GSLNLSMinimizer class for Non Linear Least Square fitting It Uses the Levemberg-Marquardt algorithm from GSL Non Linear Least Square fitting.

Definition at line 60 of file GSLNLSMinimizer.h.

Public Member Functions
	GSLNLSMinimizer (const char *=nullptr)
	Constructor from name.
	GSLNLSMinimizer (int type)
	Constructor from a type.
	~GSLNLSMinimizer () override
	Destructor (no operations).
virtual void	Clear ()
	Reset for consecutive minimization - implement if needed.
virtual bool	Contour (unsigned int ivar, unsigned int jvar, unsigned int &npoints, double xi, double xj)
	Find the contour points (xi, xj) of the function for parameter ivar and jvar around the minimum.
virtual double	Correlation (unsigned int i, unsigned int j) const
double	CovMatrix (unsigned int, unsigned int) const override
	return covariance matrices elements if the variable is fixed the matrix is zero The ordering of the variables is the same as in errors
int	CovMatrixStatus () const override
	return covariance matrix status
double	Edm () const override
	return expected distance reached from the minimum
double	ErrorDef () const
const double *	Errors () const override
	return errors at the minimum
bool	FixVariable (unsigned int ivar) override
	fix an existing variable
virtual bool	GetCovMatrix (double *covMat) const
	Fill the passed array with the covariance matrix elements if the variable is fixed or const the value is zero.
virtual bool	GetHessianMatrix (double *hMat) const
	Fill the passed array with the Hessian matrix elements The Hessian matrix is the matrix of the second derivatives and is the inverse of the covariance matrix If the variable is fixed or const the values for that variables are zero.
virtual bool	GetMinosError (unsigned int ivar, double &errLow, double &errUp, int option=0)
	Minos error for variable i, return false if Minos failed or not supported and the lower and upper errors are returned in errLow and errUp An extra flag specifies if only the lower (option=-1) or the upper (option=+1) error calculation is run.
bool	GetVariableSettings (unsigned int ivar, ROOT::Fit::ParameterSettings &varObj) const override
	get variable settings in a variable object (like ROOT::Fit::ParamsSettings)
virtual std::vector< double >	GlobalCC () const
const ROOT::Math::IMultiGradFunction *	GradObjFunction () const
	return pointer to used gradient object function (NULL if gradient is not supported)
virtual bool	Hesse ()
	Perform a full calculation of the Hessian matrix for error calculation.
bool	IsFixedVariable (unsigned int ivar) const override
	query if an existing variable is fixed (i.e.
bool	IsValidError () const
unsigned int	MaxFunctionCalls () const
	Max number of function calls.
unsigned int	MaxIterations () const
	Max iterations.
const double *	MinGradient () const override
	return pointer to gradient values at the minimum
bool	Minimize () override
	method to perform the minimization
virtual int	MinosStatus () const
	Status code of Minos (to be re-implemented by the minimizers supporting Minos).
double	MinValue () const override
	return minimum function value
unsigned int	NCalls () const override
	number of function calls to reach the minimum
unsigned int	NDim () const override
	number of dimensions
unsigned int	NFree () const override
	number of free variables (real dimension of the problem)
virtual unsigned int	NIterations () const
	Number of iterations to reach the minimum.
virtual unsigned int	NPar () const
	total number of parameter defined
const ROOT::Math::IMultiGenFunction *	ObjFunction () const
	return pointer to used objective function
virtual MinimizerOptions	Options () const
	Retrieve the minimizer options (implement derived class if needed).
double	Precision () const
	Precision of minimizer in the evaluation of the objective function.
int	PrintLevel () const
	Set print level.
void	PrintResult () const
	print result of minimization
virtual void	PrintResults ()
	Print the result according to set level (implemented for TMinuit for maintaining Minuit-style printing).
bool	ProvidesError () const override
	number of free variables (real dimension of the problem) this is <= Function().NDim() which is the total
bool	ReleaseVariable (unsigned int ivar) override
	release an existing variable
virtual bool	Scan (unsigned int ivar, unsigned int &nstep, double x, double y, double xmin=0, double xmax=0)
	Scan function minimum for variable i.
virtual bool	SetCovariance (std::span< const double > cov, unsigned int nrow)
	Set initial covariance matrix.
virtual bool	SetCovarianceDiag (std::span< const double > d2, unsigned int n)
	Set initial second derivatives.
void	SetDefaultOptions ()
	Reset the default options (defined in MinimizerOptions).
void	SetErrorDef (double up)
	Set scale for calculating the errors.
void	SetExtraOptions (const IOptions &extraOptions)
	Set only the extra options.
bool	SetFixedVariable (unsigned int, const std::string &, double) override
	set fixed variable (override if minimizer supports them )
void	SetFunction (const ROOT::Math::IMultiGenFunction &func) override
	set the function to minimize
virtual void	SetHessianFunction (std::function< bool(std::span< const double >, double *)>)
	Set the function implementing Hessian computation (re-implemented by Minimizer using it).
bool	SetLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double, double) override
	set upper/lower limited variable (override if minimizer supports them )
bool	SetLowerLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double lower) override
	set lower limit variable (override if minimizer supports them )
void	SetMaxFunctionCalls (unsigned int maxfcn)
	Set maximum of function calls.
void	SetMaxIterations (unsigned int maxiter)
	Set maximum iterations (one iteration can have many function calls).
void	SetOptions (const MinimizerOptions &opt)
	Set all options in one go.
void	SetPrecision (double prec)
	Set in the minimizer the objective function evaluation precision.
void	SetPrintLevel (int level)
	Set print level.
void	SetStrategy (int strategyLevel)
	Set the strategy.
void	SetTolerance (double tol)
	Set the tolerance.
bool	SetUpperLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double upper) override
	set upper limit variable (override if minimizer supports them )
void	SetValidError (bool on)
	Flag to check if minimizer needs to perform accurate error analysis (e.g. run Hesse for Minuit).
bool	SetVariable (unsigned int ivar, const std::string &name, double val, double step) override
	set free variable
virtual bool	SetVariableInitialRange (unsigned int, double, double)
	Set the initial range of an existing variable.
bool	SetVariableLimits (unsigned int ivar, double lower, double upper) override
	set the limits of an already existing variable
bool	SetVariableLowerLimit (unsigned int ivar, double lower) override
	set the lower-limit of an already existing variable
template<class VariableIterator>
int	SetVariables (const VariableIterator &begin, const VariableIterator &end)
	Add variables.
bool	SetVariableStepSize (unsigned int ivar, double step) override
	set the step size of an already existing variable
bool	SetVariableUpperLimit (unsigned int ivar, double upper) override
	set the upper-limit of an already existing variable
bool	SetVariableValue (unsigned int ivar, double val) override
	set the value of an existing variable
bool	SetVariableValues (const double *x) override
	set the values of all existing variables (array must be dimensioned to the size of existing parameters)
int	Status () const
	Status code of minimizer.
virtual const double *	StepSizes () const
	accessor methods
int	Strategy () const
	Strategy.
double	Tolerance () const
	Absolute tolerance.
int	VariableIndex (const std::string &name) const override
	get index of variable given a variable given a name return -1 if variable is not found
std::string	VariableName (unsigned int ivar) const override
	get name of variables (override if minimizer support storing of variable names)
const double *	X () const override
	return pointer to X values at the minimum

