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

Definition at line 152 of file GSLNLSMinimizer.h.

Public Member Functions
	GSLNLSMinimizer (int type=0)
	Default constructor. More...

	~GSLNLSMinimizer ()
	Destructor (no operations) More...

virtual double	CovMatrix (unsigned int, unsigned int) const
	return covariance matrices elements if the variable is fixed the matrix is zero The ordering of the variables is the same as in errors More...

virtual int	CovMatrixStatus () const
	return covariance matrix status More...

virtual double	Edm () const
	return expected distance reached from the minimum More...

virtual const double *	Errors () const
	return errors at the minimum More...

virtual const double *	MinGradient () const
	return pointer to gradient values at the minimum More...

virtual bool	Minimize ()
	method to perform the minimization More...

virtual unsigned int	NCalls () const
	number of function calls to reach the minimum More...

virtual bool	ProvidesError () const
	number of free variables (real dimension of the problem) this is <= Function().NDim() which is the total More...

virtual void	SetFunction (const ROOT::Math::IMultiGenFunction &func)
	set the function to minimize More...

virtual void	SetFunction (const ROOT::Math::IMultiGradFunction &func)
	set gradient the function to minimize More...

Public Member Functions inherited from ROOT::Math::BasicMinimizer
	BasicMinimizer ()
	Default constructor. More...

virtual	~BasicMinimizer ()
	Destructor. More...

virtual bool	FixVariable (unsigned int ivar)
	fix an existing variable More...

virtual bool	GetVariableSettings (unsigned int ivar, ROOT::Fit::ParameterSettings &varObj) const
	get variable settings in a variable object (like ROOT::Fit::ParamsSettings) More...

const ROOT::Math::IMultiGradFunction *	GradObjFunction () const
	return pointer to used gradient object function (NULL if gradient is not supported) More...

virtual bool	IsFixedVariable (unsigned int ivar) const
	query if an existing variable is fixed (i.e. More...

virtual bool	Minimize ()
	method to perform the minimization More...

virtual double	MinValue () const
	return minimum function value More...

virtual unsigned int	NDim () const
	number of dimensions More...

virtual unsigned int	NFree () const
	number of free variables (real dimension of the problem) More...

virtual unsigned int	NPar () const
	total number of parameter defined More...

const ROOT::Math::IMultiGenFunction *	ObjFunction () const
	return pointer to used objective function More...

void	PrintResult () const
	print result of minimization More...

virtual bool	ReleaseVariable (unsigned int ivar)
	release an existing variable More...

virtual bool	SetFixedVariable (unsigned int, const std::string &, double)
	set fixed variable (override if minimizer supports them ) More...

virtual void	SetFunction (const ROOT::Math::IMultiGenFunction &func)
	set the function to minimize More...

virtual void	SetFunction (const ROOT::Math::IMultiGradFunction &func)
	set gradient the function to minimize More...

virtual bool	SetLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double, double)
	set upper/lower limited variable (override if minimizer supports them ) More...

virtual bool	SetLowerLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double lower)
	set lower limit variable (override if minimizer supports them ) More...

virtual bool	SetUpperLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double upper)
	set upper limit variable (override if minimizer supports them ) More...

virtual bool	SetVariable (unsigned int ivar, const std::string &name, double val, double step)
	set free variable More...

virtual bool	SetVariableLimits (unsigned int ivar, double lower, double upper)
	set the limits of an already existing variable More...

virtual bool	SetVariableLowerLimit (unsigned int ivar, double lower)
	set the lower-limit of an already existing variable More...

virtual bool	SetVariableStepSize (unsigned int ivar, double step)
	set the step size of an already existing variable More...

virtual bool	SetVariableUpperLimit (unsigned int ivar, double upper)
	set the upper-limit of an already existing variable More...

virtual bool	SetVariableValue (unsigned int ivar, double val)
	set the value of an existing variable More...

virtual bool	SetVariableValues (const double *x)
	set the values of all existing variables (array must be dimensioned to the size of existing parameters) More...

virtual const double *	StepSizes () const
	accessor methods More...

const ROOT::Math::MinimTransformFunction *	TransformFunction () const
	return transformation function (NULL if not having a transformation) More...

virtual int	VariableIndex (const std::string &name) const
	get index of variable given a variable given a name return -1 if variable is not found More...

virtual std::string	VariableName (unsigned int ivar) const
	get name of variables (override if minimizer support storing of variable names) More...

virtual const double *	X () const
	return pointer to X values at the minimum More...

