Abstract Minimizer class, defining the interface for the various minimizer (like Minuit2, Minuit, GSL, etc..) in ROOT.

Plug-in's exist in ROOT to be able to instantiate the derived classes without linking the library using the static function ROOT::Math::Factory::CreateMinimizer.

Here is the list of all possible minimizers and their respective methods (algorithms) that can be instantiated: The name shown below can be used to create them. More documentation can be found in the respective class

Minuit (class TMinuitMinimizer)
- Migrad (default)
- MigradImproved (Migrad with adding a method to improve minimization when ends-up in a local minimum, see par. 6.3 of Minuit tutorial on Function Minimization)
- Simplex
- Minimize (a combination of Simplex + Migrad)
- Minimize
- Scan
- Seek
Minuit2 (class ROOT::Minuit2::Minuit2Minimizer)
- Migrad (default)
- Simplex
- Minimize
- Fumili (Fumili2)
- Scan
Fumili (class TFumiliMinimizer)
GSLMultiMin (class ROOT::Math::GSLMinimizer) available when ROOT is built with mathmore support
- BFGS2 (Default)
- BFGS
- ConjugateFR
- ConjugatePR
- SteepestDescent
GSLMultiFit (class ROOT::Math::GSLNLMinimizer) available when ROOT is built mathmore support
GSLSimAn (class ROOT::Math::GSLSimAnMinimizer) available when ROOT is built with mathmore support
Genetic (class ROOT::Math::GeneticMinimizer)
RMinimizer (class ROOT::Math::RMinimizer) available when ROOT is built with r support
- BFGS (default)
- L-BFGS-S
- Nelder-Mead
- CG
- and more methods, see the Details in the documentation of the function optimix of the optmix R package

The Minimizer class provides the interface to perform the minimization including

In addition to provide the API for function minimization (via ROOT::Math::Minimizer::Minimize) the Minimizer class provides:

the interface for setting the function to be minimized. The objective function passed to the Minimizer must implement the multi-dimensional generic interface ROOT::Math::IBaseFunctionMultiDim. If the function provides gradient calculation (e.g. implementing the ROOT::Math::IGradientFunctionMultiDim interface) the gradient will be used by the Minimizer class, when needed. There are convenient classes for the users to wrap their own functions in this required interface for minimization. These are the ROOT::Math::Functor class and the ROOT::Math::GradFunctor class for wrapping functions providing both evaluation and gradient. Some methods, like Fumili, Fumili2 and GSLMultiFit are specialized method for least-square and also likelihood minimizations. They require then that the given function implements in addition the ROOT::Math::FitMethodFunction interface.
The interface for setting the initial values for the function variables (which are the parameters in of the model function in case of solving for fitting) and specifying their limits.
The interface to set and retrieve basic minimization parameters. These parameter are controlled by the class ROOT::Math::MinimizerOptions. When no parameters are specified the default ones are used. Specific Minimizer options can also be passed via the MinimizerOptions class. For the list of the available option parameter one must look at the documentation of the corresponding derived class.
The interface to retrieve the result of minimization ( minimum X values, function value, gradient, error on the minimum, etc...)
The interface to perform a Scan, Hesse or a Contour plot (for the minimizers that support this, i.e. Minuit and Minuit2)

An example on how to use this interface is the tutorial NumericalMinimization.C in the tutorials/fit directory.

Definition at line 119 of file Minimizer.h.

Public Member Functions
	Minimizer ()
	Default constructor.

	Minimizer (Minimizer &&)=delete

	Minimizer (Minimizer const &)=delete

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

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

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

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

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

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

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

virtual bool	FixVariable (unsigned int ivar)
	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

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

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.

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

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

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

unsigned int	MaxFunctionCalls () const
	max number of function calls

unsigned int	MaxIterations () const
	max iterations

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

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

virtual int	MinosStatus () const
	status code of Minos (to be re-implemented by the minimizers supporting Minos)

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

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

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

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)

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

Minimizer &	operator= (Minimizer &&)=delete

Minimizer &	operator= (Minimizer const &)=delete

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

int	PrintLevel () const
	minimizer configuration parameters

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

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

virtual bool	ReleaseVariable (unsigned int ivar)
	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

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

virtual void	SetFunction (const ROOT::Math::IMultiGenFunction &func)=0
	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)

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

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 )

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

void	SetPrintLevel (int level)
	set print level

void	SetStrategy (int strategyLevel)
	set the strategy

void	SetTolerance (double tol)
	set the tolerance

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 )

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

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

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

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

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

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

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

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

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

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

int	Status () const
	status code of minimizer

int	Strategy () const
	strategy

double	Tolerance () const
	absolute tolerance

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

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

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

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)

#include <Math/Minimizer.h>

Inheritance diagram for ROOT::Math::Minimizer:

[legend]

Constructor & Destructor Documentation

◆ Minimizer() [1/3]

ROOT::Math::Minimizer::Minimizer ( )

inline

Default constructor.

