diff --git a/src/LauTimeDepFitModel.cc b/src/LauTimeDepFitModel.cc
index 3bc1779..aa11f2c 100644
--- a/src/LauTimeDepFitModel.cc
+++ b/src/LauTimeDepFitModel.cc
@@ -1,3377 +1,3377 @@
 
 /*
 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 <algorithm>
 #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 "LauParamFixed.hh"
 #include "LauPrint.hh"
 #include "LauRandom.hh"
 #include "LauScfMap.hh"
 #include "LauTimeDepFitModel.hh"
 #include "LauFlavTag.hh"
 
 ClassImp(LauTimeDepFitModel)
 
 LauTimeDepFitModel::LauTimeDepFitModel(LauIsobarDynamics* modelB0bar, LauIsobarDynamics* modelB0, LauFlavTag* flavTag) : LauAbsFitModel(),
 	sigModelB0bar_(modelB0bar),
 	sigModelB0_(modelB0),
 	kinematicsB0bar_(modelB0bar ? modelB0bar->getKinematics() : 0),
 	kinematicsB0_(modelB0 ? modelB0->getKinematics() : 0),
 	usingBkgnd_(kFALSE),
 	flavTag_(flavTag),
 	curEvtTrueTagFlv_(LauFlavTag::Unknown),
 	curEvtDecayFlv_(LauFlavTag::Unknown),
 	nSigComp_(0),
 	nSigDPPar_(0),
 	nDecayTimePar_(0),
 	nExtraPdfPar_(0),
 	nNormPar_(0),
 	nCalibPar_(0),
 	nTagEffPar_(0),
 	nEffiPar_(0),
 	nAsymPar_(0),
 	coeffsB0bar_(0),
 	coeffsB0_(0),
 	coeffPars_(0),
 	fitFracB0bar_(0),
 	fitFracB0_(0),
 	fitFracAsymm_(0),
 	acp_(0),
 	meanEffB0bar_("meanEffB0bar",0.0,0.0,1.0),
 	meanEffB0_("meanEffB0",0.0,0.0,1.0),
 	DPRateB0bar_("DPRateB0bar",0.0,0.0,100.0),
 	DPRateB0_("DPRateB0",0.0,0.0,100.0),
 	signalEvents_(0),
 	signalAsym_(0),
 	cpevVarName_(""),
 	cpEigenValue_(CPEven),
 	evtCPEigenVals_(0),
 	deltaM_("deltaM",0.0),
 	deltaGamma_("deltaGamma",0.0),
 	tau_("tau",LauConstants::tauB0),
 	phiMix_("phiMix", 2.0*LauConstants::beta, -LauConstants::threePi, LauConstants::threePi, kFALSE),
 	sinPhiMix_("sinPhiMix", TMath::Sin(2.0*LauConstants::beta), -1.0, 1.0, kFALSE),
 	cosPhiMix_("cosPhiMix", TMath::Cos(2.0*LauConstants::beta), -1.0, 1.0, kFALSE),
 	useSinCos_(kFALSE),
 	phiMixComplex_(TMath::Cos(-2.0*LauConstants::beta),TMath::Sin(-2.0*LauConstants::beta)),
 	signalDecayTimePdf_(),
 	BkgndTypes_(),
 	BkgndDecayTimePdfs_(),
 	curEvtDecayTime_(0.0),
 	curEvtDecayTimeErr_(0.0),
 	sigExtraPdf_(),
 	sigFlavTagPdf_(),
 	bkgdFlavTagPdf_(),
 	AProd_("AProd",0.0,-1.0,1.0,kTRUE),
 	iterationsMax_(100000000),
 	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?
 	this->setBkgndClassNames(flavTag_->getBkgndNames());
 	const ULong_t nBkgnds { this->nBkgndClasses() };
 	if ( nBkgnds > 0 ){
 		usingBkgnd_ = kTRUE;
-		for ( ULong_t iBkgnd{0}; i < nBkgnds; ++iBkgnd ) {
+		for ( ULong_t iBkgnd{0}; iBkgnd < nBkgnds; ++iBkgnd ) {
 			const TString& bkgndClass { this->bkgndClassName( iBkgnd ) };
 			AProdBkgnd_[iBkgnd] = new LauParameter("AProd_"+bkgndClass,0.0,-1.0,1.0,kTRUE);
 		}
 	}
 
 	// Make sure that the integration scheme will be symmetrised
 	sigModelB0bar_->forceSymmetriseIntegration(kTRUE);
 	sigModelB0_->forceSymmetriseIntegration(kTRUE);
 }
 
 LauTimeDepFitModel::~LauTimeDepFitModel()
 {
 	for ( LauAbsPdf* pdf : sigExtraPdf_ ) {
 		delete pdf;
 	}
 
 	for(auto& data : bkgndTree_){
 		delete data;
 	}
 }
 
 void LauTimeDepFitModel::setupBkgndVectors()
 {
 	UInt_t nBkgnds { this->nBkgndClasses() };
 	AProdBkgnd_.resize( nBkgnds );
 	BkgndDPModelsB_.resize( nBkgnds );
 	BkgndDPModelsBbar_.resize( nBkgnds );
 	BkgndDecayTimePdfs_.resize( nBkgnds );
 	BkgndPdfs_.resize( nBkgnds );
 	bkgndEvents_.resize( nBkgnds );
 	bkgndAsym_.resize( nBkgnds );
 	bkgndTree_.resize( nBkgnds );
 	reuseBkgnd_.resize( nBkgnds );
 	bkgndDPLike_.resize( nBkgnds );
 	bkgndExtraLike_.resize( nBkgnds );
 	bkgndTotalLike_.resize( nBkgnds );
 }
 
 void LauTimeDepFitModel::setNSigEvents(LauParameter* nSigEvents)
 {
 	if ( nSigEvents == 0 ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : The LauParameter pointer is null." << std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 	if ( signalEvents_ != 0 ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : You are trying to overwrite the signal yield." << std::endl;
 		return;
 	}
 	if ( signalAsym_ != 0 ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : You are trying to overwrite the signal asymmetry." << std::endl;
 		return;
 	}
 
 	signalEvents_ = nSigEvents;
 
 	signalEvents_->name("signalEvents");
 
 	Double_t value = nSigEvents->value();
 	signalEvents_->range(-2.0*(TMath::Abs(value)+1.0),2.0*(TMath::Abs(value)+1.0));
 
 	signalAsym_ = new LauParameter("signalAsym",0.0,-1.0,1.0,kTRUE);
 }
 
 void LauTimeDepFitModel::setNSigEvents(LauParameter* nSigEvents, LauParameter* sigAsym)
 {
 	if ( nSigEvents == 0 ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : The event LauParameter pointer is null." << std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 	if ( sigAsym == 0 ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : The asym LauParameter pointer is null." << std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 	if ( signalEvents_ != 0 ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : You are trying to overwrite the signal yield." << std::endl;
 		return;
 	}
 	if ( signalAsym_ != 0 ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : You are trying to overwrite the signal asymmetry." << std::endl;
 		return;
 	}
 
 	signalEvents_ = nSigEvents;
 	signalEvents_->name("signalEvents");
 	Double_t value = nSigEvents->value();
 	signalEvents_->range(-2.0*(TMath::Abs(value)+1.0), 2.0*(TMath::Abs(value)+1.0));
 
 	signalAsym_ = sigAsym;
 	signalAsym_->name("signalAsym");
 	signalAsym_->range(-1.0,1.0);
 }
 
 void LauTimeDepFitModel::setNBkgndEvents(LauAbsRValue* nBkgndEvents)
 {
          if ( nBkgndEvents == 0 ) {
                 std::cerr << "ERROR in LauTimeDepFitModel::setNBgkndEvents : The background yield LauParameter pointer is null." << std::endl;
                 gSystem->Exit(EXIT_FAILURE);
         }
 
         if ( ! this->validBkgndClass( nBkgndEvents->name() ) ) {
                 std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : Invalid background class \"" << nBkgndEvents->name() << "\"." << std::endl;
                 std::cerr << "                                        : Background class names must be provided in \"setBkgndClassNames\" before any other background-related actions can be performed." << std::endl;
                 gSystem->Exit(EXIT_FAILURE);
         }
 
         UInt_t bkgndID = this->bkgndClassID( nBkgndEvents->name() );
 
         if ( bkgndEvents_[bkgndID] != 0 ) {
                 std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : You are trying to overwrite the background yield." << std::endl;
                 return;
         }
 
         if ( bkgndAsym_[bkgndID] != 0 ) {
                 std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : You are trying to overwrite the background asymmetry." << std::endl;
                 return;
         }
 
         nBkgndEvents->name( nBkgndEvents->name()+"Events" );
 	if ( nBkgndEvents->isLValue() ) {
 		Double_t value = nBkgndEvents->value();
 		LauParameter* yield = dynamic_cast<LauParameter*>( nBkgndEvents );
 		yield->range(-2.0*(TMath::Abs(value)+1.0), 2.0*(TMath::Abs(value)+1.0));
 	}
         bkgndEvents_[bkgndID] = nBkgndEvents;
 
         bkgndAsym_[bkgndID] = new LauParameter(nBkgndEvents->name()+"Asym",0.0,-1.0,1.0,kTRUE);
 }
 
 void LauTimeDepFitModel::setNBkgndEvents(LauAbsRValue* nBkgndEvents, LauAbsRValue* bkgndAsym)
 {
         if ( nBkgndEvents == 0 ) {
                 std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : The background yield LauParameter pointer is null." << std::endl;
                 gSystem->Exit(EXIT_FAILURE);
         }
 
         if ( bkgndAsym == 0 ) {
                 std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : The background asym LauParameter pointer is null." << std::endl;
                 gSystem->Exit(EXIT_FAILURE);
         }
 
         if ( ! this->validBkgndClass( nBkgndEvents->name() ) ) {
                 std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : Invalid background class \"" << nBkgndEvents->name() << "\"." << std::endl;
                 std::cerr << "                                        : Background class names must be provided in \"setBkgndClassNames\" before any other background-related actions can be performed." << std::endl;
                 gSystem->Exit(EXIT_FAILURE);
         }
 
         UInt_t bkgndID = this->bkgndClassID( nBkgndEvents->name() );
 
         if ( bkgndEvents_[bkgndID] != 0 ) {
                 std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : You are trying to overwrite the background yield." << std::endl;
                 return;
         }
 
         if ( bkgndAsym_[bkgndID] != 0 ) {
                 std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : You are trying to overwrite the background asymmetry." << std::endl;
                 return;
         }
 
         bkgndEvents_[bkgndID]->name( nBkgndEvents->name()+"Events" );
 	if ( nBkgndEvents->isLValue() ) {
 		Double_t value = nBkgndEvents->value();
 		LauParameter* yield = dynamic_cast<LauParameter*>( nBkgndEvents );
 		yield->range(-2.0*(TMath::Abs(value)+1.0), 2.0*(TMath::Abs(value)+1.0));
 	}
         bkgndEvents_[bkgndID] = nBkgndEvents;
 
         bkgndAsym_[bkgndID]->name( nBkgndEvents->name()+"Asym" );
 	if ( bkgndAsym->isLValue() ) {
 		LauParameter* asym = dynamic_cast<LauParameter*>( bkgndAsym );
 		asym->range(-1.0, 1.0);
 	}
         bkgndAsym_[bkgndID] = bkgndAsym;
 }
 
 void LauTimeDepFitModel::setSignalDtPdf(LauDecayTimePdf* pdf)
 {
 	if (pdf==0) {
 		std::cerr<<"ERROR in LauTimeDepFitModel::setSignalDtPdf : The PDF pointer is null, not adding it."<<std::endl;
 		return;
 	}
 	signalDecayTimePdf_ = pdf;
 }
 
 void LauTimeDepFitModel::setBkgndDtPdf(const TString& bkgndClass, LauDecayTimePdf* pdf)
 {
 	// TODO If these are all histograms shouldn't need to add much more code in other functions
 	if (pdf==0) {
 		std::cerr<<"ERROR in LauTimeDepFitModel::setBkgndDtPdf : The PDF pointer is null, not adding it."<<std::endl;
 		return;
 	}
 
 	// check that this background name is valid
 	if ( ! this->validBkgndClass( bkgndClass) ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setBkgndDtPdf : Invalid background class \"" << bkgndClass << "\"." << std::endl;
 		std::cerr << "                                           : Background class names must be provided in \"setBkgndClassNames\" before any other background-related actions can be performed." << std::endl;
 		return;
 	}
 	UInt_t bkgndID = this->bkgndClassID( bkgndClass );
 	BkgndDecayTimePdfs_[bkgndID] = pdf;
 
 	usingBkgnd_ = kTRUE;
 }
 
 void LauTimeDepFitModel::setBkgndDPModels(const TString& bkgndClass, LauAbsBkgndDPModel* BModel, LauAbsBkgndDPModel* BbarModel)
 {
 	if (BModel==nullptr) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setBkgndDPModels : the model pointer is null for the particle model." << std::endl;
 		return;
 	}
 
 	// check that this background name is valid
 	if ( ! this->validBkgndClass( bkgndClass) ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setBkgndDPModels : Invalid background class \"" << bkgndClass << "\"." << std::endl;
 		std::cerr << "                                        : Background class names must be provided in \"setBkgndClassNames\" before any other background-related actions can be performed." << std::endl;
 		return;
 	}
 
 	UInt_t bkgndID = this->bkgndClassID( bkgndClass );
 	BkgndDPModelsB_[bkgndID] = BModel;
 	if (BbarModel==nullptr) {
 		std::cout << "INFO in LauTimeDepFitModel::setBkgndDPModels : the model pointer is null for the anti-particle model. Using only the particle model." << std::endl;
 		BkgndDPModelsBbar_[bkgndID] = nullptr;
 	} else {
 		BkgndDPModelsBbar_[bkgndID] = BbarModel;
 	}
 
 	usingBkgnd_ = kTRUE;
 }
 
 void LauTimeDepFitModel::setSignalPdfs(LauAbsPdf* pdf)
 {
 	// These "extra variables" are assumed to be purely kinematical, like mES and DeltaE
 	//or making use of Rest of Event information, and therefore independent of whether
 	//the parent is a B0 or a B0bar. If this assupmtion doesn't hold, do modify this part!
 	if (pdf==0) {
 		std::cerr<<"ERROR in LauTimeDepFitModel::setSignalPdfs : The PDF pointer is null."<<std::endl;
 		return;
 	}
 
 	sigExtraPdf_.push_back(pdf);
 }
 
 void LauTimeDepFitModel::setBkgndPdf(const TString& bkgndClass, LauAbsPdf* pdf)
 {
 	if (pdf==0) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setBkgndPdf : PDF pointer is null." << std::endl;
 		return;
 	}
 
 	// check that this background name is valid
 	if ( ! this->validBkgndClass( bkgndClass ) ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setBkgndPdf : Invalid background class \"" << bkgndClass << "\"." << std::endl;
 		std::cerr << "                                     : Background class names must be provided in \"setBkgndClassNames\" before any other background-related actions can be performed." << std::endl;
 		return;
 	}
 
 	UInt_t bkgndID = this->bkgndClassID( bkgndClass );
 	BkgndPdfs_[bkgndID].push_back(pdf);
 
 	usingBkgnd_ = kTRUE;
 }
 
 void LauTimeDepFitModel::setPhiMix(const Double_t phiMix, const Bool_t fixPhiMix, const Bool_t useSinCos)
 {
 	phiMix_.value(phiMix);  phiMix_.initValue(phiMix);  phiMix_.genValue(phiMix);  phiMix_.fixed(fixPhiMix);
 
 	const Double_t sinPhiMix = TMath::Sin(phiMix);
 	sinPhiMix_.value(sinPhiMix); sinPhiMix_.initValue(sinPhiMix); sinPhiMix_.genValue(sinPhiMix); sinPhiMix_.fixed(fixPhiMix);
 
 	const Double_t cosPhiMix = TMath::Cos(phiMix);
 	cosPhiMix_.value(cosPhiMix); cosPhiMix_.initValue(cosPhiMix); cosPhiMix_.genValue(cosPhiMix); cosPhiMix_.fixed(fixPhiMix);
 
 	useSinCos_ = useSinCos;
 
 	phiMixComplex_.setRealPart(cosPhiMix);
 	phiMixComplex_.setImagPart(-1.0*sinPhiMix);
 }
 
 void LauTimeDepFitModel::initialise()
 {
 	// From the initial parameter values calculate the coefficients
 	// so they can be passed to the signal model
 	this->updateCoeffs();
 
 	// Initialisation
 	if (this->useDP() == kTRUE) {
 		this->initialiseDPModels();
 	}
 
 	// Flavour tagging
 	//flavTag_->initialise();
 
 	// Decay-time PDFs
 	signalDecayTimePdf_->initialise();
 
 	//Initialise for backgrounds if necessary
 	for (auto& pdf : BkgndDecayTimePdfs_){
 		pdf->initialise();
 	}
 
 	if (!this->useDP() && sigExtraPdf_.empty()) {
 		std::cerr<<"ERROR in LauTimeDepFitModel::initialise : Signal model doesn't exist for any variable."<<std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 
 	if (this->useDP() == kTRUE) {
 		// Check that we have all the Dalitz-plot models
 		if ((sigModelB0bar_ == 0) || (sigModelB0_ == 0)) {
 			std::cerr<<"ERROR in LauTimeDepFitModel::initialise : the pointer to one (particle or anti-particle) of the signal DP models is null."<<std::endl;
 			gSystem->Exit(EXIT_FAILURE);
 		}
 	}
 
 	// Next check that, if a given component is being used we've got the
 	// right number of PDFs for all the variables involved
 	// TODO - should probably check variable names and so on as well
 
 	//UInt_t nsigpdfvars(0);
 	//for ( LauPdfList::const_iterator pdf_iter = sigExtraPdf_.begin(); pdf_iter != sigExtraPdf_.end(); ++pdf_iter ) {
 	//	std::vector<TString> varNames = (*pdf_iter)->varNames();
 	//	for ( std::vector<TString>::const_iterator var_iter = varNames.begin(); var_iter != varNames.end(); ++var_iter ) {
 	//		if ( (*var_iter) != "m13Sq" && (*var_iter) != "m23Sq" ) {
 	//			++nsigpdfvars;
 	//		}
 	//	}
 	//}
 