Protected Member Functions
bool	CheckDimension () const
bool	CheckObjFunction () const
MinimTransformFunction *	CreateTransformation (std::vector< double > &startValues, const ROOT::Math::IMultiGradFunction *func=nullptr)
template<class Func, class FitterType>
bool	DoMinimize (const Func &f, FitterType *fitter)
	Internal method to perform minimization template on the type of method function.
void	SetFinalValues (const double x, const MinimTransformFunction func=nullptr)
void	SetMinValue (double val)

Protected Attributes
MinimizerOptions	fOptions
	minimizer options
int	fStatus = -1
	status of minimizer
bool	fValidError = false
	flag to control if errors have been validated (Hesse has been run in case of Minuit)

Private Attributes
std::map< unsigned int, std::pair< double, double > >	fBounds
	map specifying the bound using as key the parameter index
std::vector< double >	fCovMatrix
unsigned int	fDim
double	fEdm
std::vector< double >	fErrors
ROOT::Math::GSLMultiFit *	fGSLMultiFit = nullptr
ROOT::Math::GSLMultiFit2 *	fGSLMultiFit2 = nullptr
double	fLSTolerance
double	fMinVal
std::vector< std::string >	fNames
unsigned int	fNCalls
unsigned int	fNFree
const ROOT::Math::IMultiGenFunction *	fObjFunc
std::vector< double >	fSteps
bool	fUseGradFunction = false
std::vector< double >	fValues
std::vector< ROOT::Math::EMinimVariableType >	fVarTypes
	vector specifying the type of variables

#include <Math/GSLNLSMinimizer.h>

Inheritance diagram for ROOT::Math::GSLNLSMinimizer:

Constructor & Destructor Documentation

◆ GSLNLSMinimizer() [1/2]

ROOT::Math::GSLNLSMinimizer::GSLNLSMinimizer ( int type )

explicit

Constructor from a type.

Definition at line 205 of file GSLNLSMinimizer.cxx.

◆ GSLNLSMinimizer() [2/2]

ROOT::Math::GSLNLSMinimizer::GSLNLSMinimizer ( const char * name = nullptr )

explicit

Constructor from name.

Definition at line 203 of file GSLNLSMinimizer.cxx.

