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diff --git a/examples/ProgOpts/Test_Dpipi_ProgOpts.cc b/examples/ProgOpts/Test_Dpipi_ProgOpts.cc
index 8ff58f1..dc786cf 100644
--- a/examples/ProgOpts/Test_Dpipi_ProgOpts.cc
+++ b/examples/ProgOpts/Test_Dpipi_ProgOpts.cc
@@ -1,164 +1,165 @@
#include <iostream>
#include <string>
#include "boost/program_options.hpp"
#include "boost/tokenizer.hpp"
#include "Test_Dpipi_ProgOpts.hh"
namespace po = boost::program_options;
void validate( boost::any& v, const std::vector<std::string>& values, Command* /*target_type*/, int)
{
// Make sure no previous assignment to 'v' has been made
po::validators::check_first_occurrence(v);
// Extract the first string from 'values'. If there is more than
// one string, it's an error, and exception will be thrown.
const std::string& s { po::validators::get_single_string(values) };
if ( s == "gen" ) {
v = boost::any( Command::Generate );
} else if ( s == "fit" ) {
v = boost::any( Command::Fit );
} else if ( s == "simfit" ) {
v = boost::any( Command::SimFit );
} else {
throw po::validation_error(po::validation_error::invalid_option_value, "command", s, 3);
}
}
void validate( boost::any& v, const std::vector<std::string>& values, LauTimeDepFitModel::CPEigenvalue* /*target_type*/, int)
{
// Make sure no previous assignment to 'v' has been made
po::validators::check_first_occurrence(v);
// Extract the first string from 'values'. If there is more than
// one string, it's an error, and exception will be thrown.
const std::string& s { po::validators::get_single_string(values) };
if ( s == "QFS" ) {
v = boost::any( LauTimeDepFitModel::CPEigenvalue::QFS );
} else if ( s == "CPEven" ) {
v = boost::any( LauTimeDepFitModel::CPEigenvalue::CPEven );
} else if ( s == "CPOdd" ) {
v = boost::any( LauTimeDepFitModel::CPEigenvalue::CPOdd );
} else {
throw po::validation_error(po::validation_error::invalid_option_value);
}
}
namespace LauDecayTime {
void validate( boost::any& v, const std::vector<std::string>& values, EfficiencyMethod* /*target_type*/, int)
{
// Make sure no previous assignment to 'v' has been made
po::validators::check_first_occurrence(v);
// Extract the first string from 'values'. If there is more than
// one string, it's an error, and exception will be thrown.
const std::string& s { po::validators::get_single_string(values) };
if ( s == "uniform" || s == "flat" ) {
v = boost::any( EfficiencyMethod::Uniform );
} else if ( s == "binned" || s == "hist" ) {
v = boost::any( EfficiencyMethod::Binned );
} else if ( s == "spline" ) {
v = boost::any( EfficiencyMethod::Spline );
} else {
throw po::validation_error(po::validation_error::invalid_option_value);
}
}
};
TestDpipi_ProgramSettings::TestDpipi_ProgramSettings(const int argc, const char ** argv)
{
po::options_description main_desc{"Main options"};
main_desc.add_options()
("command", po::value<Command>(&command)->required(), "main command: gen, fit, or simfit")
;
po::positional_options_description p;
p.add("command", 1);
po::options_description common_desc{"Common options"};
common_desc.add_options()
("help", "produce help message")
("dtype", po::value<LauTimeDepFitModel::CPEigenvalue>(&dType)->default_value(LauTimeDepFitModel::CPEigenvalue::QFS,"QFS"), "type of D decay: QFS, CPOdd, or CPEven")
("dta-model", po::value<LauDecayTime::EfficiencyMethod>(&timeEffModel)->default_value(LauDecayTime::EfficiencyMethod::Uniform,"uniform"), "decay-time acceptance model: uniform/flat, binned/hist, spline")
("dtr", po::value<Bool_t>(&timeResolution)->default_value(kTRUE), "enable/disable decay-time resolution")
("dtr-perevent", po::value<Bool_t>(&perEventTimeErr)->default_value(kFALSE), "enable/disable use of per-event decay-time error (requires decay-time resolution to be enabled to take effect)")
("seed", po::value<UInt_t>(&RNGseed)->default_value(0), "set the seed for the RNG; if not set, the time is used to generate a seed")
("dir", po::value<std::string>(&directory)->default_value("","<none>"), "set the directory used to find the nTuples within the root file. Defaults to no directory")
("bkgndList", po::value<std::string>(&bkgndListStr)->default_value("comb,Bd2DKpi,Bs2DKpi,Lb2Dppi"), "the comma-separated list of background components to include")
("fitBackInput", po::value<std::string>(&fitBackInput)->default_value("","fit0_ToyMC_QFS_expts0-0_expt0.root"), "set the file used as input to the fit: only used if fitBack is also selected")
;
po::options_description gen_desc{"Generation options"};
gen_desc.add_options()
("firstExptGen", po::value<UInt_t>(&firstExptGen)->default_value(0), "first experiment to generate")
("nExptGen", po::value<UInt_t>(&nExptGen)->default_value(1), "number of experiments to generate")
;
po::options_description fit_desc{"Fitting options"};
fit_desc.add_options()
("firstExpt", po::value<UInt_t>(&firstExptFit)->default_value(0), "first experiment to fit")
("nExpt", po::value<UInt_t>(&nExptFit)->default_value(1), "number of experiments to fit")
("iFit", po::value<UInt_t>(&iFit)->default_value(0), "fit ID - used to distinguish multiple fits to a given dataset (used to disentangle multiple minima)")
("fixTau", po::value<Bool_t>(&fixLifetime)->default_value(kTRUE), "enable/disable floating of B lifetime parameter")
("fixDm", po::value<Bool_t>(&fixDeltaM)->default_value(kTRUE), "enable/disable floating of B mixing frequency parameter")
("fixPhiMix", po::value<Bool_t>(&fixPhiMix)->default_value(kFALSE), "enable/disable floating of B mixing phase parameter(s)")
("fixSplineKnots", po::value<Bool_t>(&fixSplineKnots)->default_value(kFALSE), "enable/disable floating of the decay-time-acceptance spline")
("useSinCos", po::value<Bool_t>(&useSinCos)->default_value(kTRUE), "enable/disable using sine and cosine of B mixing phase as the floating parameters rather than the phase itself")
("useAveDeltaCalibVals", po::value<Bool_t>(&useAveDeltaCalibVals)->default_value(kTRUE), "enable/disable fitting calib values as their average +/- delta values rather than having separate values for B and Bbar")
("addTaggers", po::value<Bool_t>(&addTaggers)->default_value(kTRUE), "add/omit taggers")
("floatCalibPars", po::value<Bool_t>(&floatCalibPars)->default_value(kTRUE), "enable/disable floating of the FT calibration parameters")
("floatYields", po::value<Bool_t>(&floatYields)->default_value(kFALSE), "enable/disable floating of the yields of each component - if enabled/disabled implies inclusion/exclusion of non-DP PDFs in/from the likelihood")
("fitBack", po::value<Bool_t>(&fitBack)->default_value(kFALSE), "enable/disable refitting some generated data from a model")
+ ("blindFit", po::value<Bool_t>(&blindFit)->default_value(kFALSE), "enable/disable blinding of the physics parameters")
;
po::options_description simfit_desc{"Simultaneous fitting options"};
simfit_desc.add_options()
("port", po::value<UInt_t>(&port)->default_value(0), "port number on which sim fit coordinator is listening")
;
po::options_description all_desc;
all_desc.add(main_desc).add(common_desc).add(gen_desc).add(fit_desc).add(simfit_desc);
po::variables_map vm;
try {
po::store(po::command_line_parser(argc, argv).
options(all_desc).
positional(p).
run(),
vm);
po::notify(vm);
}
catch ( boost::wrapexcept<po::required_option>& e ) {
std::cout << argv[0] << " requires a command, one of 'gen', 'fit', or 'simfit'\n"
<< "Append --help to those commands to see help on the related options" << std::endl;
parsedOK = kFALSE;
return;
}
catch ( po::validation_error& e ) {
std::cerr << e.what() << std::endl;
parsedOK = kFALSE;
return;
}
if ( vm.count("help") ) {
po::options_description help_desc;
help_desc.add(common_desc).add(gen_desc).add(fit_desc).add(simfit_desc);
std::cout << help_desc << std::endl;
helpRequested = kTRUE;
return;
}
if ( ! bkgndListStr.empty() ) {
const boost::char_separator<char> sep{","};
const boost::tokenizer<boost::char_separator<char>> tokens{bkgndListStr, sep};
for (const auto& t : tokens) {
bkgndList.insert( t );
}
}
}
diff --git a/examples/ProgOpts/Test_Dpipi_ProgOpts.hh b/examples/ProgOpts/Test_Dpipi_ProgOpts.hh
index 3641c4a..e2b0bcf 100644
--- a/examples/ProgOpts/Test_Dpipi_ProgOpts.hh
+++ b/examples/ProgOpts/Test_Dpipi_ProgOpts.hh
@@ -1,52 +1,53 @@
#ifndef TEST_DPIPI_PROGOPTS
#define TEST_DPIPI_PROGOPTS
#include "Rtypes.h"
#include "LauDecayTime.hh"
#include "LauTimeDepFitModel.hh"
#include "Command.hh"
#include <set>
#include <string>
struct TestDpipi_ProgramSettings {
TestDpipi_ProgramSettings(const int argc, const char ** argv);
Bool_t parsedOK{kTRUE};
Bool_t helpRequested{kFALSE};
Command command{Command::Generate};
LauTimeDepFitModel::CPEigenvalue dType{LauTimeDepFitModel::CPEigenvalue::QFS};
LauDecayTime::EfficiencyMethod timeEffModel{LauDecayTime::EfficiencyMethod::Uniform};
UInt_t firstExptGen{0};
UInt_t nExptGen{1};
UInt_t firstExptFit{0};
UInt_t nExptFit{1};
UInt_t iFit{0};
UInt_t port{0};
UInt_t RNGseed{0};
Bool_t timeResolution{kTRUE};
Bool_t perEventTimeErr{kFALSE};
Bool_t fixLifetime{kTRUE};
Bool_t fixDeltaM{kTRUE};
Bool_t fixPhiMix{kFALSE};
Bool_t fixSplineKnots{kFALSE};
Bool_t useSinCos{kTRUE};
Bool_t useAveDeltaCalibVals{kTRUE};
Bool_t addTaggers{kTRUE};
Bool_t floatCalibPars{kTRUE};
Bool_t floatYields{kFALSE};
Bool_t fitBack{kFALSE};
+ Bool_t blindFit{kFALSE};
std::string bkgndListStr{""};
std::string directory{""};
std::string fitBackInput{""};
std::set<std::string> bkgndList;
};
#endif
diff --git a/inc/LauBlind.hh b/inc/LauBlind.hh
index cfe90bf..8298c2a 100644
--- a/inc/LauBlind.hh
+++ b/inc/LauBlind.hh
@@ -1,111 +1,113 @@
/*
Copyright 2015 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 LauBlind.hh
\brief File containing declaration of LauBlind class.
*/
/*! \class LauBlind
\brief Class for blinding and unblinding a number based on a blinding string.
Numbers are blinded by applying an offset. The blinding string is converted
to an integer using TMath::Hash and this integer is used to seed a TRandom3.
The offset is sampled from a Gaussian of defined width using the seeded TRandom3.
*/
#ifndef LAU_BLIND
#define LAU_BLIND
#include "TString.h"
-class LauBlind {
+class LauBlind final {
public:
+ //! Default constructor
+ /*!
+ This is purely to allow I/O to succeed, should not generally be used
+ */
+ LauBlind() = default;
+
//! Constructor
/*!
\param [in] blindingStr the blinding string
\param [in] width the width of the Gaussian for sampling the offset
+ \param [in] flipSign activate possible random sign flip (off by default)
*/
- LauBlind(const TString& blindingStr, const Double_t width);
-
- //! Copy constructor
- LauBlind(const LauBlind& rhs);
-
- //! Destructor
- virtual ~LauBlind();
+ LauBlind(const TString& blindingStr, const Double_t width, const Bool_t flipSign = kFALSE);
//! Obtain the blinded value
/*!
\param [in] val the unblinded value
\return the blinded value
*/
- inline Double_t blind(const Double_t val) const { return val+offset_; }
+ inline Double_t blind(const Double_t val) const { return flipFactor_[flip_] * val + offset_; }
//! Obtain the unblinded value
/*!
\param [in] val the blinded value
\return the unblinded value
*/
- inline Double_t unblind(const Double_t val) const { return val-offset_; }
+ inline Double_t unblind(const Double_t val) const { return flipFactor_[flip_] * (val - offset_); }
//! Obtain the blinding string
/*!
