Tool for conducting profile likelihood fit. More...

#include "NAGASH/ProfileFitter.h"

Inheritance diagram for NAGASH::ProfileFitter:

Classes
class	Observable

class	Parameter

class	PLH_FCN

class	ProfileCache

Public Types
enum class	FitMethod { ProfileLikelihood , AnalyticalChiSquare , AnalyticalBoostedProfileLikelihood }

enum class	ParameterType { Nuisance , Interest , StatGamma , Normalization , Unknown }
	Type of the parameter. More...

Public Member Functions
	ProfileFitter (std::shared_ptr< MSGTool > msg, int nthread=1)

void	BookNormalizationParameter (TString name, double init, double min, double max)

void	BookNuisanceParameter (TString name)

void	BookNuisanceParameter (TString name, TString gname)

void	BookObservableData (TString name, const std::vector< double > &vec, const std::vector< double > &vec_stat)

void	BookObservableNominal (TString name, TString samplename, const std::vector< double > &vec, const std::vector< double > &vec_stat)

void	BookObservableVariation (TString name, TString samplename, const std::vector< double > &vec, TString parname, double sigma)

void	BookObservableVariationDown (TString name, TString samplename, const std::vector< double > &vec, TString parname)

void	BookObservableVariationFromUnc (TString name, TString samplename, const std::vector< double > &vec, const std::vector< double > &vec_unc, TString parname)

void	BookObservableVariationNominal (TString name, TString samplename, const std::vector< double > &vec, TString parname)

void	BookObservableVariationUp (TString name, TString samplename, const std::vector< double > &vec, TString parname)

void	BookParameter (TString name, double init, double min, double max, ParameterType type)

void	BookParameterOfInterest (TString name, double init, double min, double max)

std::map< TString, double >	EstimateUnc (const std::vector< TString > &par_vec, FitMethod method, int toy_num)
	Estimate uncertainty decomposition using toy method.

std::map< TString, double >	EstimateUnc (TString g_name, FitMethod method, int toy_num)
	Estimate uncertainty decomposition using toy method.

void	Fit (FitMethod method)

void	FixParameter (TString name, double val)

double	GetChi2 ()

double	GetChi2 (const std::map< TString, double > &par_val)

int	GetNParameters (ParameterType type=ParameterType::Unknown)

Parameter *	GetParameter (TString name)

TString	GetParameterName (int index)

void	LinkNormalizationSample (TString name, TString samplename)

void	RebinObservable (TString name, int index)

void	ReleaseParameter (TString name)

void	SetGammaPrefix (TString samplename, TString prefix)

void	SetObservableRange (TString name, int start, int end)

void	SetParameterGroup (TString gname, TString parname)

void	SetParameterStrategy (TString name, Parameter::ExtrapStrategy str)

void	SetSmooth (TString obsname, TString samplename, TString parname, int slevel)

void	SetSymmetrization (TString obsname, TString samplename, TString parname, bool need=true)

void	SmoothVariation (std::vector< double > &var, std::vector< double > &norm, int level)

void	SymmetrizeVariation (std::vector< double > &up, std::vector< double > &down, std::vector< double > &norm)

Private Member Functions
bool	Check ()

void	FitACS ()

void	FitPLH ()

Observable *	InitializeNewObservable (TString name)

void	Prepare (FitMethod method)

void	PrintInfo ()

void	PrintResult ()

Private Attributes
Eigen::MatrixXd	C_Matrix

Eigen::MatrixXd	Epsilon_Matrix

std::map< TString, std::vector< TString > >	Gamma_Map

Eigen::MatrixXd	Gamma_Matrix

Eigen::MatrixXd	H_Matrix

Eigen::MatrixXd	Lambda_Matrix

double	MAX_NUISANCE_SIGMA = 3.0

std::map< TString, std::vector< TString > >	Norm_Map

int	NTHREAD = 1

Eigen::MatrixXd	Nuisance_Cov_Matrix

Parameter::ExtrapStrategy	NUISANCE_DEFAULT_STRATEGY = Parameter::ExtrapStrategy::POLY6EXP

