Fitter class, entry point for performing all type of fits.

Fits are performed using the generic ROOT::Fit::Fitter::Fit method. The inputs are the data points and a model function (using a ROOT::Math::IParamFunction) The result of the fit is returned and kept internally in the ROOT::Fit::FitResult class. The configuration of the fit (parameters, options, etc...) are specified in the ROOT::Math::FitConfig class. After fitting the config of the fit will be modified to have the new values the resulting parameter of the fit with step sizes equal to the errors. FitConfig can be preserved with initial parameters by calling FitConfig.SetUpdateAfterFit(false);

Definition at line 77 of file Fitter.h.

Public Types
typedef ROOT::Math::IMultiGenFunction	BaseFunc

typedef ROOT::Math::IMultiGradFunction	BaseGradFunc

typedef ROOT::Math::IParamGradFunction	IGradModel1DFunction

typedef ROOT::Math::IParamMultiGradFunction	IGradModelFunction

typedef ROOT::Math::IParamMultiGradFunction	IGradModelFunction_v

typedef ROOT::Math::IParamFunction	IModel1DFunction

typedef ROOT::Math::IParamMultiFunction	IModelFunction

typedef ROOT::Math::IParamMultiFunction	IModelFunction_v

template<class T >
using	IModelFunctionTempl = ROOT::Math::IParamMultiFunctionTempl< T >

typedef void(*	MinuitFCN_t) (int &npar, double gin, double &f, double u, int flag)
	fit using user provided FCN with Minuit-like interface If npar = 0 it is assumed that the parameters are specified in the parameter settings created before For the options same consideration as in the previous method

Public Member Functions
	Fitter ()
	Default constructor.

	Fitter (const std::shared_ptr< FitResult > &result)
	Constructor from a result.

	~Fitter ()
	Destructor.

bool	ApplyWeightCorrection (const ROOT::Math::IMultiGenFunction &loglw2, bool minimizeW2L=false)
	apply correction in the error matrix for the weights for likelihood fits This method can be called only after a fit.

bool	CalculateHessErrors ()
	perform an error analysis on the result using the Hessian Errors are obtaied from the inverse of the Hessian matrix To be called only after fitting and when a minimizer supporting the Hessian calculations is used otherwise an error (false) is returned.

bool	CalculateMinosErrors ()
	perform an error analysis on the result using MINOS To be called only after fitting and when a minimizer supporting MINOS is used otherwise an error (false) is returned.

FitConfig &	Config ()
	access to the configuration (non const method)

const FitConfig &	Config () const
	access to the fit configuration (const method)

bool	EvalFCN ()
	Perform a simple FCN evaluation.

bool	Fit (const BinData &data, const ROOT::EExecutionPolicy &executionPolicy=ROOT::EExecutionPolicy::kSequential)
	Fit a binned data set using a least square fit (default method)

template<class Data , class Function , class cond = typename std::enable_if<!(std::is_same<Function, ROOT::EExecutionPolicy>::value \|\| std::is_same<Function, int>::value), Function>::type>
bool	Fit (const Data &data, const Function &func, const ROOT::EExecutionPolicy &executionPolicy=ROOT::EExecutionPolicy::kSequential)
	fit a data set using any generic model function If data set is binned a least square fit is performed If data set is unbinned a maximum likelihood fit (not extended) is done Pre-requisite on the function: it must implement the 1D or multidimensional parametric function interface

bool	Fit (const std::shared_ptr< BinData > &data, const ROOT::EExecutionPolicy &executionPolicy=ROOT::EExecutionPolicy::kSequential)

bool	Fit (const UnBinData &data, bool extended=false, const ROOT::EExecutionPolicy &executionPolicy=ROOT::EExecutionPolicy::kSequential)
	fit an unbinned data set using loglikelihood method

bool	FitFCN ()
	Perform a fit with the previously set FCN function.

bool	FitFCN (const ROOT::Math::FitMethodFunction &fcn, const double *params=0)
	Fit using a FitMethodFunction interface.

bool	FitFCN (const ROOT::Math::FitMethodGradFunction &fcn, const double *params=0)
	Fit using a FitMethodGradFunction interface.

bool	FitFCN (const ROOT::Math::IMultiGenFunction &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false)
	Fit using the given FCN function represented by a multi-dimensional function interface (ROOT::Math::IMultiGenFunction).

bool	FitFCN (const ROOT::Math::IMultiGradFunction &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false)
	Fit using the given FCN function representing a multi-dimensional gradient function interface (ROOT::Math::IMultiGradFunction).

bool	FitFCN (MinuitFCN_t fcn, int npar=0, const double *params=0, unsigned int dataSize=0, bool chi2fit=false)

template<class Function >
bool	FitFCN (unsigned int npar, Function &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false)
	Fit using the a generic FCN function as a C++ callable object implementing double () (const double *) Note that the function dimension (i.e.