◆ ~GSLNLSMinimizer()

ROOT::Math::GSLNLSMinimizer::~GSLNLSMinimizer ( )

override

Destructor (no operations).

Definition at line 246 of file GSLNLSMinimizer.cxx.

Member Function Documentation

◆ CheckDimension()

bool ROOT::Math::BasicMinimizer::CheckDimension ( ) const

protectedinherited

Definition at line 247 of file BasicMinimizer.cxx.

◆ CheckObjFunction()

bool ROOT::Math::BasicMinimizer::CheckObjFunction ( ) const

protectedinherited

Definition at line 256 of file BasicMinimizer.cxx.

◆ Clear()

virtual void ROOT::Math::Minimizer::Clear ( )

inlinevirtualinherited

Reset for consecutive minimization - implement if needed.

Reimplemented in ROOT::Math::GeneticMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

Definition at line 141 of file Minimizer.h.

◆ Contour()

bool ROOT::Math::Minimizer::Contour	(	unsigned int	ivar,
		unsigned int	jvar,
		unsigned int &	npoints,
		double *	xi,
		double *	xj )

virtualinherited

Find the contour points (xi, xj) of the function for parameter ivar and jvar around the minimum.

The contour will be find for value of the function = Min + ErrorUp();

Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.

Definition at line 219 of file Minimizer.cxx.

◆ Correlation()

virtual double ROOT::Math::Minimizer::Correlation	(	unsigned int	i,
		unsigned int	j ) const

inlinevirtualinherited

Returns: correlation coefficient between variable i and j. If the variable is fixed or const the return value is zero

Reimplemented in ROOT::Minuit2::Minuit2Minimizer.

Definition at line 281 of file Minimizer.h.

◆ CovMatrix()

double ROOT::Math::GSLNLSMinimizer::CovMatrix	(	unsigned int	i,
		unsigned int	j ) const

overridevirtual

return covariance matrices elements if the variable is fixed the matrix is zero The ordering of the variables is the same as in errors

Reimplemented from ROOT::Math::Minimizer.

Definition at line 513 of file GSLNLSMinimizer.cxx.

◆ CovMatrixStatus()

int ROOT::Math::GSLNLSMinimizer::CovMatrixStatus ( ) const

overridevirtual

return covariance matrix status

Reimplemented from ROOT::Math::Minimizer.

Definition at line 524 of file GSLNLSMinimizer.cxx.

◆ CreateTransformation()

MinimTransformFunction * ROOT::Math::BasicMinimizer::CreateTransformation	(	std::vector< double > &	startValues,
		const ROOT::Math::IMultiGradFunction *	func = nullptr )

protectedinherited

Definition at line 265 of file BasicMinimizer.cxx.

◆ DoMinimize()

template<class Func, class FitterType>

bool ROOT::Math::GSLNLSMinimizer::DoMinimize	(	const Func &	f,
		FitterType *	fitter )

protected

Internal method to perform minimization template on the type of method function.

Definition at line 311 of file GSLNLSMinimizer.cxx.

◆ Edm()

double ROOT::Math::GSLNLSMinimizer::Edm ( ) const

inlineoverridevirtual

return expected distance reached from the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 88 of file GSLNLSMinimizer.h.

◆ ErrorDef()

double ROOT::Math::Minimizer::ErrorDef ( ) const

inlineinherited

Returns: the statistical scale used for calculate the error is typically 1 for Chi2 and 0.5 for likelihood minimization

Definition at line 334 of file Minimizer.h.

◆ Errors()

const double * ROOT::Math::GSLNLSMinimizer::Errors ( ) const

inlineoverridevirtual

return errors at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 105 of file GSLNLSMinimizer.h.

◆ FixVariable()

bool ROOT::Math::BasicMinimizer::FixVariable ( unsigned int ivar )

overridevirtualinherited

fix an existing variable

Reimplemented from ROOT::Math::Minimizer.

Definition at line 182 of file BasicMinimizer.cxx.

◆ GetCovMatrix()

bool ROOT::Math::Minimizer::GetCovMatrix ( double * covMat ) const

virtualinherited

Fill the passed array with the covariance matrix elements if the variable is fixed or const the value is zero.

The array will be filled as cov[i *ndim + j] The ordering of the variables is the same as in errors and parameter value. This is different from the direct interface of Minuit2 or TMinuit where the values were obtained only to variable parameters

Reimplemented in ROOT::Math::RMinimizer, ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.

Definition at line 144 of file Minimizer.cxx.

◆ GetHessianMatrix()

bool ROOT::Math::Minimizer::GetHessianMatrix ( double * hMat ) const

virtualinherited

Fill the passed array with the Hessian matrix elements The Hessian matrix is the matrix of the second derivatives and is the inverse of the covariance matrix If the variable is fixed or const the values for that variables are zero.

The array will be filled as h[i *ndim + j]

Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.