Eigen::MatrixXd	Nuisance_Shift

std::map< TString, Observable >	Obs_Map

std::map< TString, Parameter >	Par_Map

std::map< TString, std::vector< TString > >	ParGroup_Map

Eigen::MatrixXd	POI_Cov_Matrix

Parameter::ExtrapStrategy	POI_DEFAULT_STRATEGY = Parameter::ExtrapStrategy::FULLLINEAR

Eigen::MatrixXd	POI_Shift

std::shared_ptr< ThreadPool >	pool = nullptr

Eigen::MatrixXd	Q_Matrix

Eigen::MatrixXd	Rho_Matrix

Eigen::MatrixXd	S_Matrix

Eigen::MatrixXd	V_Matrix

Eigen::MatrixXd	Y0_Matrix

Additional Inherited Members
Protected Member Functions inherited from NAGASH::Tool
	Tool ()=delete

	Tool (const Tool &tool)=delete

	Tool (std::shared_ptr< MSGTool > MSG)
	Constructor.

	Tool (Tool &&tool)=delete

virtual	~Tool ()=default

std::shared_ptr< MSGTool >	MSGUser ()
	return the MSGTool inside.

Tool &	operator= (const Tool &tool)=delete

Tool &	operator= (Tool &&tool)=delete

Detailed Description

Tool for conducting profile likelihood fit.

Here is an example on how to use this tool:

#include "NAGASH/NAGASH.h"
 
using namespace NAGASH;
 
int main(int argc, char *argv[])
{
    // this is a demo to show how to use NAGASH::ProfileFitter
    // here is a two signal model with data, mc simulation signal, bkg and systematic variation
    // the goal is to fit the signal strength for the two signals.
    std::vector<double> DataContent{66794, 214244, 145599, 62531, 18430};
    std::vector<double> DataError{258.445, 462.865, 381.574, 250.062, 135.757};
    std::vector<double> SignalOneContent{12252.9, 47435.4, 45553.5, 21592.8, 5953.28};
    std::vector<double> SignalOneError{383.36, 728.494, 648.582, 430.871, 213.435};
    std::vector<double> SignalTwoContent{50357, 129318, 40142.3, 7079.96, 1415.54};
    std::vector<double> SignalTwoError{2727.81, 4637.69, 2361.29, 903.572, 339.72};
    std::vector<double> BkgContent{10429.1, 43201.2, 47754.4, 24940.8, 7688.81};
    std::vector<double> BkgError{234.322, 447.727, 328.898, 189.348, 102.708};
 
    std::vector<double> SignalOneVarUp{12963.3, 48982.9, 45909.3, 21290.4, 5756.26};
    std::vector<double> SignalOneVarDown{11930.7, 46005.3, 44797.4, 21799.6, 6084.36};
    std::vector<double> SignalTwoVarUp{52079.1, 134586, 40431.5, 7105.3, 1322.69};
    std::vector<double> SignalTwoVarDown{49602.8, 126769, 39258.1, 7002.01, 1317.11};
    std::vector<double> BkgVarUp{10394.3, 42322.9, 46049.8, 24141.7, 7412.09};
    std::vector<double> BkgVarDown{10583.3, 44078.9, 48915.4, 25655.8, 7976.2};
 
    // construct tool
    auto msg = std::make_shared<MSGTool>();
    auto guard = msg->StartTitleWithGuard("Profile Fitter Test");
    auto PLHFitter = std::make_shared<ProfileFitter>(msg);
 
    // signal strength for two signals
    PLHFitter->BookParameterOfInterest("sf1", 1, 0.5, 2);
    PLHFitter->BookParameterOfInterest("sf2", 1, 0.5, 2);
 
    // nominal values
    PLHFitter->BookObservableData("dist", DataContent, DataError);
    PLHFitter->BookObservableNominal("dist", "SignalOne", SignalOneContent, SignalOneError);
    PLHFitter->BookObservableNominal("dist", "SignalTwo", SignalTwoContent, SignalTwoError);
    PLHFitter->BookObservableNominal("dist", "Bkg", BkgContent, BkgError);
 