\return the blinding string
*/
inline const TString& blindingString() const { return blindingString_; }
//! Obtain the Gaussian width
/*!
\return the Gaussian width
*/
inline Double_t blindingWidth() const { return blindingWidth_; }
- private:
- //! Copy assignment operator (not implemented)
- LauBlind& operator=(const LauBlind& rhs);
-
- //! Calculate the offset
- void calcOffset();
+ //! Obtain the sign-flip setting
+ /*!
+ \return the sign-flip setting
+ */
+ inline Double_t flipSign() const { return flipSign_; }
+ private:
//! The blinding string
const TString blindingString_;
//! The Gaussian width
- const Double_t blindingWidth_;
+ const Double_t blindingWidth_{0.0};
- //! The offset used to blind the value
- Double_t offset_;
+ //! The flip sign setting
+ const Bool_t flipSign_{kFALSE};
- public:
- //! Default constructor
- /*!
- This is purely to allow I/O to succeed, should not generally be used
- */
- LauBlind();
+ //! Array to hold +1/-1 factors for efficient implementation of sign flip
+ const std::array<Double_t,2> flipFactor_{1.0,-1.0};
+
+ //! The offset used to blind the value
+ Double_t offset_{0.0};
+ //! Whether to flip sign in blinding
+ Bool_t flip_{kFALSE};
ClassDef(LauBlind, 1)
};
#endif
diff --git a/inc/LauParameter.hh b/inc/LauParameter.hh
index 391a472..891993e 100644
--- a/inc/LauParameter.hh
+++ b/inc/LauParameter.hh
@@ -1,589 +1,590 @@
/*
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 LauParameter.hh
\brief File containing declaration of LauParameter class.
*/
/*! \class LauParameter
\brief Class for defining the fit parameter objects.
Holds all relevant information for the parameters for both generation and fitting step:
current, initial and generated value, maximum and minimum range, error, asymmetric error, fix and float and etc.
*/
#ifndef LAU_PARAMETER
#define LAU_PARAMETER
#include <iosfwd>
#include <map>
#include <memory>
#include <vector>
#include "TObject.h"
#include "TString.h"
#include "LauAbsRValue.hh"
#include "LauBlind.hh"
class LauParameter final : public TObject, public LauAbsRValue {
public:
//! Default constructor
LauParameter() = default;
//! Constructor for named parameter
/*!
\param [in] parName the parameter name
*/
explicit LauParameter(const TString& parName);
//! Constructor for parameter value
/*!
\param [in] parValue the parameter value
*/
explicit LauParameter(const Double_t parValue);
//! Constructor double limit parameter
/*!
\param [in] parValue the parameter value
\param [in] min the minimum value of the parameter
\param [in] max the maximum value of the parameter
*/
LauParameter(const Double_t parValue, const Double_t min, const Double_t max);
//! Constructor double limit fixed parameter
/*!
\param [in] parValue the parameter value
\param [in] min the minimum value of the parameter
\param [in] max the maximum value of the parameter
\param [in] parFixed boolean flag to fix or float parameter
*/
LauParameter(const Double_t parValue, const Double_t min, const Double_t max, const Bool_t parFixed);
//! Constructor for double error and limit parameter
/*!
\param [in] parValue the parameter value
\param [in] parError the parameter error
\param [in] min the minimum value of the parameter
\param [in] max the maximum value of the parameter
*/
LauParameter(const Double_t parValue, const Double_t parError, const Double_t min, const Double_t max);
//! Constructor for parameter value and name
/*!
\param [in] parName the parameter name
\param [in] parValue the parameter value
*/
LauParameter(const TString& parName, const Double_t parValue);
//! Constructor double limit parameter and name
/*!
\param [in] parName the parameter name
\param [in] parValue the parameter value
\param [in] min the minimum value of the parameter
\param [in] max the maximum value of the parameter
*/
LauParameter(const TString& parName, const Double_t parValue, const Double_t min, const Double_t max);
//! Constructor double limit fixed parameter and name
/*!
\param [in] parName the parameter name
\param [in] parValue the parameter value
\param [in] min the minimum value of the parameter
\param [in] max the maximum value of the parameter
\param [in] parFixed boolean flag to fix (kTRUE) or float (kFALSE) the parameter
*/
LauParameter(const TString& parName, const Double_t parValue, const Double_t min, const Double_t max, const Bool_t parFixed);
//! Constructor double error and limit parameter and name
/*!
\param [in] parName the parameter name
\param [in] parValue the parameter value
\param [in] parError the parameter error
\param [in] min the minimum value of the parameter
\param [in] max the maximum value of the parameter
*/
LauParameter(const TString& parName, const Double_t parValue, const Double_t parError, const Double_t min, const Double_t max);
// Destructor
virtual ~LauParameter() noexcept;
//! Copy constructor
/*!
\param [in] rhs the parameter to be copied
*/
LauParameter(const LauParameter& rhs);
//! Copy assignment operator
/*!
\param [in] rhs the parameter to be copied
*/
LauParameter& operator=(const LauParameter& rhs);
//! Move constructor
/*!
\param [in] rhs the parameter to be moved from
*/
LauParameter(LauParameter&& rhs) = default;
//! Move assignment operator
/*!
\param [in] rhs the parameter to be moved from
*/
LauParameter& operator=(LauParameter&& rhs) = default;
// the simple accessor functions
//! The parameter name
/*!
\return the name of the parameter
*/
const TString& name() const override {return name_;}
//! The blinding state
/*!
\return the blinding state: kTRUE means that it is blinded, kFALSE that it is not blinded
*/
Bool_t blind() const override {return (blinder_ != nullptr);}
//! Access the blinder object
/*!
\return the blinder
*/
const LauBlind* blinder() const {return blinder_.get();}
//! The value of the parameter
/*!
\return the value of the parameter
*/
Double_t value() const override {return value_;}
//! The unblinded value of the parameter
/*!
\return the unblinded value of the parameter
*/
Double_t unblindValue() const override {return (blinder_==nullptr) ? value_ : blinder_->unblind(value_);}
//! The error on the parameter
/*!
\return the error on the parameter
*/
Double_t error() const {return error_;}
//! The lower error on the parameter
/*!
\return the lower error on the parameter
*/
Double_t negError() const {return negError_;}
//! The upper error on the parameter
/*!
\return the upper error on the parameter
*/
Double_t posError() const {return posError_;}
//! The value generated for the parameter
/*!
\return the value generated for the parameter
*/
Double_t genValue() const override {return genValue_;}
//! The initial value of the parameter
/*!
\return the initial value of the parameter given to the fitter
*/
Double_t initValue() const override {return initValue_;}
//! The minimum value allowed for the parameter
/*!
\return the minimum value allowed for the parameter
*/
Double_t minValue() const {return minValue_;}
//! The maximum value allowed for the parameter
/*!
\return the maximum value allowed for the parameter
*/
Double_t maxValue() const {return maxValue_;}
//! The range allowed for the parameter
/*!
\return the range allowed for the parameters, defined as the difference between the max and min value
*/
Double_t range() const {return this->maxValue() - this->minValue();}
//! Check whether the parameter is fixed or floated
/*!
\return the boolean flag true/false whether the parameter is fixed
*/
Bool_t fixed() const override {return fixed_;}
//! Check whether the parameter should be floated only in the second stage of a two stage fit
/*!
\return the boolean flag true/false whether it floats only in the second stage
*/
Bool_t secondStage() const {return secondStage_;}
//! Check whether a Gaussian constraints is applied
/*!
\return the boolean flag true/false whether a Gaussian constraint is applied
*/
Bool_t gaussConstraint() const override {return gaussConstraint_;}
//! The mean of the Gaussian constraint
/*!
\return the mean value of the Gaussian constraint
*/
Double_t constraintMean() const override {return constraintMean_;}
//! The width of the Gaussian constraint
/*!
\return the width of the Gaussian constraint
*/
Double_t constraintWidth() const override {return constraintWidth_;}
//! The parameter global correlation coefficient
/*!
\return the global correlation coefficient
*/
Double_t globalCorrelationCoeff() const {return gcc_;}
//! The bias in the parameter
/*!
\return the bias in the parameter, defined as the difference between the value and the generated value
*/
Double_t bias() const {return bias_;}
//! The pull value for the parameter
/*!
\return the pull value for the parameter, defined as the bias divided by the error
*/
Double_t pull() const {return pull_;}
//! Boolean to say it is an L value
/*!
\return kTRUE, LauParameters are L values
*/
Bool_t isLValue() const override {return kTRUE;}
//! Get the LauParameter itself
/*!
\return a vector of the LauParameter
*/
std::vector<LauParameter*> getPars() override;
// the simple "setter" functions
//! Set the parameter name
/*!
\param [in] newName the name of the parameter
*/
void name(const TString& newName) override;
//! Set the value of the parameter
/*!
\param [in] newValue the value of the parameter
*/
void value(const Double_t newValue);
//! Set the error on the parameter
/*!
\param [in] newError the error on the parameter
*/
void error(const Double_t newError);
//! Set the lower error on the parameter
/*!
\param [in] newNegError the lower error on the parameter
*/
void negError(const Double_t newNegError);
//! Set the upper error on the parameter
/*!
\param [in] newPosError the upper error on the parameter
*/
void posError(const Double_t newPosError);
//! Set the error values on the parameter
/*!
\param [in] newError the error on the parameter
\param [in] newNegError the lower error on the parameter
\param [in] newPosError the upper error on the parameter
*/
void errors(const Double_t newError, const Double_t newNegError, const Double_t newPosError);
//! Set the value and errors on the parameter
/*!
\param [in] newValue the value of the parameter
\param [in] newError the error on the parameter
\param [in] newNegError the lower error on the parameter (default set to zero)
\param [in] newPosError the upper error on the parameter (default set to zero)
*/
void valueAndErrors(const Double_t newValue, const Double_t newError, const Double_t newNegError = 0.0, const Double_t newPosError = 0.0);
//! Set the global correlation coefficient
/*!
\param [in] newGCCValue the value of the coefficient
*/
void globalCorrelationCoeff(const Double_t newGCCValue);
//! Set the generated value for the parameter
/*!
\param [in] newGenValue the generated value for the parameter
*/
void genValue(const Double_t newGenValue);
//! Set the inital value for the parameter
/*!
\param [in] newInitValue the initial value for the parameter
*/
void initValue(const Double_t newInitValue);
//! Set the minimum value for the parameter
/*!
\param [in] newMinValue the minimum value for the parameter
*/
void minValue(const Double_t newMinValue);
//! Set the maximum value for the parameter
/*!
\param [in] newMaxValue the maximum value for the parameter
*/
void maxValue(const Double_t newMaxValue);
//! Set the range for the parameter
/*!
\param [in] newMinValue the minimum value for the parameter
\param [in] newMaxValue the maximum value for the parameter
*/
void range(const Double_t newMinValue, const Double_t newMaxValue);
//! Set the value and range for the parameter
/*!
\param [in] newValue the value of the parameter
\param [in] newMinValue the minimum value for the parameter
\param [in] newMaxValue the maximum value for the parameter
*/
void valueAndRange(const Double_t newValue, const Double_t newMinValue, const Double_t newMaxValue);
//! Fix or float the given parameter
/*!
\param [in] parFixed boolean flag to fix or float the parameter
*/
void fixed(const Bool_t parFixed);
//! Set parameter as second-stage or not of the fit
/*!
\param [in] secondStagePar boolean flag to check whether is a second-stage parameter
*/
void secondStage(const Bool_t secondStagePar);
//! Add a Gaussian constraint (or modify an existing one)
/*!
\param [in] newGaussMean the new value of the Gaussian constraint mean
\param [in] newGaussWidth the new value of the Gaussian constraint width
*/
void addGaussianConstraint(const Double_t newGaussMean, const Double_t newGaussWidth);
//! Remove the Gaussian constraint
void removeGaussianConstraint();
//! Blind the parameter
/*!
See LauBlind documentation for details of blinding procedure
\param [in] blindingString the unique blinding string used to seed the random number generator
\param [in] width the width of the Gaussian from which the offset should be sampled
+ \param [in] flipSign activate possible random sign flip (off by default)
*/
- void blindParameter(const TString& blindingString, const Double_t width);
+ void blindParameter(const TString& blindingString, const Double_t width, const Bool_t flipSign = kFALSE);
// functions for the cloning mechanism
//! Check whether is a clone or not
/*!
\return true/false whether is a clone
*/
Bool_t clone() const {return clone_;}
//! Method to create a clone from the parent parameter using the copy constructor
/*!