ROOT::Math::IMultiGenFunction *	GetFCN () const
	return pointer to last used objective function (is NULL in case fit is not yet done) This pointer will be valid as far as the fitter class has not been deleted.

ROOT::Math::Minimizer *	GetMinimizer () const
	return pointer to last used minimizer (is NULL in case fit is not yet done) This pointer is guranteed to be valid as far as the fitter class is valid and a new fit is not redone.

bool	IsBinFit () const
	query if fit is binned.

bool	LeastSquareFit (const BinData &data)
	Fit a binned data set using a least square fit.

bool	LikelihoodFit (const BinData &data, bool extended=true, const ROOT::EExecutionPolicy &executionPolicy=ROOT::EExecutionPolicy::kSequential)
	Binned Likelihood fit.

template<class Data , class Function >
bool	LikelihoodFit (const Data &data, const Function &func, bool extended)
	fit a data set using any generic model function Pre-requisite on the function:

bool	LikelihoodFit (const std::shared_ptr< BinData > &data, bool extended=true, const ROOT::EExecutionPolicy &executionPolicy=ROOT::EExecutionPolicy::kSequential)

bool	LikelihoodFit (const std::shared_ptr< UnBinData > &data, bool extended=false, const ROOT::EExecutionPolicy &executionPolicy=ROOT::EExecutionPolicy::kSequential)

bool	LikelihoodFit (const UnBinData &data, bool extended=false, const ROOT::EExecutionPolicy &executionPolicy=ROOT::EExecutionPolicy::kSequential)
	Unbinned Likelihood fit.

bool	LinearFit (const BinData &data)
	do a linear fit on a set of bin-data

bool	LinearFit (const std::shared_ptr< BinData > &data)

const FitResult &	Result () const
	get fit result

bool	SetFCN (const ROOT::Math::FitMethodFunction &fcn, const double *params=0)
	Set the objective function (FCN) using a FitMethodFunction interface.

bool	SetFCN (const ROOT::Math::FitMethodGradFunction &fcn, const double *params=0)
	Set the objective function (FCN) using a FitMethodGradFunction interface.

bool	SetFCN (const ROOT::Math::IMultiGenFunction &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false)
	Set the FCN function represented by a multi-dimensional function interface (ROOT::Math::IMultiGenFunction) and optionally the initial parameters See also note above for the initial parameters for FitFCN.

bool	SetFCN (const ROOT::Math::IMultiGenFunction &fcn, const IModelFunction &func, const double *params=0, unsigned int dataSize=0, bool chi2fit=false)
	Set the FCN function represented by a multi-dimensional function interface (ROOT::Math::IMultiGenFunction) and optionally the initial parameters See also note above for the initial parameters for FitFCN With this interface we pass in addition a ModelFunction that will be attached to the FitResult and used to compute confidence interval of the fit.

bool	SetFCN (const ROOT::Math::IMultiGradFunction &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false)
	Set the FCN function represented by a multi-dimensional gradient function interface (ROOT::Math::IMultiGradFunction) and optionally the initial parameters See also note above for the initial parameters for FitFCN.

bool	SetFCN (const ROOT::Math::IMultiGradFunction &fcn, const IModelFunction &func, const double *params=0, unsigned int dataSize=0, bool chi2fit=false)
	Set the FCN function represented by a multi-dimensional gradient function interface (ROOT::Math::IMultiGradFunction) and optionally the initial parameters See also note above for the initial parameters for FitFCN With this interface we pass in addition a ModelFunction that will be attached to the FitResult and used to compute confidence interval of the fit.

bool	SetFCN (MinuitFCN_t fcn, int npar=0, const double *params=0, unsigned int dataSize=0, bool chi2fit=false)
	set objective function using user provided FCN with Minuit-like interface If npar = 0 it is assumed that the parameters are specified in the parameter settings created before For the options same consideration as in the previous method

template<class Function >
bool	SetFCN (unsigned int npar, Function &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false)
	Set a generic FCN function as a C++ callable object implementing double () (const double *) Note that the function dimension (i.e.

void	SetFunction (const IGradModel1DFunction &func, bool useGradient=true)
	Set the fitted function from 1D gradient parametric function interface.

void	SetFunction (const IGradModelFunction &func, bool useGradient=true)
	Set the fitted function (model function) from a parametric gradient function interface.

void	SetFunction (const IModel1DFunction &func, bool useGradient=false)
	Set the fitted function (model function) from a vectorized parametric function interface.

void	SetFunction (const IModelFunction &func, bool useGradient=false)
	Set the fitted function (model function) from a parametric function interface.

