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 94 of file Fitter.h.

Public Types
typedef ROOT::Math::IParamMultiFunction	IModelFunction

typedef ROOT::Math::IParamMultiGradFunction	IGradModelFunction

typedef ROOT::Math::IParamFunction	IModel1DFunction

typedef ROOT::Math::IParamGradFunction	IGradModel1DFunction

typedef ROOT::Math::IMultiGenFunction	BaseFunc

typedef ROOT::Math::IMultiGradFunction	BaseGradFunc

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 More...

Public Member Functions
	Fitter ()
	Default constructor. More...

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

	~Fitter ()
	Destructor. More...

template<class Data , class Function >
bool	Fit (const Data &data, const Function &func)
	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 More...

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

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

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

bool	Fit (const UnBinData &data, bool extended=false)
	fit an unbinned data set using loglikelihood method More...

bool	LikelihoodFit (const BinData &data, bool extended=true)
	Binned Likelihood fit. More...

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

bool	LikelihoodFit (const UnBinData &data, bool extended=false)
	Unbinned Likelihood fit. More...

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

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: More...

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

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

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. More...

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. More...

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). More...

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

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. More...

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

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). More...

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

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::IMultiGenFunction) and optionally the initial parameters See also note above for the initial parameters for FitFCN. More...

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

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

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 More...

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

bool	EvalFCN ()
	Perform a simple FCN evaluation. More...

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

void	SetFunction (const IModel1DFunction &func, bool useGradient=false)
	Set the fitted function from a parametric 1D function interface. More...

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

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

const FitResult &	Result () const
	get fit result More...

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. More...

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. More...

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

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

bool	IsBinFit () const
	query if fit is binned. More...

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. More...

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. More...

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. More...

Protected Member Functions
bool	DoLeastSquareFit ()
	least square fit More...

bool	DoBinnedLikelihoodFit (bool extended=true)
	binned likelihood fit More...

bool	DoUnbinnedLikelihoodFit (bool extended=false)
	un-binned likelihood fit More...

bool	DoLinearFit ()
	linear least square fit More...

bool	DoInitMinimizer ()

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

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

void	DoUpdateFitConfig ()

int	GetNCallsFromFCN ()

void	SetData (const FitData &data)

void	SetFunctionAndData (const IModelFunction &func, const FitData &data)

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

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

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

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

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

Private Attributes
bool	fUseGradient

bool	fBinFit

int	fFitType

int	fDataSize

FitConfig	fConfig

std::shared_ptr< IModelFunction >	fFunc

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

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

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

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

#include <Fit/Fitter.h>

Collaboration diagram for ROOT::Fit::Fitter:

Member Typedef Documentation

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

Definition at line 103 of file Fitter.h.

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

Definition at line 104 of file Fitter.h.

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

Definition at line 101 of file Fitter.h.

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

Definition at line 99 of file Fitter.h.

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

Definition at line 100 of file Fitter.h.

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

Definition at line 98 of file Fitter.h.

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 310 of file Fitter.h.

Constructor & Destructor Documentation

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

Default constructor.

Definition at line 47 of file Fitter.cxx.

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

Constructor from a result.

Definition at line 54 of file Fitter.cxx.

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

Destructor.

Definition at line 66 of file Fitter.cxx.

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

private

Copy constructor (disabled, class is not copyable)

Definition at line 73 of file Fitter.cxx.

Member Function Documentation

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 777 of file Fitter.cxx.

Referenced by DoBinnedLikelihoodFit(), and DoUnbinnedLikelihoodFit().

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 518 of file Fitter.cxx.

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 594 of file Fitter.cxx.

Referenced by TFractionFitter::ErrorAnalysis().

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

inline

access to the fit configuration (const method)

Definition at line 382 of file Fitter.h.

Referenced by TFractionFitter::Constrain(), DoBinFit(), DoFit(), DoLeastSquareFit(), DoUnBinFit(), DoUnBinFitVec(), DoUnbinnedLikelihoodFit(), TFractionFitter::ErrorAnalysis(), TBinomialEfficiencyFitter::Fit(), fit2DHist(), fit3DHist(), testHisto1DFit(), testHisto1DPolFit(), testHisto2DFit(), testUnBin1DFit(), TFractionFitter::TFractionFitter(), and TFractionFitter::UnConstrain().

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

inline

access to the configuration (non const method)

Definition at line 387 of file Fitter.h.

bool ROOT::Fit::Fitter::DoBinnedLikelihoodFit ( bool extended = true )

protected

binned likelihood fit

Definition at line 364 of file Fitter.cxx.

Referenced by LikelihoodFit().