Definition at line 124 of file Minimizer.h.

◆ ~Minimizer()

virtual ROOT::Math::Minimizer::~Minimizer ( )

inlinevirtual

Destructor (no operations).

Definition at line 127 of file Minimizer.h.

◆ Minimizer() [2/3]

ROOT::Math::Minimizer::Minimizer ( Minimizer const & )

delete

◆ Minimizer() [3/3]

ROOT::Math::Minimizer::Minimizer ( Minimizer && )

delete

Member Function Documentation

◆ Clear()

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

inlinevirtual

reset for consecutive minimization - implement if needed

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

Definition at line 136 of file Minimizer.h.

◆ Contour()

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

virtual

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 TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

Definition at line 211 of file Minimizer.cxx.

◆ Correlation()

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

inlinevirtual

return 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 264 of file Minimizer.h.

◆ CovMatrix()

double ROOT::Math::Minimizer::CovMatrix	(	unsigned int	ivar,
		unsigned int	jvar
	)		const

virtual

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

Reimplemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, TLinearMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::RMinimizer, ROOT::Math::GSLMinimizer, and ROOT::Math::GSLNLSMinimizer.

Definition at line 120 of file Minimizer.cxx.

◆ CovMatrixStatus()

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

inlinevirtual

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

Reimplemented in TFumiliMinimizer, ROOT::Math::GSLNLSMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

Definition at line 256 of file Minimizer.h.

◆ Edm()

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

inlinevirtual

return expected distance reached from the minimum (re-implement if minimizer provides it

Reimplemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

Definition at line 222 of file Minimizer.h.

◆ ErrorDef()

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

inline

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

Definition at line 317 of file Minimizer.h.

◆ Errors()

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

inlinevirtual

return errors at the minimum

Reimplemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, TLinearMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::RMinimizer.

Definition at line 246 of file Minimizer.h.

◆ FixVariable()

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

virtual

fix an existing variable

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

Definition at line 87 of file Minimizer.cxx.

◆ GetCovMatrix()

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

virtual

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

Definition at line 135 of file Minimizer.cxx.

◆ GetHessianMatrix()

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

virtual

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 TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

Definition at line 148 of file Minimizer.cxx.

◆ GetMinosError()

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

virtual

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 TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

Definition at line 172 of file Minimizer.cxx.

◆ GetVariableSettings()

bool ROOT::Math::Minimizer::GetVariableSettings	(	unsigned int	ivar,
		ROOT::Fit::ParameterSettings &	pars
	)		const

virtual

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

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

Definition at line 109 of file Minimizer.cxx.

◆ GlobalCC()

double ROOT::Math::Minimizer::GlobalCC ( unsigned int ivar ) const

virtual

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.

Minimizer must overload method if implemented

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

Definition at line 161 of file Minimizer.cxx.

◆ Hesse()

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

virtual

perform a full calculation of the Hessian matrix for error calculation

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

Definition at line 185 of file Minimizer.cxx.

◆ IsFixedVariable()

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

virtual

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

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

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

Definition at line 102 of file Minimizer.cxx.

◆ IsValidError()

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

inline

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

Definition at line 320 of file Minimizer.h.

◆ MaxFunctionCalls()

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

inline

max number of function calls

Definition at line 294 of file Minimizer.h.

◆ MaxIterations()

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

inline

max iterations

Definition at line 297 of file Minimizer.h.

◆ MinGradient()

virtual const double * ROOT::Math::Minimizer::MinGradient ( ) const

inlinevirtual

return pointer to gradient values at the minimum

Reimplemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

Definition at line 225 of file Minimizer.h.

◆ Minimize()

virtual bool ROOT::Math::Minimizer::Minimize ( )

pure virtual

method to perform the minimization

Implemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, ROOT::Math::GSLSimAnMinimizer, TLinearMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::RMinimizer.

◆ MinosStatus()

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

inlinevirtual

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

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

Definition at line 313 of file Minimizer.h.

◆ MinValue()

virtual double ROOT::Math::Minimizer::MinValue ( ) const

pure virtual

return minimum function value

Implemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

◆ NCalls()

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

inlinevirtual

number of function calls to reach the minimum

Reimplemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, ROOT::Math::GSLSimAnMinimizer, TLinearMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::RMinimizer.

Definition at line 228 of file Minimizer.h.

◆ NDim()

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

pure virtual

this is <= Function().NDim() which is the total number of variables (free+ constrained ones)

Implemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

◆ NFree()

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

inlinevirtual

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

Reimplemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

Definition at line 240 of file Minimizer.h.

