(),curEvtMistag_);
// 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 events for given species, tagCat and tagFlv
if (!genOK) {
break;
}
} // end of loop over tagCats for the given species and tagFlv
if (!genOK) {
break;
}
} //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 (!signalTree_.empty() && (reuseSignal_ || !genOK)) {
if (reuseSignal_ || !genOK) {
for(LauTagCatEmbDataMap::const_iterator iter = signalTree_.begin(); iter != signalTree_.end(); ++iter) {
(iter->second)->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_);
// find the right decay time PDF for the current tagging category
LauTagCatDtPdfMap::const_iterator dt_iter = signalDecayTimePdfs_.find(curEvtTagCat_);
LauDecayTimePdf* decayTimePdf = (dt_iter != signalDecayTimePdfs_.end()) ? dt_iter->second : 0;
// find the right embedded data for the current tagging category
LauTagCatEmbDataMap::const_iterator emb_iter = signalTree_.find(curEvtTagCat_);
LauEmbeddedData* embeddedData = (emb_iter != signalTree_.end()) ? emb_iter->second : 0;
// find the right extra PDFs for the current tagging category
LauTagCatPdfListMap::iterator extra_iter = sigExtraPdf_.find(curEvtTagCat_);
LauPdfList* extraPdfs = (extra_iter != sigExtraPdf_.end()) ? &(extra_iter->second) : 0;
if (this->useDP()) {
if (embeddedData) {
embeddedData->getEmbeddedEvent(kinematics);
curEvtTagFlv_ = TMath::Nint(embeddedData->getValue("tagFlv"));
curEvtDecayTimeErr_ = embeddedData->getValue(decayTimePdf->varErrName());
curEvtDecayTime_ = embeddedData->getValue(decayTimePdf->varName());
if (embeddedData->haveBranch("mcMatch")) {
Int_t match = TMath::Nint(embeddedData->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_ = decayTimePdf->generateError(kTRUE);
while (generatedEvent == kFALSE && nGenLoop_ < iterationsMax_) {
// Calculate the unnormalised truth-matched signal likelihood
// First let define the tag flavour CONVENTION WARNING
Double_t randNo = LauRandom::randomFun()->Rndm();
if (randNo < 0.5) {
curEvtTagFlv_ = +1; // B0 tag
} else {
curEvtTagFlv_ = -1; // B0bar tag
}
// Calculate event quantities that depend only on the tagCat and tagFlv
Double_t qD(0.);
Double_t qDDo2(0.);
if(flavTag_->getUsePerEvtMistag() && curEvtTagCat_!=0 ){
curEvtMistag_ = flavTag_->getEtaGen(sigFlavTagPdf_[curEvtTagCat_]);
- Double_t omega = flavTag_->getOmegaGen(curEvtMistag_);
+ Double_t omega = flavTag_->getOmegaGen(curEvtMistag_,curEvtTagFlv_);
qD = curEvtTagFlv_*(1.0-2.0*omega);
//qD = curEvtTagFlv_*(1-2*curEvtMistag_);
}else{
curEvtMistag_ = 0.5;
LauTagCatParamMap dilution_ = flavTag_->getDilution();
LauTagCatParamMap deltaDilution_ = flavTag_->getDeltaDilution();
qD = curEvtTagFlv_*dilution_[curEvtTagCat_].unblindValue();
qDDo2 = curEvtTagFlv_*0.5*deltaDilution_[curEvtTagCat_].unblindValue();
}
// 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 = decayTimePdf->minAbscissa();
const Double_t tMax = decayTimePdf->maxAbscissa();
curEvtDecayTime_ = LauRandom::randomFun()->Rndm()*(tMax-tMin) + tMin;
// Calculate all the decay time info
decayTimePdf->calcLikelihoodInfo(curEvtDecayTime_,curEvtDecayTimeErr_);
// ...and check that the calculation went ok, otherwise loop again
if (decayTimePdf->state() != LauDecayTimePdf::Good) {
std::cout<<"decayTimePdf state is bad"<<std::endl;
++nGenLoop_;
continue;
}
// Get the decay time acceptance
Double_t dtEff = decayTimePdf->getEffiTerm();
// First get all the decay time terms
//Double_t dtExp = decayTimePdf->getExpTerm();
Double_t dtCos = decayTimePdf->getCosTerm();
Double_t dtSin = decayTimePdf->getSinTerm();