Definition at line 157 of file Minimizer.cxx.

◆ GetMinosError()

bool ROOT::Math::Minimizer::GetMinosError	(	unsigned int	ivar,
		double &	errLow,
		double &	errUp,
		int	option = 0 )

virtualinherited

Minos error for variable i, return false if Minos failed or not supported and the lower and upper errors are returned in errLow and errUp An extra flag specifies if only the lower (option=-1) or the upper (option=+1) error calculation is run.

Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.

Definition at line 180 of file Minimizer.cxx.

◆ GetVariableSettings()

bool ROOT::Math::BasicMinimizer::GetVariableSettings	(	unsigned int	ivar,
		ROOT::Fit::ParameterSettings &	varObj ) const

overridevirtualinherited

get variable settings in a variable object (like ROOT::Fit::ParamsSettings)

Reimplemented from ROOT::Math::Minimizer.

Definition at line 211 of file BasicMinimizer.cxx.

◆ GlobalCC()

std::vector< double > ROOT::Math::Minimizer::GlobalCC ( ) const

virtualinherited

Returns: global correlation coefficient for variable i. This is a number between zero and one which gives the correlation between the i-th parameter and that linear combination of all other parameters which is most strongly correlated with i. Minimizer must overload method if implemented

Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.

Definition at line 170 of file Minimizer.cxx.

◆ GradObjFunction()

const ROOT::Math::IMultiGradFunction * ROOT::Math::BasicMinimizer::GradObjFunction ( ) const

inherited

return pointer to used gradient object function (NULL if gradient is not supported)

Definition at line 325 of file BasicMinimizer.cxx.

◆ Hesse()

bool ROOT::Math::Minimizer::Hesse ( )

virtualinherited

Perform a full calculation of the Hessian matrix for error calculation.

Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.

Definition at line 193 of file Minimizer.cxx.

◆ IsFixedVariable()

bool ROOT::Math::BasicMinimizer::IsFixedVariable ( unsigned int ivar ) const

overridevirtualinherited

query if an existing variable is fixed (i.e.

considered constant in the minimization) note that by default all variables are not fixed

Reimplemented from ROOT::Math::Minimizer.

Definition at line 206 of file BasicMinimizer.cxx.

◆ IsValidError()

bool ROOT::Math::Minimizer::IsValidError ( ) const

inlineinherited

Returns: true if Minimizer has performed a detailed error validation (e.g. run Hesse for Minuit)

Definition at line 337 of file Minimizer.h.

◆ MaxFunctionCalls()

unsigned int ROOT::Math::Minimizer::MaxFunctionCalls ( ) const

inlineinherited

Max number of function calls.

Definition at line 311 of file Minimizer.h.

◆ MaxIterations()

unsigned int ROOT::Math::Minimizer::MaxIterations ( ) const

inlineinherited

Max iterations.

Definition at line 314 of file Minimizer.h.

◆ MinGradient()

const double * ROOT::Math::GSLNLSMinimizer::MinGradient ( ) const

overridevirtual

return pointer to gradient values at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 507 of file GSLNLSMinimizer.cxx.

◆ Minimize()

bool ROOT::Math::GSLNLSMinimizer::Minimize ( )

overridevirtual

method to perform the minimization

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 265 of file GSLNLSMinimizer.cxx.

◆ MinosStatus()

virtual int ROOT::Math::Minimizer::MinosStatus ( ) const

inlinevirtualinherited

Status code of Minos (to be re-implemented by the minimizers supporting Minos).

Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.

Definition at line 330 of file Minimizer.h.

◆ MinValue()

double ROOT::Math::BasicMinimizer::MinValue ( ) const

inlineoverridevirtualinherited

return minimum function value

Implements ROOT::Math::Minimizer.

Definition at line 115 of file BasicMinimizer.h.

◆ NCalls()

unsigned int ROOT::Math::GSLNLSMinimizer::NCalls ( ) const

inlineoverridevirtual

number of function calls to reach the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 95 of file GSLNLSMinimizer.h.

◆ NDim()

unsigned int ROOT::Math::BasicMinimizer::NDim ( ) const

inlineoverridevirtualinherited

number of dimensions

Implements ROOT::Math::Minimizer.

Definition at line 121 of file BasicMinimizer.h.

◆ NFree()

unsigned int ROOT::Math::BasicMinimizer::NFree ( ) const

overridevirtualinherited

number of free variables (real dimension of the problem)

Reimplemented from ROOT::Math::Minimizer.

Definition at line 330 of file BasicMinimizer.cxx.

◆ NIterations()

virtual unsigned int ROOT::Math::Minimizer::NIterations ( ) const

inlinevirtualinherited

Number of iterations to reach the minimum.

Definition at line 248 of file Minimizer.h.