Protected Member Functions
bool	DoBinnedLikelihoodFit (bool extended=true, const ROOT::EExecutionPolicy &executionPolicy=ROOT::EExecutionPolicy::kSequential)
	binned likelihood fit

bool	DoInitMinimizer ()

bool	DoLeastSquareFit (const ROOT::EExecutionPolicy &executionPolicy=ROOT::EExecutionPolicy::kSequential)
	least square fit

bool	DoLinearFit ()
	linear least square fit

bool	DoMinimization (const BaseFunc &f, const ROOT::Math::IMultiGenFunction *chifunc=0)
	do minimization

bool	DoMinimization (const ROOT::Math::IMultiGenFunction *chifunc=0)

bool	DoUnbinnedLikelihoodFit (bool extended=false, const ROOT::EExecutionPolicy &executionPolicy=ROOT::EExecutionPolicy::kSequential)
	un-binned likelihood fit

void	DoUpdateFitConfig ()

bool	DoUpdateMinimizerOptions (bool canDifferentMinim=true)

void	ExamineFCN ()
	look at the user provided FCN and get data and model function is they derive from ROOT::Fit FCN classes

template<class ObjFuncType >
bool	GetDataFromFCN ()
	internal functions to get data set and model function from FCN useful for fits done with customized FCN classes

int	GetNCallsFromFCN ()

void	SetData (const FitData &data)

template<class Data >
void	SetData (const std::shared_ptr< Data > &data)

template<class T >
void	SetFunctionAndData (const IModelFunctionTempl< T > &func, const FitData &data)

Private Member Functions
	Fitter (const Fitter &)
	Copy constructor (disabled, class is not copyable)

Fitter &	operator= (const Fitter &rhs)
	Assignment operator (disabled, class is not copyable)

Private Attributes
bool	fBinFit

FitConfig	fConfig

std::shared_ptr< ROOT::Fit::FitData >	fData
	pointer to used minimizer

int	fDataSize

int	fFitType

std::shared_ptr< IModelFunction >	fFunc
	copy of the fitted function containing on output the fit result

std::shared_ptr< IModelFunction_v >	fFunc_v

std::shared_ptr< ROOT::Math::Minimizer >	fMinimizer
	pointer to the object containing the result of the fit

std::shared_ptr< ROOT::Math::IMultiGenFunction >	fObjFunction
	pointer to the fit data (binned or unbinned data)

std::shared_ptr< ROOT::Fit::FitResult >	fResult
	copy of the fitted function containing on output the fit result

bool	fUseGradient

#include <Fit/Fitter.h>

Member Typedef Documentation

◆ BaseFunc

typedef ROOT::Math::IMultiGenFunction ROOT::Fit::Fitter::BaseFunc

Definition at line 95 of file Fitter.h.

◆ BaseGradFunc

typedef ROOT::Math::IMultiGradFunction ROOT::Fit::Fitter::BaseGradFunc

Definition at line 96 of file Fitter.h.

◆ IGradModel1DFunction

typedef ROOT::Math::IParamGradFunction ROOT::Fit::Fitter::IGradModel1DFunction

Definition at line 93 of file Fitter.h.

◆ IGradModelFunction

typedef ROOT::Math::IParamMultiGradFunction ROOT::Fit::Fitter::IGradModelFunction

Definition at line 91 of file Fitter.h.

◆ IGradModelFunction_v

typedef ROOT::Math::IParamMultiGradFunction ROOT::Fit::Fitter::IGradModelFunction_v

Definition at line 89 of file Fitter.h.

◆ IModel1DFunction

typedef ROOT::Math::IParamFunction ROOT::Fit::Fitter::IModel1DFunction

Definition at line 92 of file Fitter.h.

◆ IModelFunction

typedef ROOT::Math::IParamMultiFunction ROOT::Fit::Fitter::IModelFunction

Definition at line 81 of file Fitter.h.

◆ IModelFunction_v

typedef ROOT::Math::IParamMultiFunction ROOT::Fit::Fitter::IModelFunction_v

Definition at line 88 of file Fitter.h.

◆ IModelFunctionTempl

template<class T >

using ROOT::Fit::Fitter::IModelFunctionTempl = ROOT::Math::IParamMultiFunctionTempl<T>

Definition at line 83 of file Fitter.h.

◆ MinuitFCN_t

typedef void(* ROOT::Fit::Fitter::MinuitFCN_t) (int &npar, double *gin, double &f, double *u, int flag)

fit using user provided FCN with Minuit-like interface If npar = 0 it is assumed that the parameters are specified in the parameter settings created before For the options same consideration as in the previous method

Definition at line 329 of file Fitter.h.

Constructor & Destructor Documentation

◆ Fitter() [1/3]

ROOT::Fit::Fitter::Fitter ( )

Default constructor.

Definition at line 51 of file Fitter.cxx.

◆ Fitter() [2/3]

ROOT::Fit::Fitter::Fitter ( const std::shared_ptr< FitResult > & result )

Constructor from a result.

Definition at line 58 of file Fitter.cxx.

◆ ~Fitter()

ROOT::Fit::Fitter::~Fitter ( )

Destructor.

Definition at line 70 of file Fitter.cxx.

◆ Fitter() [3/3]

ROOT::Fit::Fitter::Fitter ( const Fitter & rhs )

private

Copy constructor (disabled, class is not copyable)

Definition at line 77 of file Fitter.cxx.