    // book poi variations
    std::vector<double> SignalOneSFUp(5);
    std::vector<double> SignalOneSFDown(5);
    std::transform(SignalOneContent.begin(), SignalOneContent.end(), SignalOneSFUp.begin(), [](double x)
                { return x * 1.1; });
    std::transform(SignalOneContent.begin(), SignalOneContent.end(), SignalOneSFDown.begin(), [](double x)
                { return x * 0.9; });
 
    PLHFitter->BookObservableVariation("dist", "SignalOne", SignalOneSFUp, "sf1", 1.1);
    PLHFitter->BookObservableVariation("dist", "SignalOne", SignalOneSFDown, "sf1", 0.9);
 
    std::vector<double> SignalTwoSFUp(5);
    std::vector<double> SignalTwoSFDown(5);
    std::transform(SignalTwoContent.begin(), SignalTwoContent.end(), SignalTwoSFUp.begin(), [](double x)
                { return x * 1.1; });
    std::transform(SignalTwoContent.begin(), SignalTwoContent.end(), SignalTwoSFDown.begin(), [](double x)
                { return x * 0.9; });
 
    PLHFitter->BookObservableVariation("dist", "SignalTwo", SignalTwoSFUp, "sf2", 1.1);
    PLHFitter->BookObservableVariation("dist", "SignalTwo", SignalTwoSFDown, "sf2", 0.9);
 
    // book systematic variation
    PLHFitter->BookNuisanceParameter("var");
    PLHFitter->BookObservableVariationNominal("dist", "SignalOne", SignalOneContent, "var");
    PLHFitter->BookObservableVariationNominal("dist", "SignalTwo", SignalTwoContent, "var");
    PLHFitter->BookObservableVariationNominal("dist", "Bkg", BkgContent, "var");
 
    PLHFitter->BookObservableVariationUp("dist", "SignalOne", SignalOneVarUp, "var");
    PLHFitter->BookObservableVariationUp("dist", "SignalTwo", SignalTwoVarUp, "var");
    PLHFitter->BookObservableVariationUp("dist", "Bkg", BkgVarUp, "var");
 
    PLHFitter->BookObservableVariationDown("dist", "SignalOne", SignalOneVarDown, "var");
    PLHFitter->BookObservableVariationDown("dist", "SignalTwo", SignalTwoVarDown, "var");
    PLHFitter->BookObservableVariationDown("dist", "Bkg", BkgVarDown, "var");
 
    // start to fit
    PLHFitter->SetObservableRange("dist", 0, 4);
    PLHFitter->SetGammaPrefix("SignalOne", "SignalOne");
    PLHFitter->SetGammaPrefix("SignalTwo", "SignalTwo");
    PLHFitter->SetGammaPrefix("Bkg", "Bkg");
 
    PLHFitter->Fit(ProfileFitter::FitMethod::ProfileLikelihood);
 
    msg->MSG_INFO(PLHFitter->GetParameter("sf1")->Value, " ", PLHFitter->GetParameter("sf1")->Error);
    msg->MSG_INFO(PLHFitter->GetParameter("sf2")->Value, " ", PLHFitter->GetParameter("sf2")->Error);
 
    // get systematic uncertainty
    auto uncmap = PLHFitter->EstimateUnc(std::vector<TString>{"var"}, ProfileFitter::FitMethod::AnalyticalChiSquare, 100);
    msg->MSG_INFO(uncmap.find("sf1")->second, " ", uncmap.find("sf2")->second);
 
    return -1;
}

Definition at line 29 of file ProfileFitter.h.

Member Enumeration Documentation

◆ FitMethod

enum class NAGASH::ProfileFitter::FitMethod

strong

Enumerator
ProfileLikelihood	Traditional profile likelihood.
AnalyticalChiSquare	Analytical method, described in https://arxiv.org/abs/2307.04007, very fast.
AnalyticalBoostedProfileLikelihood	use analytical method first, then run profile likelihood fit on top of it.