\param [in] constFactor the optional constant factor by which the clone shold be multiplied
\return the cloned parameter
*/
LauParameter* createClone(const Double_t constFactor = 1.0);
//! Method to create a clone from the parent parameter using the copy constructor and setting a new name
/*!
\param [in] newName the new name of the cloned parameter
\param [in] constFactor the optional constant factor by which the clone shold be multiplied
\return the cloned parameter
*/
LauParameter* createClone(const TString& newName, const Double_t constFactor = 1.0);
//! The parent parameter
/*!
\return the parent parameter
*/
LauParameter* parent() const {return parent_;}
//! Call to update the bias and pull values
void updatePull();
//! Randomise the value of the parameter (if it is floating).
/*!
The pre-defined parameter range is used as the randomisation range.
*/
void randomiseValue();
//! Randomise the value of the parameter (if it is floating).
/*!
Use the given range unless either of the given values are
outside the range of the parameter, in which case that value
will be altered to the current max or min.
\param [in] minVal the minimum value for the parameter
\param [in] maxVal the maximum value for the parameter
*/
void randomiseValue(const Double_t minVal, const Double_t maxVal);
protected:
//! Method to check whether value provided is within the range and that the minimum and maximum limits make sense
/*!
\param [in] val the value of the parameter
\param [in] minVal the minimum value allowed
\param [in] maxVal the maximum value allowed
*/
void checkRange(const Double_t val, const Double_t minVal, const Double_t maxVal);
//! Method to check whether value provided is whithin the range and that the minimum and maximum limits make sense
void checkRange()
{
this->checkRange(this->value(),this->minValue(),this->maxValue());
}
//! Mark this as a clone of the given parent
/*!
\param theparent the parent parameter
*/
void clone(LauParameter* theparent)
{
parent_ = theparent;
clone_ = (parent_==nullptr) ? kFALSE : kTRUE;
}
//! Method to remove a clone from the list of clones
/*!
This is used in the destructor to allow a clone to inform its parent it is no longer around
\param [in] clone the clone to be removed from the list
*/
void removeFromCloneList(LauParameter* clone)
{
auto iter = clones_.find( clone );
if ( iter != clones_.end() ) {
clones_.erase( iter );
}
}
//! Method to clear the clone parameters
void wipeClones() {clones_.clear();}
//! Method to update clone values
/*!
\param [in] justValue boolean flag to determine whether it is necessary to update all the parameter settings or only its value.
*/
void updateClones(const Bool_t justValue);
private:
//! LauFitNtuple is a friend class
friend class LauFitNtuple;
//! The parameter name
TString name_;
//! The parameter value
Double_t value_{0.0};
//! The error on the parameter
Double_t error_{0.0};
//! The lower error on the parameter
Double_t negError_{0.0};
//! The upper error on the parameter
Double_t posError_{0.0};
//! Toy generation value
Double_t genValue_{0.0};
//! Initial fit value
Double_t initValue_{0.0};
//! Minimum value for the parameter
Double_t minValue_{0.0};
//! Maximum value for the parameter
Double_t maxValue_{0.0};
//! Fix/float option for parameter
Bool_t fixed_{kTRUE};
//! Flag whether it is floated only in the second stage of the fit
Bool_t secondStage_{kFALSE};
//! Choice to use Gaussian constraint
Bool_t gaussConstraint_{kFALSE};
//! Mean value of the Gaussian constraint
Double_t constraintMean_{0.0};
//! Width of the Gaussian constraint
Double_t constraintWidth_{0.0};
//! Global correlation coefficient
Double_t gcc_{0.0};
//! Parameter bias
Double_t bias_{0.0};
//! Parameter pull
Double_t pull_{0.0};
//! Flag whether the parameter is a clone
Bool_t clone_{kFALSE};
//! The parent parameter
LauParameter* parent_{nullptr};
//! The clones of this parameter
std::map<LauParameter*, Double_t> clones_;
//! The blinding engine
std::unique_ptr<LauBlind> blinder_;
ClassDefOverride(LauParameter, 4)
};
//! Output stream operator
std::ostream& operator << (std::ostream& stream, const LauParameter& par);
//! Type to define an array of parameters
typedef std::vector< std::vector<LauParameter> > LauParArray;
#endif
diff --git a/inc/LauTimeDepFitModel.hh b/inc/LauTimeDepFitModel.hh
index d2f70d3..266ca97 100644
--- a/inc/LauTimeDepFitModel.hh
+++ b/inc/LauTimeDepFitModel.hh
@@ -1,725 +1,742 @@
/*
Copyright 2006 University of Warwick
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
/*
Laura++ package authors:
John Back
Paul Harrison
Thomas Latham
*/
/*! \file LauTimeDepFitModel.hh
\brief File containing declaration of LauTimeDepFitModel class.
*/
/*! \class LauTimeDepFitModel
\brief Class for defining a time-dependent fit model.
LauTimeDepFitModel is a class that allows the user to define a three-body
Dalitz plot according to the isobar model, i.e. defining a set of
resonances that have complex amplitudes that can interfere with each other.
It extends the LauSimpleFitModel and LauCPFitModel models in that it allows
the fitting of time-dependent particle/antiparticle decays to
flavour-conjugate Dalitz plots, including their interference through mixing.
*/
#ifndef LAU_TIMEDEP_FIT_MODEL
#define LAU_TIMEDEP_FIT_MODEL
#include <vector>
#include <map>
#include <set>
#include <iostream>
#include "TString.h"
#include "TStopwatch.h"
#include "TSystem.h"
#include "LauAbsFitModel.hh"
#include "LauComplex.hh"
#include "LauConstants.hh"
#include "LauEmbeddedData.hh"
#include "LauFlavTag.hh"
#include "LauParameter.hh"
class LauAbsBkgndDPModel;
class LauAbsCoeffSet;
class LauAbsPdf;
class LauDecayTimePdf;
class LauIsobarDynamics;
class LauKinematics;
class LauScfMap;
class LauTimeDepFitModel : public LauAbsFitModel {
public:
//! Possible CP eigenvalues (the intrinsic CP of the final state particles)
enum CPEigenvalue {
CPOdd = -1, /*!< CP odd final state */
QFS = 0, /*!< Quasi Flavour Specific final state */
CPEven = 1 /*!< CP even final state */
};
//! Constructor
/*!
\param [in] modelB0bar DP model for the antiparticle
\param [in] modelB0 DP model for the particle
\param [in] flavTag flavour tagging information
*/
LauTimeDepFitModel(LauIsobarDynamics* modelB0bar, LauIsobarDynamics* modelB0, LauFlavTag* flavTag);
//! Destructor
virtual ~LauTimeDepFitModel();
//! Set the signal event yield
/*!
\param [in] nSigEvents contains the signal yield and option to fix it
*/
virtual void setNSigEvents(LauParameter* nSigEvents);
//TODO what is this asymmetry?
//! Set the signal event yield and asymmetry
/*!
\param [in] nSigEvents contains the signal yield and option to fix it
\param [in] sigAsym contains the signal asymmetry and option to fix it
*/
virtual void setNSigEvents(LauParameter* nSigEvents, LauParameter* sigAsym);
//! Set the number of background events
/*!
The name of the parameter must be that of the corresponding background category (so that it can be correctly assigned)
\param [in] nBkgndEvents contains the name, yield and option to fix the yield of the background
*/
virtual void setNBkgndEvents(LauAbsRValue* nBkgndEvents);
//TODO what is this asymmetry?
//! Set the background event yield and asymmetry
/*!
The name of the parameters must be that of the corresponding background category (so that they can be correctly assigned)
\param [in] nBkgndEvents contains the background yield and option to fix it
\param [in] bkgndAsym contains the background asymmetry and option to fix it
*/
virtual void setNBkgndEvents(LauAbsRValue* nBkgndEvents, LauAbsRValue* bkgndAsym);
//! Set the background DP models (null pointer for BbarModel implies same model for both)
/*!
\param [in] bkgndClass the name of the background class
\param [in] BModel the DP model of the background for B (particle) decays
\param [in] BbarModel the DP model of the background for Bbar (anti-particle) decays
*/
void setBkgndDPModels(const TString& bkgndClass, LauAbsBkgndDPModel* BModel, LauAbsBkgndDPModel* BbarModel);
//! Switch on/off storage of amplitude info in generated ntuple
void storeGenAmpInfo(Bool_t storeInfo) { storeGenAmpInfo_ = storeInfo; }
//! Set CP eigenvalue
/*!
The CP eigenvalue can be supplied on an event-by-event
basis, e.g. if the data contains daughters that are D0
mesons that can decay to either K+ K- (CP even) or KS pi0
(CP odd).
This method allows you to set the default value that should
be used if the data does not contain this information as
well as the name of the variable in the data that will
specify this information.
If completely unspecified all events will be assumed to be
CP even.
\param defaultCPEV the default for the eigenvalue
\param cpevVarName the variable name in the data tree that specifies the CP eigenvalue
*/
inline void setCPEigenvalue( const CPEigenvalue defaultCPEV, const TString& cpevVarName = "" )
{
cpEigenValue_ = defaultCPEV;
cpevVarName_ = cpevVarName;
}
//! Set the DP amplitude coefficients
/*!
\param [in] coeffSet the set of coefficients
*/
void setAmpCoeffSet(LauAbsCoeffSet* coeffSet);
//! Set the signal decay time PDF
/*!
\param [in] pdf the signal decay time PDF
*/
void setSignalDtPdf(LauDecayTimePdf* pdf);
//! Set the decay time PDF for a given background class
/*!
\param [in] bkgndClass the name of the background class
\param [in] pdf the background decay time PDF
*/
void setBkgndDtPdf(const TString& bkgndClass, LauDecayTimePdf* pdf);
//! Set the signal PDF for a given variable
/*!
\param [in] pdf the PDF to be added to the signal model
*/
void setSignalPdfs(LauAbsPdf* pdf);
//! Set the background PDF for a given variable and background class
/*!
\param [in] bkgndClass the name of the background class
\param [in] pdf the PDF to be added to the background model
*/
void setBkgndPdf(const TString& bkgndClass, LauAbsPdf* pdf);
//! Embed full simulation events for the signal, rather than generating toy from the PDFs
/*!
\param [in] fileName the name of the file containing the events
\param [in] treeName the name of the tree
\param [in] reuseEventsWithinEnsemble sample with replacement but only replace events once each experiment has been generated
\param [in] reuseEventsWithinExperiment sample with immediate replacement
\param [in] useReweighting perform an accept/reject routine using the configured signal amplitude model based on the MC-truth DP coordinate
*/
void embedSignal(const TString& fileName, const TString& treeName,
const Bool_t reuseEventsWithinEnsemble, const Bool_t reuseEventsWithinExperiment = kFALSE, const Bool_t useReweighting = kFALSE);
//! Embed full simulation events for the signal, rather than generating toy from the PDFs
/*!
\param [in] bkgndClass the name of the background class
\param [in] fileName the name of the file containing the events
\param [in] treeName the name of the tree
\param [in] reuseEventsWithinEnsemble sample with replacement but only replace events once each experiment has been generated
\param [in] reuseEventsWithinExperiment sample with immediate replacement
\param [in] useReweighting perform an accept/reject routine using the configured signal amplitude model based on the MC-truth DP coordinate
*/
void embedBkgnd(const TString& bkgndClass, const TString& fileName, const TString& treeName,
const Bool_t reuseEventsWithinEnsemble, const Bool_t reuseEventsWithinExperiment = kFALSE, const Bool_t useReweighting = kFALSE);
//! Set the value of the mixing phase
/*!
\param [in] phiMix the value of the mixing phase
\param [in] fixPhiMix whether the value should be fixed or floated
\param [in] useSinCos whether to use the sine and cosine as separate parameters or to just use the mixing phase itself
*/
void setPhiMix(const Double_t phiMix, const Bool_t fixPhiMix, const Bool_t useSinCos = kFALSE);
+ //! Setup blinding of the value of the mixing phase
+ /*!
+ \param [in] blindingString the string used to seed the blinding transformation for the phiMix parameter
+ \param [in] width the width of the Gaussian from which the offset should be sampled
+ \param [in] flipSign activate possible random sign flip
+ */
+ void blindPhiMix(const TString& blindingString, const Double_t width = 1.0, const Bool_t flipSign = kTRUE);
+
+ //! Setup blinding of the value of the mixing phase
+ /*!