Member Function Documentation

◆ ApplyWeightCorrection()

bool ROOT::Fit::Fitter::ApplyWeightCorrection	(	const ROOT::Math::IMultiGenFunction &	loglw2,
		bool	minimizeW2L = `false`
	)

apply correction in the error matrix for the weights for likelihood fits This method can be called only after a fit.

The passed function (loglw2) is a log-likelihood function impelemented using the sum of weight squared When using FitConfig.SetWeightCorrection() this correction is applied automatically when doing a likelihood fit (binned or unbinned)

Definition at line 981 of file Fitter.cxx.

◆ CalculateHessErrors()

bool ROOT::Fit::Fitter::CalculateHessErrors ( )

perform an error analysis on the result using the Hessian Errors are obtaied from the inverse of the Hessian matrix To be called only after fitting and when a minimizer supporting the Hessian calculations is used otherwise an error (false) is returned.

A new FitResult with the Hessian result will be produced

Definition at line 655 of file Fitter.cxx.

◆ CalculateMinosErrors()

bool ROOT::Fit::Fitter::CalculateMinosErrors ( )

perform an error analysis on the result using MINOS To be called only after fitting and when a minimizer supporting MINOS is used otherwise an error (false) is returned.

The result will be appended in the fit result class Optionally a vector of parameter indeces can be passed for selecting the parameters to analyse using FitConfig::SetMinosErrors

Definition at line 731 of file Fitter.cxx.

◆ Config() [1/2]

FitConfig & ROOT::Fit::Fitter::Config ( )

inline

access to the configuration (non const method)

Definition at line 417 of file Fitter.h.

◆ Config() [2/2]

const FitConfig & ROOT::Fit::Fitter::Config ( ) const

inline

access to the fit configuration (const method)

Definition at line 412 of file Fitter.h.

◆ DoBinnedLikelihoodFit()

bool ROOT::Fit::Fitter::DoBinnedLikelihoodFit	(	bool	extended = `true`,
		const ROOT::EExecutionPolicy &	executionPolicy = `ROOT::EExecutionPolicy::kSequential`
	)

protected

binned likelihood fit

Definition at line 424 of file Fitter.cxx.

◆ DoInitMinimizer()

bool ROOT::Fit::Fitter::DoInitMinimizer ( )

protected

Definition at line 827 of file Fitter.cxx.

◆ DoLeastSquareFit()

bool ROOT::Fit::Fitter::DoLeastSquareFit ( const ROOT::EExecutionPolicy & executionPolicy = ROOT::EExecutionPolicy::kSequential )

protected

least square fit

Definition at line 365 of file Fitter.cxx.

◆ DoLinearFit()

bool ROOT::Fit::Fitter::DoLinearFit ( )

protected

linear least square fit

Definition at line 638 of file Fitter.cxx.

◆ DoMinimization() [1/2]

bool ROOT::Fit::Fitter::DoMinimization	(	const BaseFunc &	f,
		const ROOT::Math::IMultiGenFunction *	chifunc = `0`
	)

protected

do minimization

Definition at line 944 of file Fitter.cxx.

◆ DoMinimization() [2/2]

bool ROOT::Fit::Fitter::DoMinimization ( const ROOT::Math::IMultiGenFunction * chifunc = 0 )

protected

Definition at line 901 of file Fitter.cxx.

◆ DoUnbinnedLikelihoodFit()

bool ROOT::Fit::Fitter::DoUnbinnedLikelihoodFit	(	bool	extended = `false`,
		const ROOT::EExecutionPolicy &	executionPolicy = `ROOT::EExecutionPolicy::kSequential`
	)

protected

un-binned likelihood fit

Definition at line 533 of file Fitter.cxx.

◆ DoUpdateFitConfig()

void ROOT::Fit::Fitter::DoUpdateFitConfig ( )

protected

Definition at line 955 of file Fitter.cxx.

◆ DoUpdateMinimizerOptions()

bool ROOT::Fit::Fitter::DoUpdateMinimizerOptions ( bool canDifferentMinim = true )

protected

Definition at line 869 of file Fitter.cxx.

◆ EvalFCN()

bool ROOT::Fit::Fitter::EvalFCN ( )

Perform a simple FCN evaluation.

FitResult will be modified and contain the value of the FCN

Definition at line 344 of file Fitter.cxx.

◆ ExamineFCN()

void ROOT::Fit::Fitter::ExamineFCN ( )

protected

look at the user provided FCN and get data and model function is they derive from ROOT::Fit FCN classes

Definition at line 1088 of file Fitter.cxx.

◆ Fit() [1/4]

bool ROOT::Fit::Fitter::Fit	(	const BinData &	data,
		const ROOT::EExecutionPolicy &	executionPolicy = `ROOT::EExecutionPolicy::kSequential`
	)

inline

Fit a binned data set using a least square fit (default method)

Definition at line 151 of file Fitter.h.