 	//if (usingBkgnd_) {
 	//	for (LauBkgndPdfsList::const_iterator bgclass_iter = BkgndPdfsB0_.begin(); bgclass_iter != BkgndPdfsB0_.end(); ++bgclass_iter) {
 	//		UInt_t nbkgndpdfvars(0);
 	//		const LauPdfList& pdfList = (*bgclass_iter);
 	//		for ( LauPdfList::const_iterator pdf_iter = pdfList.begin(); pdf_iter != pdfList.end(); ++pdf_iter ) {
 	//			std::vector<TString> varNames = (*pdf_iter)->varNames();
 	//			for ( std::vector<TString>::const_iterator var_iter = varNames.begin(); var_iter != varNames.end(); ++var_iter ) {
 	//				if ( (*var_iter) != "m13Sq" && (*var_iter) != "m23Sq" ) {
 	//					++nbkgndpdfvars;
 	//				}
 	//			}
 	//		}
 	//		if (nbkgndpdfvars != nsigpdfvars) {
 	//			std::cerr << "ERROR in LauTimeDepFitModel::initialise : There are " << nsigpdfvars << " signal PDF variables but " << nbkgndpdfvars << " bkgnd PDF variables." << std::endl;
 	//			gSystem->Exit(EXIT_FAILURE);
 	//		}
 	//	}
 	//}
 
 	// Clear the vectors of parameter information so we can start from scratch
 	this->clearFitParVectors();
 
 	// Set the fit parameters for signal and background models
 	this->setSignalDPParameters();
 
 	// Set the fit parameters for the decay time models
 	this->setDecayTimeParameters();
 
 	// Set the fit parameters for the extra PDFs
 	this->setExtraPdfParameters();
 
 	// Set the initial bg and signal events
 	this->setFitNEvents();
 
 	// Handle flavour-tagging calibration parameters
 	this->setCalibParams();
 
 	// Add tagging efficiency parameters
 	this->setTagEffParams();
 
 	// Add the efficiency parameters
 	this->setEffiParams();
 
 	//Asymmetry terms AProd and in setAsymmetries()?
 	this->setAsymParams();
 
 	// Check that we have the expected number of fit variables
 	const LauParameterPList& fitVars = this->fitPars();
 	if (fitVars.size() != (nSigDPPar_ + nDecayTimePar_ + nExtraPdfPar_ + nNormPar_ + nCalibPar_ + nTagEffPar_ + nEffiPar_ + nAsymPar_)) {
 		std::cerr<<"ERROR in LauTimeDepFitModel::initialise : Number of fit parameters not of expected size."<<std::endl;
 		std::cout<< fitVars.size() << " != " << nSigDPPar_  << nDecayTimePar_ << nExtraPdfPar_ << nNormPar_ << nCalibPar_ << nTagEffPar_ << nEffiPar_ << nAsymPar_ << std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 
 	this->setExtraNtupleVars();
 }
 
 void LauTimeDepFitModel::recalculateNormalisation()
 {
 	sigModelB0bar_->recalculateNormalisation();
 	sigModelB0_->recalculateNormalisation();
 	sigModelB0bar_->modifyDataTree();
 	sigModelB0_->modifyDataTree();
 	this->calcInterferenceTermIntegrals();
 }
 
 void LauTimeDepFitModel::initialiseDPModels()
 {
 	if (sigModelB0bar_ == 0) {
 		std::cerr<<"ERROR in LauTimeDepFitModel::initialiseDPModels : B0bar signal DP model doesn't exist"<<std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 	if (sigModelB0_ == 0) {
 		std::cerr<<"ERROR in LauTimeDepFitModel::initialiseDPModels : B0 signal DP model doesn't exist"<<std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 
 	// Need to check that the number of components we have and that the dynamics has matches up
 	const UInt_t nAmpB0bar = sigModelB0bar_->getnTotAmp();
 	const UInt_t nAmpB0 = sigModelB0_->getnTotAmp();
 	if ( nAmpB0bar != nAmpB0 ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::initialiseDPModels : Unequal number of signal DP components in the particle and anti-particle models: " << nAmpB0bar << " != " << nAmpB0 << std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 	if ( nAmpB0bar != nSigComp_ ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::initialiseDPModels : Number of signal DP components in the model (" << nAmpB0bar << ") not equal to number of coefficients supplied (" << nSigComp_ << ")." << std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 
 	std::cout<<"INFO in LauTimeDepFitModel::initialiseDPModels : Initialising signal DP model"<<std::endl;
 	sigModelB0bar_->initialise(coeffsB0bar_);
 	sigModelB0_->initialise(coeffsB0_);
 
 	fifjEffSum_.clear();
 	fifjEffSum_.resize(nSigComp_);
 	for (UInt_t iAmp = 0; iAmp < nSigComp_; ++iAmp) {
 		fifjEffSum_[iAmp].resize(nSigComp_);
 	}
 
 	// calculate the integrals of the A*Abar terms
 	this->calcInterferenceTermIntegrals();
 
 	this->calcInterTermNorm();
 
 	// Add backgrounds
 	if (usingBkgnd_ == kTRUE) {
 		for (auto& model : BkgndDPModelsB_){
 			model->initialise();
 		}
 		for (auto& model : BkgndDPModelsBbar_){
 			if (model != nullptr) {
 				model->initialise();
 			}
 		}
 	}
 
 }
 
 void LauTimeDepFitModel::calcInterferenceTermIntegrals()
 {
 	const std::vector<LauDPPartialIntegralInfo*>& integralInfoListB0bar = sigModelB0bar_->getIntegralInfos();
 	const std::vector<LauDPPartialIntegralInfo*>& integralInfoListB0 = sigModelB0_->getIntegralInfos();
 
 	// TODO should check (first time) that they match in terms of number of entries in the vectors and that each entry has the same number of points, ranges, weights etc.
 
 	LauComplex A, Abar, fifjEffSumTerm;
 
 	for (UInt_t iAmp = 0; iAmp < nSigComp_; ++iAmp) {
 		for (UInt_t jAmp = 0; jAmp < nSigComp_; ++jAmp) {
 			fifjEffSum_[iAmp][jAmp].zero();
 		}
 	}
 
 
 	const UInt_t nIntegralRegions = integralInfoListB0bar.size();
 	for ( UInt_t iRegion(0); iRegion < nIntegralRegions; ++iRegion ) {
 
 		const LauDPPartialIntegralInfo* integralInfoB0bar = integralInfoListB0bar[iRegion];
 		const LauDPPartialIntegralInfo* integralInfoB0 = integralInfoListB0[iRegion];
 
 		const UInt_t nm13Points = integralInfoB0bar->getnm13Points();
 		const UInt_t nm23Points = integralInfoB0bar->getnm23Points();
 
 		for (UInt_t m13 = 0; m13 < nm13Points; ++m13) {
 			for (UInt_t m23 = 0; m23 < nm23Points; ++m23) {
 
 				const Double_t weight = integralInfoB0bar->getWeight(m13,m23);
 				const Double_t eff = integralInfoB0bar->getEfficiency(m13,m23);
 				const Double_t effWeight = eff*weight;
 
 				for (UInt_t iAmp = 0; iAmp < nSigComp_; ++iAmp) {
 
 					A = integralInfoB0->getAmplitude(m13, m23, iAmp);
 
 					for (UInt_t jAmp = 0; jAmp < nSigComp_; ++jAmp) {
 
 						Abar = integralInfoB0bar->getAmplitude(m13, m23, jAmp);
 
 						fifjEffSumTerm = Abar*A.conj();
 
 						fifjEffSumTerm.rescale(effWeight);
 						fifjEffSum_[iAmp][jAmp] += fifjEffSumTerm;
 					}
 				}
 
 			}
 		}
 	}
 
 }
 
 void LauTimeDepFitModel::calcInterTermNorm()
 {
 	const std::vector<Double_t>& fNormB0bar = sigModelB0bar_->getFNorm();
 	const std::vector<Double_t>& fNormB0 = sigModelB0_->getFNorm();
 
 	LauComplex norm;
 	for (UInt_t iAmp = 0; iAmp < nSigComp_; ++iAmp) {
 		for (UInt_t jAmp = 0; jAmp < nSigComp_; ++jAmp) {
 
 			LauComplex coeffTerm = coeffsB0bar_[jAmp]*coeffsB0_[iAmp].conj();
 			coeffTerm *= fifjEffSum_[iAmp][jAmp];
 			coeffTerm.rescale(fNormB0bar[jAmp] * fNormB0[iAmp]);
 
 			norm += coeffTerm;
 		}
 	}
 	norm *= phiMixComplex_;
 
 	interTermReNorm_ = 2.0*norm.re();
 	interTermImNorm_ = 2.0*norm.im();
 }
 
 void LauTimeDepFitModel::setAmpCoeffSet(LauAbsCoeffSet* coeffSet)
 {
 	// Is there a component called compName in the signal models?
 	TString compName = coeffSet->name();
 	TString conjName = sigModelB0bar_->getConjResName(compName);
 
 	const LauDaughters* daughtersB0bar = sigModelB0bar_->getDaughters();
 	const LauDaughters* daughtersB0 = sigModelB0_->getDaughters();
 	const Bool_t conjugate = daughtersB0bar->isConjugate( daughtersB0 );
 
 	if ( ! sigModelB0bar_->hasResonance(compName) ) {
 		if ( ! sigModelB0bar_->hasResonance(conjName) ) {
 			std::cerr<<"ERROR in LauTimeDepFitModel::setAmpCoeffSet : B0bar signal DP model doesn't contain component \""<<compName<<"\"."<<std::endl;
 			return;
 		}
 		std::cerr<<"WARNING in LauTimeDepFitModel::setAmpCoeffSet : B0bar signal DP model doesn't contain component \""<<compName<<"\" but does contain the conjugate \""<<conjName<<"\", resetting name to use the conjugate."<<std::endl;
 		TString tmp = compName;
 		compName = conjName;
 		conjName = tmp;
 		coeffSet->name( compName );
 	}
 
 	if ( conjugate ) {
 		if ( ! sigModelB0_->hasResonance(conjName) ) {
 			std::cerr<<"ERROR in LauTimeDepFitModel::setAmpCoeffSet : B0 signal DP model doesn't contain component \""<<conjName<<"\"."<<std::endl;
 			return;
 		}
 	} else {
 		if ( ! sigModelB0_->hasResonance(compName) ) {
 			std::cerr<<"ERROR in LauTimeDepFitModel::setAmpCoeffSet : B0 signal DP model doesn't contain component \""<<compName<<"\"."<<std::endl;
 			return;
 		}
 	}
 
 	// Do we already have it in our list of names?
 	for (auto& coeffset : coeffPars_){
 		if (coeffset->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 (auto& param : pars){
 			if ( !param->clone() ) {
 				fitVars.push_back(param);
 				++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 (auto& param : sigDPParsB0bar){
 		if ( resVars.insert(param).second ) {
 			fitVars.push_back(param);
 			++nSigDPPar_;
 		}
 	}
 	for (auto& param : sigDPParsB0){
 		if ( resVars.insert(param).second ) {
 			fitVars.push_back(param);
 			++nSigDPPar_;
 		}
 	}
 }
 
 UInt_t LauTimeDepFitModel::addParametersToFitList(std::vector<LauDecayTimePdf*> theVector)
 {
 	UInt_t counter(0);
 	LauParameterPList& fitVars = this->fitPars();
 	// loop through the map
 	for (auto& pdf : theVector){
 		// grab the pdf and then its parameters
 		LauAbsRValuePList& rvalues = pdf->getParameters();
 		// loop through the parameters
 		for (auto& parlist : rvalues){
 			LauParameterPList params = parlist->getPars();
 			for (auto& par : params){
 				// for each "original" parameter add it to the list of fit parameters and increment the counter
 				if ( !par->clone() && ( !par->fixed() ||
 							(this->twoStageFit() && par->secondStage()) ) ) {
 					fitVars.push_back(par);
 					++counter;
 				}
 			}
 		}
 	}
 	return counter;
 }
 
 UInt_t LauTimeDepFitModel::addParametersToFitList(LauPdfList* theList)
 {
 	UInt_t counter(0);
 	counter += this->addFitParameters(*(theList));
 	return counter;
 }
 
 void LauTimeDepFitModel::setDecayTimeParameters()
 {
 	nDecayTimePar_ = 0;
 
 	std::cout << "INFO in LauTimeDepFitModel::setDecayTimeParameters : Setting the initial fit parameters of the DecayTime Pdfs." << std::endl;
 
 	LauParameterPList& fitVars = this->fitPars();
 
 	// Loop over the Dt PDFs
 	LauAbsRValuePList& rvalues = signalDecayTimePdf_->getParameters();
 	// loop through the parameters
 	for (auto& parlist : rvalues){
 		LauParameterPList params = parlist->getPars();
 		for (auto& par : params){
 			// for each "original" parameter add it to the list of fit parameters and increment the counter
 			if ( !par->clone() && ( !par->fixed() ||
 						(this->twoStageFit() && par->secondStage()) ) ) {
 				fitVars.push_back(par);
 				++nDecayTimePar_;
 			}
 		}
 	}
 
 	if (usingBkgnd_){
 		nDecayTimePar_ += this->addParametersToFitList(BkgndDecayTimePdfs_);
 	}
 
 	if (useSinCos_) {
 		if ( not sinPhiMix_.fixed() ) {
 			fitVars.push_back(&sinPhiMix_);
 			fitVars.push_back(&cosPhiMix_);
 			nDecayTimePar_ += 2;
 		}
 	} else {
 		if ( not phiMix_.fixed() ) {
 			fitVars.push_back(&phiMix_);
 			++nDecayTimePar_;
 		}
 	}
 }
 
 void LauTimeDepFitModel::setExtraPdfParameters()
 {
 	// Include the parameters of the PDF for each tagging category in the fit
 	// NB all of them are passed to the fit, even though some have been fixed through parameter.fixed(kTRUE)
 	// With the new "cloned parameter" scheme only "original" parameters are passed to the fit.
 	// Their clones are updated automatically when the originals are updated.
 
 	nExtraPdfPar_ = 0;
 
 	std::cout << "INFO in LauTimeDepFitModel::setExtraPdfParameters : Setting the initial fit parameters of the extra Pdfs." << std::endl;
 
 	nExtraPdfPar_ += this->addFitParameters(sigExtraPdf_);
 
 	if (usingBkgnd_ == kTRUE) {
 		for (auto& pdf : BkgndPdfs_){
 			nExtraPdfPar_ += this->addFitParameters(pdf);
 		}
 	}
 }
 
 void LauTimeDepFitModel::setFitNEvents()
 {
 	nNormPar_ = 0;
 
 	std::cout << "INFO in LauTimeDepFitModel::setFitNEvents : Setting the initial fit parameters of the signal and background yields." << std::endl;
 
 	// Initialise the total number of events to be the sum of all the hypotheses
 	Double_t nTotEvts = signalEvents_->value();
 
 	this->eventsPerExpt(TMath::FloorNint(nTotEvts));
 
 	LauParameterPList& fitVars = this->fitPars();
 
 	// if doing an extended ML fit add the signal fraction into the fit parameters
 	if (this->doEMLFit()) {
 		std::cout<<"INFO in LauTimeDepFitModel::setFitNEvents : Initialising number of events for signal and background components..."<<std::endl;
 		if ( not signalEvents_->fixed() ) {
 			fitVars.push_back(signalEvents_);
 			++nNormPar_;
 		}
 	} else {
 		std::cout<<"INFO in LauTimeDepFitModel::setFitNEvents : Initialising number of events for background components (and hence signal)..."<<std::endl;
 	}
 
 	// if not using the DP in the model we need an explicit signal asymmetry parameter
 	if (this->useDP() == kFALSE) {
 		fitVars.push_back(signalAsym_);
 		++nNormPar_;
 	}
 
 	// TODO arguably should delegate this
 	//LauTagCatParamMap& signalTagCatFrac = flavTag_->getSignalTagCatFrac();
 
 	// tagging-category fractions for signal events
 	//for (LauTagCatParamMap::iterator iter = signalTagCatFrac.begin(); iter != signalTagCatFrac.end(); ++iter) {
 	//	if (iter == signalTagCatFrac.begin()) {
 	//		continue;
 	//	}
 	//	LauParameter* par = &((*iter).second);
 	//	fitVars.push_back(par);
 	//	++nNormPar_;
 	//}
 
 	// Backgrounds
 	if (usingBkgnd_ == kTRUE) {
 		for (auto& params : bkgndEvents_){
 			std::vector<LauParameter*> parameters = params->getPars();
 			for ( LauParameter* parameter : parameters ) {
 				if (parameter->fixed()){continue;}
 				if(!parameter->clone()) {
 					fitVars.push_back(parameter);
 					++nNormPar_;
 				}
 			}
 		}
 		for (auto& params : bkgndAsym_){
 			std::vector<LauParameter*> parameters = params->getPars();
 			for ( LauParameter* parameter : parameters ) {
 				if (parameter->fixed()){continue;}
 				if(!parameter->clone()) {
 					fitVars.push_back(parameter);
 					++nNormPar_;
 				}
 			}
 		}
 	}
 }
 
 void LauTimeDepFitModel::setAsymParams()
 {
 	nAsymPar_ = 0;
 
 	//Signal
 	LauParameterPList& fitVars = this->fitPars();
 	if (!AProd_.fixed()){
 		fitVars.push_back(&AProd_);
 		nAsymPar_+=1;
 	}
 
 	//Background(s)
 	for(auto& AProd : AProdBkgnd_){
 		if (AProd->fixed()){continue;}
 		fitVars.push_back(AProd);
 		nAsymPar_+=1;
 	}
 }
 
 void LauTimeDepFitModel::setTagEffParams()
 {
 	nTagEffPar_ = 0;
 	Bool_t useAltPars = flavTag_->getUseAveDelta();
 
 	std::cout << "INFO in LauTimeDepFitModel::setTagEffParams : Setting the initial fit parameters for flavour tagging efficiencies." << std::endl;
 
 	if (useAltPars){
 		std::vector<LauParameter*> tageff_ave = flavTag_->getTagEffAve();
 		std::vector<LauParameter*> tageff_delta = flavTag_->getTagEffDelta();
 