◆ NPar()

virtual unsigned int ROOT::Math::BasicMinimizer::NPar ( ) const

inlinevirtualinherited

total number of parameter defined

Definition at line 127 of file BasicMinimizer.h.

◆ ObjFunction()

const ROOT::Math::IMultiGenFunction * ROOT::Math::BasicMinimizer::ObjFunction ( ) const

inlineinherited

return pointer to used objective function

Definition at line 130 of file BasicMinimizer.h.

◆ Options()

virtual MinimizerOptions ROOT::Math::Minimizer::Options ( ) const

inlinevirtualinherited

Retrieve the minimizer options (implement derived class if needed).

Reimplemented in ROOT::Math::GeneticMinimizer.

Definition at line 340 of file Minimizer.h.

◆ Precision()

double ROOT::Math::Minimizer::Precision ( ) const

inlineinherited

Precision of minimizer in the evaluation of the objective function.

(a value <=0 corresponds to the let the minimizer choose its default one)

Definition at line 321 of file Minimizer.h.

◆ PrintLevel()

int ROOT::Math::Minimizer::PrintLevel ( ) const

inlineinherited

Set print level.

Definition at line 308 of file Minimizer.h.

◆ PrintResult()

void ROOT::Math::BasicMinimizer::PrintResult ( ) const

inherited

print result of minimization

Definition at line 313 of file BasicMinimizer.cxx.

◆ PrintResults()

virtual void ROOT::Math::Minimizer::PrintResults ( )

inlinevirtualinherited

Print the result according to set level (implemented for TMinuit for maintaining Minuit-style printing).

Returns: reference to the objective function virtual const ROOT::Math::IGenFunction & Function() const = 0;

Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.

Definition at line 299 of file Minimizer.h.

◆ ProvidesError()

bool ROOT::Math::GSLNLSMinimizer::ProvidesError ( ) const

inlineoverridevirtual

number of free variables (real dimension of the problem) this is <= Function().NDim() which is the total

minimizer provides error and error matrix

Reimplemented from ROOT::Math::Minimizer.

Definition at line 102 of file GSLNLSMinimizer.h.

◆ ReleaseVariable()

bool ROOT::Math::BasicMinimizer::ReleaseVariable ( unsigned int ivar )

overridevirtualinherited

release an existing variable

Reimplemented from ROOT::Math::Minimizer.

Definition at line 189 of file BasicMinimizer.cxx.

◆ Scan()

bool ROOT::Math::Minimizer::Scan	(	unsigned int	ivar,
		unsigned int &	nstep,
		double *	x,
		double *	y,
		double	xmin = 0,
		double	xmax = 0 )

virtualinherited

Scan function minimum for variable i.

Variable and function must be set before using Scan.

Returns: false if an error or if minimizer does not support this functionality

Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.

Definition at line 203 of file Minimizer.cxx.

◆ SetCovariance()

bool ROOT::Math::Minimizer::SetCovariance	(	std::span< const double >	cov,
		unsigned int	nrow )

virtualinherited

Set initial covariance matrix.

Set initial values for covariance/error matrix.

The covariance matrix must be provided in compressed form (row-major ordered upper traingular part)

Reimplemented in ROOT::Minuit2::Minuit2Minimizer.

Definition at line 26 of file Minimizer.cxx.

◆ SetCovarianceDiag()

bool ROOT::Math::Minimizer::SetCovarianceDiag	(	std::span< const double >	d2,
		unsigned int	n )

virtualinherited

Set initial second derivatives.

set initial second derivatives

Reimplemented in ROOT::Minuit2::Minuit2Minimizer.

Definition at line 15 of file Minimizer.cxx.

◆ SetDefaultOptions()

void ROOT::Math::Minimizer::SetDefaultOptions ( )

inlineinherited

Reset the default options (defined in MinimizerOptions).

Definition at line 378 of file Minimizer.h.

◆ SetErrorDef()

void ROOT::Math::Minimizer::SetErrorDef ( double up )

inlineinherited

Set scale for calculating the errors.

Definition at line 364 of file Minimizer.h.

◆ SetExtraOptions()

void ROOT::Math::Minimizer::SetExtraOptions ( const IOptions & extraOptions )

inlineinherited

Set only the extra options.

Definition at line 375 of file Minimizer.h.

◆ SetFinalValues()

void ROOT::Math::BasicMinimizer::SetFinalValues	(	const double *	x,
		const MinimTransformFunction *	func = nullptr )

protectedinherited

Definition at line 300 of file BasicMinimizer.cxx.

◆ SetFixedVariable()

bool ROOT::Math::BasicMinimizer::SetFixedVariable	(	unsigned int	ivar,
		const std::string &	name,
		double	val )

overridevirtualinherited

set fixed variable (override if minimizer supports them )

Reimplemented from ROOT::Math::Minimizer.

Definition at line 116 of file BasicMinimizer.cxx.