Definition at line 41 of file ProfileFitter.h.

◆ ParameterType

enum class NAGASH::ProfileFitter::ParameterType

strong

Type of the parameter.

Enumerator
Nuisance	Nuisance parameter.
Interest	POI.
StatGamma	Statistical Gamma, used to represent the statistical uncertainties.
Normalization	Normalization parameter.
Unknown

Definition at line 33 of file ProfileFitter.h.

Constructor & Destructor Documentation

◆ ProfileFitter()

ProfileFitter::ProfileFitter	(	std::shared_ptr< MSGTool >	msg,
		int	nthread = `1`
	)

Definition at line 113 of file ProfileFitter.cxx.

Member Function Documentation

◆ BookNormalizationParameter()

void NAGASH::ProfileFitter::BookNormalizationParameter	(	TString	name,
		double	init,
		double	min,
		double	max
	)

inline

Definition at line 314 of file ProfileFitter.h.

◆ BookNuisanceParameter() [1/2]

void NAGASH::ProfileFitter::BookNuisanceParameter ( TString name )

inline

Definition at line 324 of file ProfileFitter.h.

◆ BookNuisanceParameter() [2/2]

void NAGASH::ProfileFitter::BookNuisanceParameter	(	TString	name,
		TString	gname
	)

inline

Definition at line 328 of file ProfileFitter.h.

◆ BookObservableData()

void ProfileFitter::BookObservableData	(	TString	name,
		const std::vector< double > &	vec,
		const std::vector< double > &	vec_stat
	)

Definition at line 153 of file ProfileFitter.cxx.

◆ BookObservableNominal()

void ProfileFitter::BookObservableNominal	(	TString	name,
		TString	samplename,
		const std::vector< double > &	vec,
		const std::vector< double > &	vec_stat
	)

Definition at line 181 of file ProfileFitter.cxx.

◆ BookObservableVariation()

void ProfileFitter::BookObservableVariation	(	TString	name,
		TString	samplename,
		const std::vector< double > &	vec,
		TString	parname,
		double	sigma
	)

Definition at line 261 of file ProfileFitter.cxx.

◆ BookObservableVariationDown()

void NAGASH::ProfileFitter::BookObservableVariationDown	(	TString	name,
		TString	samplename,
		const std::vector< double > &	vec,
		TString	parname
	)

inline

Definition at line 224 of file ProfileFitter.h.

◆ BookObservableVariationFromUnc()

void ProfileFitter::BookObservableVariationFromUnc	(	TString	name,
		TString	samplename,
		const std::vector< double > &	vec,
		const std::vector< double > &	vec_unc,
		TString	parname
	)

Definition at line 411 of file ProfileFitter.cxx.

◆ BookObservableVariationNominal()

void NAGASH::ProfileFitter::BookObservableVariationNominal	(	TString	name,
		TString	samplename,
		const std::vector< double > &	vec,
		TString	parname
	)

inline

Definition at line 216 of file ProfileFitter.h.

◆ BookObservableVariationUp()

void NAGASH::ProfileFitter::BookObservableVariationUp	(	TString	name,
		TString	samplename,
		const std::vector< double > &	vec,
		TString	parname
	)

inline

Definition at line 220 of file ProfileFitter.h.

◆ BookParameter()

void ProfileFitter::BookParameter	(	TString	name,
		double	init,
		double	min,
		double	max,
		ParameterType	type
	)

Definition at line 123 of file ProfileFitter.cxx.

◆ BookParameterOfInterest()

void NAGASH::ProfileFitter::BookParameterOfInterest	(	TString	name,
		double	init,
		double	min,
		double	max
	)

inline

Definition at line 319 of file ProfileFitter.h.

◆ Check()

bool ProfileFitter::Check ( )

private

Definition at line 574 of file ProfileFitter.cxx.

◆ EstimateUnc() [1/2]

std::map< TString, double > ProfileFitter::EstimateUnc	(	const std::vector< TString > &	par_vec,
		FitMethod	method,
		int	toy_num
	)

Estimate uncertainty decomposition using toy method.