 		LauParameterPList& fitVars = this->fitPars();
 
 		for(auto& eff : tageff_ave){
 			if (eff==nullptr){continue;}
 			if (eff->fixed()){continue;}
 			fitVars.push_back(eff);
 			++nTagEffPar_;
 		}
 		for(auto& eff : tageff_delta){
 			if (eff==nullptr){continue;}
 			if (eff->fixed()){continue;}
 			fitVars.push_back(eff);
 			++nTagEffPar_;
 		}
 	} else {
 		std::vector<LauParameter*> tageff_b0 = flavTag_->getTagEffB0();
 		std::vector<LauParameter*> tageff_b0bar = flavTag_->getTagEffB0bar();
 
 		LauParameterPList& fitVars = this->fitPars();
 
 		for(auto& eff : tageff_b0){
 			if (eff==nullptr){continue;}
 			if (eff->fixed()){continue;}
 			fitVars.push_back(eff);
 			++nTagEffPar_;
 		}
 		for(auto& eff : tageff_b0bar){
 			if (eff==nullptr){continue;}
 			if (eff->fixed()){continue;}
 			fitVars.push_back(eff);
 			++nTagEffPar_;
 		}
 	}
 
 	if (usingBkgnd_){
 		if (useAltPars){
 			std::vector<std::vector<LauParameter*>> tageff_ave = flavTag_->getTagEffBkgndAve();
 			std::vector<std::vector<LauParameter*>> tageff_delta = flavTag_->getTagEffBkgndDelta();
 
 			LauParameterPList& fitVars = this->fitPars();
 
 			for(auto& innerVec : tageff_ave){
 				for(auto& eff : innerVec){
 					if (eff == nullptr){continue;}
 					if (eff->fixed()){continue;}
 					fitVars.push_back(eff);
 					++nTagEffPar_;
 				}
 			}
 			for(auto& innerVec : tageff_delta){
 				for(auto& eff : innerVec){
 					if (eff == nullptr){continue;}
 					if (eff->fixed()){continue;}
 					fitVars.push_back(eff);
 					++nTagEffPar_;
 				}
 			}
 		} else {
 			std::vector<std::vector<LauParameter*>> tageff_b0 = flavTag_->getTagEffBkgndB0();
 			std::vector<std::vector<LauParameter*>> tageff_b0bar = flavTag_->getTagEffBkgndB0bar();
 
 			LauParameterPList& fitVars = this->fitPars();
 
 			for(auto& innerVec : tageff_b0){
 				for(auto& eff : innerVec){
 					if (eff == nullptr){continue;}
 					if (eff->fixed()){continue;}
 					fitVars.push_back(eff);
 					++nTagEffPar_;
 				}
 			}
 			for(auto& innerVec : tageff_b0bar){
 				for(auto& eff : innerVec){
 					if (eff == nullptr){continue;}
 					if (eff->fixed()){continue;}
 					fitVars.push_back(eff);
 					++nTagEffPar_;
 				}
 			}
 		}
 	}
 }
 
 void LauTimeDepFitModel::setCalibParams()
 {
 	Bool_t useAltPars = flavTag_->getUseAveDelta();
 
 	std::cout << "INFO in LauTimeDepFitModel::setCalibParams : Setting the initial fit parameters of the flavour tagging calibration parameters." << std::endl;
 
 	if (useAltPars){
 		std::vector<LauParameter*> p0pars_ave = flavTag_->getCalibP0Ave();
 		std::vector<LauParameter*> p0pars_delta = flavTag_->getCalibP0Delta();
 		std::vector<LauParameter*> p1pars_ave = flavTag_->getCalibP1Ave();
 		std::vector<LauParameter*> p1pars_delta = flavTag_->getCalibP1Delta();
 
 		LauParameterPList& fitVars = this->fitPars();
 
 		for(auto& p0 : p0pars_ave){
 			if (p0->fixed()){continue;}
 			fitVars.push_back(p0);
 			++nCalibPar_;
 		}
 		for(auto& p0 : p0pars_delta){
 			if (p0->fixed()){continue;}
 			fitVars.push_back(p0);
 			++nCalibPar_;
 		}
 		for(auto& p1 : p1pars_ave){
 			if (p1->fixed()){continue;}
 			fitVars.push_back(p1);
 			++nCalibPar_;
 		}
 		for(auto& p1 : p1pars_delta){
 			if (p1->fixed()){continue;}
 			fitVars.push_back(p1);
 			++nCalibPar_;
 		}
 	} else {
 		std::vector<LauParameter*> p0pars_b0 = flavTag_->getCalibP0B0();
 		std::vector<LauParameter*> p0pars_b0bar = flavTag_->getCalibP0B0bar();
 		std::vector<LauParameter*> p1pars_b0 = flavTag_->getCalibP1B0();
 		std::vector<LauParameter*> p1pars_b0bar = flavTag_->getCalibP1B0bar();
 
 		LauParameterPList& fitVars = this->fitPars();
 
 		for(auto& p0 : p0pars_b0){
 			if (p0->fixed()){continue;}
 			fitVars.push_back(p0);
 			++nCalibPar_;
 		}
 		for(auto& p0 : p0pars_b0bar){
 			if (p0->fixed()){continue;}
 			fitVars.push_back(p0);
 			++nCalibPar_;
 		}
 		for(auto& p1 : p1pars_b0){
 			if (p1->fixed()){continue;}
 			fitVars.push_back(p1);
 			++nCalibPar_;
 		}
 		for(auto& p1 : p1pars_b0bar){
 			if (p1->fixed()){continue;}
 			fitVars.push_back(p1);
 			++nCalibPar_;
 		}
 	}
 }
 
 void LauTimeDepFitModel::setEffiParams()
 {
 	nEffiPar_ = 0;
 	LauParameterPList& fitVars = this->fitPars();
 
 	LauParameterPList& effiPars = signalDecayTimePdf_->getEffiPars();
 
 	// If all of the knots are fixed we have nothing to do
 	LauParamFixed isFixed;
 	if ( std::all_of( effiPars.begin(), effiPars.end(), isFixed ) ) {
 		return;
 	}
 
 	// If any knots are floating, add all knots (fixed or floating)
 	for(auto& par : effiPars){
 		fitVars.push_back(par);
 		++nEffiPar_;
 	}
 }
 
 void LauTimeDepFitModel::setExtraNtupleVars()
 {
 	// Set-up other parameters derived from the fit results, e.g. fit fractions.
 
 	if (this->useDP() != kTRUE) {
 		return;
 	}
 
 	// First clear the vectors so we start from scratch
 	this->clearExtraVarVectors();
 
 	LauParameterList& extraVars = this->extraPars();
 
 	// Add the B0 and B0bar fit fractions for each signal component
 	fitFracB0bar_ = sigModelB0bar_->getFitFractions();
 	if (fitFracB0bar_.size() != nSigComp_) {
 		std::cerr<<"ERROR in LauTimeDepFitModel::setExtraNtupleVars : Initial Fit Fraction array of unexpected dimension: "<<fitFracB0bar_.size()<<std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 	for (UInt_t i(0); i<nSigComp_; ++i) {
 		if (fitFracB0bar_[i].size() != nSigComp_) {
 			std::cerr<<"ERROR in LauTimeDepFitModel::setExtraNtupleVars : Initial Fit Fraction array of unexpected dimension: "<<fitFracB0bar_[i].size()<<std::endl;
 			gSystem->Exit(EXIT_FAILURE);
 		}
 	}
 
 	for (UInt_t i(0); i<nSigComp_; ++i) {
 		for (UInt_t j = i; j < nSigComp_; j++) {
 			TString name = fitFracB0bar_[i][j].name();
 			name.Insert( name.Index("FitFrac"), "B0bar" );
 			fitFracB0bar_[i][j].name(name);
 			extraVars.push_back(fitFracB0bar_[i][j]);
 		}
 	}
 
 	fitFracB0_ = sigModelB0_->getFitFractions();
 	if (fitFracB0_.size() != nSigComp_) {
 		std::cerr<<"ERROR in LauTimeDepFitModel::setExtraNtupleVars : Initial Fit Fraction array of unexpected dimension: "<<fitFracB0_.size()<<std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 	for (UInt_t i(0); i<nSigComp_; ++i) {
 		if (fitFracB0_[i].size() != nSigComp_) {
 			std::cerr<<"ERROR in LauTimeDepFitModel::setExtraNtupleVars : Initial Fit Fraction array of unexpected dimension: "<<fitFracB0_[i].size()<<std::endl;
 			gSystem->Exit(EXIT_FAILURE);
 		}
 	}
 
 	for (UInt_t i(0); i<nSigComp_; ++i) {
 		for (UInt_t j = i; j < nSigComp_; j++) {
 			TString name = fitFracB0_[i][j].name();
 			name.Insert( name.Index("FitFrac"), "B0" );
 			fitFracB0_[i][j].name(name);
 			extraVars.push_back(fitFracB0_[i][j]);
 		}
 	}
 
 	// Calculate the ACPs and FitFrac asymmetries
 	this->calcAsymmetries(kTRUE);
 
 	// Add the Fit Fraction asymmetry for each signal component
 	for (UInt_t i = 0; i < nSigComp_; i++) {
 		extraVars.push_back(fitFracAsymm_[i]);
 	}
 
 	// Add the calculated CP asymmetry for each signal component
 	for (UInt_t i = 0; i < nSigComp_; i++) {
 		extraVars.push_back(acp_[i]);
 	}
 
 	// Now add in the DP efficiency values
 	Double_t initMeanEffB0bar = sigModelB0bar_->getMeanEff().initValue();
 	meanEffB0bar_.value(initMeanEffB0bar); meanEffB0bar_.initValue(initMeanEffB0bar); meanEffB0bar_.genValue(initMeanEffB0bar);
 	extraVars.push_back(meanEffB0bar_);
 
 	Double_t initMeanEffB0 = sigModelB0_->getMeanEff().initValue();
 	meanEffB0_.value(initMeanEffB0); meanEffB0_.initValue(initMeanEffB0); meanEffB0_.genValue(initMeanEffB0);
 	extraVars.push_back(meanEffB0_);
 
 	// Also add in the DP rates
 	Double_t initDPRateB0bar = sigModelB0bar_->getDPRate().initValue();
 	DPRateB0bar_.value(initDPRateB0bar); DPRateB0bar_.initValue(initDPRateB0bar); DPRateB0bar_.genValue(initDPRateB0bar);
 	extraVars.push_back(DPRateB0bar_);
 
 	Double_t initDPRateB0 = sigModelB0_->getDPRate().initValue();
 	DPRateB0_.value(initDPRateB0); DPRateB0_.initValue(initDPRateB0); DPRateB0_.genValue(initDPRateB0);
 	extraVars.push_back(DPRateB0_);
 }
 
 void LauTimeDepFitModel::setAsymmetries(const Double_t AProd, const Bool_t AProdFix){
 	AProd_.value(AProd);
 	AProd_.fixed(AProdFix);
 }
 
 void LauTimeDepFitModel::setBkgndAsymmetries(const TString& bkgndClass, const Double_t AProd, const Bool_t AProdFix){
 	// check that this background name is valid
 	if ( ! this->validBkgndClass( bkgndClass) ) {
 		std::cerr << "ERROR in LauTimeDepFitModel::setBkgndAsymmetries : Invalid background class \"" << bkgndClass << "\"." << std::endl;
 		std::cerr << "                                                 : Background class names must be provided in \"setBkgndClassNames\" before any other background-related actions can be performed." << std::endl;
 		return;
 	}
 
 	UInt_t bkgndID = this->bkgndClassID( bkgndClass );
 	AProdBkgnd_[bkgndID]->value( AProd );
 	AProdBkgnd_[bkgndID]->genValue( AProd );
 	AProdBkgnd_[bkgndID]->initValue( AProd );
 	AProdBkgnd_[bkgndID]->fixed( AProdFix );
 }
 
 void LauTimeDepFitModel::finaliseFitResults(const TString& tablePrefixName)
 {
 	// Retrieve parameters from the fit results for calculations and toy generation
 	// and eventually store these in output root ntuples/text files
 
 	// Now take the fit parameters and update them as necessary
 	// i.e. to make mag > 0.0, phase in the right range.
 	// This function will also calculate any other values, such as the
 	// fit fractions, using any errors provided by fitParErrors as appropriate.
 	// Also obtain the pull values: (measured - generated)/(average error)
 
 	if (this->useDP() == kTRUE) {
 		for (UInt_t i = 0; i < nSigComp_; ++i) {
 			// Check whether we have "a > 0.0", and phases in the right range
 			coeffPars_[i]->finaliseValues();
 		}
 	}
 
 
 	// update the pulls on the event fractions and asymmetries
 	if (this->doEMLFit()) {
 		signalEvents_->updatePull();
 	}
 	if (this->useDP() == kFALSE) {
 		signalAsym_->updatePull();
 	}
 
 	// Finalise the pulls on the decay time parameters
 	signalDecayTimePdf_->updatePulls();
 
 	// and for backgrounds if required
 	if (usingBkgnd_){
 		for (auto& pdf : BkgndDecayTimePdfs_){
 			pdf->updatePulls();
 		}
 	}
 
 	if (useSinCos_) {
 		if ( not sinPhiMix_.fixed() ) {
 			sinPhiMix_.updatePull();
 			cosPhiMix_.updatePull();
 		}
 	} else {
 		this->checkMixingPhase();
 	}
 
 	if (usingBkgnd_ == kTRUE) {
 		for (auto& params : bkgndEvents_){
 			std::vector<LauParameter*> parameters = params->getPars();
 			for ( LauParameter* parameter : parameters ) {
 				parameter->updatePull();
 			}
 		}
 		for (auto& params : bkgndAsym_){
 			std::vector<LauParameter*> parameters = params->getPars();
 			for ( LauParameter* parameter : parameters ) {
 				parameter->updatePull();
 			}
 		}
 	}
 
 	// Update the pulls on all the extra PDFs' parameters
 	this->updateFitParameters(sigExtraPdf_);
 
 	if (usingBkgnd_ == kTRUE) {
 		for (auto& pdf : BkgndPdfs_){
 			this->updateFitParameters(pdf);
 		}
 	}
 
 	// Fill the fit results to the ntuple
 
 	// update the coefficients and then calculate the fit fractions and ACP's
 	if (this->useDP() == kTRUE) {
 		this->updateCoeffs();
 		sigModelB0bar_->updateCoeffs(coeffsB0bar_);  sigModelB0bar_->calcExtraInfo();
 		sigModelB0_->updateCoeffs(coeffsB0_);        sigModelB0_->calcExtraInfo();
 
 		LauParArray fitFracB0bar = sigModelB0bar_->getFitFractions();
 		if (fitFracB0bar.size() != nSigComp_) {
 			std::cerr<<"ERROR in LauTimeDepFitModel::finaliseFitResults : Fit Fraction array of unexpected dimension: "<<fitFracB0bar.size()<<std::endl;
 			gSystem->Exit(EXIT_FAILURE);
 		}
 		for (UInt_t i(0); i<nSigComp_; ++i) {
 			if (fitFracB0bar[i].size() != nSigComp_) {
 				std::cerr<<"ERROR in LauTimeDepFitModel::finaliseFitResults : Fit Fraction array of unexpected dimension: "<<fitFracB0bar[i].size()<<std::endl;
 				gSystem->Exit(EXIT_FAILURE);
 			}
 		}
 		LauParArray fitFracB0 = sigModelB0_->getFitFractions();
 		if (fitFracB0.size() != nSigComp_) {
 			std::cerr<<"ERROR in LauTimeDepFitModel::finaliseFitResults : Fit Fraction array of unexpected dimension: "<<fitFracB0.size()<<std::endl;
 			gSystem->Exit(EXIT_FAILURE);
 		}
 		for (UInt_t i(0); i<nSigComp_; ++i) {
 			if (fitFracB0[i].size() != nSigComp_) {
 				std::cerr<<"ERROR in LauTimeDepFitModel::finaliseFitResults : Fit Fraction array of unexpected dimension: "<<fitFracB0[i].size()<<std::endl;
 				gSystem->Exit(EXIT_FAILURE);
 			}
 		}
 
 		for (UInt_t i(0); i<nSigComp_; ++i) {
 			for (UInt_t j(i); j<nSigComp_; ++j) {
 				fitFracB0bar_[i][j].value(fitFracB0bar[i][j].value());
 				fitFracB0_[i][j].value(fitFracB0[i][j].value());
 			}
 		}
 
 		meanEffB0bar_.value(sigModelB0bar_->getMeanEff().value());
 		meanEffB0_.value(sigModelB0_->getMeanEff().value());
 		DPRateB0bar_.value(sigModelB0bar_->getDPRate().value());
 		DPRateB0_.value(sigModelB0_->getDPRate().value());
 
 		this->calcAsymmetries();
 
 		// Then store the final fit parameters, and any extra parameters for
 		// the signal model (e.g. fit fractions, FF asymmetries, ACPs, mean efficiency and DP rate)
 
 		this->clearExtraVarVectors();
 		LauParameterList& extraVars = this->extraPars();
 
 		for (UInt_t i(0); i<nSigComp_; ++i) {
 			for (UInt_t j(i); j<nSigComp_; ++j) {
 				extraVars.push_back(fitFracB0bar_[i][j]);
 			}
 		}
 		for (UInt_t i(0); i<nSigComp_; ++i) {
 			for (UInt_t j(i); j<nSigComp_; ++j) {
 				extraVars.push_back(fitFracB0_[i][j]);
 			}
 		}
 		for (UInt_t i(0); i<nSigComp_; ++i) {
 			extraVars.push_back(fitFracAsymm_[i]);
 		}
 		for (UInt_t i(0); i<nSigComp_; ++i) {
 			extraVars.push_back(acp_[i]);
 		}
 		extraVars.push_back(meanEffB0bar_);
 		extraVars.push_back(meanEffB0_);
 		extraVars.push_back(DPRateB0bar_);
 		extraVars.push_back(DPRateB0_);
 
 		this->printFitFractions(std::cout);
 		this->printAsymmetries(std::cout);
 	}
 
 	const LauParameterPList& fitVars = this->fitPars();
 	const LauParameterList& extraVars = this->extraPars();
 	LauFitNtuple* ntuple = this->fitNtuple();
 	ntuple->storeParsAndErrors(fitVars, extraVars);
 