◆ SetFunction()

void ROOT::Math::GSLNLSMinimizer::SetFunction ( const ROOT::Math::IMultiGenFunction & func )

overridevirtual

set the function to minimize

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 254 of file GSLNLSMinimizer.cxx.

◆ SetHessianFunction()

virtual void ROOT::Math::Minimizer::SetHessianFunction ( std::function< bool(std::span< const double >, double *)> )

inlinevirtualinherited

Set the function implementing Hessian computation (re-implemented by Minimizer using it).

Reimplemented in ROOT::Minuit2::Minuit2Minimizer.

Definition at line 147 of file Minimizer.h.

◆ SetLimitedVariable()

bool ROOT::Math::BasicMinimizer::SetLimitedVariable	(	unsigned int	ivar,
		const std::string &	name,
		double	val,
		double	step,
		double	lower,
		double	upper )

overridevirtualinherited

set upper/lower limited variable (override if minimizer supports them )

Reimplemented from ROOT::Math::Minimizer.

Definition at line 107 of file BasicMinimizer.cxx.

◆ SetLowerLimitedVariable()

bool ROOT::Math::BasicMinimizer::SetLowerLimitedVariable	(	unsigned int	ivar,
		const std::string &	name,
		double	val,
		double	step,
		double	lower )

overridevirtualinherited

set lower limit variable (override if minimizer supports them )

Reimplemented from ROOT::Math::Minimizer.

Definition at line 88 of file BasicMinimizer.cxx.

◆ SetMaxFunctionCalls()

void ROOT::Math::Minimizer::SetMaxFunctionCalls ( unsigned int maxfcn )

inlineinherited

Set maximum of function calls.

Definition at line 348 of file Minimizer.h.

◆ SetMaxIterations()

void ROOT::Math::Minimizer::SetMaxIterations ( unsigned int maxiter )

inlineinherited

Set maximum iterations (one iteration can have many function calls).

Definition at line 351 of file Minimizer.h.

◆ SetMinValue()

void ROOT::Math::BasicMinimizer::SetMinValue ( double val )

inlineprotectedinherited

Definition at line 152 of file BasicMinimizer.h.

◆ SetOptions()

void ROOT::Math::Minimizer::SetOptions ( const MinimizerOptions & opt )

inlineinherited

Set all options in one go.

Definition at line 370 of file Minimizer.h.

◆ SetPrecision()

void ROOT::Math::Minimizer::SetPrecision ( double prec )

inlineinherited

Set in the minimizer the objective function evaluation precision.

(a value <=0 means the minimizer will choose its optimal value automatically, i.e. default case)

Definition at line 358 of file Minimizer.h.

◆ SetPrintLevel()

void ROOT::Math::Minimizer::SetPrintLevel ( int level )

inlineinherited

Set print level.

Definition at line 345 of file Minimizer.h.

◆ SetStrategy()

void ROOT::Math::Minimizer::SetStrategy ( int strategyLevel )

inlineinherited

Set the strategy.

Definition at line 361 of file Minimizer.h.

◆ SetTolerance()

void ROOT::Math::Minimizer::SetTolerance ( double tol )

inlineinherited

Set the tolerance.

Definition at line 354 of file Minimizer.h.

◆ SetUpperLimitedVariable()

bool ROOT::Math::BasicMinimizer::SetUpperLimitedVariable	(	unsigned int	ivar,
		const std::string &	name,
		double	val,
		double	step,
		double	upper )

overridevirtualinherited

set upper limit variable (override if minimizer supports them )

Reimplemented from ROOT::Math::Minimizer.

Definition at line 97 of file BasicMinimizer.cxx.

◆ SetValidError()

void ROOT::Math::Minimizer::SetValidError ( bool on )

inlineinherited

Flag to check if minimizer needs to perform accurate error analysis (e.g. run Hesse for Minuit).

Definition at line 367 of file Minimizer.h.

◆ SetVariable()

bool ROOT::Math::BasicMinimizer::SetVariable	(	unsigned int	ivar,
		const std::string &	name,
		double	val,
		double	step )

overridevirtualinherited

set free variable

Implements ROOT::Math::Minimizer.

Definition at line 63 of file BasicMinimizer.cxx.

◆ SetVariableInitialRange()

virtual bool ROOT::Math::Minimizer::SetVariableInitialRange	(	unsigned int	,
		double	,
		double	)

inlinevirtualinherited

Set the initial range of an existing variable.

Definition at line 225 of file Minimizer.h.

◆ SetVariableLimits()

bool ROOT::Math::BasicMinimizer::SetVariableLimits	(	unsigned int	ivar,
		double	lower,
		double	upper )

overridevirtualinherited

set the limits of an already existing variable

Reimplemented from ROOT::Math::Minimizer.

Definition at line 159 of file BasicMinimizer.cxx.