◆ Fit() [2/4]

template<class Data , class Function , class cond = typename std::enable_if<!(std::is_same<Function, ROOT::EExecutionPolicy>::value || std::is_same<Function, int>::value), Function>::type>

bool ROOT::Fit::Fitter::Fit	(	const Data &	data,
		const Function &	func,
		const ROOT::EExecutionPolicy &	executionPolicy = `ROOT::EExecutionPolicy::kSequential`
	)

inline

fit a data set using any generic model function If data set is binned a least square fit is performed If data set is unbinned a maximum likelihood fit (not extended) is done Pre-requisite on the function: it must implement the 1D or multidimensional parametric function interface

Definition at line 141 of file Fitter.h.

◆ Fit() [3/4]

bool ROOT::Fit::Fitter::Fit	(	const std::shared_ptr< BinData > &	data,
		const ROOT::EExecutionPolicy &	executionPolicy = `ROOT::EExecutionPolicy::kSequential`
	)

inline

Definition at line 155 of file Fitter.h.

◆ Fit() [4/4]

bool ROOT::Fit::Fitter::Fit	(	const UnBinData &	data,
		bool	extended = `false`,
		const ROOT::EExecutionPolicy &	executionPolicy = `ROOT::EExecutionPolicy::kSequential`
	)

inline

fit an unbinned data set using loglikelihood method

Definition at line 170 of file Fitter.h.

◆ FitFCN() [1/7]

bool ROOT::Fit::Fitter::FitFCN ( )

Perform a fit with the previously set FCN function.

Require SetFCN before

Definition at line 326 of file Fitter.cxx.

◆ FitFCN() [2/7]

bool ROOT::Fit::Fitter::FitFCN	(	const ROOT::Math::FitMethodFunction &	fcn,
		const double *	params = `0`
	)

Fit using a FitMethodFunction interface.

Same as method above, but now extra information can be taken from the function class

Definition at line 283 of file Fitter.cxx.

◆ FitFCN() [3/7]

bool ROOT::Fit::Fitter::FitFCN	(	const ROOT::Math::FitMethodGradFunction &	fcn,
		const double *	params = `0`
	)

Fit using a FitMethodGradFunction interface.

Same as method above, but now extra information can be taken from the function class

◆ FitFCN() [4/7]

bool ROOT::Fit::Fitter::FitFCN	(	const ROOT::Math::IMultiGenFunction &	fcn,
		const double *	params = `0`,
		unsigned int	dataSize = `0`,
		bool	chi2fit = `false`
	)

Fit using the given FCN function represented by a multi-dimensional function interface (ROOT::Math::IMultiGenFunction).

Give optionally the initial arameter values, data size to have the fit Ndf correctly set in the FitResult and flag specifying if it is a chi2 fit. Note that if the parameters values are not given (params=0) the current parameter settings are used. The parameter settings can be created before by using the FitConfig::SetParamsSetting. If they have not been created they are created automatically when the params pointer is not zero. Note that passing a params != 0 will set the parameter settings to the new value AND also the step sizes to some pre-defined value (stepsize = 0.3 * abs(parameter_value) )

Definition at line 265 of file Fitter.cxx.

◆ FitFCN() [5/7]

bool ROOT::Fit::Fitter::FitFCN	(	const ROOT::Math::IMultiGradFunction &	fcn,
		const double *	params = `0`,
		unsigned int	dataSize = `0`,
		bool	chi2fit = `false`
	)

Fit using the given FCN function representing a multi-dimensional gradient function interface (ROOT::Math::IMultiGradFunction).

In this case the minimizer will use the gradient information provided by the function. For the options same consideration as in the previous method

Definition at line 274 of file Fitter.cxx.

◆ FitFCN() [6/7]

bool ROOT::Fit::Fitter::FitFCN	(	MinuitFCN_t	fcn,
		int	npar = `0`,
		const double *	params = `0`,
		unsigned int	dataSize = `0`,
		bool	chi2fit = `false`
	)

Definition at line 316 of file Fitter.cxx.

◆ FitFCN() [7/7]

template<class Function >

bool ROOT::Fit::Fitter::FitFCN	(	unsigned int	npar,
		Function &	fcn,
		const double *	params = `0`,
		unsigned int	dataSize = `0`,
		bool	chi2fit = `false`
	)

Fit using the a generic FCN function as a C++ callable object implementing double () (const double *) Note that the function dimension (i.e.

the number of parameter) is needed in this case For the options see documentation for following methods FitFCN(IMultiGenFunction & fcn,..)

Definition at line 610 of file Fitter.h.

◆ GetDataFromFCN()

template<class ObjFuncType >

bool ROOT::Fit::Fitter::GetDataFromFCN

protected

internal functions to get data set and model function from FCN useful for fits done with customized FCN classes

Definition at line 544 of file Fitter.h.