 	// find out the correlation matrix for the parameters
 	ntuple->storeCorrMatrix(this->iExpt(), this->fitStatus(), this->covarianceMatrix());
 
 	// Fill the data into ntuple
 	ntuple->updateFitNtuple();
 
 	// Print out the partial fit fractions, phases and the
 	// averaged efficiency, reweighted by the dynamics (and anything else)
 	if (this->writeLatexTable()) {
 		TString sigOutFileName(tablePrefixName);
 		sigOutFileName += "_"; sigOutFileName += this->iExpt(); sigOutFileName += "Expt.tex";
 		this->writeOutTable(sigOutFileName);
 	}
 }
 
 void LauTimeDepFitModel::printFitFractions(std::ostream& output)
 {
 	// Print out Fit Fractions, total DP rate and mean efficiency
 	// First for the B0bar events
 	for (UInt_t i = 0; i < nSigComp_; i++) {
 		const TString compName(coeffPars_[i]->name());
 		output<<"B0bar FitFraction for component "<<i<<" ("<<compName<<") = "<<fitFracB0bar_[i][i]<<std::endl;
 	}
 	output<<"B0bar overall DP rate (integral of matrix element squared) = "<<DPRateB0bar_<<std::endl;
 	output<<"B0bar average efficiency weighted by whole DP dynamics = "<<meanEffB0bar_<<std::endl;
 
 	// Then for the B0 sample
 	for (UInt_t i = 0; i < nSigComp_; i++) {
 		const TString compName(coeffPars_[i]->name());
 		const TString conjName(sigModelB0bar_->getConjResName(compName));
 		output<<"B0 FitFraction for component "<<i<<" ("<<conjName<<") = "<<fitFracB0_[i][i]<<std::endl;
 	}
 	output<<"B0 overall DP rate (integral of matrix element squared) = "<<DPRateB0_<<std::endl;
 	output<<"B0 average efficiency weighted by whole DP dynamics = "<<meanEffB0_<<std::endl;
 }
 
 void LauTimeDepFitModel::printAsymmetries(std::ostream& output)
 {
 	for (UInt_t i = 0; i < nSigComp_; i++) {
 		const TString compName(coeffPars_[i]->name());
 		output<<"Fit Fraction asymmetry for component "<<i<<" ("<<compName<<") = "<<fitFracAsymm_[i]<<std::endl;
 	}
 	for (UInt_t i = 0; i < nSigComp_; i++) {
 		const TString compName(coeffPars_[i]->name());
 		output<<"ACP for component "<<i<<" ("<<compName<<") = "<<acp_[i].value()<<" +- "<<acp_[i].error()<<std::endl;
 	}
 }
 
 void LauTimeDepFitModel::writeOutTable(const TString& outputFile)
 {
 	// Write out the results of the fit to a tex-readable table
 	std::ofstream fout(outputFile);
 	LauPrint print;
 
 	std::cout<<"INFO in LauTimeDepFitModel::writeOutTable : Writing out results of the fit to the tex file "<<outputFile<<std::endl;
 
 	if (this->useDP() == kTRUE) {
 		// print the fit coefficients in one table
 		coeffPars_.front()->printTableHeading(fout);
 		for (UInt_t i = 0; i < nSigComp_; i++) {
 			coeffPars_[i]->printTableRow(fout);
 		}
 		fout<<"\\hline"<<std::endl;
 		fout<<"\\end{tabular}"<<std::endl<<std::endl;
 
 		// print the fit fractions in another
 		fout<<"\\begin{tabular}{|l|c|c|c|c|}"<<std::endl;
 		fout<<"\\hline"<<std::endl;
 		fout<<"Component & \\Bzb\\ Fit Fraction & \\Bz\\ Fit Fraction & Fit Fraction Asymmetry & $A_{\\CP}$ \\\\"<<std::endl;
 		fout<<"\\hline"<<std::endl;
 		Double_t fitFracSumB0bar(0.0);
 		Double_t fitFracSumB0(0.0);
 		for (UInt_t i = 0; i < nSigComp_; i++) {
 			TString resName = coeffPars_[i]->name();
 			resName = resName.ReplaceAll("_", "\\_");
 			fout<<resName<<"  &  $";
 			Double_t fitFracB0bar = fitFracB0bar_[i][i].value();
 			fitFracSumB0bar += fitFracB0bar;
 			print.printFormat(fout, fitFracB0bar);
 			fout << "$  &  $" << std::endl;
 			Double_t fitFracB0 = fitFracB0_[i][i].value();
 			fitFracSumB0 += fitFracB0;
 			print.printFormat(fout, fitFracB0);
 			fout << "$  &  $" << std::endl;
 			Double_t fitFracAsymm = fitFracAsymm_[i].value();
 			print.printFormat(fout, fitFracAsymm);
 			fout << "$  &  $" << std::endl;
 			Double_t acp = acp_[i].value();
 			Double_t acpErr = acp_[i].error();
 			print.printFormat(fout, acp);
 			fout<<" \\pm ";
 			print.printFormat(fout, acpErr);
 			fout<<"$ \\\\"<<std::endl;
 		}
 		fout<<"\\hline"<<std::endl;
 
 
 		// Also print out sum of fit fractions
 		fout << "Fit Fraction Sum = & $";
 		print.printFormat(fout, fitFracSumB0bar);
 		fout << "$  &  $";
 		print.printFormat(fout, fitFracSumB0);
 		fout << "$  &   &   \\\\" << std::endl;
 
 		fout << "\\hline \n\\hline" << std::endl;
 
 		fout << "DP rate = & $";
 		print.printFormat(fout, DPRateB0bar_.value());
 		fout << "$  &  $";
 		print.printFormat(fout, DPRateB0_.value());
 		fout << "$  &   &   \\\\" << std::endl;
 
 		fout << "$< \\varepsilon > =$ & $";
 		print.printFormat(fout, meanEffB0bar_.value());
 		fout << "$  &  $";
 		print.printFormat(fout, meanEffB0_.value());
 		fout << "$  &   &   \\\\" << std::endl;
 
 		if (useSinCos_) {
 			fout << "$\\sinPhiMix =$ & $";
 			print.printFormat(fout, sinPhiMix_.value());
 			fout << " \\pm ";
 			print.printFormat(fout, sinPhiMix_.error());
 			fout << "$ &  &  &  &  &  &  &  \\\\" << std::endl;
 
 			fout << "$\\cosPhiMix =$ & $";
 			print.printFormat(fout, cosPhiMix_.value());
 			fout << " \\pm ";
 			print.printFormat(fout, cosPhiMix_.error());
 			fout << "$ &  &  &  &  &  &  &  \\\\" << std::endl;
 		} else {
 			fout << "$\\phiMix =$ & $";
 			print.printFormat(fout, phiMix_.value());
 			fout << " \\pm ";
 			print.printFormat(fout, phiMix_.error());
 			fout << "$ &  &  &  &  &  &  &  \\\\" << std::endl;
 		}
 
 		fout << "\\hline \n\\end{tabular}" << std::endl;
 	}
 
 	if (!sigExtraPdf_.empty()) {
 		fout<<"\\begin{tabular}{|l|c|}"<<std::endl;
 		fout<<"\\hline"<<std::endl;
 		fout<<"\\Extra Signal PDFs' Parameters: & \\\\"<<std::endl;
 		this->printFitParameters(sigExtraPdf_, fout);
 		if (usingBkgnd_ == kTRUE && !BkgndPdfs_.empty()) {
 			fout << "\\hline" << std::endl;
 			fout << "\\Extra Background PDFs' Parameters: & \\\\" << std::endl;
 			for (auto& pdf : BkgndPdfs_){
 				this->printFitParameters(pdf, fout);
 			}
 		}
 		fout<<"\\hline \n\\end{tabular}"<<std::endl<<std::endl;
 	}
 }
 
 void LauTimeDepFitModel::checkInitFitParams()
 {
 	// Update the number of signal events to be total-sum(background events)
 	this->updateSigEvents();
 
 	// Check whether we want to have randomised initial fit parameters for the signal model
 	if (this->useRandomInitFitPars() == kTRUE) {
 		this->randomiseInitFitPars();
 	}
 }
 
 void LauTimeDepFitModel::randomiseInitFitPars()
 {
 	// Only randomise those parameters that are not fixed!
 	std::cout<<"INFO in LauTimeDepFitModel::randomiseInitFitPars : Randomising the initial values of the coefficients of the DP components (and phiMix)..."<<std::endl;
 
 	for (UInt_t i = 0; i < nSigComp_; i++) {
 		coeffPars_[i]->randomiseInitValues();
 	}
 
 	phiMix_.randomiseValue(-LauConstants::pi, LauConstants::pi);
 	if (useSinCos_) {
 		sinPhiMix_.initValue(TMath::Sin(phiMix_.initValue()));
 		cosPhiMix_.initValue(TMath::Cos(phiMix_.initValue()));
 	}
 }
 
 LauTimeDepFitModel::LauGenInfo LauTimeDepFitModel::eventsToGenerate()
 {
 	// Determine the number of events to generate for each hypothesis
 	// If we're smearing then smear each one individually
 	// NB this individual smearing has to be done individually per tagging category as well
 
 	LauGenInfo nEvtsGen;
 
 	// Signal
 	// If we're including the DP and decay time we can't decide on the tag
 	// yet, since it depends on the whole DP+dt PDF, however, if
 	// we're not then we need to decide.
 	Double_t evtWeight(1.0);
 	Double_t nEvts = signalEvents_->genValue();
 	if ( nEvts < 0.0 ) {
 		evtWeight = -1.0;
 		nEvts = TMath::Abs( nEvts );
 	}
 
 	//TOD sigAysm doesn't do anything here?
 	Double_t sigAsym(0.0);
 	if (this->useDP() == kFALSE) {
 		sigAsym = signalAsym_->genValue();
 		//TODO fill in here if we care
 
 	} else {
 		Double_t rateB0bar = sigModelB0bar_->getDPRate().value();
 		Double_t rateB0 = sigModelB0_->getDPRate().value();
 		if ( rateB0bar+rateB0 > 1e-30) {
 			sigAsym = (rateB0bar-rateB0)/(rateB0bar+rateB0);
 		}
 
 		//for (LauTagCatParamMap::const_iterator iter = signalTagCatFrac.begin(); iter != signalTagCatFrac.end(); ++iter) {
 		//	const LauParameter& par = iter->second;
 		//	Double_t eventsbyTagCat = par.value() * nEvts;
 		//	if (this->doPoissonSmearing()) {
 		//		eventsbyTagCat = LauRandom::randomFun()->Poisson(eventsbyTagCat);
 		//	}
 		//	eventsB0[iter->first] = std::make_pair( TMath::Nint(eventsbyTagCat), evtWeight );
 		//}
 		//nEvtsGen[std::make_pair("signal",0)] = eventsB0; // generate signal event, decide tag later.
 		nEvtsGen["signal"] = std::make_pair( nEvts, evtWeight );
 	}
 
 	std::cout<<"INFO in LauTimeDepFitModel::eventsToGenerate : Generating toy MC with:"<<std::endl;
 	std::cout<<"                                             : Signal asymmetry  = "<<sigAsym<<" and number of signal events = "<<signalEvents_->genValue()<<std::endl;
 
 	//TODO backgrounds
 	if (usingBkgnd_){
 		for ( UInt_t bkgndID(0); bkgndID < this->nBkgndClasses(); ++bkgndID ) {
 			nEvtsGen[this->bkgndClassName(bkgndID)] = std::make_pair( bkgndEvents_[bkgndID]->genValue(), evtWeight);
 			std::cout<<"                                             : Number of "<<this->bkgndClassName(bkgndID)<<" background events = "<<bkgndEvents_[bkgndID]->genValue()<<std::endl;
 		}
 	}
 
 
 	return nEvtsGen;
 }
 
 Bool_t LauTimeDepFitModel::genExpt()
 {
 	// Routine to generate toy Monte Carlo events according to the various models we have defined.
 
 	// Determine the number of events to generate for each hypothesis
 	LauGenInfo nEvts = this->eventsToGenerate();
 
 	Bool_t genOK(kTRUE);
 	Int_t evtNum(0);
 
 	const UInt_t nBkgnds = this->nBkgndClasses();
 	std::vector<TString> bkgndClassNames(nBkgnds);
 	std::vector<TString> bkgndClassNamesGen(nBkgnds);
 	for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
 		TString name( this->bkgndClassName(iBkgnd) );
 		bkgndClassNames[iBkgnd] = name;
 		bkgndClassNamesGen[iBkgnd] = "gen"+name;
 	}
 
 	// Loop over the hypotheses and generate the appropriate number of
 	// events for each one
 	for (auto& hypo : nEvts){
 
 		// find the category of events (e.g. signal)
 		const TString& evtCategory(hypo.first);
 
 		// Type
 		const TString& type(hypo.first);
 
 		// Number of events
 		Int_t nEvtsGen( hypo.second.first );
 
 		// get the event weight for this category
 		const Double_t evtWeight( hypo.second.second );
 
 		for (Int_t iEvt(0); iEvt<nEvtsGen; ++iEvt) {
 
 			this->setGenNtupleDoubleBranchValue( "evtWeight", evtWeight );
 
 			if (evtCategory == "signal") {
 				this->setGenNtupleIntegerBranchValue("genSig",1);
 				for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
 					this->setGenNtupleIntegerBranchValue( bkgndClassNamesGen[iBkgnd], 0 );
 				}
 				// All the generate*Event() methods have to fill in curEvtDecayTime_ and curEvtDecayTimeErr_
 				// In addition, generateSignalEvent has to decide on the tag and fill in curEvtTagFlv_
 				genOK = this->generateSignalEvent();
 			} else {
 				this->setGenNtupleIntegerBranchValue("genSig",0);
 				UInt_t bkgndID(0);
 				for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
 					Int_t gen(0);
 					if ( bkgndClassNames[iBkgnd] == type ) {
 						gen = 1;
 						bkgndID = iBkgnd;
 					}
 					this->setGenNtupleIntegerBranchValue( bkgndClassNamesGen[iBkgnd], gen );
 				}
 				genOK = this->generateBkgndEvent(bkgndID);
 			}
 
 			if (!genOK) {
 				// If there was a problem with the generation then break out and return.
 				// The problem model will have adjusted itself so that all should be OK next time.
 				break;
 			}
 
 			if (this->useDP() == kTRUE) {
 				this->setDPDtBranchValues();	// store DP, decay time and tagging variables in the ntuple
 			}
 
 			// Store the event's tag and tagging category
 			this->setGenNtupleIntegerBranchValue("cpEigenvalue", cpEigenValue_);
 
 			const TString& trueTagVarName { flavTag_->getTrueTagVarName() };
 			if ( trueTagVarName != "" ) {
 				this->setGenNtupleIntegerBranchValue(trueTagVarName, curEvtTrueTagFlv_);
 			}
 
 			if ( cpEigenValue_ == QFS ) {
 				const TString& decayFlvVarName { flavTag_->getDecayFlvVarName() };
 				if ( decayFlvVarName != "" ) {
 					this->setGenNtupleIntegerBranchValue(decayFlvVarName, curEvtDecayFlv_);
 				}
 			}
 
 			const std::vector<TString>& tagVarNames { flavTag_->getTagVarNames() };
 			const std::vector<TString>& mistagVarNames { flavTag_->getMistagVarNames() };
 
 			// Loop over the taggers - values set via generateSignalEvent
 			const ULong_t nTaggers {flavTag_->getNTaggers()};
 			for (ULong_t i=0; i<nTaggers; ++i){
 				this->setGenNtupleIntegerBranchValue(tagVarNames[i], curEvtTagFlv_[i]);
 				this->setGenNtupleDoubleBranchValue(mistagVarNames[i], curEvtMistag_[i]);
 			}
 
 			// Store the event number (within this experiment)
 			// and then increment it
 			this->setGenNtupleIntegerBranchValue("iEvtWithinExpt",evtNum);
 			++evtNum;
 
 			// Write the values into the tree
 			this->fillGenNtupleBranches();
 
 			// Print an occasional progress message
 			if (iEvt%1000 == 0) {std::cout<<"INFO in LauTimeDepFitModel::genExpt : Generated event number "<<iEvt<<" out of "<<nEvtsGen<<" "<<evtCategory<<" events."<<std::endl;}
 
 		}
 
 	}	//end of loop over species and tagFlv.
 
 	if (this->useDP() && genOK) {
 
 		sigModelB0bar_->checkToyMC(kTRUE);
 		sigModelB0_->checkToyMC(kTRUE);
 
 		std::cout<<"aSqMaxSet = "<<aSqMaxSet_<<" and aSqMaxVar = "<<aSqMaxVar_<<std::endl;
 