Double_t dtCosh = decayTimePdf->getCoshTerm();
Double_t dtSinh = decayTimePdf->getSinhTerm();
//std::cout << dtCos << " " << dtSin << " " << dtCosh << " " << dtSinh << std::endl;
// Combine all terms
Double_t cosTerm = dtCos * qD * aSqDif;
Double_t sinTerm = dtSin * qD * interTermIm;
Double_t coshTerm = dtCosh * (1.0 + qDDo2) * aSqSum;
Double_t sinhTerm = dtSinh * (1.0 + qDDo2) * interTermRe;
//std::cout << "dtCos * qD * aSqDif (dtSin * interTermIm) " << dtCos << " " << qD << " " << aSqDif << " " << dtSin << " " << interTermIm << std::endl;
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;
//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
randNo = LauRandom::randomFun()->Rndm();
if (randNo <= ASq/aSqMaxSet_ ) {
generatedEvent = kTRUE;
nGenLoop_ = 0;
if (ASq > aSqMaxVar_) {aSqMaxVar_ = ASq;}
} else {
nGenLoop_++;
}
} // end of while !generatedEvent loop
} // end of if (embeddedData) else control
} else {
if ( embeddedData ) {
embeddedData->getEmbeddedEvent(0);
curEvtTagFlv_ = TMath::Nint(embeddedData->getValue("tagFlv"));
curEvtDecayTimeErr_ = embeddedData->getValue(decayTimePdf->varErrName());
curEvtDecayTime_ = embeddedData->getValue(decayTimePdf->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(extraPdfs, embeddedData);
}
// Check for problems with the embedding
if (embeddedData && (embeddedData->nEvents() == embeddedData->nUsedEvents())) {
std::cerr<<"WARNING in LauTimeDepFitModel::generateSignalEvent : Source of embedded signal 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");
this->addGenNtupleIntegerBranch("tagFlv");
this->addGenNtupleIntegerBranch("tagCat");
if (this->useDP() == kTRUE) {
// Let's add the decay time variables.
if (signalDecayTimePdfs_.begin() != signalDecayTimePdfs_.end()) {
LauDecayTimePdf* pdf = signalDecayTimePdfs_.begin()->second;
this->addGenNtupleDoubleBranch(pdf->varName());
this->addGenNtupleDoubleBranch(pdf->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_.empty() ) {
LauPdfList oneTagCatPdfList = sigExtraPdf_.begin()->second;
for (LauPdfList::const_iterator pdf_iter = oneTagCatPdfList.begin(); pdf_iter != oneTagCatPdfList.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.
if (signalDecayTimePdfs_.begin() != signalDecayTimePdfs_.end()) {
LauDecayTimePdf* pdf = signalDecayTimePdfs_.begin()->second;
this->setGenNtupleDoubleBranchValue(pdf->varName(),curEvtDecayTime_);
this->setGenNtupleDoubleBranchValue(pdf->varErrName(),curEvtDecayTimeErr_);
}
// CONVENTION WARNING
LauKinematics* kinematics(0);
if (curEvtTagFlv_<0) {
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(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;
// TODO loop over the background yields and subtract
signalEvents_->range(-2.0*nTotEvts,2.0*nTotEvts);
if ( ! signalEvents_->fixed() ) {
signalEvents_->value(signalEvents);
}
}
// tagging-category fractions for signal events
flavTag_->setFirstTagCatFractions();
}
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
for (LauTagCatDtPdfMap::iterator dt_iter = signalDecayTimePdfs_.begin(); dt_iter != signalDecayTimePdfs_.end(); ++dt_iter) {
(*dt_iter).second->cacheInfo(*inputFitData);
}
}
// ...and then the extra PDFs
for (LauTagCatPdfListMap::iterator pdf_iter = sigExtraPdf_.begin(); pdf_iter != sigExtraPdf_.end(); ++pdf_iter) {
this->cacheInfo(pdf_iter->second, *inputFitData);
}
if (this->useDP() == kTRUE) {
sigModelB0bar_->fillDataTree(*inputFitData);
sigModelB0_->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_->getEvtTagFlvVals(iEvt);
// Also get the tagging category.