◆ SetVariableLowerLimit()

bool ROOT::Math::BasicMinimizer::SetVariableLowerLimit	(	unsigned int	ivar,
		double	lower )

overridevirtualinherited

set the lower-limit of an already existing variable

Reimplemented from ROOT::Math::Minimizer.

Definition at line 147 of file BasicMinimizer.cxx.

◆ SetVariables()

template<class VariableIterator>

int ROOT::Math::Minimizer::SetVariables	(	const VariableIterator &	begin,
		const VariableIterator &	end )

inlineinherited

Add variables.

Returns: number of variables successfully added

Definition at line 151 of file Minimizer.h.

◆ SetVariableStepSize()

bool ROOT::Math::BasicMinimizer::SetVariableStepSize	(	unsigned int	ivar,
		double	step )

overridevirtualinherited

set the step size of an already existing variable

Reimplemented from ROOT::Math::Minimizer.

Definition at line 140 of file BasicMinimizer.cxx.

◆ SetVariableUpperLimit()

bool ROOT::Math::BasicMinimizer::SetVariableUpperLimit	(	unsigned int	ivar,
		double	upper )

overridevirtualinherited

set the upper-limit of an already existing variable

Reimplemented from ROOT::Math::Minimizer.

Definition at line 153 of file BasicMinimizer.cxx.

◆ SetVariableValue()

bool ROOT::Math::BasicMinimizer::SetVariableValue	(	unsigned int	ivar,
		double	val )

overridevirtualinherited

set the value of an existing variable

Reimplemented from ROOT::Math::Minimizer.

Definition at line 125 of file BasicMinimizer.cxx.

◆ SetVariableValues()

bool ROOT::Math::BasicMinimizer::SetVariableValues ( const double * x )

overridevirtualinherited

set the values of all existing variables (array must be dimensioned to the size of existing parameters)

Reimplemented from ROOT::Math::Minimizer.

Definition at line 133 of file BasicMinimizer.cxx.

◆ Status()

int ROOT::Math::Minimizer::Status ( ) const

inlineinherited

Status code of minimizer.

Definition at line 327 of file Minimizer.h.

◆ StepSizes()

virtual const double * ROOT::Math::BasicMinimizer::StepSizes ( ) const

inlinevirtualinherited

accessor methods

Definition at line 140 of file BasicMinimizer.h.

◆ Strategy()

int ROOT::Math::Minimizer::Strategy ( ) const

inlineinherited

Strategy.

Definition at line 324 of file Minimizer.h.

◆ Tolerance()

double ROOT::Math::Minimizer::Tolerance ( ) const

inlineinherited

Absolute tolerance.

Definition at line 317 of file Minimizer.h.

◆ VariableIndex()

int ROOT::Math::BasicMinimizer::VariableIndex ( const std::string & name ) const

overridevirtualinherited

get index of variable given a variable given a name return -1 if variable is not found

Reimplemented from ROOT::Math::Minimizer.

Definition at line 232 of file BasicMinimizer.cxx.

◆ VariableName()

std::string ROOT::Math::BasicMinimizer::VariableName ( unsigned int ivar ) const

overridevirtualinherited

get name of variables (override if minimizer support storing of variable names)

Reimplemented from ROOT::Math::Minimizer.

Definition at line 227 of file BasicMinimizer.cxx.

◆ X()

const double * ROOT::Math::BasicMinimizer::X ( ) const

inlineoverridevirtualinherited

return pointer to X values at the minimum

Implements ROOT::Math::Minimizer.

Definition at line 118 of file BasicMinimizer.h.

Member Data Documentation

◆ fBounds

std::map< unsigned int, std::pair<double, double> > ROOT::Math::BasicMinimizer::fBounds

privateinherited

map specifying the bound using as key the parameter index

Definition at line 166 of file BasicMinimizer.h.

◆ fCovMatrix

std::vector<double> ROOT::Math::GSLNLSMinimizer::fCovMatrix

private

Definition at line 141 of file GSLNLSMinimizer.h.

◆ fDim

unsigned int ROOT::Math::BasicMinimizer::fDim

privateinherited

Definition at line 157 of file BasicMinimizer.h.

◆ fEdm

double ROOT::Math::GSLNLSMinimizer::fEdm

private

Definition at line 138 of file GSLNLSMinimizer.h.

◆ fErrors

std::vector<double> ROOT::Math::GSLNLSMinimizer::fErrors

private

Definition at line 140 of file GSLNLSMinimizer.h.

◆ fGSLMultiFit

ROOT::Math::GSLMultiFit* ROOT::Math::GSLNLSMinimizer::fGSLMultiFit = nullptr

private

Definition at line 135 of file GSLNLSMinimizer.h.

◆ fGSLMultiFit2

ROOT::Math::GSLMultiFit2* ROOT::Math::GSLNLSMinimizer::fGSLMultiFit2 = nullptr

private

Definition at line 136 of file GSLNLSMinimizer.h.