+ \param [in] sinBlindingString the string used to seed the blinding transformation for the sin(phiMix) parameter
+ \param [in] cosBlindingString the string used to seed the blinding transformation for the cos(phiMix) parameter
+ \param [in] width the width of the Gaussian from which the offset should be sampled
+ \param [in] flipSign activate possible random sign flip
+ */
+ void blindPhiMix(const TString& sinBlindingString, const TString& cosBlindingString, const Double_t width = 0.5, const Bool_t flipSign = kTRUE);
+
//! Initialise the fit
virtual void initialise();
//! Initialise the signal DP model
virtual void initialiseDPModels();
//! Recalculate Normalization the signal DP models
virtual void recalculateNormalisation();
//! Update the coefficients
virtual void updateCoeffs();
// Toy MC generation and fitting overloaded functions
virtual Bool_t genExpt();
//! Set the maximum value of A squared to be used in the accept/reject
/*!
\param [in] value the new value
*/
inline void setASqMaxValue(const Double_t value) {aSqMaxSet_ = value;}
//! Weight events based on the DP model
/*!
\param [in] dataFileName the name of the data file
\param [in] dataTreeName the name of the data tree
*/
virtual void weightEvents( const TString& dataFileName, const TString& dataTreeName );
//! Calculate things that depend on the fit parameters after they have been updated by Minuit
virtual void propagateParUpdates();
//! Read in the input fit data variables, e.g. m13Sq and m23Sq
virtual void cacheInputFitVars();
//! Check the initial fit parameters
virtual void checkInitFitParams();
//! Get the fit results and store them
/*!
\param [in] tablePrefixName prefix for the name of the output file
*/
virtual void finaliseFitResults(const TString& tablePrefixName);
//! Save the pdf Plots for all the resonances of experiment number fitExp
/*!
TODO - not working in this model!!
\param [in] label prefix for the file name to be saved
*/
virtual void savePDFPlots(const TString& label);
//! Save the pdf Plots for the sum of ressonances correspondint to "sin" of experiment number fitExp
/*!
TODO - not working in this model!!
\param [in] label prefix for the file name to be saved
\param [in] spin spin of the wave to be saved
*/
virtual void savePDFPlotsWave(const TString& label, const Int_t& spin);
//! Print the fit fractions, total DP rate and mean efficiency
/*!
\param [out] output the stream to which to print
*/
virtual void printFitFractions(std::ostream& output);
//! Print the asymmetries
/*!
\param [out] output the stream to which to print
*/
virtual void printAsymmetries(std::ostream& output);
//! Write the fit results in latex table format
/*!
\param [in] outputFile the name of the output file
*/
virtual void writeOutTable(const TString& outputFile);
//! Store the per event likelihood values
virtual void storePerEvtLlhds();
// Methods to do with calculating the likelihood functions
// and manipulating the fitting parameters.
//! Get the total likelihood for each event
/*!
\param [in] iEvt the event number
*/
virtual Double_t getTotEvtLikelihood(const UInt_t iEvt);
//! Calculate the signal and background likelihoods for the DP for a given event
/*!
\param [in] iEvt the event number
*/
virtual void getEvtDPDtLikelihood(const UInt_t iEvt);
//! Determine the signal and background likelihood for the extra variables for a given event
/*!
\param [in] iEvt the event number
*/
virtual void getEvtExtraLikelihoods(const UInt_t iEvt);
//! Get the total number of events
/*!
\return the total number of events
*/
virtual Double_t getEventSum() const;
//! Set the fit parameters for the DP model
void setSignalDPParameters();
//! Set the fit parameters for the decay time PDFs
void setDecayTimeParameters();
//! Set the fit parameters for the extra PDFs
void setExtraPdfParameters();
//! Set the initial yields
void setFitNEvents();
//! Set the calibration parameters
void setCalibParams();
//! Set the tagging efficiency parameters
void setTagEffParams();
//! Set the asymmetry parameters
void setAsymParams();
//! Set the tagging asymmetry parameters
void setFlavTagAsymParams();
//! Set-up other parameters that are derived from the fit results, e.g. fit fractions
void setExtraNtupleVars();
//! Set production and detections asymmetries
/*!
\param [in] AProd is the production asymmetry definied as (N_BqBar-N_Bq)/(N_BqBar+N_Bq)
\param [in] AProdFix whether the production asymmetry should be fixed in the fit
*/
void setAsymmetries(const Double_t AProd, const Bool_t AProdFix);
//! Set production and detections asymmetries
/*!
\param [in] bkgndClass the name of the background class
\param [in] AProd is the production asymmetry definied as (N_BqBar-N_Bq)/(N_BqBar+N_Bq)
\param [in] AProdFix whether the production asymmetry should be fixed in the fit
*/
void setBkgndAsymmetries(const TString& bkgndClass, const Double_t AProd, const Bool_t AProdFix);
//! Randomise the initial fit parameters
void randomiseInitFitPars();
//! Method to set up the storage for background-related quantities called by setBkgndClassNames
virtual void setupBkgndVectors();
//! Calculate the CP asymmetries
/*!
\param [in] initValues is this before or after the fit
*/
void calcAsymmetries(const Bool_t initValues = kFALSE);
//! Finalise value of mixing phase
void checkMixingPhase();
protected:
//! container to hold information on the number of events (and their weight) to generate for each category
typedef std::map<TString,std::pair<Int_t,Double_t>> LauGenInfo;
//! container of background DP models
typedef std::vector<LauAbsBkgndDPModel*> LauBkgndDPModelList;
//! container of background PDFs
typedef std::vector<LauPdfPList> LauBkgndPdfsList;
//! container of background yields or asymmetries
typedef std::vector<LauAbsRValue*> LauBkgndYieldList;
//! container of boolean toggles for each background category
typedef std::vector<Bool_t> LauBkgndReuseEventsList;
//! Determine the number of events to generate for each event category
LauGenInfo eventsToGenerate();
//! Generate signal event
/*!
\return whether the generation was successful (kTRUE) or not (kFALSE)
*/
Bool_t generateSignalEvent();
//! Generate background event
/*!
\param [in] bgID ID number of the background class
\return whether the generation was successful (kTRUE) or not (kFALSE)
*/
Bool_t generateBkgndEvent(UInt_t bgID);
//! Setup the required ntuple branches
void setupGenNtupleBranches();
//! Store all of the DP and decay time information
void setDPDtBranchValues();
//! Generate from the extra PDFs
/*!
\param [in] extraPdfs the list of extra PDFs
\param [in] embeddedData the embedded data sample
*/
void generateExtraPdfValues(LauPdfPList& extraPdfs, LauEmbeddedData* embeddedData);
//! Add sPlot branches for the extra PDFs
/*!
\param [in] extraPdfs the list of extra PDFs
\param [in] prefix the list of prefixes for the branch names
*/
void addSPlotNtupleBranches(const LauPdfPList& extraPdfs, const TString& prefix);
//! Set the branches for the sPlot ntuple with extra PDFs
/*!
\param [in] extraPdfs the list of extra PDFs
\param [in] prefix the prefix for the branch names
\param [in] iEvt the event number
*/
Double_t setSPlotNtupleBranchValues(LauPdfPList& extraPdfs, const TString& prefix, const UInt_t iEvt);
//! Update the signal events after Minuit sets background parameters
void updateSigEvents();
//! Add branches to store experiment number and the event number within the experiment
virtual void setupSPlotNtupleBranches();
//! Returns the names of all variables in the fit
virtual LauSPlot::NameSet variableNames() const;
//! Returns the names and yields of species that are free in the fit
virtual LauSPlot::NumbMap freeSpeciesNames() const;
//! Returns the names and yields of species that are fixed in the fit
virtual LauSPlot::NumbMap fixdSpeciesNames() const;
//! Returns the species and variables for all 2D PDFs in the fit
virtual LauSPlot::TwoDMap twodimPDFs() const;
//! Check if the signal is split into well-reconstructed and mis-reconstructed types
virtual Bool_t splitSignal() const { return kFALSE; }
//! Check if the mis-reconstructed signal is to be smeared in the DP
virtual Bool_t scfDPSmear() const { return kFALSE; }
//! Calculate the component integrals of the interference term
void calcInterferenceTermIntegrals();
//! Calculate the total integral of the interference term
void calcInterferenceTermNorm();
private:
//! Keep access to the base class methods that we're further overloading
using LauAbsFitModel::addFitParameters;
//! Add the parameters from a decay time PDF into the fit
/*!
\param [in] decayTimePdf the container of PDFs
*/
UInt_t addFitParameters(LauDecayTimePdf* decayTimePdf);
//! Add the parameters from each decay time PDF into the fit
/*!
\param [in] decayTimePdfList the container of PDFs
*/
UInt_t addFitParameters(std::vector<LauDecayTimePdf*>& decayTimePdfList);
//! Dalitz plot PDF for the antiparticle
LauIsobarDynamics* sigModelB0bar_;
//! Dalitz plot PDF for the particle
LauIsobarDynamics* sigModelB0_;
//! Kinematics object for antiparticle
LauKinematics* kinematicsB0bar_;
//! Kinematics object for particle
LauKinematics* kinematicsB0_;
//! The background Dalitz plot models for particles
LauBkgndDPModelList BkgndDPModelsB_;
//! The background Dalitz plot models for anti-particles
LauBkgndDPModelList BkgndDPModelsBbar_;
//! The background PDFs
LauBkgndPdfsList BkgndPdfs_;
//! Background boolean
Bool_t usingBkgnd_;
//! LauFlavTag object for flavour tagging
LauFlavTag* flavTag_;
//! Flavour tag for current event
std::vector<LauFlavTag::Flavour> curEvtTagFlv_;
//! Per event mistag for current event
std::vector<Double_t> curEvtMistag_;
//! Per event transformed mistag for current event
std::vector<Double_t> curEvtMistagPrime_;
//! True tag flavour (i.e. flavour at production) for the current event (only relevant for toy generation)
LauFlavTag::Flavour curEvtTrueTagFlv_;
//! Flavour at decay for the current event (only relevant for QFS)
LauFlavTag::Flavour curEvtDecayFlv_;
//! Number of signal components
UInt_t nSigComp_;
//! Number of signal DP parameters
UInt_t nSigDPPar_;
//! Number of decay time PDF parameters
UInt_t nDecayTimePar_;
//! Number of extra PDF parameters
UInt_t nExtraPdfPar_;
//! Number of normalisation parameters (yields, asymmetries)
UInt_t nNormPar_;
//! Number of calibration parameters (p0, p1)
UInt_t nCalibPar_;
//! Number of tagging efficneyc parameters
UInt_t nTagEffPar_;
//! Number of efficiency parameters (p0, p1)
UInt_t nEffiPar_;
//! Number of asymmetry parameters
UInt_t nAsymPar_;
//! Number of tagging asymmetry parameters
UInt_t nTagAsymPar_;
//! The complex coefficients for antiparticle
std::vector<LauComplex> coeffsB0bar_;
//! The complex coefficients for particle
std::vector<LauComplex> coeffsB0_;
//! Magnitudes and Phases or Real and Imaginary Parts
std::vector<LauAbsCoeffSet*> coeffPars_;
//! The integrals of the efficiency corrected amplitude cross terms for each pair of amplitude components
/*!