Public Member Functions inherited from ROOT::Math::Minimizer
	Minimizer ()
	Default constructor. More...

virtual	~Minimizer ()
	Destructor (no operations) More...

virtual void	Clear ()
	reset for consecutive minimizations - implement if needed More...

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

virtual double	Correlation (unsigned int i, unsigned int j) const
	return correlation coefficient between variable i and j. More...

virtual double	CovMatrix (unsigned int ivar, unsigned int jvar) const
	return covariance matrices element for variables ivar,jvar if the variable is fixed the return value is zero The ordering of the variables is the same as in the parameter and errors vectors More...

virtual int	CovMatrixStatus () const
	return status of covariance matrix using Minuit convention {0 not calculated 1 approximated 2 made pos def , 3 accurate} Minimizer who implements covariance matrix calculation will re-implement the method More...

virtual double	Edm () const
	return expected distance reached from the minimum (re-implement if minimizer provides it More...

double	ErrorDef () const
	return the statistical scale used for calculate the error is typically 1 for Chi2 and 0.5 for likelihood minimization More...

virtual const double *	Errors () const
	return errors at the minimum More...

virtual bool	FixVariable (unsigned int ivar)
	fix an existing variable More...

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. More...

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. More...

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 (This feature is not yet implemented) More...

virtual bool	GetVariableSettings (unsigned int ivar, ROOT::Fit::ParameterSettings &pars) const
	get variable settings in a variable object (like ROOT::Fit::ParamsSettings) More...

virtual double	GlobalCC (unsigned int ivar) const
	return 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. More...

virtual bool	Hesse ()
	perform a full calculation of the Hessian matrix for error calculation More...

virtual bool	IsFixedVariable (unsigned int ivar) const
	query if an existing variable is fixed (i.e. More...

bool	IsValidError () const
	return true if Minimizer has performed a detailed error validation (e.g. run Hesse for Minuit) More...

unsigned int	MaxFunctionCalls () const
	max number of function calls More...

unsigned int	MaxIterations () const
	max iterations More...

virtual const double *	MinGradient () const
	return pointer to gradient values at the minimum More...

virtual bool	Minimize ()=0
	method to perform the minimization More...

virtual double	MinValue () const =0
	return minimum function value More...

virtual unsigned int	NCalls () const
	number of function calls to reach the minimum More...

virtual unsigned int	NDim () const =0
	this is <= Function().NDim() which is the total number of variables (free+ constrained ones) More...

virtual unsigned int	NFree () const
	number of free variables (real dimension of the problem) this is <= Function().NDim() which is the total (re-implement if minimizer supports bounded parameters) More...

virtual unsigned int	NIterations () const
	number of iterations to reach the minimum More...

virtual MinimizerOptions	Options () const
	retrieve the minimizer options (implement derived class if needed) More...

double	Precision () const
	precision of minimizer in the evaluation of the objective function ( a value <=0 corresponds to the let the minimizer choose its default one) More...

int	PrintLevel () const
	minimizer configuration parameters More...

virtual void	PrintResults ()
	return reference to the objective function virtual const ROOT::Math::IGenFunction & Function() const = 0; More...

virtual bool	ProvidesError () const
	minimizer provides error and error matrix More...

virtual bool	ReleaseVariable (unsigned int ivar)
	release an existing variable More...