 		// Get the fit fractions if they're to be written into the latex table
 		if (this->writeLatexTable()) {
 			LauParArray fitFracB0bar = sigModelB0bar_->getFitFractions();
 			if (fitFracB0bar.size() != nSigComp_) {
 				std::cerr<<"ERROR in LauTimeDepFitModel::generate : Fit Fraction array of unexpected dimension: "<<fitFracB0bar.size()<<std::endl;
 				gSystem->Exit(EXIT_FAILURE);
 			}
 			for (UInt_t i(0); i<nSigComp_; ++i) {
 				if (fitFracB0bar[i].size() != nSigComp_) {
 					std::cerr<<"ERROR in LauTimeDepFitModel::generate : Fit Fraction array of unexpected dimension: "<<fitFracB0bar[i].size()<<std::endl;
 					gSystem->Exit(EXIT_FAILURE);
 				}
 			}
 			LauParArray fitFracB0 = sigModelB0_->getFitFractions();
 			if (fitFracB0.size() != nSigComp_) {
 				std::cerr<<"ERROR in LauTimeDepFitModel::generate : Fit Fraction array of unexpected dimension: "<<fitFracB0.size()<<std::endl;
 				gSystem->Exit(EXIT_FAILURE);
 			}
 			for (UInt_t i(0); i<nSigComp_; ++i) {
 				if (fitFracB0[i].size() != nSigComp_) {
 					std::cerr<<"ERROR in LauTimeDepFitModel::generate : Fit Fraction array of unexpected dimension: "<<fitFracB0[i].size()<<std::endl;
 					gSystem->Exit(EXIT_FAILURE);
 				}
 			}
 			for (UInt_t i(0); i<nSigComp_; ++i) {
 				for (UInt_t j(i); j<nSigComp_; ++j) {
 					fitFracB0bar_[i][j].value(fitFracB0bar[i][j].value());
 					fitFracB0_[i][j].value(fitFracB0[i][j].value());
 				}
 			}
 			meanEffB0bar_.value(sigModelB0bar_->getMeanEff().value());
 			meanEffB0_.value(sigModelB0_->getMeanEff().value());
 			DPRateB0bar_.value(sigModelB0bar_->getDPRate().value());
 			DPRateB0_.value(sigModelB0_->getDPRate().value());
 		}
 	}
 
 	// If we're reusing embedded events or if the generation is being
 	// reset then clear the lists of used events
 
 	if (reuseSignal_ || !genOK) {
 		if (signalTree_) {
 			signalTree_->clearUsedList();
 		}
 	}
 	for ( UInt_t bkgndID(0); bkgndID < nBkgnds; ++bkgndID ) {
 		LauEmbeddedData* data = bkgndTree_[bkgndID];
 		if (reuseBkgnd_[bkgndID] || !genOK) {
 			if (data) {
 				data->clearUsedList();
 			}
 		}
 	}
 	return genOK;
 }
 
 Bool_t LauTimeDepFitModel::generateSignalEvent()
 {
 	// Generate signal event, including SCF if necessary.
 	// DP:DecayTime generation follows.
 	// If it's ok, we then generate mES, DeltaE, Fisher/NN...
 	Bool_t genOK(kTRUE);
 	Bool_t generatedEvent(kFALSE);
 
 	Bool_t doSquareDP = kinematicsB0bar_->squareDP();
 	doSquareDP &= kinematicsB0_->squareDP();
 
 	LauKinematics* kinematics(kinematicsB0bar_);
 
 	if (this->useDP()) {
 		if (signalTree_) {
 			signalTree_->getEmbeddedEvent(kinematics);
 			//curEvtTagFlv_ = TMath::Nint(signalTree_->getValue("tagFlv"));
 			curEvtDecayTimeErr_ = signalTree_->getValue(signalDecayTimePdf_->varErrName());
 			curEvtDecayTime_ = signalTree_->getValue(signalDecayTimePdf_->varName());
 			if (signalTree_->haveBranch("mcMatch")) {
 				Int_t match = TMath::Nint(signalTree_->getValue("mcMatch"));
 				if (match) {
 					this->setGenNtupleIntegerBranchValue("genTMSig",1);
 					this->setGenNtupleIntegerBranchValue("genSCFSig",0);
 				} else {
 					this->setGenNtupleIntegerBranchValue("genTMSig",0);
 					this->setGenNtupleIntegerBranchValue("genSCFSig",1);
 				}
 			}
 		} else {
 
 			nGenLoop_ = 0;
 
 			// Now generate from the combined DP / decay-time PDF
 			while (generatedEvent == kFALSE && nGenLoop_ < iterationsMax_) {
 
 				curEvtTrueTagFlv_ = LauFlavTag::Flavour::Unknown;
 				curEvtDecayFlv_ = LauFlavTag::Flavour::Unknown;
 
 				// First choose the true tag, accounting for the production asymmetry
 				// CONVENTION WARNING regarding meaning of sign of AProd
 				Double_t random = LauRandom::randomFun()->Rndm();
 				if (random <= 0.5 * ( 1.0 - AProd_.unblindValue() ) ) {
 					curEvtTrueTagFlv_ = LauFlavTag::Flavour::B;
 				} else {
 					curEvtTrueTagFlv_ = LauFlavTag::Flavour::Bbar;
 				}
 
 				// 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);
 
 				// Generate decay time
 				const Double_t tMin = signalDecayTimePdf_->minAbscissa();
 				const Double_t tMax = signalDecayTimePdf_->maxAbscissa();
 				curEvtDecayTime_ = LauRandom::randomFun()->Uniform(tMin,tMax);
 
 				// Generate the decay time error (NB the kTRUE forces the generation of a new value)
 				curEvtDecayTimeErr_ = signalDecayTimePdf_->generateError(kTRUE);
 
 				// Calculate all the decay time info
 				signalDecayTimePdf_->calcLikelihoodInfo(curEvtDecayTime_,curEvtDecayTimeErr_);
 
 
 				// Retrieve the amplitudes and efficiency from the dynamics
 				const LauComplex& Abar { sigModelB0bar_->getEvtDPAmp() };
 				const LauComplex& A { sigModelB0_->getEvtDPAmp() };
 				const Double_t ASq { A.abs2() };
 				const Double_t AbarSq { Abar.abs2() };
 				const Double_t dpEff { sigModelB0bar_->getEvtEff() };
 
 				// Also retrieve all the decay time terms
 				const Double_t dtCos { signalDecayTimePdf_->getCosTerm() };
 				const Double_t dtSin { signalDecayTimePdf_->getSinTerm() };
 				const Double_t dtCosh { signalDecayTimePdf_->getCoshTerm() };
 				const Double_t dtSinh { signalDecayTimePdf_->getSinhTerm() };
 				// and the decay time acceptance
 				const Double_t dtEff { signalDecayTimePdf_->getEffiTerm() };
 
 				if ( cpEigenValue_ == QFS) {
 					// Calculate the total intensities for each flavour-specific final state
 					const Double_t ATotSq    { ( ASq    * dtCosh + curEvtTrueTagFlv_ * ASq    * dtCos ) * dpEff * dtEff };
 					const Double_t AbarTotSq { ( AbarSq * dtCosh - curEvtTrueTagFlv_ * AbarSq * dtCos ) * dpEff * dtEff };
 					const Double_t ASumSq { ATotSq + AbarTotSq };
 
 					// Finally we throw the dice to see whether this event should be generated (and, if so, which final state)
 					const Double_t randNum = LauRandom::randomFun()->Rndm();
 					if (randNum <= ASumSq / aSqMaxSet_ ) {
 						generatedEvent = kTRUE;
 						nGenLoop_ = 0;
 						if (ASumSq > aSqMaxVar_) {aSqMaxVar_ = ASumSq;}
 
 						if ( randNum <= ATotSq / aSqMaxSet_ ) {
 							curEvtDecayFlv_ = LauFlavTag::Flavour::B;
 						} else {
 							curEvtDecayFlv_ = LauFlavTag::Flavour::Bbar;
 						}
 
 						// Generate the flavour tagging information from the true tag
 						// (we do this after accepting the event to save time)
 						flavTag_->generateEventInfo( curEvtTrueTagFlv_, curEvtDecayTime_ );
 						curEvtTagFlv_ = flavTag_->getCurEvtTagFlv();
 						curEvtMistag_ = flavTag_->getCurEvtMistag();
 					} else {
 						nGenLoop_++;
 					}
 				} else {
 					// Calculate the DP terms
 					const Double_t aSqSum { ASq + AbarSq };
 					const Double_t aSqDif { ASq - AbarSq };
 					const LauComplex inter { Abar * A.conj() * phiMixComplex_ };
 					const Double_t interTermIm { ( cpEigenValue_ == CPEven ) ? 2.0 * inter.im() : -2.0 * inter.im() };
 					const Double_t interTermRe { ( cpEigenValue_ == CPEven ) ? 2.0 * inter.re() : -2.0 * inter.re() };
 
 					// Combine DP and decay-time info for all terms
 					const Double_t coshTerm { aSqSum      * dtCosh };
 					const Double_t sinhTerm { interTermRe * dtSinh };
 					const Double_t cosTerm  { aSqDif      * dtCos };
 					const Double_t sinTerm  { interTermIm * dtSin };
 
 					// Sum to obtain the total and multiply by the efficiency
 					// Multiplying the cos and sin terms by the true flavour at production
 					const Double_t ATotSq { ( coshTerm + sinhTerm + curEvtTrueTagFlv_ * ( cosTerm - sinTerm ) ) * dpEff * dtEff };
 
 					//Finally we throw the dice to see whether this event should be generated
 					const Double_t randNum = LauRandom::randomFun()->Rndm();
 					if (randNum <= ATotSq/aSqMaxSet_ ) {
 						generatedEvent = kTRUE;
 						nGenLoop_ = 0;
 						if (ATotSq > aSqMaxVar_) {aSqMaxVar_ = ATotSq;}
 
 						// Generate the flavour tagging information from the true tag
 						// (we do this after accepting the event to save time)
 						flavTag_->generateEventInfo( curEvtTrueTagFlv_, curEvtDecayTime_ );
 						curEvtTagFlv_ = flavTag_->getCurEvtTagFlv();
 						curEvtMistag_ = flavTag_->getCurEvtMistag();
 					} else {
 						nGenLoop_++;
 					}
 				}
 
 			} // end of while !generatedEvent loop
 
 		} // end of if (signalTree_) else control
 	} else {
 		if ( signalTree_ ) {
 			signalTree_->getEmbeddedEvent(0);
 			//curEvtTagFlv_ = TMath::Nint(signalTree_->getValue("tagFlv"));
 			curEvtDecayTimeErr_ = signalTree_->getValue(signalDecayTimePdf_->varErrName());
 			curEvtDecayTime_ = signalTree_->getValue(signalDecayTimePdf_->varName());
 		}
 	}
 
 	// Check whether we have generated the toy MC OK.
 	if (nGenLoop_ >= iterationsMax_) {
 		aSqMaxSet_ = 1.01 * aSqMaxVar_;
 		genOK = kFALSE;
 		std::cerr<<"WARNING in LauTimeDepFitModel::generateSignalEvent : Hit max iterations: setting aSqMaxSet_ to "<<aSqMaxSet_<<std::endl;
 	} else if (aSqMaxVar_ > aSqMaxSet_) {
 		aSqMaxSet_ = 1.01 * aSqMaxVar_;
 		genOK = kFALSE;
 		std::cerr<<"WARNING in LauTimeDepFitModel::generateSignalEvent : Found a larger ASq value: setting aSqMaxSet_ to "<<aSqMaxSet_<<std::endl;
 	}
 
 	if (genOK) {
 		//Some variables, like Fisher or NN, might use m13Sq and m23Sq from the kinematics
 		//kinematicsB0bar_ is up to date, update kinematicsB0_
 		kinematicsB0_->updateKinematics(kinematicsB0bar_->getm13Sq(), kinematicsB0bar_->getm23Sq() );
 		this->generateExtraPdfValues(sigExtraPdf_, signalTree_);
 	}
 	// Check for problems with the embedding
 	if (signalTree_ && (signalTree_->nEvents() == signalTree_->nUsedEvents())) {
 		std::cerr<<"WARNING in LauTimeDepFitModel::generateSignalEvent : Source of embedded signal events used up, clearing the list of used events."<<std::endl;
 		signalTree_->clearUsedList();
 	}
 
 	return genOK;
 }
 
 Bool_t LauTimeDepFitModel::generateBkgndEvent(UInt_t bkgndID)
 {
 	// Generate Bkgnd event
 	Bool_t genOK{kTRUE};
 
 	//Check necessary ingredients are in place
 	//TODO these checks should be part of a general sanity check during the initialisation phase
 	if (BkgndDPModelsB_[bkgndID] == nullptr){
 		std::cerr << "ERROR in LauTimeDepFitModel::generateBkgndEvent : Dalitz plot model is missing" << std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 	if (BkgndDecayTimePdfs_[bkgndID] == nullptr){
 		std::cerr << "ERROR in LauTimeDepFitModel::generateBkgndEvent : Decay time model is missing" << std::endl;
 		gSystem->Exit(EXIT_FAILURE);
 	}
 
 	//TODO restore the ability to embed events from an external source
 	//LauAbsBkgndDPModel* model(0);
 	//LauEmbeddedData* embeddedData(0);
 	//LauPdfList* extraPdfs(0);
 	//LauKinematics* kinematics(0);
 
 	//model = BkgndDPModels_[bkgndID];
 	//if (this->enableEmbedding()) {
 	//	// find the right embedded data for the current tagging category
 	//	LauTagCatEmbDataMap::const_iterator emb_iter = bkgndTree_[bkgndID].find(curEvtTagCat_);
 	//	embeddedData = (emb_iter != bkgndTree_[bkgndID].end()) ? emb_iter->second : 0;
 	//}
 	//extraPdfs = &BkgndPdfs_[bkgndID];
 	//kinematics = kinematicsB0bar_;
 
 	//if (this->useDP()) {
 	//	if (embeddedData) {
 	//		embeddedData->getEmbeddedEvent(kinematics);
 	//	} else {
 	//		if (model == 0) {
 	//			const TString& bkgndClass = this->bkgndClassName(bkgndID);
 	//			std::cerr << "ERROR in LauCPFitModel::generateBkgndEvent : Can't find the DP model for background class \"" << bkgndClass << "\"." << std::endl;
 	//			gSystem->Exit(EXIT_FAILURE);
 	//		}
 	//		genOK = model->generate();
 	//	}
 	//} else {
 	//	if (embeddedData) {
 	//		embeddedData->getEmbeddedEvent(0);
 	//	}
 	//}
 	//if (genOK) {
 	//	this->generateExtraPdfValues(extraPdfs, embeddedData);
 	//}
 
 	//// Check for problems with the embedding
 	//if (embeddedData && (embeddedData->nEvents() == embeddedData->nUsedEvents())) {
 	//	const TString& bkgndClass = this->bkgndClassName(bkgndID);
 	//	std::cerr << "WARNING in LauCPFitModel::generateBkgndEvent : Source of embedded " << bkgndClass << " events used up, clearing the list of used events." << std::endl;
 	//	embeddedData->clearUsedList();
 	//}
 	//
 
 	switch ( BkgndTypes_[bkgndID] ) {
 		case LauFlavTag::Combinatorial:
 			{
 
 				// This doesn't really mean anything for combinatorial background
 				// TODO But maybe we need some sort of asymmetry parameter here?
 				Double_t random = LauRandom::randomFun()->Rndm();
 				if ( random <= 0.5 ) {
 					curEvtTrueTagFlv_ = LauFlavTag::Flavour::B;
 				} else {
 					curEvtTrueTagFlv_ = LauFlavTag::Flavour::Bbar;
 				}
 
 				// generate the true decay flavour - again this doesn't make much sense for combinatorial so we just flip a coin
 				// TODO - we maybe need an asymmetry parameter here as well?
 				if ( cpEigenValue_ == CPEigenvalue::QFS ) {
 					if (random <= 0.5 ) {
 						curEvtDecayFlv_ = LauFlavTag::Flavour::B;
 					} else {
 						curEvtDecayFlv_ = LauFlavTag::Flavour::Bbar;
 					}
 				}
 
 				// generate the DP position
 				BkgndDPModelsB_[bkgndID]->generate();
 
 				// generate decay time and its error
 				curEvtDecayTimeErr_ = BkgndDecayTimePdfs_[bkgndID]->generateError(kTRUE);
 				curEvtDecayTime_ = BkgndDecayTimePdfs_[bkgndID]->generate( kinematicsB0_ );
 
 				// generate the flavour tagging response
 				flavTag_->generateBkgndEventInfo( curEvtTrueTagFlv_, curEvtDecayTime_, bkgndID );
 				curEvtTagFlv_ = flavTag_->getCurEvtTagFlv();
 				curEvtMistag_ = flavTag_->getCurEvtMistag();
 
 				break;
 			}
 
 		case LauFlavTag::FlavourSpecific:
 			{
 				const LauDecayTimePdf::FuncType dtType { BkgndDecayTimePdfs_[bkgndID]->getFuncType() };
 				if ( dtType == LauDecayTimePdf::FuncType::ExpTrig or dtType == LauDecayTimePdf::FuncType::ExpHypTrig ) {
 					nGenLoop_ = 0;
 					Bool_t generatedEvent{kFALSE};
 					do {
 						curEvtTrueTagFlv_ = LauFlavTag::Flavour::Unknown;
 						curEvtDecayFlv_ = LauFlavTag::Flavour::Unknown;
 
 						// First choose the true tag, accounting for the production asymmetry
 						// CONVENTION WARNING regarding meaning of sign of AProd
 						Double_t random = LauRandom::randomFun()->Rndm();
 						if (random <= 0.5 * ( 1.0 - AProdBkgnd_[bkgndID]->unblindValue() ) ) {
 							curEvtTrueTagFlv_ = LauFlavTag::Flavour::B;
 						} else {
 							curEvtTrueTagFlv_ = LauFlavTag::Flavour::Bbar;
 						}
 
 						// Generate the DP position
 						Double_t m13Sq{0.0}, m23Sq{0.0};
 						kinematicsB0bar_->genFlatPhaseSpace(m13Sq, m23Sq);
 
 						// Next, calculate the total A^2 and Abar^2 for the given DP position
 						BkgndDPModelsB_[bkgndID]->calcLikelihoodInfo(m13Sq, m23Sq);
 						BkgndDPModelsBbar_[bkgndID]->calcLikelihoodInfo(m13Sq, m23Sq);
 
 						// Generate decay time
 						const Double_t tMin = BkgndDecayTimePdfs_[bkgndID]->minAbscissa();
 						const Double_t tMax = BkgndDecayTimePdfs_[bkgndID]->maxAbscissa();
 						curEvtDecayTime_ = LauRandom::randomFun()->Uniform(tMin,tMax);
 
 						// Generate the decay time error (NB the kTRUE forces the generation of a new value)
 						curEvtDecayTimeErr_ = BkgndDecayTimePdfs_[bkgndID]->generateError(kTRUE);
 
 						// Calculate all the decay time info
 						BkgndDecayTimePdfs_[bkgndID]->calcLikelihoodInfo(curEvtDecayTime_,curEvtDecayTimeErr_);
 
