TLinearMinimizer class: minimizer implementation based on TMinuit.

Definition at line 31 of file TLinearMinimizer.h.

Public Member Functions
	TLinearMinimizer (const char *type)
	Constructor from a char * (used by PM)

	TLinearMinimizer (int type=0)
	Default constructor.

	~TLinearMinimizer () override
	Destructor (no operations)

double	CovMatrix (unsigned int i, unsigned int j) 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

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

virtual TClass *	IsA () const

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

bool	Minimize () override
	method to perform the minimization

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

unsigned int	NFree () const override
	number of free variables (real dimension of the problem) this is <= Function().NDim() which is the total

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

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 fit model function

bool	SetVariable (unsigned int, const std::string &, double, double) override
	set free variable (dummy impl. since there is no need to set variables in the Linear Fitter)

virtual void	Streamer (TBuffer &)

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

const double *	X () const override
	return pointer to X values at the minimum

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

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

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.

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(const std::vector< 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

Static Public Member Functions
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Private Member Functions
	TLinearMinimizer (const TLinearMinimizer &)
	Copy constructor.

TLinearMinimizer &	operator= (const TLinearMinimizer &rhs)
	Assignment operator.

Private Attributes
std::vector< double >	fCovar

unsigned int	fDim

std::vector< double >	fErrors

TLinearFitter *	fFitter

double	fMinVal

unsigned int	fNFree

const ROOT::Math::IMultiGradFunction *	fObjFunc

std::vector< double >	fParams

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

Additional Inherited Members
Protected Attributes inherited from ROOT::Math::Minimizer
MinimizerOptions	fOptions
	minimizer options

int	fStatus
	status of minimizer

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

#include <TLinearMinimizer.h>

Inheritance diagram for TLinearMinimizer:

[legend]

Constructor & Destructor Documentation

◆ TLinearMinimizer() [1/3]

TLinearMinimizer::TLinearMinimizer ( int type = 0 )

Default constructor.

Definition at line 71 of file TLinearMinimizer.cxx.

◆ TLinearMinimizer() [2/3]

TLinearMinimizer::TLinearMinimizer ( const char * type )

Constructor from a char * (used by PM)

Definition at line 83 of file TLinearMinimizer.cxx.

◆ ~TLinearMinimizer()

TLinearMinimizer::~TLinearMinimizer ( )

override

Destructor (no operations)

Definition at line 101 of file TLinearMinimizer.cxx.

◆ TLinearMinimizer() [3/3]

TLinearMinimizer::TLinearMinimizer ( const TLinearMinimizer & )

private

Copy constructor.

Definition at line 107 of file TLinearMinimizer.cxx.

Member Function Documentation

◆ Class()

static TClass * TLinearMinimizer::Class ( )

static

Returns: TClass describing this class

◆ Class_Name()

static const char * TLinearMinimizer::Class_Name ( )

static

Returns: Name of this class

◆ Class_Version()

static constexpr Version_t TLinearMinimizer::Class_Version ( )

inlinestaticconstexpr

Returns: Version of this class

Definition at line 141 of file TLinearMinimizer.h.

◆ CovMatrix()

double TLinearMinimizer::CovMatrix	(	unsigned int	i,
		unsigned int	j
	)		const

inlineoverridevirtual

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 110 of file TLinearMinimizer.h.

◆ CovMatrixStatus()

int TLinearMinimizer::CovMatrixStatus ( ) const

inlineoverridevirtual

return covariance matrix status

Reimplemented from ROOT::Math::Minimizer.

Definition at line 115 of file TLinearMinimizer.h.

◆ DeclFileName()

static const char * TLinearMinimizer::DeclFileName ( )

inlinestatic

Returns: Name of the file containing the class declaration

Definition at line 141 of file TLinearMinimizer.h.

◆ Edm()

double TLinearMinimizer::Edm ( ) const

inlineoverridevirtual

return expected distance reached from the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 81 of file TLinearMinimizer.h.

◆ Errors()

const double * TLinearMinimizer::Errors ( ) const

inlineoverridevirtual

return errors at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 104 of file TLinearMinimizer.h.

◆ IsA()

virtual TClass * TLinearMinimizer::IsA ( ) const

inlinevirtual

Returns: TClass describing current object

Definition at line 141 of file TLinearMinimizer.h.

◆ MinGradient()

const double * TLinearMinimizer::MinGradient ( ) const

inlineoverridevirtual

return pointer to gradient values at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 87 of file TLinearMinimizer.h.

◆ Minimize()

bool TLinearMinimizer::Minimize ( )

overridevirtual

method to perform the minimization

Implements ROOT::Math::Minimizer.

Definition at line 192 of file TLinearMinimizer.cxx.

◆ MinValue()

double TLinearMinimizer::MinValue ( ) const

inlineoverridevirtual

return minimum function value

Implements ROOT::Math::Minimizer.

Definition at line 78 of file TLinearMinimizer.h.