◆ fLSTolerance

double ROOT::Math::GSLNLSMinimizer::fLSTolerance

private

Definition at line 139 of file GSLNLSMinimizer.h.

◆ fMinVal

double ROOT::Math::BasicMinimizer::fMinVal

privateinherited

Definition at line 161 of file BasicMinimizer.h.

◆ fNames

std::vector<std::string> ROOT::Math::BasicMinimizer::fNames

privateinherited

Definition at line 164 of file BasicMinimizer.h.

◆ fNCalls

unsigned int ROOT::Math::GSLNLSMinimizer::fNCalls

private

Definition at line 133 of file GSLNLSMinimizer.h.

◆ fNFree

unsigned int ROOT::Math::GSLNLSMinimizer::fNFree

private

Definition at line 132 of file GSLNLSMinimizer.h.

◆ fObjFunc

const ROOT::Math::IMultiGenFunction* ROOT::Math::BasicMinimizer::fObjFunc

privateinherited

Definition at line 159 of file BasicMinimizer.h.

◆ fOptions

MinimizerOptions ROOT::Math::Minimizer::fOptions

protectedinherited

minimizer options

Definition at line 387 of file Minimizer.h.

◆ fStatus

int ROOT::Math::Minimizer::fStatus = -1

protectedinherited

status of minimizer

Definition at line 388 of file Minimizer.h.

◆ fSteps

std::vector<double> ROOT::Math::BasicMinimizer::fSteps

privateinherited

Definition at line 163 of file BasicMinimizer.h.

◆ fUseGradFunction

bool ROOT::Math::GSLNLSMinimizer::fUseGradFunction = false

private

Definition at line 131 of file GSLNLSMinimizer.h.

◆ fValidError

bool ROOT::Math::Minimizer::fValidError = false

protectedinherited

flag to control if errors have been validated (Hesse has been run in case of Minuit)

Definition at line 386 of file Minimizer.h.

◆ fValues

std::vector<double> ROOT::Math::BasicMinimizer::fValues

privateinherited

Definition at line 162 of file BasicMinimizer.h.

◆ fVarTypes

std::vector<ROOT::Math::EMinimVariableType> ROOT::Math::BasicMinimizer::fVarTypes

privateinherited

vector specifying the type of variables

Definition at line 165 of file BasicMinimizer.h.

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

math/mathmore/inc/Math/GSLNLSMinimizer.h
math/mathmore/src/GSLNLSMinimizer.cxx

Public Member Functions

Protected Member Functions

Protected Attributes

Private Attributes

Constructor & Destructor Documentation

◆ GSLNLSMinimizer() [1/2]

◆ GSLNLSMinimizer() [2/2]

◆ ~GSLNLSMinimizer()

Member Function Documentation

◆ CheckDimension()

◆ CheckObjFunction()

◆ Clear()

◆ Contour()

◆ Correlation()

◆ CovMatrix()

◆ CovMatrixStatus()

◆ CreateTransformation()

◆ DoMinimize()

◆ Edm()

◆ ErrorDef()

◆ Errors()

◆ FixVariable()

◆ GetCovMatrix()

◆ GetHessianMatrix()

◆ GetMinosError()

◆ GetVariableSettings()

◆ GlobalCC()

◆ GradObjFunction()

◆ Hesse()

◆ IsFixedVariable()

◆ IsValidError()

◆ MaxFunctionCalls()

◆ MaxIterations()

◆ MinGradient()

◆ Minimize()

◆ MinosStatus()

◆ MinValue()

◆ NCalls()

◆ NDim()

◆ NFree()

◆ NIterations()

◆ NPar()

◆ ObjFunction()

◆ Options()

◆ Precision()

◆ PrintLevel()

◆ PrintResult()

◆ PrintResults()

◆ ProvidesError()

◆ ReleaseVariable()

◆ Scan()

◆ SetCovariance()

◆ SetCovarianceDiag()

◆ SetDefaultOptions()

◆ SetErrorDef()

◆ SetExtraOptions()

◆ SetFinalValues()

◆ SetFixedVariable()

◆ SetFunction()

◆ SetHessianFunction()

◆ SetLimitedVariable()

◆ SetLowerLimitedVariable()

◆ SetMaxFunctionCalls()

◆ SetMaxIterations()

◆ SetMinValue()

◆ SetOptions()

◆ SetPrecision()

◆ SetPrintLevel()

◆ SetStrategy()

◆ SetTolerance()

◆ SetUpperLimitedVariable()

◆ SetValidError()

◆ SetVariable()

◆ SetVariableInitialRange()

◆ SetVariableLimits()

◆ SetVariableLowerLimit()

◆ SetVariables()

◆ SetVariableStepSize()

◆ SetVariableUpperLimit()

◆ SetVariableValue()