curEvtTagCat_ = flavTag_->getEvtTagCatVals(iEvt);
// 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)
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;
Double_t signalEvents = signalEvents_->unblindValue();
if (this->useDP() == kFALSE) {
signalEvents *= 0.5 * (1.0 + curEvtTagFlv_ * signalAsym_->unblindValue());
}
// TODO better to store this info for each event
LauTagCatParamMap& signalTagCatFrac = flavTag_->getSignalTagCatFrac();
const Double_t sigTagCatFrac = signalTagCatFrac[curEvtTagCat_].unblindValue();
//std::cout << "Signal tag cat frac = " << sigTagCatFrac << std::endl;
// Construct the total event likelihood
Double_t likelihood(sigLike*sigTagCatFrac);
//std::cout << "Likelihoood = " << likelihood << std::endl;
if ( ! signalEvents_->fixed() ) {
likelihood *= signalEvents;
}
return likelihood;
}
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.
sigDPLike_ = 1.0; //There's always a likelihood term for signal, so we better not zero it.
if ( this->useDP() == kFALSE ) {
return;
}
// Mistag probabilities. Defined as: omega = prob of the tagging B0 being reported as B0bar
// Whether we want omega or omegaBar depends on q_tag, hence curEvtTagFlv_*... in the previous lines
//Double_t misTagFrac = 0.5 * (1.0 - dilution_[curEvtTagCat_] - qDDo2);
//Double_t misTagFracBar = 0.5 * (1.0 - dilution_[curEvtTagCat_] + qDDo2);
// Calculate event quantities
Double_t qD(0);
Double_t qDDo2(0);
if (flavTag_->getUsePerEvtMistag()){
//qDDo2 term accounted for automatically with per event information
Double_t omega = flavTag_->getOmega(iEvt);
qD = curEvtTagFlv_*(1.0-2.0*omega);
} else {
// TODO need to sort out references here
LauTagCatParamMap dilution_ = flavTag_->getDilution();
LauTagCatParamMap deltaDilution_ = flavTag_->getDeltaDilution();
qD = curEvtTagFlv_*dilution_[curEvtTagCat_].unblindValue();
qDDo2 = curEvtTagFlv_*0.5*deltaDilution_[curEvtTagCat_].unblindValue();
}
// Get the dynamics to calculate everything required for the likelihood calculation
sigModelB0bar_->calcLikelihoodInfo(iEvt);
sigModelB0_->calcLikelihoodInfo(iEvt);
// 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
LauDecayTimePdf* decayTimePdf = signalDecayTimePdfs_[curEvtTagCat_];
decayTimePdf->calcLikelihoodInfo(iEvt);
// Get the decay time acceptance
Double_t dtEff = decayTimePdf->getEffiTerm();
// First get all the decay time terms
Double_t dtCos = decayTimePdf->getCosTerm();
Double_t dtSin = decayTimePdf->getSinTerm();
Double_t dtCosh = decayTimePdf->getCoshTerm();
Double_t dtSinh = decayTimePdf->getSinhTerm();
Double_t cosTerm = dtCos * qD * aSqDif;
Double_t sinTerm = dtSin * qD * interTermIm;
Double_t coshTerm = dtCosh * (1.0 + qDDo2) * aSqSum;
Double_t sinhTerm = dtSinh * (1.0 + qDDo2) * interTermRe;
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;
// Calculate the DP and time normalisation
Double_t normTermIndep = sigModelB0bar_->getDPNorm() + sigModelB0_->getDPNorm();
Double_t normTermCosh(0.0);
Double_t norm(0.0);
if (decayTimePdf->getFuncType() == LauDecayTimePdf::ExpTrig){
normTermCosh = decayTimePdf->getNormTermExp();
norm = normTermIndep*normTermCosh;
}
if (decayTimePdf->getFuncType() == LauDecayTimePdf::ExpHypTrig){
normTermCosh = decayTimePdf->getNormTermCosh();
Double_t normTermDep = interTermReNorm_;
Double_t normTermSinh = decayTimePdf->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
LauTagCatPdfListMap::iterator sig_iter = sigExtraPdf_.find(curEvtTagCat_);
LauPdfList* pdfList = (sig_iter != sigExtraPdf_.end())? &(sig_iter->second) : 0;
if (pdfList) {
sigExtraLike_ = this->prodPdfValue( *pdfList, iEvt );
}
}
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.