◆ GetFCN()

ROOT::Math::IMultiGenFunction * ROOT::Fit::Fitter::GetFCN ( ) const

inline

return pointer to last used objective function (is NULL in case fit is not yet done) This pointer will be valid as far as the fitter class has not been deleted.

To be used after the fitting. The pointer should not be stored and will be invalided after performing a new fitting. In this case a new instance of the function pointer will be re-created and can be obtained calling again GetFCN()

Definition at line 445 of file Fitter.h.

◆ GetMinimizer()

ROOT::Math::Minimizer * ROOT::Fit::Fitter::GetMinimizer ( ) const

inline

return pointer to last used minimizer (is NULL in case fit is not yet done) This pointer is guranteed to be valid as far as the fitter class is valid and a new fit is not redone.

To be used only after fitting. The pointer should not be stored and will be invalided after performing a new fitting. In this case a new instance of ROOT::Math::Minimizer will be re-created and can be obtained calling again GetMinimizer()

Definition at line 434 of file Fitter.h.

◆ GetNCallsFromFCN()

int ROOT::Fit::Fitter::GetNCallsFromFCN ( )

protected

Definition at line 965 of file Fitter.cxx.

◆ IsBinFit()

bool ROOT::Fit::Fitter::IsBinFit ( ) const

inline

query if fit is binned.

In cse of false teh fit can be unbinned or is not defined (like in case of fitting through a FitFCN)

Definition at line 423 of file Fitter.h.

◆ LeastSquareFit()

bool ROOT::Fit::Fitter::LeastSquareFit ( const BinData & data )

inline

Fit a binned data set using a least square fit.

Definition at line 163 of file Fitter.h.

◆ LikelihoodFit() [1/5]

bool ROOT::Fit::Fitter::LikelihoodFit	(	const BinData &	data,
		bool	extended = `true`,
		const ROOT::EExecutionPolicy &	executionPolicy = `ROOT::EExecutionPolicy::kSequential`
	)

inline

Binned Likelihood fit.

Default is extended

Definition at line 178 of file Fitter.h.

◆ LikelihoodFit() [2/5]

template<class Data , class Function >

bool ROOT::Fit::Fitter::LikelihoodFit	(	const Data &	data,
		const Function &	func,
		bool	extended
	)

inline

fit a data set using any generic model function Pre-requisite on the function:

Definition at line 207 of file Fitter.h.

◆ LikelihoodFit() [3/5]

bool ROOT::Fit::Fitter::LikelihoodFit	(	const std::shared_ptr< BinData > &	data,
		bool	extended = `true`,
		const ROOT::EExecutionPolicy &	executionPolicy = `ROOT::EExecutionPolicy::kSequential`
	)

inline

Definition at line 184 of file Fitter.h.

◆ LikelihoodFit() [4/5]

bool ROOT::Fit::Fitter::LikelihoodFit	(	const std::shared_ptr< UnBinData > &	data,
		bool	extended = `false`,
		const ROOT::EExecutionPolicy &	executionPolicy = `ROOT::EExecutionPolicy::kSequential`
	)

inline

Definition at line 196 of file Fitter.h.

◆ LikelihoodFit() [5/5]

bool ROOT::Fit::Fitter::LikelihoodFit	(	const UnBinData &	data,
		bool	extended = `false`,
		const ROOT::EExecutionPolicy &	executionPolicy = `ROOT::EExecutionPolicy::kSequential`
	)

inline

Unbinned Likelihood fit.

Default is not extended

Definition at line 192 of file Fitter.h.

◆ LinearFit() [1/2]

bool ROOT::Fit::Fitter::LinearFit ( const BinData & data )

inline

do a linear fit on a set of bin-data

Definition at line 215 of file Fitter.h.

◆ LinearFit() [2/2]

bool ROOT::Fit::Fitter::LinearFit ( const std::shared_ptr< BinData > & data )

inline

Definition at line 219 of file Fitter.h.

◆ operator=()

Fitter & ROOT::Fit::Fitter::operator= ( const Fitter & rhs )

private

Assignment operator (disabled, class is not copyable)

Definition at line 84 of file Fitter.cxx.

◆ Result()

const FitResult & ROOT::Fit::Fitter::Result ( ) const

inline

get fit result

Definition at line 384 of file Fitter.h.

◆ SetData() [1/2]

void ROOT::Fit::Fitter::SetData ( const FitData & data )

inlineprotected

Definition at line 485 of file Fitter.h.

◆ SetData() [2/2]

template<class Data >

void ROOT::Fit::Fitter::SetData ( const std::shared_ptr< Data > & data )

inlineprotected

Definition at line 497 of file Fitter.h.

◆ SetFCN() [1/8]

bool ROOT::Fit::Fitter::SetFCN	(	const ROOT::Math::FitMethodFunction &	fcn,
		const double *	params = `0`
	)

Set the objective function (FCN) using a FitMethodFunction interface.

Same as method above, but now extra information can be taken from the function class

Definition at line 241 of file Fitter.cxx.