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

protected

Definition at line 659 of file Fitter.cxx.

Referenced by ApplyWeightCorrection(), CalculateHessErrors(), DoMinimization(), and FitFCN().

bool ROOT::Fit::Fitter::DoLeastSquareFit ( )

protected

least square fit

Definition at line 323 of file Fitter.cxx.

Referenced by DoLinearFit(), and Fit().

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

protected

linear least square fit

Definition at line 501 of file Fitter.cxx.

Referenced by LinearFit().

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

protected

do minimization

Definition at line 740 of file Fitter.cxx.

Referenced by DoBinnedLikelihoodFit(), DoLeastSquareFit(), DoUnbinnedLikelihoodFit(), and FitFCN().

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

protected

Definition at line 702 of file Fitter.cxx.

bool ROOT::Fit::Fitter::DoUnbinnedLikelihoodFit ( bool extended = false )

protected

un-binned likelihood fit

Definition at line 434 of file Fitter.cxx.

Referenced by Fit(), and LikelihoodFit().

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

protected

Definition at line 751 of file Fitter.cxx.

Referenced by CalculateHessErrors(), and DoMinimization().

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

Perform a simple FCN evaluation.

FitResult will be modified and contain the value of the FCN

Definition at line 303 of file Fitter.cxx.

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 884 of file Fitter.cxx.

Referenced by FitFCN().

template<class Data , class Function >

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

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 146 of file Fitter.h.

Referenced by DoBinFit(), DoFit(), DoUnBinFit(), LeastSquareFit(), testGraphFit(), testHisto1DFit(), testHisto1DPolFit(), testHisto2DFit(), and testUnBin1DFit().

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

inline

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

Definition at line 154 of file Fitter.h.

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

inline

Definition at line 158 of file Fitter.h.

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

inline

fit an unbinned data set using loglikelihood method

Definition at line 173 of file Fitter.h.

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 538 of file Fitter.h.

Referenced by DoUnBinFitVec(), TFractionFitter::Fit(), and TBinomialEfficiencyFitter::Fit().

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 232 of file Fitter.cxx.

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 248 of file Fitter.cxx.

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 241 of file Fitter.cxx.

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

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 277 of file Fitter.cxx.

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

Perform a fit with the previously set FCN function.

Require SetFCN before

Definition at line 285 of file Fitter.cxx.

Referenced by FitFCN().

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 510 of file Fitter.h.

Referenced by ExamineFCN().

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 415 of file Fitter.h.

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 404 of file Fitter.h.

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

protected

Definition at line 761 of file Fitter.cxx.

Referenced by CalculateHessErrors(), and DoMinimization().

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 393 of file Fitter.h.

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

inline

Fit a binned data set using a least square fit.

Definition at line 166 of file Fitter.h.

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

inline

Binned Likelihood fit.

Default is extended

Definition at line 181 of file Fitter.h.

Referenced by DoFit(), fit2DHist(), fit3DHist(), LikelihoodFit(), testHisto1DFit(), and testHisto2DFit().

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

inline

Definition at line 185 of file Fitter.h.

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

inline

Unbinned Likelihood fit.

Default is not extended

Definition at line 192 of file Fitter.h.

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

inline

Definition at line 196 of file Fitter.h.

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.

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.

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

inline

Definition at line 219 of file Fitter.h.

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

private

Assignment operator (disabled, class is not copyable)

Definition at line 80 of file Fitter.cxx.

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

inline

get fit result

Definition at line 354 of file Fitter.h.

Referenced by DoBinFit(), DoFit(), DoUnBinFit(), DoUnBinFitVec(), TFractionFitter::ErrorAnalysis(), TFractionFitter::Fit(), TBinomialEfficiencyFitter::Fit(), fit2DHist(), fit3DHist(), TFractionFitter::GetPlot(), TFractionFitter::GetResult(), testGraphFit(), testHisto1DFit(), testHisto1DPolFit(), testHisto2DFit(), and testUnBin1DFit().

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

inlineprotected

Definition at line 454 of file Fitter.h.

Referenced by Fit(), LikelihoodFit(), LinearFit(), and SetFunctionAndData().

template<class Data >

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

inlineprotected

Definition at line 465 of file Fitter.h.

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 543 of file Fitter.h.

Referenced by TFractionFitter::Fit(), TBinomialEfficiencyFitter::Fit(), FitFCN(), and SetFCN().

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 174 of file Fitter.cxx.

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 210 of file Fitter.cxx.

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::IMultiGenFunction) and optionally the initial parameters See also note above for the initial parameters for FitFCN.

Definition at line 202 of file Fitter.cxx.

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

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 261 of file Fitter.cxx.