Calculated as the sum of A* x Abar x efficiency
*/
std::vector< std::vector<LauComplex> > fifjEffSum_;
//! The normalisation for the term 2.0*Re(A*Abar*phiMix)
Double_t interTermReNorm_;
//! The normalisation for the term 2.0*Im(A*Abar*phiMix)
Double_t interTermImNorm_;
//! The antiparticle fit fractions
LauParArray fitFracB0bar_;
//! The particle fit fractions
LauParArray fitFracB0_;
//! The fit fraction asymmetries
std::vector<LauParameter> fitFracAsymm_;
//! A_CP parameter
std::vector<LauParameter> acp_;
//! The mean efficiency for the antiparticle
LauParameter meanEffB0bar_;
//! The mean efficiency for the particle
LauParameter meanEffB0_;
//! The average DP rate for the antiparticle
LauParameter DPRateB0bar_;
//! The average DP rate for the particle
LauParameter DPRateB0_;
//! Signal yields
LauParameter* signalEvents_;
//! Signal asymmetry
LauParameter* signalAsym_;
//! Background yield(s)
LauBkgndYieldList bkgndEvents_;
//! Background asymmetries(s)
LauBkgndYieldList bkgndAsym_;
//! CP eigenvalue variable name
TString cpevVarName_;
//! CP eigenvalue for current event
CPEigenvalue cpEigenValue_;
//! Vector to store event CP eigenvalues
std::vector<CPEigenvalue> evtCPEigenVals_;
//! The mass difference between the neutral mass eigenstates
LauParameter deltaM_;
//! The width difference between the neutral mass eigenstates
LauParameter deltaGamma_;
//! The lifetime
LauParameter tau_;
//! The mixing phase
LauParameter phiMix_;
//! The sine of the mixing phase
LauParameter sinPhiMix_;
//! The cosine of the mixing phase
LauParameter cosPhiMix_;
//! Flag whether to use the sine and cosine of the mixing phase or the phase itself as the fit parameters
Bool_t useSinCos_;
//! e^{-i*phiMix}
LauComplex phiMixComplex_;
//! Signal Decay time PDFs (one per tagging category)
LauDecayTimePdf* signalDecayTimePdf_;
//! Background types
std::vector<LauFlavTag::BkgndType> BkgndTypes_;
//! Background Decay time PDFs (one per tagging category)
std::vector<LauDecayTimePdf*> BkgndDecayTimePdfs_;
//! Decay time for the current event
Double_t curEvtDecayTime_;
//! Decay time error for the current event
Double_t curEvtDecayTimeErr_;
//! PDFs for other variables
LauPdfPList sigExtraPdf_;
//! Production asymmetry between B0 and B0bar
LauParameter AProd_;
//! Production asymmetry between B0 and B0bar for bkgnds
std::vector<LauParameter*> AProdBkgnd_;
// Toy generation stuff
//! The maximum allowed number of attempts when generating an event
Int_t iterationsMax_;
//! The number of unsucessful attempts to generate an event so far
Int_t nGenLoop_;
//! The value of A squared for the current event
Double_t ASq_;
//! The maximum value of A squared that has been seen so far while generating
Double_t aSqMaxVar_;
//! The maximum allowed value of A squared
Double_t aSqMaxSet_;
//! Flag for storage of amplitude info in generated ntuple
Bool_t storeGenAmpInfo_;
//! The signal event tree for embedding fully simulated events
LauEmbeddedData* signalTree_;
//! The background event tree for embedding fully simulated events
std::vector<LauEmbeddedData*> bkgndTree_;
//! Boolean to control reuse of embedded signal events
Bool_t reuseSignal_;
//! Boolean to use reweighting when embedding
Bool_t useReweighting_;
//! Vector of booleans to reuse background events
LauBkgndReuseEventsList reuseBkgnd_;
// Likelihood values
//! Signal DP likelihood value
Double_t sigDPLike_;
//! Signal likelihood from extra PDFs
Double_t sigExtraLike_;
//! Total signal likelihood
Double_t sigTotalLike_;
//! Background DP likelihood value(s)
std::vector<Double_t> bkgndDPLike_;
//! Background likelihood value(s) from extra PDFs
std::vector<Double_t> bkgndExtraLike_;
//! Total background likelihood(s)
std::vector<Double_t> bkgndTotalLike_;
ClassDef(LauTimeDepFitModel,0) // Time-dependent neutral model
};
#endif
diff --git a/src/LauBlind.cc b/src/LauBlind.cc
index 087e8dd..e763a14 100644
--- a/src/LauBlind.cc
+++ b/src/LauBlind.cc
@@ -1,71 +1,51 @@
/*
Copyright 2015 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 LauBlind.cc
\brief File containing implementation of LauBlind class.
*/
#include "LauBlind.hh"
#include "TMath.h"
#include "TRandom3.h"
ClassImp(LauBlind)
-LauBlind::LauBlind() :
- blindingString_(""),
- blindingWidth_(0.0),
- offset_(0.0)
-{
-}
-
-LauBlind::LauBlind(const TString& blindingStr, const Double_t width) :
+LauBlind::LauBlind(const TString& blindingStr, const Double_t width, const Bool_t flipSign) :
blindingString_(blindingStr),
blindingWidth_(width),
- offset_(0.0)
-{
- this->calcOffset();
-}
-
-LauBlind::LauBlind(const LauBlind& rhs) :
- blindingString_(rhs.blindingString_),
- blindingWidth_(rhs.blindingWidth_),
- offset_(rhs.offset_)
-{
-}
-
-LauBlind::~LauBlind()
-{
-}
-
-void LauBlind::calcOffset()
+ flipSign_(flipSign)
{
//hash the blinding string to obtain a seed
TRandom3 r(TMath::Hash(blindingString_));
//offsets are Gaussian distributed with defined width
offset_ = blindingWidth_ * r.Gaus();
+
+ //should we also flip the sign?
+ flip_ = r.Integer(2);
}
diff --git a/src/LauParameter.cc b/src/LauParameter.cc
index 0266296..21ad0e9 100644
--- a/src/LauParameter.cc
+++ b/src/LauParameter.cc
@@ -1,595 +1,595 @@
/*
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 LauParameter.cc
\brief File containing implementation of LauParameter class.
*/
#include <iostream>
#include <map>
#include "TRandom.h"
#include "LauParameter.hh"
#include "LauRandom.hh"
ClassImp(LauParameter)
LauParameter::LauParameter(const TString& parName) :
name_{parName}
{
}
LauParameter::LauParameter(const Double_t parValue) :
value_{parValue},
genValue_{parValue},
initValue_{parValue},
minValue_{parValue-1e-6},
maxValue_{parValue+1e-6}
{
}
LauParameter::LauParameter(const TString& parName, const Double_t parValue) :
name_{parName},
value_{parValue},
genValue_{parValue},
initValue_{parValue},
minValue_{parValue-1e-6},
maxValue_{parValue+1e-6}
{
}
LauParameter::LauParameter(const Double_t parValue, const Double_t min, const Double_t max) :
value_{parValue},
genValue_{parValue},
initValue_{parValue},
minValue_{min},
maxValue_{max}
{
this->checkRange();
}
LauParameter::LauParameter(const Double_t parValue, const Double_t parError, const Double_t min, const Double_t max) :
value_{parValue},
error_{parError},
genValue_{parValue},
initValue_{parValue},
minValue_{min},
maxValue_{max}
{
this->checkRange();
}
LauParameter::LauParameter(const Double_t parValue, const Double_t min, const Double_t max, const Bool_t parFixed) :
value_{parValue},
genValue_{parValue},
initValue_{parValue},
minValue_{min},
maxValue_{max},
fixed_{parFixed}
{
this->checkRange();
}
LauParameter::LauParameter(const TString& parName, const Double_t parValue, const Double_t min, const Double_t max) :
name_{parName},
value_{parValue},
genValue_{parValue},
initValue_{parValue},
minValue_{min},
maxValue_{max}
{
this->checkRange();
}
LauParameter::LauParameter(const TString& parName, const Double_t parValue, const Double_t min, const Double_t max, const Bool_t parFixed) :
name_{parName},
value_{parValue},
genValue_{parValue},
initValue_{parValue},
minValue_{min},
maxValue_{max},
fixed_{parFixed}
{
this->checkRange();
}
LauParameter::LauParameter(const TString& parName, const Double_t parValue, const Double_t parError, const Double_t min, const Double_t max) :
name_{parName},
value_{parValue},
error_{parError},
genValue_{parValue},
initValue_{parValue},
minValue_{min},
maxValue_{max}
{
this->checkRange();
}
LauParameter::LauParameter(const LauParameter& rhs) : TObject(rhs), LauAbsRValue(rhs),
name_{rhs.name_},
value_{rhs.value_},
error_{rhs.error_},
negError_{rhs.negError_},
posError_{rhs.posError_},
genValue_{rhs.genValue_},
initValue_{rhs.initValue_},
minValue_{rhs.minValue_},
maxValue_{rhs.maxValue_},
fixed_{rhs.fixed_},
secondStage_{rhs.secondStage_},
gaussConstraint_{rhs.gaussConstraint_},
constraintMean_{rhs.constraintMean_},
constraintWidth_{rhs.constraintWidth_},
gcc_{rhs.gcc_},
bias_{rhs.bias_},
pull_{rhs.pull_},
clone_{rhs.clone_},
parent_{rhs.parent_},
clones_{rhs.clones_},
blinder_{(rhs.blinder_) ? std::make_unique<LauBlind>(*(rhs.blinder_)) : nullptr}
{
}
LauParameter& LauParameter::operator=(const LauParameter& rhs)
{
if (&rhs != this) {
TObject::operator=(rhs);
LauAbsRValue::operator=(rhs);
name_ = rhs.name_;
value_ = rhs.value_;
error_ = rhs.error_;
negError_ = rhs.negError_;
posError_ = rhs.posError_;
genValue_ = rhs.genValue_;
initValue_ = rhs.initValue_;
minValue_ = rhs.minValue_;
maxValue_ = rhs.maxValue_;
fixed_ = rhs.fixed_;
secondStage_ = rhs.secondStage_;
gaussConstraint_ = rhs.gaussConstraint_;
constraintMean_ = rhs.constraintMean_;
constraintWidth_ = rhs.constraintWidth_;
gcc_ = rhs.gcc_;
bias_ = rhs.bias_;
pull_ = rhs.pull_;
clone_ = rhs.clone_;
parent_ = rhs.parent_;
clones_ = rhs.clones_;
blinder_.reset();
if ( rhs.blinder_ ) {
blinder_ = std::make_unique<LauBlind>(*(rhs.blinder_));
}
}
return *this;
}
LauParameter::~LauParameter() noexcept
{
// if we're a clone, we just need to inform our parent of our demise
if ( this->clone() ) {
parent_->removeFromCloneList(this);
return;
}
// if we have no clones there's nothing to do
if ( clones_.empty() ) {
return;
}
// otherwise if we have clones we need to make one of them the new parent and inform the rest of the change
// let's (arbitrarily) make the first parameter in the map the new parent
auto iter = clones_.begin();
auto [ newParent, constFactor ] { *iter };
// remove that entry in the map
clones_.erase(iter);
// for all the other entries, we need to tell them they are clones of the new parent
// and also rescale the constants so that they are relative to the new parent
for ( auto& [ theClone, theFactor ] : clones_ ) {
theClone->clone(newParent);
theFactor /= constFactor;
}
// transfer the list of clones to the new parent
newParent->clones_ = std::move(clones_);
// finally, the new parent has to be told that it isn't a clone anymore
newParent->clone(nullptr);
}
std::vector<LauParameter*> LauParameter::getPars()
{
std::vector<LauParameter*> list;
list.push_back(this);
return list;
}
void LauParameter::value(const Double_t newValue)
{
if (this->clone()) {
parent_->value(newValue);
} else {
this->checkRange(newValue,this->minValue(),this->maxValue());
this->updateClones(kTRUE);
}
}
void LauParameter::error(const Double_t newError)
{
if (this->clone()) {
parent_->error(newError);
} else {
error_ = TMath::Abs(newError);
this->updateClones(kFALSE);
}
}
void LauParameter::negError(const Double_t newNegError)
{
if (this->clone()) {
parent_->negError(newNegError);
} else {
negError_ = TMath::Abs(newNegError);
this->updateClones(kFALSE);
}
}
void LauParameter::posError(const Double_t newPosError)
{
if (this->clone()) {
parent_->posError(newPosError);
} else {
posError_ = TMath::Abs(newPosError);
this->updateClones(kFALSE);
}
}
void LauParameter::errors(const Double_t newError, const Double_t newNegError, const Double_t newPosError)
{
if (this->clone()) {
parent_->errors(newError,newNegError,newPosError);
} else {
error_ = TMath::Abs(newError);
negError_ = TMath::Abs(newNegError);
posError_ = TMath::Abs(newPosError);
this->updateClones(kFALSE);
}
}
void LauParameter::valueAndErrors(const Double_t newValue, const Double_t newError, const Double_t newNegError, const Double_t newPosError)
{
if (this->clone()) {
parent_->valueAndErrors(newValue,newError,newNegError,newPosError);
} else {
this->checkRange(newValue,this->minValue(),this->maxValue());
error_ = TMath::Abs(newError);
negError_ = TMath::Abs(newNegError);
posError_ = TMath::Abs(newPosError);
this->updateClones(kFALSE);
}
}
void LauParameter::globalCorrelationCoeff(const Double_t newGCCValue)