◆ NCalls()

unsigned int TLinearMinimizer::NCalls ( ) const

inlineoverridevirtual

number of function calls to reach the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 90 of file TLinearMinimizer.h.

◆ NDim()

unsigned int TLinearMinimizer::NDim ( ) const

inlineoverridevirtual

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

Implements ROOT::Math::Minimizer.

Definition at line 94 of file TLinearMinimizer.h.

◆ NFree()

unsigned int TLinearMinimizer::NFree ( ) const

inlineoverridevirtual

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

Reimplemented from ROOT::Math::Minimizer.

Definition at line 98 of file TLinearMinimizer.h.

◆ operator=()

TLinearMinimizer & TLinearMinimizer::operator= ( const TLinearMinimizer & rhs )

private

Assignment operator.

Definition at line 113 of file TLinearMinimizer.cxx.

◆ ProvidesError()

bool TLinearMinimizer::ProvidesError ( ) const

inlineoverridevirtual

minimizer provides error and error matrix

Reimplemented from ROOT::Math::Minimizer.

Definition at line 101 of file TLinearMinimizer.h.

◆ SetFixedVariable()

bool TLinearMinimizer::SetFixedVariable	(	unsigned int	ivar,
		const std::string &	,
		double	val
	)

overridevirtual

set fixed variable (override if minimizer supports them )

Reimplemented from ROOT::Math::Minimizer.

Definition at line 185 of file TLinearMinimizer.cxx.

◆ SetFunction()

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

overridevirtual

set the fit model function

Implements ROOT::Math::Minimizer.

Definition at line 121 of file TLinearMinimizer.cxx.

◆ SetVariable()

bool TLinearMinimizer::SetVariable	(	unsigned int	,
		const std::string &	,
		double	,
		double
	)

inlineoverridevirtual

set free variable (dummy impl. since there is no need to set variables in the Linear Fitter)

Implements ROOT::Math::Minimizer.

Definition at line 69 of file TLinearMinimizer.h.

◆ Streamer()

virtual void TLinearMinimizer::Streamer ( TBuffer & )

virtual

◆ StreamerNVirtual()

void TLinearMinimizer::StreamerNVirtual ( TBuffer & ClassDef_StreamerNVirtual_b )

inline

Definition at line 141 of file TLinearMinimizer.h.

◆ X()

const double * TLinearMinimizer::X ( ) const

inlineoverridevirtual

return pointer to X values at the minimum

Implements ROOT::Math::Minimizer.

Definition at line 84 of file TLinearMinimizer.h.

Member Data Documentation

◆ fCovar

std::vector<double> TLinearMinimizer::fCovar

private

Definition at line 136 of file TLinearMinimizer.h.

◆ fDim

unsigned int TLinearMinimizer::fDim

private

Definition at line 131 of file TLinearMinimizer.h.

◆ fErrors

std::vector<double> TLinearMinimizer::fErrors

private

Definition at line 135 of file TLinearMinimizer.h.

◆ fFitter

TLinearFitter* TLinearMinimizer::fFitter

private

Definition at line 139 of file TLinearMinimizer.h.

◆ fMinVal

double TLinearMinimizer::fMinVal

private

Definition at line 133 of file TLinearMinimizer.h.

◆ fNFree

unsigned int TLinearMinimizer::fNFree

private

Definition at line 132 of file TLinearMinimizer.h.

◆ fObjFunc

const ROOT::Math::IMultiGradFunction* TLinearMinimizer::fObjFunc

private

Definition at line 138 of file TLinearMinimizer.h.

◆ fParams

std::vector<double> TLinearMinimizer::fParams

private

Definition at line 134 of file TLinearMinimizer.h.

◆ fRobust

bool TLinearMinimizer::fRobust

private

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

Definition at line 130 of file TLinearMinimizer.h.

Libraries for TLinearMinimizer:

[legend]

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

math/minuit/inc/TLinearMinimizer.h
math/minuit/src/TLinearMinimizer.cxx

Public Member Functions

Static Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Constructor & Destructor Documentation

◆ TLinearMinimizer() [1/3]

◆ TLinearMinimizer() [2/3]

◆ ~TLinearMinimizer()

◆ TLinearMinimizer() [3/3]

Member Function Documentation

◆ Class()

◆ Class_Name()

◆ Class_Version()

◆ CovMatrix()

◆ CovMatrixStatus()

◆ DeclFileName()

◆ Edm()

◆ Errors()

◆ IsA()

◆ MinGradient()

◆ Minimize()

◆ MinValue()

◆ NCalls()

◆ NDim()

◆ NFree()

◆ operator=()

◆ ProvidesError()

◆ SetFixedVariable()

◆ SetFunction()

◆ SetVariable()

◆ Streamer()

◆ StreamerNVirtual()

◆ X()

Member Data Documentation

◆ fCovar

◆ fDim

◆ fErrors

◆ fFitter

◆ fMinVal

◆ fNFree

◆ fObjFunc

◆ fParams

◆ fRobust