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. More...

void	SetDefaultOptions ()
	reset the defaut options (defined in MinimizerOptions) More...

void	SetErrorDef (double up)
	set scale for calculating the errors More...

virtual bool	SetFixedVariable (unsigned int ivar, const std::string &name, double val)
	set a new fixed variable (override if minimizer supports them ) More...

virtual void	SetFunction (const ROOT::Math::IMultiGenFunction &func)=0
	set the function to minimize More...

virtual void	SetFunction (const ROOT::Math::IMultiGradFunction &func)
	set a function to minimize using gradient More...

virtual bool	SetLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double lower, double upper)
	set a new upper/lower limited variable (override if minimizer supports them ) otherwise as default set an unlimited variable More...

virtual bool	SetLowerLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double lower)
	set a new lower limit variable (override if minimizer supports them ) More...

void	SetMaxFunctionCalls (unsigned int maxfcn)
	set maximum of function calls More...

void	SetMaxIterations (unsigned int maxiter)
	set maximum iterations (one iteration can have many function calls) More...

void	SetOptions (const MinimizerOptions &opt)
	set all options in one go More...

void	SetPrecision (double prec)
	set in the minimizer the objective function evaluation precision ( a value <=0 means the minimizer will choose its optimal value automatically, i.e. More...

void	SetPrintLevel (int level)
	set print level More...

void	SetStrategy (int strategyLevel)
	set the strategy More...

void	SetTolerance (double tol)
	set the tolerance More...

virtual bool	SetUpperLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double upper)
	set a new upper limit variable (override if minimizer supports them ) More...

void	SetValidError (bool on)
	flag to check if minimizer needs to perform accurate error analysis (e.g. run Hesse for Minuit) More...

virtual bool	SetVariable (unsigned int ivar, const std::string &name, double val, double step)=0
	set a new free variable More...

virtual bool	SetVariableInitialRange (unsigned int, double, double)
	set the initial range of an existing variable More...

virtual bool	SetVariableLimits (unsigned int ivar, double lower, double upper)
	set the limits of an already existing variable More...

virtual bool	SetVariableLowerLimit (unsigned int ivar, double lower)
	set the lower-limit of an already existing variable More...

template<class VariableIterator >
int	SetVariables (const VariableIterator &begin, const VariableIterator &end)
	add variables . Return number of variables successfully added More...

virtual bool	SetVariableStepSize (unsigned int ivar, double value)
	set the step size of an already existing variable More...

virtual bool	SetVariableUpperLimit (unsigned int ivar, double upper)
	set the upper-limit of an already existing variable More...

virtual bool	SetVariableValue (unsigned int ivar, double value)
	set the value of an already existing variable More...

virtual bool	SetVariableValues (const double *x)
	set the values of all existing variables (array must be dimensioned to the size of the existing parameters) More...

int	Status () const
	status code of minimizer More...

int	Strategy () const
	strategy More...

double	Tolerance () const
	absolute tolerance More...

virtual int	VariableIndex (const std::string &name) const
	get index of variable given a variable given a name return -1 if variable is not found More...

virtual std::string	VariableName (unsigned int ivar) const
	get name of variables (override if minimizer support storing of variable names) return an empty string if variable is not found More...

virtual const double *	X () const =0
	return pointer to X values at the minimum More...

Private Member Functions
	GSLNLSMinimizer (const GSLNLSMinimizer &)
	Copy constructor. More...

GSLNLSMinimizer &	operator= (const GSLNLSMinimizer &rhs)
	Assignment operator. More...

Private Attributes
const ROOT::Math::FitMethodFunction *	fChi2Func

std::vector< double >	fCovMatrix

double	fEdm

std::vector< double >	fErrors

ROOT::Math::GSLMultiFit *	fGSLMultiFit

double	fLSTolerance

unsigned int	fNFree

std::vector< LSResidualFunc >	fResiduals

unsigned int	fSize

Additional Inherited Members
Protected Member Functions inherited from ROOT::Math::BasicMinimizer
bool	CheckDimension () const

bool	CheckObjFunction () const

MinimTransformFunction *	CreateTransformation (std::vector< double > &startValues, const ROOT::Math::IMultiGradFunction *func=0)

void	SetFinalValues (const double *x)

void	SetMinValue (double val)

Protected Attributes inherited from ROOT::Math::Minimizer
MinimizerOptions	fOptions

int	fStatus

bool	fValidError

#include <Math/GSLNLSMinimizer.h>

Inheritance diagram for ROOT::Math::GSLNLSMinimizer:

[legend]

Constructor & Destructor Documentation

◆ GSLNLSMinimizer() [1/2]

ROOT::Math::GSLNLSMinimizer::GSLNLSMinimizer ( int type = 0 )

Default constructor.

Definition at line 136 of file GSLNLSMinimizer.cxx.