{
if (this->clone()) {
parent_->globalCorrelationCoeff(newGCCValue);
} else {
gcc_ = newGCCValue;
this->updateClones(kFALSE);
}
}
void LauParameter::genValue(const Double_t newGenValue)
{
if (this->clone()) {
parent_->genValue(newGenValue);
} else {
genValue_ = newGenValue;
this->updateClones(kFALSE);
}
}
void LauParameter::initValue(const Double_t newInitValue)
{
if (this->clone()) {
parent_->initValue(newInitValue);
} else {
initValue_ = newInitValue;
this->updateClones(kFALSE);
}
}
void LauParameter::minValue(const Double_t newMinValue)
{
if (this->clone()) {
parent_->minValue(newMinValue);
} else {
this->checkRange(this->value(),newMinValue,this->maxValue());
this->updateClones(kFALSE);
}
}
void LauParameter::maxValue(const Double_t newMaxValue)
{
if (this->clone()) {
parent_->maxValue(newMaxValue);
} else {
this->checkRange(this->value(),this->minValue(),newMaxValue);
this->updateClones(kFALSE);
}
}
void LauParameter::range(const Double_t newMinValue, const Double_t newMaxValue)
{
if (this->clone()) {
parent_->range(newMinValue,newMaxValue);
} else {
this->checkRange(this->value(),newMinValue,newMaxValue);
this->updateClones(kFALSE);
}
}
void LauParameter::valueAndRange(const Double_t newValue, const Double_t newMinValue, const Double_t newMaxValue)
{
if (this->clone()) {
parent_->valueAndRange(newValue,newMinValue,newMaxValue);
} else {
this->checkRange(newValue,newMinValue,newMaxValue);
this->updateClones(kFALSE);
}
}
void LauParameter::name(const TString& newName)
{
// no need to update clones here
// clones are allowed to have different names
name_ = newName;
}
void LauParameter::fixed(const Bool_t parFixed)
{
if (this->clone()) {
parent_->fixed(parFixed);
} else {
fixed_ = parFixed;
this->updateClones(kFALSE);
}
}
void LauParameter::secondStage(const Bool_t secondStagePar)
{
if (this->clone()) {
parent_->secondStage(secondStagePar);
} else {
secondStage_ = secondStagePar;
this->updateClones(kFALSE);
}
}
void LauParameter::addGaussianConstraint(const Double_t newGaussMean, const Double_t newGaussWidth)
{
if (this->clone()) {
parent_->addGaussianConstraint(newGaussMean,newGaussWidth);
} else {
gaussConstraint_ = kTRUE;
constraintMean_ = newGaussMean;
constraintWidth_ = newGaussWidth;
this->updateClones(kFALSE);
}
}
void LauParameter::removeGaussianConstraint()
{
if (this->clone()) {
parent_->removeGaussianConstraint();
} else {
gaussConstraint_ = kFALSE;
this->updateClones(kFALSE);
}
}
-void LauParameter::blindParameter(const TString& blindingString, const Double_t width)
+void LauParameter::blindParameter(const TString& blindingString, const Double_t width, const Bool_t flipSign)
{
if (this->clone()) {
- parent_->blindParameter(blindingString,width);
+ parent_->blindParameter(blindingString,width,flipSign);
return;
}
if ( blinder_ ) {
std::cerr << "WARNING in LauParameter::blindParameter : blinding has already been set up for this parameter" << std::endl;
return;
}
- blinder_ = std::make_unique<LauBlind>(blindingString,width);
+ blinder_ = std::make_unique<LauBlind>(blindingString,width,flipSign);
for ( auto& [ clonePar, _ ] : clones_ ) {
if ( clonePar->blinder_ != nullptr ) {
std::cerr << "WARNING in LauParameter::blindParameter : blinding has already been set up for a clone of this parameter - it will be replaced!" << std::endl;
clonePar->blinder_.reset();
}
clonePar->blinder_ = std::make_unique<LauBlind>(*blinder_);
}
}
void LauParameter::updatePull()
{
if (this->clone()) {
parent_->updatePull();
return;
}
// calculate the bias
bias_ = value_ - genValue_;
// if we have errors calculated then calculate
// the pull using the best error available
if ((bias_ > 0.0) && (negError_ > 1e-10)) {
pull_ = bias_ / negError_;
} else if ((bias_ < 0.0) && (posError_ > 1e-10)) {
pull_ = bias_ / posError_;
} else if (error_ > 1e-10) {
pull_ = bias_ / error_;
} else {
pull_ = 0.0;
}
this->updateClones(kFALSE);
}
void LauParameter::checkRange(const Double_t val, const Double_t minVal, const Double_t maxVal)
{
// first check that min is less than max (or they are the same - this is allowed)
if (minVal > maxVal) {
std::cerr<<"ERROR in LauParameter::checkRange : minValue: "<<minVal<<" greater than maxValue: "<<maxVal<<std::endl;
if (minValue_ > maxValue_) {
minValue_ = maxValue_;
std::cerr<<" : Setting both to "<<maxValue_<<"."<<std::endl;
} else {
std::cerr<<" : Not changing anything."<<std::endl;
}
return;
}
minValue_ = minVal;
maxValue_ = maxVal;
// now check that the value is still within the range
if ((val < minVal) || (val > maxVal)) {
if (name_ != "") {
std::cerr<<"ERROR in LauParameter::checkRange : value: "<<val<<" not in allowed range ["<<minVal<<" , "<<maxVal<<"] for parameter \""<<name_<<"\"."<<std::endl;
} else {
std::cerr<<"ERROR in LauParameter::checkRange : value: "<<val<<" not in allowed range ["<<minVal<<" , "<<maxVal<<"]."<<std::endl;
}
if (val < minVal) {
std::cerr<<" : Setting value to minValue: "<<minVal<<std::endl;
value_ = minVal;
} else {
std::cerr<<" : Setting value to maxValue: "<<maxVal<<std::endl;
value_ = maxVal;
}
} else {
value_ = val;
}
}
LauParameter* LauParameter::createClone(const Double_t constFactor)
{
// if we're a clone we mustn't be cloned ourselves
// but instead return another clone of our parent
// (this is so that the parent knows of all its clones)
if (this->clone()) {
LauParameter* clonePar = parent_->createClone(constFactor);
clonePar->name(this->name());
return clonePar;
}
// clone ourselves using the copy-constructor
LauParameter* clonePar = new LauParameter(*this);
Double_t newValue = clonePar->value() * constFactor;
clonePar->value( newValue );
clonePar->wipeClones();
clonePar->clone(this);
clones_.insert( std::make_pair( clonePar, constFactor ) );
return clonePar;
}
LauParameter* LauParameter::createClone(const TString& newName, const Double_t constFactor)
{
// self message to create the clone
LauParameter* clonePar = this->createClone(constFactor);
// set the new name
clonePar->name(newName);
// and return
return clonePar;
}
void LauParameter::updateClones(const Bool_t justValue)
{
// if we don't have any clones then there's nothing to do
if ( clones_.empty() ) {
return;
}
// we have to set the values directly rather than using member functions because otherwise we'd get into an infinite loop
if (justValue) {
for ( auto& [ clonePar, constFactor ] : clones_ ) {
clonePar->value_ = constFactor*value_;
}
} else {
for ( auto& [ clonePar, constFactor ] : clones_ ) {
clonePar->value_ = constFactor*value_;
clonePar->error_ = constFactor*error_;
clonePar->negError_ = constFactor*negError_;
clonePar->posError_ = constFactor*posError_;
clonePar->genValue_ = constFactor*genValue_;
clonePar->initValue_ = constFactor*initValue_;
clonePar->minValue_ = constFactor*minValue_;
clonePar->maxValue_ = constFactor*maxValue_;
clonePar->fixed_ = fixed_;
clonePar->secondStage_ = secondStage_;
clonePar->gaussConstraint_ = gaussConstraint_;
clonePar->constraintMean_ = constraintMean_;
clonePar->constraintWidth_ = constraintWidth_;
clonePar->gcc_ = gcc_;
clonePar->bias_ = bias_;
clonePar->pull_ = pull_;
}
}
}
void LauParameter::randomiseValue()
{
this->randomiseValue(this->minValue(), this->maxValue());
}
void LauParameter::randomiseValue(const Double_t minVal, const Double_t maxVal)
{
// if we're fixed then do nothing
if (this->fixed()) {
return;
}
// check supplied values are sensible
if (maxVal < minVal) {
std::cerr<<"ERROR in LauParameter::randomiseValue : Supplied maximum value smaller than minimum value."<<std::endl;
return;
}
// use the zero-seed random number generator to get values that are
// uniformly distributed over the given range (truncating to ensure it is within our nominal range)
const Double_t val { LauRandom::zeroSeedRandom()->Uniform( TMath::Max( minVal, this->minValue() ), TMath::Min( maxVal, this->maxValue() ) ) };
this->initValue(val);
}
// ostream operator
std::ostream& operator << (std::ostream& stream, const LauParameter& par)
{
stream << par.value();
return stream;
}
diff --git a/src/LauTimeDepFitModel.cc b/src/LauTimeDepFitModel.cc
index dd87e70..e29b2ec 100644
--- a/src/LauTimeDepFitModel.cc
+++ b/src/LauTimeDepFitModel.cc
@@ -1,3241 +1,3262 @@
/*
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 <chrono>
#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::Flavour::Unknown),
curEvtDecayFlv_(LauFlavTag::Flavour::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_(flavTag_->getBkgndTypes()),
BkgndDecayTimePdfs_(),
curEvtDecayTime_(0.0),
curEvtDecayTimeErr_(0.0),
sigExtraPdf_(),
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),
sigTotalLike_(0.0)
{
// Set up ftag here?
this->setBkgndClassNames(flavTag_->getBkgndNames());
const std::size_t nBkgnds { this->nBkgndClasses() };
if ( nBkgnds > 0 ){
usingBkgnd_ = kTRUE;
for ( std::size_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;
TString yieldName = signalEvents_->name();
if ( ! yieldName.BeginsWith("signalEvents") ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : The signal yield parameter name should start with \"signalEvents\" (plus any optional suffix)." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
Double_t value = nSigEvents->value();
signalEvents_->range(-2.0*(TMath::Abs(value)+1.0),2.0*(TMath::Abs(value)+1.0));
TString asymName = yieldName;
asymName.ReplaceAll( "Events", "Asym" );
signalAsym_ = new LauParameter(asymName,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;
TString yieldName = signalEvents_->name();
if ( ! yieldName.BeginsWith("signalEvents") ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNSigEvents : The signal yield parameter name should start with \"signalEvents\" (plus any optional suffix)." << std::endl;
gSystem->Exit(EXIT_FAILURE);
}
Double_t value = nSigEvents->value();
signalEvents_->range(-2.0*(TMath::Abs(value)+1.0), 2.0*(TMath::Abs(value)+1.0));
signalAsym_ = sigAsym;
TString asymName = yieldName;
asymName.ReplaceAll( "Events", "Asym" );
signalAsym_->name(asymName);
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);
}
TString yieldName = nBkgndEvents->name();
TString bkgndClassName = yieldName;
if ( bkgndClassName.Contains("Events") ) {
bkgndClassName.Remove( bkgndClassName.Index("Events") );
} else {
yieldName += "Events";
nBkgndEvents->name( yieldName );
}
if ( ! this->validBkgndClass( bkgndClassName ) ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : Invalid background class \"" << bkgndClassName << "\"." << 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( bkgndClassName );
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;
}
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;
TString asymName = yieldName;
asymName.ReplaceAll( "Events", "Asym" );
bkgndAsym_[bkgndID] = new LauParameter(asymName,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);
}
TString yieldName = nBkgndEvents->name();
TString bkgndClassName = yieldName;
if ( bkgndClassName.Contains("Events") ) {
bkgndClassName.Remove( bkgndClassName.Index("Events") );
} else {
yieldName += "Events";
nBkgndEvents->name( yieldName );
}
TString asymName = yieldName;
asymName.ReplaceAll( "Events", "Asym" );
bkgndAsym->name( asymName );
if ( ! this->validBkgndClass( bkgndClassName ) ) {
std::cerr << "ERROR in LauTimeDepFitModel::setNBkgndEvents : Invalid background class \"" << bkgndClassName << "\"." << 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( bkgndClassName );
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;
}
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;
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::blindPhiMix(const TString& blindingString, const Double_t width, const Bool_t flipSign)