◆ SetFCN() [2/8]

bool ROOT::Fit::Fitter::SetFCN	(	const ROOT::Math::FitMethodGradFunction &	fcn,
		const double *	params = `0`
	)

Set the objective function (FCN) using a FitMethodGradFunction interface.

Same as method above, but now extra information can be taken from the function class

◆ SetFCN() [3/8]

bool ROOT::Fit::Fitter::SetFCN	(	const ROOT::Math::IMultiGenFunction &	fcn,
		const double *	params = `0`,
		unsigned int	dataSize = `0`,
		bool	chi2fit = `false`
	)

Set the FCN function represented by a multi-dimensional function interface (ROOT::Math::IMultiGenFunction) and optionally the initial parameters See also note above for the initial parameters for FitFCN.

Definition at line 181 of file Fitter.cxx.

◆ SetFCN() [4/8]

bool ROOT::Fit::Fitter::SetFCN	(	const ROOT::Math::IMultiGenFunction &	fcn,
		const IModelFunction &	func,
		const double *	params = `0`,
		unsigned int	dataSize = `0`,
		bool	chi2fit = `false`
	)

Set the FCN function represented by a multi-dimensional function interface (ROOT::Math::IMultiGenFunction) and optionally the initial parameters See also note above for the initial parameters for FitFCN With this interface we pass in addition a ModelFunction that will be attached to the FitResult and used to compute confidence interval of the fit.

Definition at line 213 of file Fitter.cxx.

◆ SetFCN() [5/8]

bool ROOT::Fit::Fitter::SetFCN	(	const ROOT::Math::IMultiGradFunction &	fcn,
		const double *	params = `0`,
		unsigned int	dataSize = `0`,
		bool	chi2fit = `false`
	)

Set the FCN function represented by a multi-dimensional gradient function interface (ROOT::Math::IMultiGradFunction) and optionally the initial parameters See also note above for the initial parameters for FitFCN.

Definition at line 221 of file Fitter.cxx.

◆ SetFCN() [6/8]

bool ROOT::Fit::Fitter::SetFCN	(	const ROOT::Math::IMultiGradFunction &	fcn,
		const IModelFunction &	func,
		const double *	params = `0`,
		unsigned int	dataSize = `0`,
		bool	chi2fit = `false`
	)

Set the FCN function represented by a multi-dimensional gradient function interface (ROOT::Math::IMultiGradFunction) and optionally the initial parameters See also note above for the initial parameters for FitFCN With this interface we pass in addition a ModelFunction that will be attached to the FitResult and used to compute confidence interval of the fit.

Definition at line 232 of file Fitter.cxx.

◆ SetFCN() [7/8]

bool ROOT::Fit::Fitter::SetFCN	(	MinuitFCN_t	fcn,
		int	npar = `0`,
		const double *	params = `0`,
		unsigned int	dataSize = `0`,
		bool	chi2fit = `false`
	)

set objective function using user provided FCN with Minuit-like interface If npar = 0 it is assumed that the parameters are specified in the parameter settings created before For the options same consideration as in the previous method

Definition at line 299 of file Fitter.cxx.

◆ SetFCN() [8/8]

template<class Function >

bool ROOT::Fit::Fitter::SetFCN	(	unsigned int	npar,
		Function &	fcn,
		const double *	params = `0`,
		unsigned int	dataSize = `0`,
		bool	chi2fit = `false`
	)

Set a generic FCN function as a C++ callable object implementing double () (const double *) Note that the function dimension (i.e.

the number of parameter) is needed in this case For the options see documentation for following methods FitFCN(IMultiGenFunction & fcn,..)

Definition at line 615 of file Fitter.h.

◆ SetFunction() [1/4]

void ROOT::Fit::Fitter::SetFunction	(	const IGradModel1DFunction &	func,
		bool	useGradient = `true`
	)

Set the fitted function from 1D gradient parametric function interface.

Definition at line 168 of file Fitter.cxx.

◆ SetFunction() [2/4]

void ROOT::Fit::Fitter::SetFunction	(	const IGradModelFunction &	func,
		bool	useGradient = `true`
	)

Set the fitted function (model function) from a parametric gradient function interface.

Definition at line 154 of file Fitter.cxx.

◆ SetFunction() [3/4]

void ROOT::Fit::Fitter::SetFunction	(	const IModel1DFunction &	func,
		bool	useGradient = `false`
	)

Set the fitted function (model function) from a vectorized parametric function interface.

Set the fitted function from a parametric 1D function interface

Definition at line 130 of file Fitter.cxx.

◆ SetFunction() [4/4]

void ROOT::Fit::Fitter::SetFunction	(	const IModelFunction &	func,
		bool	useGradient = `false`
	)

Set the fitted function (model function) from a parametric function interface.

Definition at line 103 of file Fitter.cxx.