◆ NIterations()

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

inlinevirtual

number of iterations to reach the minimum

Definition at line 231 of file Minimizer.h.

◆ operator=() [1/2]

Minimizer & ROOT::Math::Minimizer::operator= ( Minimizer && )

delete

◆ operator=() [2/2]

Minimizer & ROOT::Math::Minimizer::operator= ( Minimizer const & )

delete

◆ Options()

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

inlinevirtual

retrieve the minimizer options (implement derived class if needed)

Reimplemented in ROOT::Math::GeneticMinimizer.

Definition at line 323 of file Minimizer.h.

◆ Precision()

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

inline

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 304 of file Minimizer.h.

◆ PrintLevel()

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

inline

minimizer configuration parameters

set print level

Definition at line 291 of file Minimizer.h.

◆ PrintResults()

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

inlinevirtual

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

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

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

Definition at line 282 of file Minimizer.h.

◆ ProvidesError()

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

inlinevirtual

minimizer provides error and error matrix

Reimplemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, TLinearMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::RMinimizer.

Definition at line 243 of file Minimizer.h.

◆ ReleaseVariable()

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

virtual

release an existing variable

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

Definition at line 94 of file Minimizer.cxx.

◆ Scan()

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

virtual

scan function minimum for variable i.

Variable and function must be set before using Scan Return false if an error or if minimizer does not support this functionality

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

Definition at line 195 of file Minimizer.cxx.

◆ SetCovariance()

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

virtual

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 25 of file Minimizer.cxx.

◆ SetCovarianceDiag()

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

virtual

set initial second derivatives

Reimplemented in ROOT::Minuit2::Minuit2Minimizer.

Definition at line 15 of file Minimizer.cxx.

◆ SetDefaultOptions()

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

inline

reset the default options (defined in MinimizerOptions)

Definition at line 361 of file Minimizer.h.

◆ SetErrorDef()

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

inline

set scale for calculating the errors

Definition at line 347 of file Minimizer.h.

◆ SetExtraOptions()

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

inline

set only the extra options

Definition at line 358 of file Minimizer.h.

◆ SetFixedVariable()

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

virtual

set a new fixed variable (override if minimizer supports them )

Reimplemented in ROOT::Math::GeneticMinimizer, TFumiliMinimizer, ROOT::Math::BasicMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

Definition at line 44 of file Minimizer.cxx.

◆ SetFunction()

virtual void ROOT::Math::Minimizer::SetFunction ( const ROOT::Math::IMultiGenFunction & func )

pure virtual

set the function to minimize

Implemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

◆ SetHessianFunction()

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

inlinevirtual

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

Reimplemented in ROOT::Minuit2::Minuit2Minimizer.

Definition at line 142 of file Minimizer.h.

◆ SetLimitedVariable()

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

virtual

set a new upper/lower limited variable (override if minimizer supports them ) otherwise as default set an unlimited variable

Reimplemented in TFumiliMinimizer, ROOT::Math::BasicMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::GeneticMinimizer.

Definition at line 34 of file Minimizer.cxx.

◆ SetLowerLimitedVariable()

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

inlinevirtual

set a new lower limit variable (override if minimizer supports them )

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

Definition at line 175 of file Minimizer.h.

◆ SetMaxFunctionCalls()

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

inline

set maximum of function calls

Definition at line 331 of file Minimizer.h.

◆ SetMaxIterations()

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

inline

set maximum iterations (one iteration can have many function calls)

Definition at line 334 of file Minimizer.h.

◆ SetOptions()

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

inline

set all options in one go

Definition at line 353 of file Minimizer.h.

◆ SetPrecision()

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

inline

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 341 of file Minimizer.h.

◆ SetPrintLevel()

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

inline

set print level

Definition at line 328 of file Minimizer.h.

◆ SetStrategy()

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

inline

set the strategy

Definition at line 344 of file Minimizer.h.

◆ SetTolerance()

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

inline

set the tolerance

Definition at line 337 of file Minimizer.h.

◆ SetUpperLimitedVariable()

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

inlinevirtual

set a new upper limit variable (override if minimizer supports them )

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

Definition at line 179 of file Minimizer.h.

◆ SetValidError()

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

inline

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

Definition at line 350 of file Minimizer.h.

◆ SetVariable()

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

pure virtual

set a new free variable

Implemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and TLinearMinimizer.

◆ SetVariableInitialRange()

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

inlinevirtual

set the initial range of an existing variable

Definition at line 208 of file Minimizer.h.

◆ SetVariableLimits()

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

inlinevirtual

set the limits of an already existing variable

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

Definition at line 199 of file Minimizer.h.