+{
+ phiMix_.range( -2.0*LauConstants::threePi, 2.0*LauConstants::threePi );
+ phiMix_.blindParameter( blindingString, width, flipSign );
+}
+
+void LauTimeDepFitModel::blindPhiMix(const TString& sinBlindingString, const TString& cosBlindingString, const Double_t width, const Bool_t flipSign)
+{
+ if ( ! useSinCos_ ) {
+ std::cerr << "WARNING in LauTimeDepFitModel::blindPhiMix : not using sine/cosine parameters, so using the sine blinding string to blind the phase itself." << std::endl;
+ this->blindPhiMix(sinBlindingString);
+ return;
+ }
+
+ sinPhiMix_.range( -2.0, 2.0 );
+ cosPhiMix_.range( -2.0, 2.0 );
+
+ sinPhiMix_.blindParameter( sinBlindingString, width, flipSign );
+ cosPhiMix_.blindParameter( cosBlindingString, width, flipSign );
+}
+
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 ( LauPdfPList::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 LauPdfPList& pdfList = (*bgclass_iter);
// for ( LauPdfPList::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();
//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->calcInterferenceTermNorm();
// 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::calcInterferenceTermNorm()
{
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
for (UInt_t i = 0; i < nSigComp_; ++i) {
LauParameterPList pars = coeffPars_[i]->getParameters();
nSigDPPar_ += this->addFitParameters( pars, kTRUE );
}
// 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
LauParameterPList& sigDPParsB0bar = sigModelB0bar_->getFloatingParameters();
LauParameterPList& sigDPParsB0 = sigModelB0_->getFloatingParameters();
nSigDPPar_ += this->addResonanceParameters( sigDPParsB0bar );
nSigDPPar_ += this->addResonanceParameters( sigDPParsB0 );
}
UInt_t LauTimeDepFitModel::addFitParameters(LauDecayTimePdf* decayTimePdf)
{
return this->addFitParameters( decayTimePdf->getParameters());
}
UInt_t LauTimeDepFitModel::addFitParameters(std::vector<LauDecayTimePdf*>& decayTimePdfList)
{
UInt_t nParsAdded{0};
for ( auto decayTimePdf : decayTimePdfList ) {
nParsAdded += this->addFitParameters( decayTimePdf );
}
return nParsAdded;
}
void LauTimeDepFitModel::setDecayTimeParameters()
{
nDecayTimePar_ = 0;
std::cout << "INFO in LauTimeDepFitModel::setDecayTimeParameters : Setting the initial fit parameters of the DecayTime Pdfs." << std::endl;
// Loop over the Dt PDFs
nDecayTimePar_ += this->addFitParameters( signalDecayTimePdf_ );
if (usingBkgnd_){
nDecayTimePar_ += this->addFitParameters(BkgndDecayTimePdfs_);
}
if (useSinCos_) {
nDecayTimePar_ += this->addFitParameters( &sinPhiMix_ );
nDecayTimePar_ += this->addFitParameters( &cosPhiMix_ );
} else {
nDecayTimePar_ += this->addFitParameters( &phiMix_ );
}
}
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));
// 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;
nNormPar_ += this->addFitParameters( signalEvents_ );
} 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) {
nNormPar_ += this->addFitParameters( signalAsym_ );
}
// 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) {
nNormPar_ += this->addFitParameters( bkgndEvents_ );
nNormPar_ += this->addFitParameters( bkgndAsym_ );
}
}
void LauTimeDepFitModel::setAsymParams()
{
nAsymPar_ = 0;
//Signal
nAsymPar_ += this->addFitParameters( &AProd_ );
//Background(s)
nAsymPar_ += this->addFitParameters( AProdBkgnd_ );
}
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();
nTagEffPar_ += this->addFitParameters( tageff_ave );
nTagEffPar_ += this->addFitParameters( tageff_delta );
} else {
std::vector<LauParameter*> tageff_b0 = flavTag_->getTagEffB0();
std::vector<LauParameter*> tageff_b0bar = flavTag_->getTagEffB0bar();
nTagEffPar_ += this->addFitParameters( tageff_b0 );
nTagEffPar_ += this->addFitParameters( tageff_b0bar );
}
if (usingBkgnd_){
if (useAltPars){
auto tageff_ave = flavTag_->getTagEffBkgndAve();
auto tageff_delta = flavTag_->getTagEffBkgndDelta();
for(auto& innerVec : tageff_ave){
nTagEffPar_ += this->addFitParameters( innerVec );
}
for(auto& innerVec : tageff_delta){
nTagEffPar_ += this->addFitParameters( innerVec );
}
} else {
auto tageff_b0 = flavTag_->getTagEffBkgndB0();
auto tageff_b0bar = flavTag_->getTagEffBkgndB0bar();
for(auto& innerVec : tageff_b0){
nTagEffPar_ += this->addFitParameters( innerVec );
}
for(auto& innerVec : tageff_b0bar){
nTagEffPar_ += this->addFitParameters( innerVec );
}
}
}
}
void LauTimeDepFitModel::setCalibParams()
{
nCalibPar_ = 0;
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();
nCalibPar_ += this->addFitParameters( p0pars_ave );
nCalibPar_ += this->addFitParameters( p0pars_delta );
nCalibPar_ += this->addFitParameters( p1pars_ave );
nCalibPar_ += this->addFitParameters( p1pars_delta );
} 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();
nCalibPar_ += this->addFitParameters( p0pars_b0 );
nCalibPar_ += this->addFitParameters( p0pars_b0bar );
nCalibPar_ += this->addFitParameters( p1pars_b0 );
nCalibPar_ += this->addFitParameters( p1pars_b0bar );
}
}
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();
}
}
// Finalise the pulls on the flavour tagging parameters
flavTag_->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.
if (this->doPoissonSmearing()) {
nEvts = LauRandom::randomFun()->Poisson(signalEvents_->genValue());
}
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 ) {
if (this->doPoissonSmearing()) {
nEvtsGen[this->bkgndClassName(bkgndID)] = std::make_pair( LauRandom::randomFun()->Poisson(bkgndEvents_[bkgndID]->genValue()), evtWeight);
} else {
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 );
auto t1 = std::chrono::high_resolution_clock::now();
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 == "" ) {
std::cerr<<"ERROR in LauTimeDepFitModel::genExpt : Decay flavour variable not set for QFS decay, see LauFlavTag::setDecayFlvVarName()."<<std::endl;
gSystem->Exit(EXIT_FAILURE);
} else {
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 std::size_t nTaggers {flavTag_->getNTaggers()};
for (std::size_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;}
}
auto t2 = std::chrono::high_resolution_clock::now();
if(nEvtsGen != 0)
{
std::chrono::duration<double, std::milli> ms_double = ( t2 - t1 )/nEvtsGen;
std::cout<<"INFO in LauTimeDepFitModel::genExpt : Average per-event generation time for "<<evtCategory<<": "<<ms_double.count()<<" ms"<<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);
if (this->useDP()) {
if (signalTree_) {
signalTree_->getEmbeddedEvent(kinematicsB0bar_);
//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);
//LauPdfPList* 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();
//}
//
LauKinematics* kinematics{nullptr};
switch ( BkgndTypes_[bkgndID] ) {
case LauFlavTag::BkgndType::Combinatorial:
{
// First choose the true tag, accounting for the production asymmetry
// CONVENTION WARNING regarding meaning of sign of AProd
// NB the true tag doesn't really mean anything for combinatorial background
Double_t random = LauRandom::randomFun()->Rndm();
if ( random <= 0.5 * ( 1.0 - AProdBkgnd_[bkgndID]->unblindValue() ) ) {
curEvtTrueTagFlv_ = LauFlavTag::Flavour::B;
} else {
curEvtTrueTagFlv_ = LauFlavTag::Flavour::Bbar;
}
if ( cpEigenValue_ == CPEigenvalue::QFS ) {
if ( BkgndDPModelsBbar_[bkgndID] != nullptr ) {
// generate the true decay flavour and the corresponding DP position
// (the supply of two DP models indicates a possible asymmetry)
const Double_t rateB { BkgndDPModelsB_[bkgndID]->getPdfNorm() };
const Double_t rateBbar { BkgndDPModelsBbar_[bkgndID]->getPdfNorm() };
const Double_t ADet { ( rateBbar - rateB ) / ( rateBbar + rateB ) };
random = LauRandom::randomFun()->Rndm();
if ( random <= 0.5 * ( 1.0 - ADet ) ) {
curEvtDecayFlv_ = LauFlavTag::Flavour::B;
BkgndDPModelsB_[bkgndID]->generate();
kinematics = kinematicsB0_;
} else {
curEvtDecayFlv_ = LauFlavTag::Flavour::Bbar;
BkgndDPModelsBbar_[bkgndID]->generate();
kinematics = kinematicsB0bar_;
}
} else {
// generate the true decay flavour
// (the supply of only a single model indicates no asymmetry)
random = LauRandom::randomFun()->Rndm();
if ( random <= 0.5 ) {
curEvtDecayFlv_ = LauFlavTag::Flavour::B;
} else {
curEvtDecayFlv_ = LauFlavTag::Flavour::Bbar;
}
// generate the DP position
BkgndDPModelsB_[bkgndID]->generate();
kinematics = kinematicsB0_;
}
} else {
// mark that the decay flavour is unknown
curEvtDecayFlv_ = LauFlavTag::Flavour::Unknown;
// generate the DP position
BkgndDPModelsB_[bkgndID]->generate();
kinematics = kinematicsB0_;
}
// generate decay time and its error
curEvtDecayTimeErr_ = BkgndDecayTimePdfs_[bkgndID]->generateError(kTRUE);
curEvtDecayTime_ = BkgndDecayTimePdfs_[bkgndID]->generate( kinematics );
// generate the flavour tagging information from the true tag and decay flavour
// (we do this after accepting the event to save time)
flavTag_->generateBkgndEventInfo( bkgndID, curEvtTrueTagFlv_, curEvtDecayFlv_, curEvtDecayTime_ );
curEvtTagFlv_ = flavTag_->getCurEvtTagFlv();
curEvtMistag_ = flavTag_->getCurEvtMistag();
break;
}
case LauFlavTag::BkgndType::FlavourSpecific:
{
const LauDecayTime::FuncType dtType { BkgndDecayTimePdfs_[bkgndID]->getFuncType() };
if ( dtType == LauDecayTime::FuncType::ExpTrig or dtType == LauDecayTime::FuncType::ExpHypTrig ) {
const Double_t tMin = BkgndDecayTimePdfs_[bkgndID]->minAbscissa();
const Double_t tMax = BkgndDecayTimePdfs_[bkgndID]->maxAbscissa();
const Double_t maxDtEff { BkgndDecayTimePdfs_[bkgndID]->getMaxEfficiency() };
// TODO - do we need the factor 2?
const Double_t ASumSqMax { 2.0 * ( BkgndDPModelsB_[bkgndID]->getMaxHeight() + BkgndDPModelsBbar_[bkgndID]->getMaxHeight() ) * maxDtEff };
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 and calculate the total A^2 and Abar^2
kinematics = BkgndDPModelsB_[bkgndID]->genUniformPoint();
BkgndDPModelsB_[bkgndID]->calcLikelihoodInfo(kinematics);
BkgndDPModelsBbar_[bkgndID]->calcLikelihoodInfo(kinematics);
// Generate decay time
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]->getRawValue() };
const Double_t AbarSq { BkgndDPModelsBbar_[bkgndID]->getRawValue() };
// 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() };
// 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 };
// 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;
}
//Debug ASumSqMax huge size w.r.t. ASumSq for SDPs
//std::cout<<"ASq "<<ASq<<" AbarSq "<<AbarSq<<" dtCos "<<dtCos<<" dtCosh "<<dtCosh<<" dtEff "<<dtEff<<" ATotSq "<<ATotSq<<" AbarTotSq "<<AbarTotSq<<" ASumSq "<<ASumSq<<" ASumSqMax "<<ASumSqMax<<std::endl;
// Generate the flavour tagging information from the true tag and decay flavour
// (we do this after accepting the event to save time)
flavTag_->generateBkgndEventInfo( bkgndID, curEvtTrueTagFlv_, curEvtDecayFlv_, curEvtDecayTime_ );
curEvtTagFlv_ = flavTag_->getCurEvtTagFlv();
curEvtMistag_ = flavTag_->getCurEvtMistag();
} else {
nGenLoop_++;
}
} while (generatedEvent == kFALSE && nGenLoop_ < iterationsMax_);
} else {
// Hist, Delta, Exp, DeltaExp decay-time types
// Since there are no oscillations for these decay-time types,
// the true decay flavour must be equal to the true tag flavour
// First choose the true tag and decay flavour, accounting for both the production and detection asymmetries
// CONVENTION WARNING regarding meaning of sign of AProd and ADet
const Double_t AProd { AProdBkgnd_[bkgndID]->unblindValue() };
const Double_t rateB { BkgndDPModelsB_[bkgndID]->getPdfNorm() };
const Double_t rateBbar { BkgndDPModelsBbar_[bkgndID]->getPdfNorm() };
const Double_t ADet { ( rateBbar - rateB ) / ( rateBbar + rateB ) };
const Double_t random = LauRandom::randomFun()->Rndm();
// TODO - is this the correct way to combine the production and detection asymmetries?