 
 						// Retrieve the DP intensities
 						const Double_t ASq { BkgndDPModelsB_[bkgndID]->getUnNormValue() };
 						const Double_t AbarSq { BkgndDPModelsBbar_[bkgndID]->getUnNormValue() };
 
 						// Also retrieve all the decay time terms
 						const Double_t dtCos { BkgndDecayTimePdfs_[bkgndID]->getCosTerm() };
 						const Double_t dtCosh { BkgndDecayTimePdfs_[bkgndID]->getCoshTerm() };
 						// and the decay time acceptance
 						const Double_t dtEff { BkgndDecayTimePdfs_[bkgndID]->getEffiTerm() };
 
 						if ( cpEigenValue_ == QFS) {
 							// Calculate the total intensities for each flavour-specific final state
 							const Double_t ATotSq    { ( ASq    * dtCosh + curEvtTrueTagFlv_ * ASq    * dtCos ) * dtEff };
 							const Double_t AbarTotSq { ( AbarSq * dtCosh - curEvtTrueTagFlv_ * AbarSq * dtCos ) * dtEff };
 							const Double_t ASumSq { ATotSq + AbarTotSq };
 
 							// TODO - check if this really is the max possible
 							const Double_t ASumSqMax { 2.0 * ( BkgndDPModelsB_[bkgndID]->getMaxHeight() + BkgndDPModelsBbar_[bkgndID]->getMaxHeight() ) };
 
 							// Finally we throw the dice to see whether this event should be generated (and, if so, which final state)
 							const Double_t randNum = LauRandom::randomFun()->Rndm();
 							if (randNum <= ASumSq / ASumSqMax ) {
 								generatedEvent = kTRUE;
 								nGenLoop_ = 0;
 								if (ASumSq > ASumSqMax) {
 									std::cerr << "WARNING in LauTimeDepFitModel::generateBkgndEvent : ASumSq > ASumSqMax" << std::endl;
 								}
 
 								if ( randNum <= ATotSq / ASumSqMax ) {
 									curEvtDecayFlv_ = LauFlavTag::Flavour::B;
 								} else {
 									curEvtDecayFlv_ = LauFlavTag::Flavour::Bbar;
 								}
 
 								// Generate the flavour tagging information from the true tag
 								// (we do this after accepting the event to save time)
 								flavTag_->generateBkgndEventInfo( curEvtTrueTagFlv_, curEvtDecayTime_, bkgndID );
 								curEvtTagFlv_ = flavTag_->getCurEvtTagFlv();
 								curEvtMistag_ = flavTag_->getCurEvtMistag();
 							} else {
 								nGenLoop_++;
 							}
 						} else {
 							// Calculate the DP terms
 							const Double_t aSqSum { ASq + AbarSq };
 							const Double_t aSqDif { ASq - AbarSq };
 
 							// Combine DP and decay-time info for all terms
 							const Double_t coshTerm { aSqSum * dtCosh };
 							const Double_t cosTerm  { aSqDif * dtCos  };
 
 							// Sum to obtain the total and multiply by the efficiency
 							// Multiplying the cos term by the true flavour at production
 							const Double_t ATotSq { ( coshTerm + curEvtTrueTagFlv_ * cosTerm ) * dtEff };
 
 							// TODO - check if this really is the max possible
 							const Double_t ATotSqMax { 2.0 * TMath::Max( BkgndDPModelsB_[bkgndID]->getMaxHeight(), BkgndDPModelsBbar_[bkgndID]->getMaxHeight() ) };
 
 							// Finally we throw the dice to see whether this event should be generated
 							const Double_t randNum = LauRandom::randomFun()->Rndm();
 							if (randNum <= ATotSq/ATotSqMax ) {
 								generatedEvent = kTRUE;
 								nGenLoop_ = 0;
 
 								if (ATotSq > ATotSqMax) {
 									// TODO
 									std::cerr << "WARNING in LauTimeDepFitModel::generateBkgndEvent : ATotSq > ATotSqMax" << std::endl;
 								}
 
 								// Generate the flavour tagging information from the true tag
 								// (we do this after accepting the event to save time)
 								flavTag_->generateBkgndEventInfo( curEvtTrueTagFlv_, curEvtDecayTime_, bkgndID );
 								curEvtTagFlv_ = flavTag_->getCurEvtTagFlv();
 								curEvtMistag_ = flavTag_->getCurEvtMistag();
 							} else {
 								nGenLoop_++;
 							}
 						}
 
 					} while (generatedEvent == kFALSE && nGenLoop_ < iterationsMax_);
 				} else {
 					// Hist, Delta, Exp, DeltaExp decay-time types
 
 					// First choose the true tag, accounting for the production asymmetry
 					// CONVENTION WARNING regarding meaning of sign of AProd
 					Double_t random = LauRandom::randomFun()->Rndm();
 					if (random <= 0.5 * ( 1.0 - AProdBkgnd_[bkgndID]->unblindValue() ) ) {
 						curEvtTrueTagFlv_ = LauFlavTag::Flavour::B;
 					} else {
 						curEvtTrueTagFlv_ = LauFlavTag::Flavour::Bbar;
 					}
 
 					// Since there are no oscillations for these decay-time types,
 					// the true decay flavour must be equal to the true tag flavour
 					curEvtDecayFlv_ = curEvtTrueTagFlv_;
 
 					// generate the DP position
 					if ( curEvtDecayFlv_ == LauFlavTag::Flavour::B ) {
 						BkgndDPModelsB_[bkgndID]->generate();
 					} else {
 						BkgndDPModelsBbar_[bkgndID]->generate();
 					}
 
 					// generate decay time and its error
 					const LauKinematics* kinematics { ( curEvtDecayFlv_ == LauFlavTag::Flavour::B ) ? kinematicsB0_ : kinematicsB0bar_ };
 					curEvtDecayTimeErr_ = BkgndDecayTimePdfs_[bkgndID]->generateError(kTRUE);
 					curEvtDecayTime_ = BkgndDecayTimePdfs_[bkgndID]->generate( kinematics );
 
 					// generate the flavour tagging response
 					flavTag_->generateBkgndEventInfo( curEvtTrueTagFlv_, curEvtDecayTime_, bkgndID );
 					curEvtTagFlv_ = flavTag_->getCurEvtTagFlv();
 					curEvtMistag_ = flavTag_->getCurEvtMistag();
 				}
 
 				break;
 			}
 
 		case LauFlavTag::SelfConjugate:
 			// TODO
 			break;
 
 		case LauFlavTag::NonSelfConjugate:
 			// TODO
 			break;
 	}
 
 	return genOK;
 }
 
 void LauTimeDepFitModel::setupGenNtupleBranches()
 {
 	// Setup the required ntuple branches
 	this->addGenNtupleDoubleBranch("evtWeight");
 	this->addGenNtupleIntegerBranch("genSig");
 
 	this->addGenNtupleIntegerBranch("cpEigenvalue");
 
 	const TString& trueTagVarName { flavTag_->getTrueTagVarName() };
 	if ( trueTagVarName != "" ) {
 		this->addGenNtupleIntegerBranch(trueTagVarName);
 	}
 
 	if ( cpEigenValue_ == QFS ) {
 		const TString& decayFlvVarName { flavTag_->getDecayFlvVarName() };
 		if ( decayFlvVarName != "" ) {
 			this->addGenNtupleIntegerBranch(decayFlvVarName);
 		}
 	}
 
 	const std::vector<TString>& tagVarNames { flavTag_->getTagVarNames() };
 	const std::vector<TString>& mistagVarNames { flavTag_->getMistagVarNames() };
 
 	const ULong_t nTaggers {flavTag_->getNTaggers()};
 	for (ULong_t position{0}; position<nTaggers; ++position){
 		this->addGenNtupleIntegerBranch(tagVarNames[position]);
 		this->addGenNtupleDoubleBranch(mistagVarNames[position]);
 	}
 
 	if (this->useDP() == kTRUE) {
 		// Let's add the decay time variables.
 		this->addGenNtupleDoubleBranch(signalDecayTimePdf_->varName());
 		this->addGenNtupleDoubleBranch(signalDecayTimePdf_->varErrName());
 		this->addGenNtupleDoubleBranch("m12");
 		this->addGenNtupleDoubleBranch("m23");
 		this->addGenNtupleDoubleBranch("m13");
 		this->addGenNtupleDoubleBranch("m12Sq");
 		this->addGenNtupleDoubleBranch("m23Sq");
 		this->addGenNtupleDoubleBranch("m13Sq");
 		this->addGenNtupleDoubleBranch("cosHel12");
 		this->addGenNtupleDoubleBranch("cosHel23");
 		this->addGenNtupleDoubleBranch("cosHel13");
 		if (kinematicsB0bar_->squareDP() && kinematicsB0_->squareDP()) {
 			this->addGenNtupleDoubleBranch("mPrime");
 			this->addGenNtupleDoubleBranch("thPrime");
 		}
 
 		// Can add the real and imaginary parts of the B0 and B0bar total
 		// amplitudes seen in the generation (restrict this with a flag
 		// that defaults to false)
 		if ( storeGenAmpInfo_ ) {
 			this->addGenNtupleDoubleBranch("reB0Amp");
 			this->addGenNtupleDoubleBranch("imB0Amp");
 			this->addGenNtupleDoubleBranch("reB0barAmp");
 			this->addGenNtupleDoubleBranch("imB0barAmp");
 		}
 	}
 
 	// Let's look at the extra variables for signal in one of the tagging categories
 	for ( const LauAbsPdf* pdf : sigExtraPdf_ ) {
 		const std::vector<TString> varNames{ pdf->varNames() };
 		for ( const TString& varName : varNames ) {
 			if ( varName != "m13Sq" && varName != "m23Sq" ) {
 				this->addGenNtupleDoubleBranch( varName );
 			}
 		}
 	}
 }
 
 void LauTimeDepFitModel::setDPDtBranchValues()
 {
 	// Store the decay time variables.
 	this->setGenNtupleDoubleBranchValue(signalDecayTimePdf_->varName(),curEvtDecayTime_);
 	this->setGenNtupleDoubleBranchValue(signalDecayTimePdf_->varErrName(),curEvtDecayTimeErr_);
 
 	// CONVENTION WARNING
 	// TODO check - for now use B0 for any tags
 	//LauKinematics* kinematics(0);
 	//if (curEvtTagFlv_[position]<0) {
 	LauKinematics* kinematics = kinematicsB0_;
 	//} else {
 	//	kinematics = kinematicsB0bar_;
 	//}
 
 	// Store all the DP information
 	this->setGenNtupleDoubleBranchValue("m12", kinematics->getm12());
 	this->setGenNtupleDoubleBranchValue("m23", kinematics->getm23());
 	this->setGenNtupleDoubleBranchValue("m13", kinematics->getm13());
 	this->setGenNtupleDoubleBranchValue("m12Sq", kinematics->getm12Sq());
 	this->setGenNtupleDoubleBranchValue("m23Sq", kinematics->getm23Sq());
 	this->setGenNtupleDoubleBranchValue("m13Sq", kinematics->getm13Sq());
 	this->setGenNtupleDoubleBranchValue("cosHel12", kinematics->getc12());
 	this->setGenNtupleDoubleBranchValue("cosHel23", kinematics->getc23());
 	this->setGenNtupleDoubleBranchValue("cosHel13", kinematics->getc13());
 	if (kinematics->squareDP()) {
 		this->setGenNtupleDoubleBranchValue("mPrime", kinematics->getmPrime());
 		this->setGenNtupleDoubleBranchValue("thPrime", kinematics->getThetaPrime());
 	}
 
 	// Can add the real and imaginary parts of the B0 and B0bar total
 	// amplitudes seen in the generation (restrict this with a flag
 	// that defaults to false)
 	if ( storeGenAmpInfo_ ) {
 		if ( this->getGenNtupleIntegerBranchValue("genSig")==1 ) {
 			LauComplex Abar = sigModelB0bar_->getEvtDPAmp();
 			LauComplex A = sigModelB0_->getEvtDPAmp();
 
 			this->setGenNtupleDoubleBranchValue("reB0Amp", A.re());
 			this->setGenNtupleDoubleBranchValue("imB0Amp", A.im());
 			this->setGenNtupleDoubleBranchValue("reB0barAmp", Abar.re());
 			this->setGenNtupleDoubleBranchValue("imB0barAmp", Abar.im());
 		} else {
 			this->setGenNtupleDoubleBranchValue("reB0Amp", 0.0);
 			this->setGenNtupleDoubleBranchValue("imB0Amp", 0.0);
 			this->setGenNtupleDoubleBranchValue("reB0barAmp", 0.0);
 			this->setGenNtupleDoubleBranchValue("imB0barAmp", 0.0);
 		}
 	}
 }
 
 void LauTimeDepFitModel::generateExtraPdfValues(LauPdfList& extraPdfs, LauEmbeddedData* embeddedData)
 {
 	// CONVENTION WARNING
 	LauKinematics* kinematics = kinematicsB0_;
 	//LauKinematics* kinematics(0);
 	//if (curEvtTagFlv_<0) {
 	//	kinematics = kinematicsB0_;
 	//} else {
 	//	kinematics = kinematicsB0bar_;
 	//}
 
 	// Generate from the extra PDFs
 	for (auto& pdf : extraPdfs){
 		LauFitData genValues;
 		if (embeddedData) {
 			genValues = embeddedData->getValues( pdf->varNames() );
 		} else {
 			genValues = pdf->generate(kinematics);
 		}
 		for (auto& var : genValues){
 			TString varName = var.first;
 			if ( varName != "m13Sq" && varName != "m23Sq" ) {
 				Double_t value = var.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 decay time normalisation
 	if ( signalDecayTimePdf_ ) {
 	      signalDecayTimePdf_->propagateParUpdates();
 	}
 	// TODO
 	// - maybe also need to add an update of the background decay time PDFs here
 
 	// Update the signal events from the background numbers if not doing an extended fit
 	// And update the tagging category fractions
 	this->updateSigEvents();
 }
 
 void LauTimeDepFitModel::updateSigEvents()
 {
 	// The background parameters will have been set from Minuit.
 	// We need to update the signal events using these.
 	if (!this->doEMLFit()) {
 		Double_t nTotEvts = this->eventsPerExpt();
 		Double_t signalEvents = nTotEvts;
 		signalEvents_->range(-2.0*nTotEvts,2.0*nTotEvts);
 		for (auto& nBkgndEvents : bkgndEvents_){
 			if ( nBkgndEvents->isLValue() ) {
 				LauParameter* yield = dynamic_cast<LauParameter*>( nBkgndEvents );
 				yield->range(-2.0*nTotEvts,2.0*nTotEvts);
 			}
 		}
 
 		// Subtract background events (if any) from signal.
 		if (usingBkgnd_ == kTRUE) {
 			for (auto& nBkgndEvents : bkgndEvents_){
 				signalEvents -= nBkgndEvents->value();
 			}
 		}
 		if ( ! signalEvents_->fixed() ) {
 			signalEvents_->value(signalEvents);
 		}
 	}
 }
 
 void LauTimeDepFitModel::cacheInputFitVars()
 {
 	// Fill the internal data trees of the signal and background models.
 	// Note that we store the events of both charges in both the
 	// negative and the positive models. It's only later, at the stage
 	// when the likelihood is being calculated, that we separate them.
 
 	LauFitDataTree* inputFitData = this->fitData();
 
 	evtCPEigenVals_.clear();
 
 	const Bool_t hasCPEV = ( (cpevVarName_ != "") && inputFitData->haveBranch( cpevVarName_ ) );
 
 	UInt_t nEvents = inputFitData->nEvents();
 	evtCPEigenVals_.reserve( nEvents );
 	LauFitData::const_iterator fitdata_iter;
 	for (UInt_t iEvt = 0; iEvt < nEvents; iEvt++) {
 		const LauFitData& dataValues = inputFitData->getData(iEvt);
 
 		// if the CP-eigenvalue is in the data use those, otherwise use the default
 		if ( hasCPEV ) {
 			fitdata_iter = dataValues.find( cpevVarName_ );
 			const Int_t cpEV = static_cast<Int_t>( fitdata_iter->second );
 			if ( cpEV == 1 ) {
 				cpEigenValue_ = CPEven;
 			} else if ( cpEV == -1 ) {
 				cpEigenValue_ = CPOdd;
 			} else if ( cpEV == 0 ) {
 				cpEigenValue_ = QFS;
 			} 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.
 
 	if (this->useDP() == kTRUE) {
 		// DecayTime and SigmaDecayTime
 		signalDecayTimePdf_->cacheInfo(*inputFitData);
 		// cache all the backgrounds too
 		for(auto& bg : BkgndDecayTimePdfs_)
 		{bg->cacheInfo(*inputFitData);}
 	}
 
 	// Flavour tagging information
 	flavTag_->cacheInputFitVars(inputFitData,signalDecayTimePdf_->varName());
 
 	// ...and then the extra PDFs
 	if (not sigExtraPdf_.empty()){
 		this->cacheInfo(sigExtraPdf_, *inputFitData);
 	}
 
 	if(usingBkgnd_ == kTRUE){
 		for (auto& pdf : BkgndPdfs_){
 			this->cacheInfo(pdf, *inputFitData);
 		}
 	}
 
 	if (this->useDP() == kTRUE) {
 		sigModelB0bar_->fillDataTree(*inputFitData);
 		sigModelB0_->fillDataTree(*inputFitData);
 		if (usingBkgnd_ == kTRUE) {
 			for (auto& model : BkgndDPModelsB_){
 				model->fillDataTree(*inputFitData);
 			}
 			for (auto& model : BkgndDPModelsBbar_){
 				if (model != nullptr) {
 					model->fillDataTree(*inputFitData);
 				}
 			}
 		}
 	}
 }
 
 Double_t LauTimeDepFitModel::getTotEvtLikelihood(const UInt_t 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 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_ * sigExtraLike_;
 
 	Double_t signalEvents = signalEvents_->unblindValue();
 	// TODO - consider what to do here - do we even want the option not to use the DP in this model?
 	//if ( not this->useDP() ) {
 		//signalEvents *= 0.5 * (1.0 + curEvtTagFlv_ * signalAsym_->unblindValue());
 	//}
 