Parameters

par_vec	vector of parameter names.
method	fit method, ProfileFitter::FitMethod::AnalyticalChiSquare is recommanded for its performance.
toy_num	number of toy models.

Returns: a map of parameter names and their uncertainties.

Definition at line 1828 of file ProfileFitter.cxx.

◆ EstimateUnc() [2/2]

std::map< TString, double > ProfileFitter::EstimateUnc	(	TString	g_name,
		FitMethod	method,
		int	toy_num
	)

Estimate uncertainty decomposition using toy method.

Parameters

g_name	name of the parameter group.
method	fit method, ProfileFitter::FitMethod::AnalyticalChiSquare is recommanded for its performance.
toy_num	number of toy models.

Returns: a map of parameter names and their uncertainties.

Definition at line 1808 of file ProfileFitter.cxx.

◆ Fit()

void ProfileFitter::Fit ( ProfileFitter::FitMethod method )

Definition at line 471 of file ProfileFitter.cxx.

◆ FitACS()

void ProfileFitter::FitACS ( )

private

Definition at line 1171 of file ProfileFitter.cxx.

◆ FitPLH()

void ProfileFitter::FitPLH ( )

private

Definition at line 1348 of file ProfileFitter.cxx.

◆ FixParameter()

void NAGASH::ProfileFitter::FixParameter	(	TString	name,
		double	val
	)

inline

Definition at line 301 of file ProfileFitter.h.

◆ GetChi2() [1/2]

double ProfileFitter::GetChi2 ( )

Definition at line 1912 of file ProfileFitter.cxx.

◆ GetChi2() [2/2]

double ProfileFitter::GetChi2 ( const std::map< TString, double > & par_val )

Definition at line 1936 of file ProfileFitter.cxx.

◆ GetNParameters()

int ProfileFitter::GetNParameters ( ParameterType type = ParameterType::Unknown )

Definition at line 807 of file ProfileFitter.cxx.

◆ GetParameter()

ProfileFitter::Parameter * ProfileFitter::GetParameter ( TString name )

Definition at line 249 of file ProfileFitter.cxx.

◆ GetParameterName()

TString ProfileFitter::GetParameterName ( int index )

Definition at line 820 of file ProfileFitter.cxx.

◆ InitializeNewObservable()

ProfileFitter::Observable * ProfileFitter::InitializeNewObservable ( TString name )

private

Definition at line 452 of file ProfileFitter.cxx.

◆ LinkNormalizationSample()

void ProfileFitter::LinkNormalizationSample	(	TString	name,
		TString	samplename
	)

Definition at line 1587 of file ProfileFitter.cxx.

◆ Prepare()

void ProfileFitter::Prepare ( ProfileFitter::FitMethod method )

private

Definition at line 580 of file ProfileFitter.cxx.

◆ PrintInfo()

void ProfileFitter::PrintInfo ( )

private

Definition at line 534 of file ProfileFitter.cxx.

◆ PrintResult()

void ProfileFitter::PrintResult ( )

private

Definition at line 498 of file ProfileFitter.cxx.

◆ RebinObservable()

void ProfileFitter::RebinObservable	(	TString	name,
		int	index
	)

Definition at line 1691 of file ProfileFitter.cxx.

◆ ReleaseParameter()

void NAGASH::ProfileFitter::ReleaseParameter ( TString name )

inline

Definition at line 308 of file ProfileFitter.h.

◆ SetGammaPrefix()

void ProfileFitter::SetGammaPrefix	(	TString	samplename,
		TString	prefix
	)

Definition at line 1546 of file ProfileFitter.cxx.

◆ SetObservableRange()

void ProfileFitter::SetObservableRange	(	TString	name,
		int	start,
		int	end
	)

Definition at line 1709 of file ProfileFitter.cxx.

◆ SetParameterGroup()

void ProfileFitter::SetParameterGroup	(	TString	gname,
		TString	parname
	)

Definition at line 1782 of file ProfileFitter.cxx.