if ( random <= 0.5 * ( 1.0 - AProd ) * ( 1.0 - ADet ) ) {
curEvtDecayFlv_ = curEvtTrueTagFlv_ = LauFlavTag::Flavour::B;
} else {
curEvtDecayFlv_ = curEvtTrueTagFlv_ = LauFlavTag::Flavour::Bbar;
}
// generate the DP position
if ( curEvtDecayFlv_ == LauFlavTag::Flavour::B ) {
BkgndDPModelsB_[bkgndID]->generate();
kinematics = kinematicsB0_;
} else {
BkgndDPModelsBbar_[bkgndID]->generate();
kinematics = kinematicsB0bar_;
}
// generate decay time and its error
curEvtDecayTimeErr_ = BkgndDecayTimePdfs_[bkgndID]->generateError(kTRUE);
curEvtDecayTime_ = BkgndDecayTimePdfs_[bkgndID]->generate( kinematics );
// generate the flavour tagging information from the true tag and decay flavour
// (we do this after accepting the event to save time)
flavTag_->generateBkgndEventInfo( bkgndID, curEvtTrueTagFlv_, curEvtDecayFlv_, curEvtDecayTime_ );
curEvtTagFlv_ = flavTag_->getCurEvtTagFlv();
curEvtMistag_ = flavTag_->getCurEvtMistag();
}
break;
}
case LauFlavTag::BkgndType::SelfConjugate:
// TODO
break;
case LauFlavTag::BkgndType::NonSelfConjugate:
// TODO
break;
}
if ( genOK ) {
// Make sure both kinematics objects are up-to-date
kinematicsB0_->updateKinematics(kinematics->getm13Sq(), kinematics->getm23Sq() );
kinematicsB0bar_->updateKinematics(kinematics->getm13Sq(), kinematics->getm23Sq() );
this->generateExtraPdfValues(BkgndPdfs_[bkgndID], bkgndTree_[bkgndID]);
}
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 == "" ) {
std::cerr<<"ERROR in LauTimeDepFitModel::setupGenNtupleBranches : Decay flavour variable not set for QFS decay, see LauFlavTag::setDecayFlvVarName()."<<std::endl;
gSystem->Exit(EXIT_FAILURE);
} else {
this->addGenNtupleIntegerBranch(decayFlvVarName);
}
}
const std::vector<TString>& tagVarNames { flavTag_->getTagVarNames() };
const std::vector<TString>& mistagVarNames { flavTag_->getMistagVarNames() };
const std::size_t nTaggers {flavTag_->getNTaggers()};
for (std::size_t taggerID{0}; taggerID<nTaggers; ++taggerID){
this->addGenNtupleIntegerBranch(tagVarNames[taggerID]);
this->addGenNtupleDoubleBranch(mistagVarNames[taggerID]);
}
if (this->useDP() == kTRUE) {
// Let's add the decay time variables.
this->addGenNtupleDoubleBranch(signalDecayTimePdf_->varName());
if ( signalDecayTimePdf_->varErrName() != "" ) {
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_);
if ( signalDecayTimePdf_->varErrName() != "" ) {
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(LauPdfPList& 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->calcInterferenceTermNorm();
}
// 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 ) {
const Double_t bkgndEvents { 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(static_cast<std::size_t>(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
curEvtDecayFlv_ = LauFlavTag::Flavour::Unknown;
if (cpEigenValue_ == QFS){
curEvtDecayFlv_ = flavTag_->getCurEvtDecayFlv();
if ( curEvtDecayFlv_ == LauFlavTag::Flavour::B ) {
Abar.zero();
} else if ( curEvtDecayFlv_ == LauFlavTag::Flavour::Bbar ) {
A.zero();
} else {
std::cerr<<"ERROR in LauTimeDepFitModel::getEvtDPDtLikelihood : Decay flavour must be known for QFS decays."<<std::endl;
gSystem->Exit(EXIT_FAILURE);
}
}
// 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 std::size_t nTaggers { flavTag_->getNTaggers() };
for (std::size_t taggerID{0}; taggerID<nTaggers; ++taggerID){
omega *= flavTag_->getCapitalOmega(taggerID, LauFlavTag::Flavour::B);
omegabar *= flavTag_->getCapitalOmega(taggerID, 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 move to new function as getEvtBkgndLikelihoods?
const UInt_t nBkgnds = this->nBkgndClasses();
for ( UInt_t bkgndID(0); bkgndID < nBkgnds; ++bkgndID ) {
if ( not usingBkgnd_ ) {
bkgndDPLike_[bkgndID] = 0.0;
continue;
}
Double_t omegaBkgnd{1.0};
Double_t omegaBarBkgnd{1.0};
BkgndDecayTimePdfs_[bkgndID]->calcLikelihoodInfo(static_cast<std::size_t>(iEvt));
// Consider background type
switch ( BkgndTypes_[bkgndID] ) {
case LauFlavTag::BkgndType::Combinatorial :
{
// For combinatorial background the DP and decay-time models factorise completely, just mulitply them
// Start with the DP likelihood...
if ( (cpEigenValue_ == QFS) and BkgndDPModelsBbar_[bkgndID] != nullptr ) { //Flavour specific (with possible detection asymmetry)
// TODO - need to detect CP-eigenstate and two histos case in initialisation and abort since it doesn't make any sense
if ( curEvtDecayFlv_ == LauFlavTag::Flavour::B ) {
bkgndDPLike_[bkgndID] = BkgndDPModelsB_[bkgndID]->getUnNormValue(iEvt);
} else {
bkgndDPLike_[bkgndID] = BkgndDPModelsBbar_[bkgndID]->getUnNormValue(iEvt);
}
bkgndDPLike_[bkgndID] /= ( BkgndDPModelsB_[bkgndID]->getPdfNorm() + BkgndDPModelsBbar_[bkgndID]->getPdfNorm() );
} else {
// No detection asymmetry (could be QFS or CP-eigenstate - which implies slightly different normalisation)
bkgndDPLike_[bkgndID] = BkgndDPModelsB_[bkgndID]->getLikelihood(iEvt);
if ( cpEigenValue_ == QFS ) {
bkgndDPLike_[bkgndID] *= 0.5;
}
}
// ...include the decay time...
switch( BkgndDecayTimePdfs_[bkgndID]->getFuncType() ) {
case LauDecayTime::FuncType::Hist :
bkgndDPLike_[bkgndID] *= BkgndDecayTimePdfs_[bkgndID]->getHistTerm();
break;
case LauDecayTime::FuncType::Exp :
bkgndDPLike_[bkgndID] *= ( BkgndDecayTimePdfs_[bkgndID]->getExpTerm() / BkgndDecayTimePdfs_[bkgndID]->getNormTermExp() );
break;
// TODO - any other decay time function types that make sense for combinatorial?
// - should also have a set of checks in initialise that we have everything we need for the backgrounds and that the various settings make sense
default :
// TODO as per comment just above, once the above mentioned checks are implemented this error message can be removed
std::cerr << "WARNING in LauTimeDepFitModel::getEvtDPDtLikelihood : bkgnd types other than Hist and Exp don't make sense for combinatorial!" << std::endl;
break;
}
// ...include flavour tagging
for (std::size_t taggerID{0}; taggerID<nTaggers; ++taggerID){
// Only need omega==omegabar for combinatorial
omegaBkgnd *= flavTag_->getCapitalOmegaBkgnd(bkgndID, taggerID, LauFlavTag::Flavour::B, curEvtDecayFlv_);
}
bkgndDPLike_[bkgndID] *= omegaBkgnd;
break;
}
case LauFlavTag::BkgndType::FlavourSpecific :
{
// DP terms needed by all decay-time cases
Double_t Asq { BkgndDPModelsB_[bkgndID]->getUnNormValue(iEvt) };
Double_t Asqbar { BkgndDPModelsBbar_[bkgndID]->getUnNormValue(iEvt) };
if ( cpEigenValue_ == QFS ){
// If the signal is flavour-specific we can know which DP to use, so zero the other one
if ( curEvtDecayFlv_ == LauFlavTag::Flavour::B ) {
Asqbar = 0.0;
} else if ( curEvtDecayFlv_ == LauFlavTag::Flavour::Bbar ) {
Asq = 0.0;
}
}
const Double_t AsqSum { Asq + Asqbar };
// DP norm terms needed by all decay-time cases
const Double_t AsqNorm { BkgndDPModelsB_[bkgndID]->getPdfNorm() };
const Double_t AsqbarNorm { BkgndDPModelsBbar_[bkgndID]->getPdfNorm() };
const Double_t AsqNormSum { AsqNorm + AsqbarNorm };
// FT terms needed by all decay-time cases
omegaBkgnd = omegaBarBkgnd = 1.0;
for (std::size_t taggerID{0}; taggerID<nTaggers; ++taggerID){
omegaBkgnd *= flavTag_->getCapitalOmegaBkgnd(bkgndID, taggerID, LauFlavTag::Flavour::B, curEvtDecayFlv_);
omegaBarBkgnd *= flavTag_->getCapitalOmegaBkgnd(bkgndID, taggerID, LauFlavTag::Flavour::Bbar, curEvtDecayFlv_);
}
const Double_t AProd { AProdBkgnd_[bkgndID]->unblindValue() };
const Double_t ftOmegaHypBkgnd { (1.0 - AProd)*omegaBkgnd + (1.0 + AProd)*omegaBarBkgnd };
switch( BkgndDecayTimePdfs_[bkgndID]->getFuncType() )
{
case LauDecayTime::FuncType::Hist: // DP and decay-time still factorise
{
// Start with the DP terms...
bkgndDPLike_[bkgndID] = AsqSum / AsqNormSum;
// ...include the decay time...
bkgndDPLike_[bkgndID] *= BkgndDecayTimePdfs_[bkgndID]->getHistTerm();
// ...include flavour tagging
bkgndDPLike_[bkgndID] *= ( 0.5 * ftOmegaHypBkgnd );
break;
}
case LauDecayTime::FuncType::Exp : // DP and decay-time still factorise
{
// Start with the DP terms...
bkgndDPLike_[bkgndID] = AsqSum / AsqNormSum;
// ...include the decay time...
bkgndDPLike_[bkgndID] *= ( BkgndDecayTimePdfs_[bkgndID]->getExpTerm() / BkgndDecayTimePdfs_[bkgndID]->getNormTermExp() );
// ...include flavour tagging
bkgndDPLike_[bkgndID] *= ( 0.5 * ftOmegaHypBkgnd );
break;
}
case LauDecayTime::FuncType::ExpTrig: // DP and decay-time don't factorise
case LauDecayTime::FuncType::ExpHypTrig:
{
// DP and FT terms specific to this case
const Double_t AsqDiff { Asq - Asqbar };
const Double_t AsqNormDiff { AsqNorm - AsqbarNorm }; //TODO check this shouldn't be `fabs`ed
const Double_t ftOmegaTrigBkgnd { (1.0 - AProd)*omegaBkgnd - (1.0 + AProd)*omegaBarBkgnd };
// decay time terms
// Sin and Sinh terms are ignored: the FS modes can't exhibit TD CPV
const Double_t dtCoshBkgnd { BkgndDecayTimePdfs_[bkgndID]->getCoshTerm() };
const Double_t dtCosBkgnd { BkgndDecayTimePdfs_[bkgndID]->getCosTerm() };
const Double_t normCoshTermBkgnd { BkgndDecayTimePdfs_[bkgndID]->getNormTermCosh() };
const Double_t normCosTermBkgnd { BkgndDecayTimePdfs_[bkgndID]->getNormTermCos() };
// Combine the DP, FT, and decay time terms
const Double_t coshTermBkgnd { ftOmegaHypBkgnd * dtCoshBkgnd * AsqSum };
const Double_t cosTermBkgnd { ftOmegaTrigBkgnd * dtCosBkgnd * AsqDiff };
// Similarly for the normalisation, see Laura note eq. 41
const Double_t normBkgnd { 2.0 * ( (normCoshTermBkgnd * AsqNormSum) - AProd*(normCosTermBkgnd * AsqNormDiff) ) };
bkgndDPLike_[bkgndID] = (coshTermBkgnd + cosTermBkgnd) / normBkgnd;
break;
}
case LauDecayTime::FuncType::Delta:
case LauDecayTime::FuncType::DeltaExp:
// TODO as per comment above, once the checks in initialise are implemented this error message can be removed
std::cerr << "WARNING in LauTimeDepFitModel::getEvtDPDtLikelihood : bkgnd types Delta and DeltaExp don't make sense!" << std::endl;
break;
}
break;
}
case LauFlavTag::BkgndType::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;
case LauFlavTag::BkgndType::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 );
}
}
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;
}
}
}
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,
const Bool_t reuseEventsWithinEnsemble, const Bool_t reuseEventsWithinExperiment, const Bool_t useReweighting)
{
if (signalTree_) {
std::cerr<<"ERROR in LauTimeDepFitModel::embedSignal : Already embedding signal from file."<<std::endl;
return;
}
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;
useReweighting_ = useReweighting;
this->enableEmbedding(kTRUE);
}
void LauTimeDepFitModel::embedBkgnd(const TString& bkgndClass, const TString& fileName, const TString& treeName,
const Bool_t reuseEventsWithinEnsemble, const Bool_t reuseEventsWithinExperiment, const Bool_t useReweighting)
{
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;
useReweighting_ = useReweighting;
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 LauPdfPList& 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(LauPdfPList& 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);
LauPdfPList& 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*/)
{
}

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