 	// Construct the total event likelihood
 	Double_t likelihood { sigLike * signalEvents };
 	if (usingBkgnd_) {
 		const UInt_t nBkgnds = this->nBkgndClasses();
 		for ( UInt_t bkgndID(0); bkgndID < nBkgnds; ++bkgndID ) {
 			// TODO
 			// for combinatorial background (and perhaps others) this factor 0.5 needs to be here
 			// to balance the factor 2 in the signal normalisation that arises from the sum over
 			// tag decisions and integral over eta
 			// for other (more signal-like) backgrounds where we need to think about things depending
 			// on the tag decision and where there may be asymmetries as well this will (probably) arise naturally
 			const Double_t bkgndEvents { 0.5 * bkgndEvents_[bkgndID]->unblindValue() };
 			likelihood += bkgndEvents*bkgndDPLike_[bkgndID]*bkgndExtraLike_[bkgndID];
 		}
 	}
 	return likelihood;
 }
 
 Double_t LauTimeDepFitModel::getEventSum() const
 {
 	Double_t eventSum(0.0);
 	eventSum += signalEvents_->unblindValue();
 	if (usingBkgnd_) {
 		for ( const auto& yieldPar : bkgndEvents_ ) {
 			eventSum += yieldPar->unblindValue();
 		}
 	}
 	return eventSum;
 }
 
 void LauTimeDepFitModel::getEvtDPDtLikelihood(const UInt_t iEvt)
 {
 	// Function to return the signal and background likelihoods for the
 	// Dalitz plot for the given event evtNo.
 
 	if ( ! this->useDP() ) {
 		// There's always going to be a term in the likelihood for the
 		// signal, so we'd better not zero it.
 		sigDPLike_ = 1.0;
 
 		const UInt_t nBkgnds = this->nBkgndClasses();
 		for ( UInt_t bkgndID(0); bkgndID < nBkgnds; ++bkgndID ) {
 			if (usingBkgnd_ == kTRUE) {
 				bkgndDPLike_[bkgndID] = 1.0;
 			} else {
 				bkgndDPLike_[bkgndID] = 0.0;
 			}
 		}
 
 		return;
 	}
 
 	// Calculate event quantities
 	// Get the DP dynamics, decay time, and flavour tagging to calculate
 	// everything required for the likelihood calculation
 
 	sigModelB0bar_->calcLikelihoodInfo(iEvt);
 	sigModelB0_->calcLikelihoodInfo(iEvt);
 
 	signalDecayTimePdf_->calcLikelihoodInfo(iEvt);
 
 	flavTag_->updateEventInfo(iEvt);
 
 
 	// Retrieve the amplitudes and efficiency from the dynamics
 	LauComplex Abar { sigModelB0bar_->getEvtDPAmp() };
 	LauComplex A { sigModelB0_->getEvtDPAmp() };
 
 	const Double_t dpEff { sigModelB0bar_->getEvtEff() };
 
 
 	// If this is a QFS decay, one of the DP amplitudes needs to be zeroed
 	if (cpEigenValue_ == QFS){
 		curEvtDecayFlv_ = flavTag_->getCurEvtDecayFlv();
 		if ( curEvtDecayFlv_ == +1 ) {
 			Abar.zero();
 		} else if ( curEvtDecayFlv_ == -1 ) {
 			A.zero();
 		}
 	}
 
 
 	// Next calculate the DP terms
 	const Double_t aSqSum { A.abs2() + Abar.abs2() };
 	const Double_t aSqDif { A.abs2() - Abar.abs2() };
 	Double_t interTermRe { 0.0 };
 	Double_t interTermIm { 0.0 };
 	if ( cpEigenValue_ != QFS ) {
 		const LauComplex inter { Abar * A.conj() * phiMixComplex_ };
 		if ( cpEigenValue_ == CPEven ) {
 			interTermIm = 2.0 * inter.im();
 			interTermRe = 2.0 * inter.re();
 		} else {
 			interTermIm = -2.0 * inter.im();
 			interTermRe = -2.0 * inter.re();
 		}
 	}
 
 	// First get all the decay time terms
 
 	// TODO Backgrounds
 
 	// Get the decay time acceptance
 	const Double_t dtEff { signalDecayTimePdf_->getEffiTerm() };
 
 	// Get all the decay time terms
 	const Double_t dtCos { signalDecayTimePdf_->getCosTerm() };
 	const Double_t dtSin { signalDecayTimePdf_->getSinTerm() };
 	const Double_t dtCosh { signalDecayTimePdf_->getCoshTerm() };
 	const Double_t dtSinh { signalDecayTimePdf_->getSinhTerm() };
 
 	// Get the decay time error term
 	const Double_t dtErrLike { signalDecayTimePdf_->getErrTerm() };
 
 	// Get flavour tagging terms
 	Double_t omega{1.0};
 	Double_t omegabar{1.0};
 	const ULong_t nTaggers { flavTag_->getNTaggers() };
 	for (ULong_t position{0}; position<nTaggers; ++position){
 		omega    *= flavTag_->getCapitalOmega(position, LauFlavTag::Flavour::B);
 		omegabar *= flavTag_->getCapitalOmega(position, LauFlavTag::Flavour::Bbar);
 	}
 
 	const Double_t prodAsym { AProd_.unblindValue() };
 	const Double_t ftOmegaHyp  { ((1.0 - prodAsym)*omega + (1.0 + prodAsym)*omegabar) };
 	const Double_t ftOmegaTrig { ((1.0 - prodAsym)*omega - (1.0 + prodAsym)*omegabar) };
 
 	const Double_t coshTerm { ftOmegaHyp * dtCosh * aSqSum };
 	const Double_t sinhTerm { ftOmegaHyp * dtSinh * interTermRe };
 	const Double_t cosTerm  { ftOmegaTrig * dtCos * aSqDif };
 	const Double_t sinTerm  { ftOmegaTrig * dtSin * interTermIm };
 
 	// Combine all terms to get the total amplitude squared
 	const Double_t ASq { coshTerm + sinhTerm + cosTerm - sinTerm };
 
 
 	// Calculate the DP and time normalisation
 	const Double_t normASqSum  { sigModelB0_->getDPNorm() + sigModelB0bar_->getDPNorm() };
 	const Double_t normASqDiff { sigModelB0_->getDPNorm() - sigModelB0bar_->getDPNorm() };
 	Double_t normInterTermRe { 0.0 };
 	Double_t normInterTermIm { 0.0 };
 	if ( cpEigenValue_ != QFS ) {
 		// TODO - double check this sign flipping here (it's presumably right but...)
 		normInterTermRe = ( cpEigenValue_ == CPOdd ) ? -1.0 * interTermReNorm_ : interTermReNorm_;
 		normInterTermIm = ( cpEigenValue_ == CPOdd ) ? -1.0 * interTermImNorm_ : interTermImNorm_;
 	}
 
 	const Double_t normCoshTerm { signalDecayTimePdf_->getNormTermCosh() };
 	const Double_t normSinhTerm { signalDecayTimePdf_->getNormTermSinh() };
 	const Double_t normCosTerm { signalDecayTimePdf_->getNormTermCos() };
 	const Double_t normSinTerm { signalDecayTimePdf_->getNormTermSin() };
 
 	const Double_t normHyp { normASqSum * normCoshTerm + normInterTermRe * normSinhTerm };
 	const Double_t normTrig { - prodAsym * ( normASqDiff * normCosTerm + normInterTermIm * normSinTerm ) };
 
 	// Combine all terms to get the total normalisation
 	const Double_t norm { 2.0 * ( normHyp + normTrig ) };
 
 	// Multiply the squared-amplitude by the efficiency (DP and decay time) and decay-time error likelihood
 	// and normalise to obtain the signal likelihood
 	sigDPLike_ = ( ASq * dpEff * dtEff * dtErrLike ) / norm;
 
 
 	// Background part
 	// TODO add them into the actual Likelihood calculatiions
 	// TODO sort out B and Bbar backgrounds for the DP here
 	// TODO need to include the flavour tagging parts here as well (per tagger and per background source) and will vary by Bkgnd type as well
 	// TODO add new function as getEvtBkgndLikelihoods?
 	// TODO normalisation?
 	const UInt_t nBkgnds = this->nBkgndClasses();
 	for ( UInt_t bkgndID(0); bkgndID < nBkgnds; ++bkgndID ) {
 		if (usingBkgnd_ == kTRUE) {
 			Double_t omegaBkgnd{1.0};
 			Double_t omegaBarBkgnd{1.0};
 
 			BkgndDecayTimePdfs_[bkgndID]->calcLikelihoodInfo(iEvt);
 
 			// Consider background type
 			// TODO would this not be cleaner as a switch/cases block?
 			if (BkgndTypes_[bkgndID] == LauFlavTag::Combinatorial){
 				// For Histogram Dt Pdfs
 				// TODO - any other decay time function types that make sense for combinatorial?
 				//      - if so, maybe convert this to a switch with a default case to catch the types that don't make sense?
 				// For comb background the DP and TD models factorise completely, just mulitply them
 				bkgndDPLike_[bkgndID] = BkgndDPModelsB_[bkgndID]->getLikelihood(iEvt);
 				if (BkgndDecayTimePdfs_[bkgndID]->getFuncType() == LauDecayTimePdf::Hist){
 					bkgndDPLike_[bkgndID] *= BkgndDecayTimePdfs_[bkgndID]->getHistTerm();
 				} else {
 					bkgndDPLike_[bkgndID] *= BkgndDecayTimePdfs_[bkgndID]->getExpTerm()/BkgndDecayTimePdfs_[bkgndID]->getNormTermExp();
 				}
 				// For flavour tagging
 				for (ULong_t position{0}; position<nTaggers; ++position){
 					// Only need omega==omegabar for combinatorial
 					omegaBkgnd *= flavTag_->getCapitalOmegaBkgnd(position, LauFlavTag::Flavour::B, bkgndID);
 				}
 				bkgndDPLike_[bkgndID] *= omegaBkgnd;
 				// TODO Add other bkg types
 			} else if (BkgndTypes_[bkgndID] == LauFlavTag::FlavourSpecific){
 
 				switch( BkgndDecayTimePdfs_[bkgndID]->getFuncType() )
 				{
 					case LauDecayTimePdf::FuncType::Exp : //it still factorises
 						{
 							bkgndDPLike_[bkgndID] = 0.5*(BkgndDPModelsB_[bkgndID]->getLikelihood(iEvt) + BkgndDPModelsBbar_[bkgndID]->getLikelihood(iEvt));
 							bkgndDPLike_[bkgndID] *= BkgndDecayTimePdfs_[bkgndID]->getExpTerm()/BkgndDecayTimePdfs_[bkgndID]->getNormTermExp();
 							for (ULong_t position{0}; position<nTaggers; ++position){
 								omegaBkgnd    *= flavTag_->getCapitalOmegaBkgnd(position, LauFlavTag::Flavour::B   , bkgndID);
 								omegaBarBkgnd *= flavTag_->getCapitalOmegaBkgnd(position, LauFlavTag::Flavour::Bbar, bkgndID);
 							}
 							bkgndDPLike_[bkgndID] *= ((1.0 - prodAsym)*omegaBkgnd + (1.0 + prodAsym)*omegaBarBkgnd);
 							break;
 						}
 					case LauDecayTimePdf::FuncType::Hist: //it still factorises
 						{
 							bkgndDPLike_[bkgndID] = 0.5*(BkgndDPModelsB_[bkgndID]->getLikelihood(iEvt) + BkgndDPModelsBbar_[bkgndID]->getLikelihood(iEvt));
 							bkgndDPLike_[bkgndID] *= BkgndDecayTimePdfs_[bkgndID]->getHistTerm();
 							for (ULong_t position{0}; position<nTaggers; ++position){
 								omegaBkgnd    *= flavTag_->getCapitalOmegaBkgnd(position, LauFlavTag::Flavour::B   , bkgndID);
 								omegaBarBkgnd *= flavTag_->getCapitalOmegaBkgnd(position, LauFlavTag::Flavour::Bbar, bkgndID);
 							}
 							bkgndDPLike_[bkgndID] *= ((1.0 - prodAsym)*omegaBkgnd + (1.0 + prodAsym)*omegaBarBkgnd);
 							break;
 						}
 					case LauDecayTimePdf::FuncType::ExpTrig: // it doesn't factorise
 					case LauDecayTimePdf::FuncType::ExpHypTrig:
 						{
 							//DP components first
 							Double_t Asq    { BkgndDPModelsB_[bkgndID]   ->getUnNormValue(iEvt) };
 							Double_t Asqbar { BkgndDPModelsBbar_[bkgndID]->getUnNormValue(iEvt) };
 
 							//Used in the normalisation
 							const Double_t AsqNorm    { BkgndDPModelsB_[bkgndID]   ->getPdfNorm() };
 							const Double_t AsqbarNorm { BkgndDPModelsBbar_[bkgndID]->getPdfNorm() };
 
 							//Do different things depending on whether the signal is Flav Specific or Self Conjugate
 							if (cpEigenValue_ == QFS){ //Flavour specific
 								curEvtDecayFlv_ = flavTag_->getCurEvtDecayFlv();
 								if ( curEvtDecayFlv_ == +1 ) {
 									Asqbar = 0.;
 								} else if ( curEvtDecayFlv_ == -1 ) {
 									Asq = 0.;
 								}
 							}
 							const Double_t AsqSum  { Asq + Asqbar };
 							const Double_t AsqDiff { Asq - Asqbar };
 
 							const Double_t AsqNormSum  { AsqNorm + AsqbarNorm };
 							//TODO check this shouldn't be `fabs`ed
 							const Double_t AsqNormDiff { AsqNorm - AsqbarNorm };
 
 							// Now get all the decay time terms
 							// Sin and Sinh terms are ignored: they FS modes can't exhibit TD CPV
 							const Double_t dtCosBkgnd  { BkgndDecayTimePdfs_[bkgndID]->getCosTerm() };
 							const Double_t dtCoshBkgnd { BkgndDecayTimePdfs_[bkgndID]->getCoshTerm() };
 							// Get all norm terms
 							const Double_t normCosTermBkgnd  { BkgndDecayTimePdfs_[bkgndID]->getNormTermCos() };
 							const Double_t normCoshTermBkgnd { BkgndDecayTimePdfs_[bkgndID]->getNormTermCosh() };
 							// Use signal flavour tagging
 							for (ULong_t position{0}; position<nTaggers; ++position){
 								omegaBkgnd    *= flavTag_->getCapitalOmegaBkgnd(position, LauFlavTag::Flavour::B   , bkgndID);
 								omegaBarBkgnd *= flavTag_->getCapitalOmegaBkgnd(position, LauFlavTag::Flavour::Bbar, bkgndID);
 							}
 							// Depends on the background source? Or use the signal one?
 							// TODO change prodAsym to be that of this specific background, not the signal
 							const Double_t ftOmegaHypBkgnd  { ((1.0 - AProdBkgnd_[bkgndID]->unblindValue())*omegaBkgnd + (1.0 + AProdBkgnd_[bkgndID]->unblindValue())*omegaBarBkgnd) };
 							const Double_t ftOmegaTrigBkgnd { ((1.0 - AProdBkgnd_[bkgndID]->unblindValue())*omegaBkgnd - (1.0 + AProdBkgnd_[bkgndID]->unblindValue())*omegaBarBkgnd) };
 							//ExpTrig or ExpHypTrig modes
 							//TODO Check normalisation
 							const Double_t coshTermBkgnd { ftOmegaHypBkgnd * dtCoshBkgnd * AsqSum  };
 							const Double_t cosTermBkgnd  { ftOmegaTrigBkgnd * dtCosBkgnd * AsqDiff };
 
 							//See Laura note eq. 41
 							const Double_t normBkgnd { (normCoshTermBkgnd * AsqNormSum) - prodAsym*(normCosTermBkgnd * AsqNormDiff) };
 
 							bkgndDPLike_[bkgndID] *= (coshTermBkgnd + cosTermBkgnd)/normBkgnd;
 							break;
 						}
 					case LauDecayTimePdf::FuncType::Delta: //prompt case: irrellevant
 					case LauDecayTimePdf::FuncType::DeltaExp:
 						//TODO move this error message
 						std::cerr << "WARNING in LauTimeDepFitModel::getEvtDPDtLikelihood : bkgnd types Delta and DeltaExp don't make sense!" << std::endl;
 						break;
 				}
 
 			} else if (BkgndTypes_[bkgndID] == LauFlavTag::SelfConjugate) {
 				//Copy this from the CPeigenstate signal case
 				std::cerr << "WARNING in LauTimeDepFitModel::getEvtDPDtLikelihood : SelfConjugate states aren't implemented yet!" << std::endl;
 				bkgndDPLike_[bkgndID] = 0.0; break;
 			} else if (BkgndTypes_[bkgndID] == LauFlavTag::NonSelfConjugate) {
 				// TODO this has been ignored for now since it's not used in the B->Dpipi case
 				std::cerr << "WARNING in LauTimeDepFitModel::getEvtDPDtLikelihood : NonSelfConjugate states aren't implemented yet!" << std::endl;
 				bkgndDPLike_[bkgndID] = 0.0; break;
 			}
 
 			// Get the decay time acceptance
 			const Double_t dtEffBkgnd { BkgndDecayTimePdfs_[bkgndID]->getEffiTerm() };
 			// Get the decay time error term
 			const Double_t dtErrLikeBkgnd { BkgndDecayTimePdfs_[bkgndID]->getErrTerm() };
 			// Include these terms in the background likelihood
 			bkgndDPLike_[bkgndID] *= dtEffBkgnd * dtErrLikeBkgnd;
 		} else {
 			bkgndDPLike_[bkgndID] = 0.0;
 		}
 	}
 }
 
 void LauTimeDepFitModel::getEvtExtraLikelihoods(const UInt_t iEvt)
 {
 	// Function to return the signal and background likelihoods for the
 	// extra variables for the given event evtNo.
 	sigExtraLike_ = 1.0;	//There's always a likelihood term for signal, so we better not zero it.
 