◆ SetParameterStrategy()

void NAGASH::ProfileFitter::SetParameterStrategy	(	TString	name,
		Parameter::ExtrapStrategy	str
	)

inline

Definition at line 232 of file ProfileFitter.h.

◆ SetSmooth()

void ProfileFitter::SetSmooth	(	TString	obsname,
		TString	samplename,
		TString	parname,
		int	slevel
	)

Definition at line 1755 of file ProfileFitter.cxx.

◆ SetSymmetrization()

void ProfileFitter::SetSymmetrization	(	TString	obsname,
		TString	samplename,
		TString	parname,
		bool	need = `true`
	)

Definition at line 1728 of file ProfileFitter.cxx.

◆ SmoothVariation()

void ProfileFitter::SmoothVariation	(	std::vector< double > &	var,
		std::vector< double > &	norm,
		int	level
	)

Definition at line 1651 of file ProfileFitter.cxx.

◆ SymmetrizeVariation()

void ProfileFitter::SymmetrizeVariation	(	std::vector< double > &	up,
		std::vector< double > &	down,
		std::vector< double > &	norm
	)

Definition at line 1631 of file ProfileFitter.cxx.

Member Data Documentation

◆ C_Matrix

Eigen::MatrixXd NAGASH::ProfileFitter::C_Matrix

private

Definition at line 285 of file ProfileFitter.h.

◆ Epsilon_Matrix

Eigen::MatrixXd NAGASH::ProfileFitter::Epsilon_Matrix

private

Definition at line 290 of file ProfileFitter.h.

◆ Gamma_Map

std::map<TString, std::vector<TString> > NAGASH::ProfileFitter::Gamma_Map

private

Definition at line 260 of file ProfileFitter.h.

◆ Gamma_Matrix

Eigen::MatrixXd NAGASH::ProfileFitter::Gamma_Matrix

private

Definition at line 281 of file ProfileFitter.h.

◆ H_Matrix

Eigen::MatrixXd NAGASH::ProfileFitter::H_Matrix

private

Definition at line 286 of file ProfileFitter.h.

◆ Lambda_Matrix

Eigen::MatrixXd NAGASH::ProfileFitter::Lambda_Matrix

private

Definition at line 288 of file ProfileFitter.h.

◆ MAX_NUISANCE_SIGMA

double NAGASH::ProfileFitter::MAX_NUISANCE_SIGMA = 3.0

private

Definition at line 267 of file ProfileFitter.h.

◆ Norm_Map

std::map<TString, std::vector<TString> > NAGASH::ProfileFitter::Norm_Map

private

Definition at line 261 of file ProfileFitter.h.

◆ NTHREAD

int NAGASH::ProfileFitter::NTHREAD = 1

private

Definition at line 265 of file ProfileFitter.h.

◆ Nuisance_Cov_Matrix

Eigen::MatrixXd NAGASH::ProfileFitter::Nuisance_Cov_Matrix

private

Definition at line 296 of file ProfileFitter.h.

◆ NUISANCE_DEFAULT_STRATEGY

Parameter::ExtrapStrategy NAGASH::ProfileFitter::NUISANCE_DEFAULT_STRATEGY = Parameter::ExtrapStrategy::POLY6EXP

private

Definition at line 270 of file ProfileFitter.h.

◆ Nuisance_Shift

Eigen::MatrixXd NAGASH::ProfileFitter::Nuisance_Shift

private

Definition at line 293 of file ProfileFitter.h.

◆ Obs_Map

std::map<TString, Observable> NAGASH::ProfileFitter::Obs_Map

private

Definition at line 259 of file ProfileFitter.h.

◆ Par_Map

std::map<TString, Parameter> NAGASH::ProfileFitter::Par_Map

private

Definition at line 258 of file ProfileFitter.h.

◆ ParGroup_Map

std::map<TString, std::vector<TString> > NAGASH::ProfileFitter::ParGroup_Map

private

Definition at line 262 of file ProfileFitter.h.