// First, those independent of the tagging of the event:
// signal
LauAbsPdf* pdf = sigFlavTagPdf_[curEvtTagCat_];
if (pdf) {
pdf->calcLikelihoodInfo(iEvt);
sigFlavTagLike_ = pdf->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(Int_t tagCat, const TString& fileName, const TString& treeName,
Bool_t reuseEventsWithinEnsemble, Bool_t reuseEventsWithinExperiment)
{
if (signalTree_[tagCat]) {
std::cerr<<"ERROR in LauTimeDepFitModel::embedSignal : Already embedding signal from file for tagging category "<<tagCat<<"."<<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_[tagCat] = new LauEmbeddedData(fileName,treeName,reuseEventsWithinExperiment);
Bool_t dataOK = signalTree_[tagCat]->findBranches();
if (!dataOK) {
delete signalTree_[tagCat]; signalTree_[tagCat] = 0;
std::cerr<<"ERROR in LauTimeDepFitModel::embedSignal : Problem creating data tree for embedding."<<std::endl;
return;
}
reuseSignal_ = reuseEventsWithinEnsemble;
}
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");
// Store the DP likelihoods
if (this->useDP()) {
this->addSPlotNtupleDoubleBranch("sigDPLike");
}
// Store the likelihoods for each extra PDF
const LauPdfList* pdfList( &(sigExtraPdf_.begin()->second) );
this->addSPlotNtupleBranches(pdfList, "sig");
}
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");
}
LauPdfList pdfList( (sigExtraPdf_.begin()->second) );
for (LauPdfList::const_iterator pdf_iter = pdfList.begin(); pdf_iter != pdfList.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();
}
return numbMap;
}
LauSPlot::NumbMap LauTimeDepFitModel::fixdSpeciesNames() const
{
LauSPlot::NumbMap numbMap;
if (signalEvents_->fixed() && this->doEMLFit()) {
numbMap["sig"] = signalEvents_->genValue();
}
return numbMap;
}
LauSPlot::TwoDMap LauTimeDepFitModel::twodimPDFs() const
{
LauSPlot::TwoDMap twodimMap;
const LauPdfList* pdfList = &(sigExtraPdf_.begin()->second);
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] ) ) );
}
}
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
curEvtTagFlv_ = flavTag_->getEvtTagFlvVals(iEvt);
curEvtTagCat_ = flavTag_->getEvtTagCatVals(iEvt);
curEvtMistag_ = flavTag_->getOmega(iEvt);
LauTagCatPdfListMap::iterator sig_iter = sigExtraPdf_.find(curEvtTagCat_);
LauPdfList* sigPdfs = (sig_iter != sigExtraPdf_.end())? &(sig_iter->second) : 0;
// 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_);
} else {
sigTotalLike_ = 1.0;
}
// the signal PDF values
sigTotalLike_ *= this->setSPlotNtupleBranchValues(sigPdfs, "sig", iEvt);
// the total likelihoods
this->setSPlotNtupleDoubleBranchValue("sigTotalLike",sigTotalLike_);
// 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::setSignalFlavTagPdfs(const Int_t tagCat, LauAbsPdf* pdf)
{
if (!flavTag_->validTagCat(tagCat)) {
std::cerr<<"ERROR in LauTimeDepFitModel::setSignalFlavTagPdfs : Tagging category \""<<tagCat<<"\" not valid, not adding models."<<std::endl;
return;
}
if (pdf==0) {
std::cerr<<"ERROR in LauTimeDepFitModel::setSignalFlavTagPdfs : The PDF pointer is null."<<std::endl;
return;
}
sigFlavTagPdf_[tagCat] = pdf;
}
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;
}

File Metadata

Mime Type
text/x-diff
Expires
Mon, Jan 20, 10:26 PM (1 d, 13 h)
Storage Engine
blob
Storage Format
Raw Data
Storage Handle
4242656
Default Alt Text
(198 KB)

Event Timeline