◆ SetFunctionAndData()

template<class T >

void ROOT::Fit::Fitter::SetFunctionAndData	(	const IModelFunctionTempl< T > &	func,
		const FitData &	data
	)

inlineprotected

Definition at line 490 of file Fitter.h.

Member Data Documentation

◆ fBinFit

bool ROOT::Fit::Fitter::fBinFit

private

Definition at line 516 of file Fitter.h.

◆ fConfig

FitConfig ROOT::Fit::Fitter::fConfig

private

Definition at line 524 of file Fitter.h.

◆ fData

std::shared_ptr<ROOT::Fit::FitData> ROOT::Fit::Fitter::fData

private

pointer to used minimizer

Definition at line 534 of file Fitter.h.

◆ fDataSize

int ROOT::Fit::Fitter::fDataSize

private

Definition at line 522 of file Fitter.h.

◆ fFitType

int ROOT::Fit::Fitter::fFitType

private

Definition at line 520 of file Fitter.h.

◆ fFunc

std::shared_ptr<IModelFunction> ROOT::Fit::Fitter::fFunc

private

copy of the fitted function containing on output the fit result

Definition at line 528 of file Fitter.h.

◆ fFunc_v

std::shared_ptr<IModelFunction_v> ROOT::Fit::Fitter::fFunc_v

private

Definition at line 526 of file Fitter.h.

◆ fMinimizer

std::shared_ptr<ROOT::Math::Minimizer> ROOT::Fit::Fitter::fMinimizer

private

pointer to the object containing the result of the fit

Definition at line 532 of file Fitter.h.

◆ fObjFunction

std::shared_ptr<ROOT::Math::IMultiGenFunction> ROOT::Fit::Fitter::fObjFunction

private

pointer to the fit data (binned or unbinned data)

Definition at line 536 of file Fitter.h.

◆ fResult

std::shared_ptr<ROOT::Fit::FitResult> ROOT::Fit::Fitter::fResult

private

copy of the fitted function containing on output the fit result

Definition at line 530 of file Fitter.h.

◆ fUseGradient

bool ROOT::Fit::Fitter::fUseGradient

private

Definition at line 514 of file Fitter.h.

Libraries for ROOT::Fit::Fitter:

[legend]

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

math/mathcore/inc/Fit/Fitter.h
math/mathcore/src/Fitter.cxx

Public Types

Public Member Functions

Protected Member Functions

Private Member Functions

Private Attributes

Member Typedef Documentation

◆ BaseFunc

◆ BaseGradFunc

◆ IGradModel1DFunction

◆ IGradModelFunction

◆ IGradModelFunction_v

◆ IModel1DFunction

◆ IModelFunction

◆ IModelFunction_v

◆ IModelFunctionTempl

◆ MinuitFCN_t

Constructor & Destructor Documentation

◆ Fitter() [1/3]

◆ Fitter() [2/3]

◆ ~Fitter()

◆ Fitter() [3/3]

Member Function Documentation

◆ ApplyWeightCorrection()

◆ CalculateHessErrors()

◆ CalculateMinosErrors()

◆ Config() [1/2]

◆ Config() [2/2]

◆ DoBinnedLikelihoodFit()

◆ DoInitMinimizer()

◆ DoLeastSquareFit()

◆ DoLinearFit()

◆ DoMinimization() [1/2]

◆ DoMinimization() [2/2]

◆ DoUnbinnedLikelihoodFit()

◆ DoUpdateFitConfig()

◆ DoUpdateMinimizerOptions()

◆ EvalFCN()

◆ ExamineFCN()

◆ Fit() [1/4]

◆ Fit() [2/4]

◆ Fit() [3/4]

◆ Fit() [4/4]

◆ FitFCN() [1/7]

◆ FitFCN() [2/7]

◆ FitFCN() [3/7]

◆ FitFCN() [4/7]

◆ FitFCN() [5/7]

◆ FitFCN() [6/7]

◆ FitFCN() [7/7]

◆ GetDataFromFCN()

◆ GetFCN()

◆ GetMinimizer()

◆ GetNCallsFromFCN()

◆ IsBinFit()

◆ LeastSquareFit()

◆ LikelihoodFit() [1/5]

◆ LikelihoodFit() [2/5]

◆ LikelihoodFit() [3/5]

◆ LikelihoodFit() [4/5]

◆ LikelihoodFit() [5/5]

◆ LinearFit() [1/2]

◆ LinearFit() [2/2]

◆ operator=()

◆ Result()

◆ SetData() [1/2]

◆ SetData() [2/2]

◆ SetFCN() [1/8]

◆ SetFCN() [2/8]

◆ SetFCN() [3/8]

◆ SetFCN() [4/8]

◆ SetFCN() [5/8]

◆ SetFCN() [6/8]

◆ SetFCN() [7/8]

◆ SetFCN() [8/8]

◆ SetFunction() [1/4]

◆ SetFunction() [2/4]

◆ SetFunction() [3/4]

◆ SetFunction() [4/4]

◆ SetFunctionAndData()

Member Data Documentation