◆ POI_Cov_Matrix

Eigen::MatrixXd NAGASH::ProfileFitter::POI_Cov_Matrix

private

Definition at line 295 of file ProfileFitter.h.

◆ POI_DEFAULT_STRATEGY

Parameter::ExtrapStrategy NAGASH::ProfileFitter::POI_DEFAULT_STRATEGY = Parameter::ExtrapStrategy::FULLLINEAR

private

Definition at line 269 of file ProfileFitter.h.

◆ POI_Shift

Eigen::MatrixXd NAGASH::ProfileFitter::POI_Shift

private

Definition at line 292 of file ProfileFitter.h.

◆ pool

std::shared_ptr<ThreadPool> NAGASH::ProfileFitter::pool = nullptr

private

Definition at line 264 of file ProfileFitter.h.

◆ Q_Matrix

Eigen::MatrixXd NAGASH::ProfileFitter::Q_Matrix

private

Definition at line 283 of file ProfileFitter.h.

◆ Rho_Matrix

Eigen::MatrixXd NAGASH::ProfileFitter::Rho_Matrix

private

Definition at line 289 of file ProfileFitter.h.

◆ S_Matrix

Eigen::MatrixXd NAGASH::ProfileFitter::S_Matrix

private

Definition at line 284 of file ProfileFitter.h.

◆ V_Matrix

Eigen::MatrixXd NAGASH::ProfileFitter::V_Matrix

private

Definition at line 282 of file ProfileFitter.h.

◆ Y0_Matrix

Eigen::MatrixXd NAGASH::ProfileFitter::Y0_Matrix

private

Definition at line 287 of file ProfileFitter.h.

The documentation for this class was generated from the following files:

include/NAGASH/ProfileFitter.h
src/ProfileFitter.cxx

Classes

Public Types

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Member Enumeration Documentation

◆ FitMethod

◆ ParameterType

Constructor & Destructor Documentation

◆ ProfileFitter()

Member Function Documentation

◆ BookNormalizationParameter()

◆ BookNuisanceParameter() [1/2]

◆ BookNuisanceParameter() [2/2]

◆ BookObservableData()

◆ BookObservableNominal()

◆ BookObservableVariation()

◆ BookObservableVariationDown()

◆ BookObservableVariationFromUnc()

◆ BookObservableVariationNominal()

◆ BookObservableVariationUp()

◆ BookParameter()

◆ BookParameterOfInterest()

◆ Check()

◆ EstimateUnc() [1/2]

◆ EstimateUnc() [2/2]

◆ Fit()

◆ FitACS()

◆ FitPLH()

◆ FixParameter()

◆ GetChi2() [1/2]

◆ GetChi2() [2/2]

◆ GetNParameters()

◆ GetParameter()

◆ GetParameterName()

◆ InitializeNewObservable()

◆ LinkNormalizationSample()

◆ Prepare()

◆ PrintInfo()

◆ PrintResult()

◆ RebinObservable()

◆ ReleaseParameter()

◆ SetGammaPrefix()

◆ SetObservableRange()

◆ SetParameterGroup()

◆ SetParameterStrategy()

◆ SetSmooth()

◆ SetSymmetrization()

◆ SmoothVariation()

◆ SymmetrizeVariation()

Member Data Documentation

◆ C_Matrix

◆ Epsilon_Matrix

◆ Gamma_Map

◆ Gamma_Matrix

◆ H_Matrix

◆ Lambda_Matrix

◆ MAX_NUISANCE_SIGMA

◆ Norm_Map

◆ NTHREAD

◆ Nuisance_Cov_Matrix

◆ NUISANCE_DEFAULT_STRATEGY

◆ Nuisance_Shift

◆ Obs_Map

◆ Par_Map

◆ ParGroup_Map

◆ POI_Cov_Matrix

◆ POI_DEFAULT_STRATEGY

◆ POI_Shift

◆ pool

◆ Q_Matrix

◆ Rho_Matrix

◆ S_Matrix

◆ V_Matrix

◆ Y0_Matrix