 	// First, those independent of the tagging of the event:
 	// signal
 	if ( not sigExtraPdf_.empty() ) {
 		sigExtraLike_ = this->prodPdfValue( sigExtraPdf_, iEvt );
 	}
 
 	// Background
 	const UInt_t nBkgnds = this->nBkgndClasses();
 	for ( UInt_t bkgndID(0); bkgndID < nBkgnds; ++bkgndID ) {
 		if (usingBkgnd_) {
 			bkgndExtraLike_[bkgndID] = this->prodPdfValue( BkgndPdfs_[bkgndID], iEvt );
 		} else {
 			bkgndExtraLike_[bkgndID] = 0.0;
 		}
 	}
 
 }
 
 //TODO obsolete?
 void LauTimeDepFitModel::getEvtFlavTagLikelihood(const UInt_t iEvt)
 {
 	// Function to return the signal and background likelihoods for the
 	// extra variables for the given event evtNo.
 	sigFlavTagLike_ = 1.0;	//There's always a likelihood term for signal, so we better not zero it.
 
 	// Loop over taggers
 	const ULong_t nTaggers { flavTag_->getNTaggers() };
 	for (ULong_t position{0}; position<nTaggers; ++position){
 		if (sigFlavTagPdf_[position]) {
 			sigFlavTagPdf_[position]->calcLikelihoodInfo(iEvt);
 			sigFlavTagLike_ = sigFlavTagPdf_[position]->getLikelihood();
 		}
 	}
 
 	if (sigFlavTagLike_<=0){
 		std::cout<<"INFO in LauTimeDepFitModel::getEvtFlavTagLikelihood : Event with 0 FlavTag Liklihood"<<std::endl;
 	}
 	// TODO Add in the background components too
 
 }
 
 void LauTimeDepFitModel::updateCoeffs()
 {
 	coeffsB0bar_.clear(); coeffsB0_.clear();
 	coeffsB0bar_.reserve(nSigComp_); coeffsB0_.reserve(nSigComp_);
 	for (UInt_t i = 0; i < nSigComp_; ++i) {
 		coeffsB0bar_.push_back(coeffPars_[i]->antiparticleCoeff());
 		coeffsB0_.push_back(coeffPars_[i]->particleCoeff());
 	}
 }
 
 void LauTimeDepFitModel::checkMixingPhase()
 {
 	Double_t phase = phiMix_.value();
 	Double_t genPhase = phiMix_.genValue();
 
 	// Check now whether the phase lies in the right range (-pi to pi).
 	Bool_t withinRange(kFALSE);
 	while (withinRange == kFALSE) {
 		if (phase > -LauConstants::pi && phase < LauConstants::pi) {
 			withinRange = kTRUE;
 		} else {
 			// Not within the specified range
 			if (phase > LauConstants::pi) {
 				phase -= LauConstants::twoPi;
 			} else if (phase < -LauConstants::pi) {
 				phase += LauConstants::twoPi;
 			}
 		}
 	}
 
 	// A further problem can occur when the generated phase is close to -pi or pi.
 	// The phase can wrap over to the other end of the scale -
 	// this leads to artificially large pulls so we wrap it back.
 	Double_t diff = phase - genPhase;
 	if (diff > LauConstants::pi) {
 		phase -= LauConstants::twoPi;
 	} else if (diff < -LauConstants::pi) {
 		phase += LauConstants::twoPi;
 	}
 
 	// finally store the new value in the parameter
 	// and update the pull
 	phiMix_.value(phase);
 	phiMix_.updatePull();
 }
 
 void LauTimeDepFitModel::embedSignal(const TString& fileName, const TString& treeName,
 					Bool_t reuseEventsWithinEnsemble, Bool_t reuseEventsWithinExperiment)
 {
 	if (signalTree_) {
 		std::cerr<<"ERROR in LauTimeDepFitModel::embedSignal : Already embedding signal from file."<<std::endl;
 		return;
 	}
 
 	if (!reuseEventsWithinEnsemble && reuseEventsWithinExperiment) {
 		std::cerr<<"WARNING in LauTimeDepFitModel::embedSignal : Conflicting options provided, will not reuse events at all."<<std::endl;
 		reuseEventsWithinExperiment = kFALSE;
 	}
 
 	signalTree_ = new LauEmbeddedData(fileName,treeName,reuseEventsWithinExperiment);
 	Bool_t dataOK = signalTree_->findBranches();
 	if (!dataOK) {
 		delete signalTree_; signalTree_ = 0;
 		std::cerr<<"ERROR in LauTimeDepFitModel::embedSignal : Problem creating data tree for embedding."<<std::endl;
 		return;
 	}
 
 	reuseSignal_ = reuseEventsWithinEnsemble;
 }
 
 void LauTimeDepFitModel::embedBkgnd(const TString& bkgndClass, const TString& fileName, const TString& treeName,
 		Bool_t reuseEventsWithinEnsemble, Bool_t reuseEventsWithinExperiment)
 {
 	if ( ! this->validBkgndClass( bkgndClass ) ) {
 		std::cerr << "ERROR in LauSimpleFitModel::embedBkgnd : Invalid background class \"" << bkgndClass << "\"." << std::endl;
 		std::cerr << "                                       : Background class names must be provided in \"setBkgndClassNames\" before any other background-related actions can be performed." << std::endl;
 		return;
 	}
 
 	UInt_t bkgndID = this->bkgndClassID( bkgndClass );
 
 	LauEmbeddedData* bkgTree = bkgndTree_[bkgndID];
 
 	if (bkgTree) {
 		std::cerr << "ERROR in LauSimpleFitModel::embedBkgnd : Already embedding background from a file." << std::endl;
 		return;
 	}
 
 	bkgTree = new LauEmbeddedData(fileName,treeName,reuseEventsWithinExperiment);
 
 	Bool_t dataOK = bkgTree->findBranches();
 	if (!dataOK) {
 		delete bkgTree; bkgTree = 0;
 		std::cerr << "ERROR in LauSimpleFitModel::embedBkgnd : Problem creating data tree for embedding." << std::endl;
 		return;
 	}
 
 	reuseBkgnd_[bkgndID] = reuseEventsWithinEnsemble;
 
 	if (this->enableEmbedding() == kFALSE) {
 		this->enableEmbedding(kTRUE);
 	}
 }
 
 void LauTimeDepFitModel::setupSPlotNtupleBranches()
 {
 	// add branches for storing the experiment number and the number of
 	// the event within the current experiment
 	this->addSPlotNtupleIntegerBranch("iExpt");
 	this->addSPlotNtupleIntegerBranch("iEvtWithinExpt");
 
 	// Store the efficiency of the event (for inclusive BF calculations).
 	if (this->storeDPEff()) {
 		this->addSPlotNtupleDoubleBranch("efficiency");
 	}
 
 	// Store the total event likelihood for each species.
 	this->addSPlotNtupleDoubleBranch("sigTotalLike");
 
 	if (usingBkgnd_) {
 		const UInt_t nBkgnds = this->nBkgndClasses();
 		for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
 			TString name( this->bkgndClassName(iBkgnd) );
 			name += "TotalLike";
 			this->addSPlotNtupleDoubleBranch(name);
 		}
 	}
 
 	// Store the DP likelihoods
 	if (this->useDP()) {
 		this->addSPlotNtupleDoubleBranch("sigDPLike");
 		if (usingBkgnd_) {
 			const UInt_t nBkgnds = this->nBkgndClasses();
 			for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
 				TString name( this->bkgndClassName(iBkgnd) );
 				name += "DPLike";
 				this->addSPlotNtupleDoubleBranch(name);
 			}
 		}
 	}
 
 	// Store the likelihoods for each extra PDF
 	this->addSPlotNtupleBranches(sigExtraPdf_, "sig");
 	if (usingBkgnd_) {
 		const UInt_t nBkgnds = this->nBkgndClasses();
 		for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
 			const TString& bkgndClass = this->bkgndClassName(iBkgnd);
 			this->addSPlotNtupleBranches(BkgndPdfs_[iBkgnd], bkgndClass);
 		}
 	}
 }
 
 void LauTimeDepFitModel::addSPlotNtupleBranches(const LauPdfList& extraPdfs, const TString& prefix)
 {
 	// Loop through each of the PDFs
 	for ( const LauAbsPdf* pdf : extraPdfs ) {
 
 		// 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};
 		const std::vector<TString> varNames { pdf->varNames() };
 		for ( const TString& varName : varNames ) {
 			if ( varName != "m13Sq" && varName != "m23Sq" ) {
 				++nVars;
 			}
 		}
 
 		if ( nVars == 1 ) {
 			// If the PDF only has one variable then
 			// simply add one branch for that variable
 			TString name{prefix};
 			name += pdf->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 ( const TString& varName : varNames ) {
 				if ( varName != "m13Sq" && varName != "m23Sq" ) {
 					allVars += varName;
 					TString name{prefix};
 					name += varName;
 					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, const 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.empty() ) {
 		return totalLike;
 	}
 
 	for ( LauAbsPdf* pdf : extraPdfs ) {
 
 		// calculate the likelihood for this event
 		pdf->calcLikelihoodInfo(iEvt);
 		extraLike = pdf->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};
 		const std::vector<TString> varNames { pdf->varNames() };
 		for ( const TString& varName : varNames ) {
 			if ( varName != "m13Sq" && varName != "m23Sq" ) {
 				++nVars;
 			}
 		}
 
 		if ( nVars == 1 ) {
 			// If the PDF only has one variable then
 			// simply store the value for that variable
 			TString name{prefix};
 			name += pdf->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 ( const TString& varName : varNames ) {
 				if ( varName != "m13Sq" && varName != "m23Sq" ) {
 					allVars += varName;
 					TString name{prefix};
 					name += varName;
 					name += "Like";
 					const Double_t indivLike = pdf->getLikelihood( varName );
 					this->setSPlotNtupleDoubleBranchValue(name, indivLike);
 				}
 			}
 			TString name{prefix};
 			name += allVars;
 			name += "Like";
 			this->setSPlotNtupleDoubleBranchValue(name, extraLike);
 		} else {
 			std::cerr<<"WARNING in LauAllFitModel::setSPlotNtupleBranchValues : Can't yet deal with 3D PDFs."<<std::endl;
 		}
 	}
 	return totalLike;
 }
 
 LauSPlot::NameSet LauTimeDepFitModel::variableNames() const
 {
 	LauSPlot::NameSet nameSet;
 	if (this->useDP()) {
 		nameSet.insert("DP");
 	}
 	for ( const LauAbsPdf* pdf : sigExtraPdf_ ) {
 		// Loop over the variables involved in each PDF
 		const std::vector<TString> varNames { pdf->varNames() };
 		for ( const TString& varName : varNames ) {
 			// If they are not DP coordinates then add them
 			if ( varName != "m13Sq" && varName != "m23Sq" ) {
 				nameSet.insert( varName );
 			}
 		}
 	}
 	return nameSet;
 }
 
 LauSPlot::NumbMap LauTimeDepFitModel::freeSpeciesNames() const
 {
 	LauSPlot::NumbMap numbMap;
 	if (!signalEvents_->fixed() && this->doEMLFit()) {
 		numbMap["sig"] = signalEvents_->genValue();
 	}
 	if ( usingBkgnd_ ) {
 		const UInt_t nBkgnds = this->nBkgndClasses();
 		for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
 			const TString& bkgndClass = this->bkgndClassName(iBkgnd);
 			const LauAbsRValue* par = bkgndEvents_[iBkgnd];
 			if (!par->fixed()) {
 				numbMap[bkgndClass] = par->genValue();
 				if ( ! par->isLValue() ) {
 					std::cerr << "WARNING in LauTimeDepFitModel::freeSpeciesNames : \"" << par->name() << "\" is a LauFormulaPar, which implies it is perhaps not entirely free to float in the fit, so the sWeight calculation may not be reliable" << std::endl;
 				}
 			}
 		}
 	}
 	return numbMap;
 }
 
 LauSPlot::NumbMap LauTimeDepFitModel::fixdSpeciesNames() const
 {
 	LauSPlot::NumbMap numbMap;
 	if (signalEvents_->fixed() && this->doEMLFit()) {
 		numbMap["sig"] = signalEvents_->genValue();
 	}
 	if ( usingBkgnd_ ) {
 		const UInt_t nBkgnds = this->nBkgndClasses();
 		for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
 			const TString& bkgndClass = this->bkgndClassName(iBkgnd);
 			const LauAbsRValue* par = bkgndEvents_[iBkgnd];
 			if (par->fixed()) {
 				numbMap[bkgndClass] = par->genValue();
 			}
 		}
 	}
 	return numbMap;
 }
 
 LauSPlot::TwoDMap LauTimeDepFitModel::twodimPDFs() const
 {
 	LauSPlot::TwoDMap twodimMap;
 
 	for ( const LauAbsPdf* pdf : sigExtraPdf_ ) {
 		// Count the number of input variables that are not DP variables
 		UInt_t nVars{0};
 		const std::vector<TString> varNames { pdf->varNames() };
 		for ( const TString& varName : varNames ) {
 			if ( varName != "m13Sq" && varName != "m23Sq" ) {
 				++nVars;
 			}
 		}
 		if ( nVars == 2 ) {
 			twodimMap.insert( std::make_pair( "sig", std::make_pair( varNames[0], varNames[1] ) ) );
 		}
 	}
 
 	if (usingBkgnd_) {
 		const UInt_t nBkgnds = this->nBkgndClasses();
 		for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
 			const TString& bkgndClass = this->bkgndClassName(iBkgnd);
 			for ( const LauAbsPdf* pdf : BkgndPdfs_[iBkgnd] ) {
 				// Count the number of input variables that are not DP variables
 				UInt_t nVars{0};
 				const std::vector<TString> varNames { pdf->varNames() };
 				for ( const TString& varName : varNames ) {
 					if ( varName != "m13Sq" && varName != "m23Sq" ) {
 						++nVars;
 					}
 				}
 				if ( nVars == 2 ) {
 					twodimMap.insert( std::make_pair( bkgndClass, std::make_pair( varNames[0], varNames[1] ) ) );
 				}
 			}
 		}
 	}
 	return twodimMap;
 }
 
 void LauTimeDepFitModel::storePerEvtLlhds()
 {
 	std::cout<<"INFO in LauTimeDepFitModel::storePerEvtLlhds : Storing per-event likelihood values..."<<std::endl;
 
 	LauFitDataTree* inputFitData = this->fitData();
 
 	// if we've not been using the DP model then we need to cache all
 	// the info here so that we can get the efficiency from it
 	if (!this->useDP() && this->storeDPEff()) {
 		sigModelB0bar_->initialise(coeffsB0bar_);
 		sigModelB0_->initialise(coeffsB0_);
 		sigModelB0bar_->fillDataTree(*inputFitData);
 		sigModelB0_->fillDataTree(*inputFitData);
 	}
 
 	UInt_t evtsPerExpt(this->eventsPerExpt());
 
 	LauIsobarDynamics* sigModel(sigModelB0bar_);
 
 	for (UInt_t iEvt = 0; iEvt < evtsPerExpt; ++iEvt) {
 		// Find out whether we have B0bar or B0
 
 		flavTag_->updateEventInfo(iEvt);
 		curEvtTagFlv_ = flavTag_->getCurEvtTagFlv();
 		curEvtMistag_ = flavTag_->getCurEvtMistag();
 
 		// the DP information
 		this->getEvtDPDtLikelihood(iEvt);
 		if (this->storeDPEff()) {
 			if (!this->useDP()) {
 				sigModel->calcLikelihoodInfo(iEvt);
 			}
 			this->setSPlotNtupleDoubleBranchValue("efficiency",sigModel->getEvtEff());
 		}
 		if (this->useDP()) {
 			sigTotalLike_ = sigDPLike_;
 			this->setSPlotNtupleDoubleBranchValue("sigDPLike",sigDPLike_);
 			if (usingBkgnd_) {
 				const UInt_t nBkgnds = this->nBkgndClasses();
 				for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
 					TString name = this->bkgndClassName(iBkgnd);
 					name += "DPLike";
 					this->setSPlotNtupleDoubleBranchValue(name,bkgndDPLike_[iBkgnd]);
 				}
 			}
 		} else {
 			sigTotalLike_ = 1.0;
 		}
 
 		// the signal PDF values
 		sigTotalLike_ *= this->setSPlotNtupleBranchValues(sigExtraPdf_, "sig", iEvt);
 
 		// the background PDF values
 		if (usingBkgnd_) {
 			const UInt_t nBkgnds = this->nBkgndClasses();
 			for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
 				const TString& bkgndClass = this->bkgndClassName(iBkgnd);
 				LauPdfList& pdfs = BkgndPdfs_[iBkgnd];
 				bkgndTotalLike_[iBkgnd] *= this->setSPlotNtupleBranchValues(pdfs, bkgndClass, iEvt);
 			}
 		}
 
 		// the total likelihoods
 		this->setSPlotNtupleDoubleBranchValue("sigTotalLike",sigTotalLike_);
 		if (usingBkgnd_) {
 			const UInt_t nBkgnds = this->nBkgndClasses();
 			for ( UInt_t iBkgnd(0); iBkgnd < nBkgnds; ++iBkgnd ) {
 				TString name = this->bkgndClassName(iBkgnd);
 				name += "TotalLike";
 				this->setSPlotNtupleDoubleBranchValue(name,bkgndTotalLike_[iBkgnd]);
 			}
 		}
 
 		// fill the tree
 		this->fillSPlotNtupleBranches();
 	}
 	std::cout<<"INFO in LauTimeDepFitModel::storePerEvtLlhds : Finished storing per-event likelihood values."<<std::endl;
 }
 
 void LauTimeDepFitModel::weightEvents( const TString& /*dataFileName*/, const TString& /*dataTreeName*/ )
 {
 	std::cerr << "ERROR in LauTimeDepFitModel::weightEvents : Method not available for this fit model." << std::endl;
 	return;
 }
 
 void LauTimeDepFitModel::savePDFPlots(const TString& /*label*/)
 {
 }
 
 void LauTimeDepFitModel::savePDFPlotsWave(const TString& /*label*/, const Int_t& /*spin*/)
 {
 }
 
 //TODO obsolete?
 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;
 }