◆ ~GSLNLSMinimizer()

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

Destructor (no operations)

Definition at line 161 of file GSLNLSMinimizer.cxx.

◆ GSLNLSMinimizer() [2/2]

ROOT::Math::GSLNLSMinimizer::GSLNLSMinimizer ( const GSLNLSMinimizer & )

inlineprivate

Copy constructor.

Definition at line 172 of file GSLNLSMinimizer.h.

Member Function Documentation

◆ CovMatrix()

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

virtual

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 371 of file GSLNLSMinimizer.cxx.

◆ CovMatrixStatus()

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

virtual

return covariance matrix status

Reimplemented from ROOT::Math::Minimizer.

Definition at line 379 of file GSLNLSMinimizer.cxx.

◆ Edm()

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

inlinevirtual

return expected distance reached from the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 196 of file GSLNLSMinimizer.h.

◆ Errors()

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

inlinevirtual

return errors at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 213 of file GSLNLSMinimizer.h.

◆ MinGradient()

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

virtual

return pointer to gradient values at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 365 of file GSLNLSMinimizer.cxx.

◆ Minimize()

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

virtual

method to perform the minimization

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 200 of file GSLNLSMinimizer.cxx.

◆ NCalls()

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

inlinevirtual

number of function calls to reach the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 203 of file GSLNLSMinimizer.h.

◆ operator=()

GSLNLSMinimizer & ROOT::Math::GSLNLSMinimizer::operator= ( const GSLNLSMinimizer & rhs )

inlineprivate

Assignment operator.

Definition at line 177 of file GSLNLSMinimizer.h.

◆ ProvidesError()

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

inlinevirtual

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 210 of file GSLNLSMinimizer.h.

◆ SetFunction() [1/2]

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

virtual

set the function to minimize

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 168 of file GSLNLSMinimizer.cxx.

◆ SetFunction() [2/2]

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

virtual

set gradient the function to minimize

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 193 of file GSLNLSMinimizer.cxx.

Member Data Documentation

◆ fChi2Func

const ROOT::Math::FitMethodFunction* ROOT::Math::GSLNLSMinimizer::fChi2Func

private

Definition at line 238 of file GSLNLSMinimizer.h.

◆ fCovMatrix

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

private

Definition at line 243 of file GSLNLSMinimizer.h.

◆ fEdm

double ROOT::Math::GSLNLSMinimizer::fEdm

private

Definition at line 240 of file GSLNLSMinimizer.h.

◆ fErrors

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

private

Definition at line 242 of file GSLNLSMinimizer.h.

◆ fGSLMultiFit

ROOT::Math::GSLMultiFit* ROOT::Math::GSLNLSMinimizer::fGSLMultiFit

private

Definition at line 237 of file GSLNLSMinimizer.h.

◆ fLSTolerance

double ROOT::Math::GSLNLSMinimizer::fLSTolerance

private

Definition at line 241 of file GSLNLSMinimizer.h.

◆ fNFree

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

private

Definition at line 234 of file GSLNLSMinimizer.h.

◆ fResiduals

std::vector<LSResidualFunc> ROOT::Math::GSLNLSMinimizer::fResiduals

private

Definition at line 244 of file GSLNLSMinimizer.h.

◆ fSize

unsigned int ROOT::Math::GSLNLSMinimizer::fSize

private

Definition at line 235 of file GSLNLSMinimizer.h.

Libraries for ROOT::Math::GSLNLSMinimizer:

[legend]

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Constructor & Destructor Documentation

◆ GSLNLSMinimizer() [1/2]

◆ ~GSLNLSMinimizer()

◆ GSLNLSMinimizer() [2/2]

Member Function Documentation

◆ CovMatrix()

◆ CovMatrixStatus()

◆ Edm()

◆ Errors()

◆ MinGradient()

◆ Minimize()

◆ NCalls()

◆ operator=()

◆ ProvidesError()

◆ SetFunction() [1/2]

◆ SetFunction() [2/2]

Member Data Documentation

◆ fChi2Func

◆ fCovMatrix

◆ fEdm

◆ fErrors

◆ fGSLMultiFit

◆ fLSTolerance

◆ fNFree

◆ fResiduals

◆ fSize