◆ SetVariableLowerLimit()

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

virtual

set the lower-limit of an already existing variable

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

Definition at line 70 of file Minimizer.cxx.

◆ SetVariables()

template<class VariableIterator >

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

inline

add variables . Return number of variables successfully added

Definition at line 146 of file Minimizer.h.

◆ SetVariableStepSize()

bool ROOT::Math::Minimizer::SetVariableStepSize	(	unsigned int	ivar,
		double	value
	)

virtual

set the step size of an already existing variable

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

Definition at line 62 of file Minimizer.cxx.

◆ SetVariableUpperLimit()

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

virtual

set the upper-limit of an already existing variable

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

Definition at line 78 of file Minimizer.cxx.

◆ SetVariableValue()

bool ROOT::Math::Minimizer::SetVariableValue	(	unsigned int	ivar,
		double	value
	)

virtual

set the value of an already existing variable

Reimplemented in TFumiliMinimizer, ROOT::Math::BasicMinimizer, ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.

Definition at line 53 of file Minimizer.cxx.

◆ SetVariableValues()

virtual bool ROOT::Math::Minimizer::SetVariableValues ( const double * x )

inlinevirtual

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

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

Definition at line 187 of file Minimizer.h.

◆ Status()

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

inline

status code of minimizer

Definition at line 310 of file Minimizer.h.

◆ Strategy()

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

inline

strategy

Definition at line 307 of file Minimizer.h.

◆ Tolerance()

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

inline

absolute tolerance

Definition at line 300 of file Minimizer.h.

◆ VariableIndex()

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

virtual

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

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

Definition at line 232 of file Minimizer.cxx.

◆ VariableName()

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

virtual

get name of variables (override if minimizer support storing of variable names) return an empty string if variable is not found

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

Definition at line 224 of file Minimizer.cxx.

◆ X()

virtual const double * ROOT::Math::Minimizer::X ( ) const

pure virtual

return pointer to X values at the minimum

Implemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.

Member Data Documentation

◆ fOptions

MinimizerOptions ROOT::Math::Minimizer::fOptions

protected

minimizer options

Definition at line 370 of file Minimizer.h.

◆ fStatus

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

protected

status of minimizer

Definition at line 371 of file Minimizer.h.

◆ fValidError

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

protected

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

Definition at line 369 of file Minimizer.h.

Libraries for ROOT::Math::Minimizer:

[legend]

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

math/mathcore/inc/Math/Minimizer.h
math/mathcore/src/Minimizer.cxx

Public Member Functions

Protected Attributes

Constructor & Destructor Documentation

◆ Minimizer() [1/3]

◆ ~Minimizer()

◆ Minimizer() [2/3]

◆ Minimizer() [3/3]

Member Function Documentation

◆ Clear()

◆ Contour()

◆ Correlation()

◆ CovMatrix()

◆ CovMatrixStatus()

◆ Edm()

◆ ErrorDef()

◆ Errors()

◆ FixVariable()

◆ GetCovMatrix()

◆ GetHessianMatrix()

◆ GetMinosError()

◆ GetVariableSettings()

◆ GlobalCC()

◆ Hesse()

◆ IsFixedVariable()

◆ IsValidError()

◆ MaxFunctionCalls()

◆ MaxIterations()

◆ MinGradient()

◆ Minimize()

◆ MinosStatus()

◆ MinValue()

◆ NCalls()

◆ NDim()

◆ NFree()

◆ NIterations()

◆ operator=() [1/2]

◆ operator=() [2/2]

◆ Options()

◆ Precision()

◆ PrintLevel()

◆ PrintResults()

◆ ProvidesError()

◆ ReleaseVariable()

◆ Scan()

◆ SetCovariance()

◆ SetCovarianceDiag()

◆ SetDefaultOptions()

◆ SetErrorDef()

◆ SetExtraOptions()

◆ SetFixedVariable()

◆ SetFunction()

◆ SetHessianFunction()

◆ SetLimitedVariable()

◆ SetLowerLimitedVariable()

◆ SetMaxFunctionCalls()

◆ SetMaxIterations()

◆ SetOptions()

◆ SetPrecision()

◆ SetPrintLevel()

◆ SetStrategy()

◆ SetTolerance()

◆ SetUpperLimitedVariable()

◆ SetValidError()

◆ SetVariable()

◆ SetVariableInitialRange()

◆ SetVariableLimits()

◆ SetVariableLowerLimit()

◆ SetVariables()

◆ SetVariableStepSize()

◆ SetVariableUpperLimit()

◆ SetVariableValue()

◆ SetVariableValues()

◆ Status()

◆ Strategy()

◆ Tolerance()

◆ VariableIndex()

◆ VariableName()

◆ X()

Member Data Documentation

◆ fOptions