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ROOT » MATH » MATHMORE » ROOT::Math::GSLNLSMinimizer

class ROOT::Math::GSLNLSMinimizer: public ROOT::Math::Minimizer


    LSResidualFunc class description.
    Internal class used for accessing the residuals of the Least Square function
    and their derivates which are estimated numerically using GSL numerical derivation.
    The class contains a pointer to the fit method function and an index specifying
    the i-th residual and wraps it in a multi-dim gradient function interface
    ROOT::Math::IGradientFunctionMultiDim.
    The class is used by ROOT::Math::GSLNLSMinimizer (GSL non linear least square fitter)

    @ingroup MultiMin

Function Members (Methods)

public:

virtual	~GSLNLSMinimizer()
virtual void	ROOT::Math::Minimizer::Clear()
virtual bool	ROOT::Math::Minimizer::Contour(unsigned int, unsigned int, unsigned int&, double, double)
virtual double	ROOT::Math::Minimizer::Correlation(unsigned int i, unsigned int j) const
virtual double	CovMatrix(unsigned int, unsigned int) const
virtual int	CovMatrixStatus() const
virtual double	Edm() const
double	ROOT::Math::Minimizer::ErrorDef() const
virtual const double*	Errors() const
virtual bool	ROOT::Math::Minimizer::GetCovMatrix(double*) const
virtual bool	ROOT::Math::Minimizer::GetHessianMatrix(double*) const
virtual bool	ROOT::Math::Minimizer::GetMinosError(unsigned int, double& errLow, double& errUp, int = 0)
virtual double	ROOT::Math::Minimizer::GlobalCC(unsigned int) const
ROOT::Math::GSLNLSMinimizer	GSLNLSMinimizer(int type = 0)
virtual bool	ROOT::Math::Minimizer::Hesse()
bool	ROOT::Math::Minimizer::IsValidError() const
unsigned int	ROOT::Math::Minimizer::MaxFunctionCalls() const
unsigned int	ROOT::Math::Minimizer::MaxIterations() const
virtual const double*	MinGradient() const
virtual bool	Minimize()
virtual double	MinValue() const
virtual unsigned int	NCalls() const
virtual unsigned int	NDim() const
virtual unsigned int	NFree() const
virtual ROOT::Math::MinimizerOptions	ROOT::Math::Minimizer::Options() const
double	ROOT::Math::Minimizer::Precision() const
int	ROOT::Math::Minimizer::PrintLevel() const
virtual void	ROOT::Math::Minimizer::PrintResults()
virtual bool	ProvidesError() const
virtual bool	ROOT::Math::Minimizer::Scan(unsigned int, unsigned int&, double, double, double = 0, double = 0)
void	ROOT::Math::Minimizer::SetDefaultOptions()
void	ROOT::Math::Minimizer::SetErrorDef(double up)
virtual bool	SetFixedVariable(unsigned int ivar, const string& name, double val)
virtual void	SetFunction(const ROOT::Math::IMultiGenFunction& func)
virtual void	SetFunction(const ROOT::Math::IMultiGradFunction& func)
virtual bool	SetLimitedVariable(unsigned int ivar, const string& name, double val, double step, double lower, double upper)
virtual bool	SetLowerLimitedVariable(unsigned int ivar, const string& name, double val, double step, double lower)
void	ROOT::Math::Minimizer::SetMaxFunctionCalls(unsigned int maxfcn)
void	ROOT::Math::Minimizer::SetMaxIterations(unsigned int maxiter)
void	ROOT::Math::Minimizer::SetOptions(const ROOT::Math::MinimizerOptions& opt)
void	ROOT::Math::Minimizer::SetPrecision(double prec)
void	ROOT::Math::Minimizer::SetPrintLevel(int level)
void	ROOT::Math::Minimizer::SetStrategy(int strategyLevel)
void	ROOT::Math::Minimizer::SetTolerance(double tol)
virtual bool	SetUpperLimitedVariable(unsigned int ivar, const string& name, double val, double step, double upper)
void	ROOT::Math::Minimizer::SetValidError(bool on)
virtual bool	SetVariable(unsigned int ivar, const string& name, double val, double step)
virtual bool	SetVariableValue(unsigned int ivar, double val)
virtual bool	SetVariableValues(const double* x)
int	ROOT::Math::Minimizer::Status() const
int	ROOT::Math::Minimizer::Strategy() const
double	ROOT::Math::Minimizer::Tolerance() const
virtual int	ROOT::Math::Minimizer::VariableIndex(const string&) const
virtual string	ROOT::Math::Minimizer::VariableName(unsigned int) const
virtual const double*	X() const

private:

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

Data Members

protected:

int	ROOT::Math::Minimizer::fDebug	print level
unsigned int	ROOT::Math::Minimizer::fMaxCalls	max number of function calls
unsigned int	ROOT::Math::Minimizer::fMaxIter	max number or iterations used to find the minimum
double	ROOT::Math::Minimizer::fPrec	precision
int	ROOT::Math::Minimizer::fStatus	status of minimizer
int	ROOT::Math::Minimizer::fStrategy	minimizer strategy
double	ROOT::Math::Minimizer::fTol	tolerance (absolute)
double	ROOT::Math::Minimizer::fUp	error scale
bool	ROOT::Math::Minimizer::fValidError	flag to control if errors have been validated (Hesse has been run in case of Minuit)

private:

map<unsigned int,std::pair<double,double> >	fBounds	map specifying the bound using as key the parameter index
vector<double>	fCovMatrix	cov matrix (stored as cov[ i * dim + j]
unsigned int	fDim	dimension of the function to be minimized
double	fEdm	edm value
vector<double>	fErrors
ROOT::Math::GSLMultiFit*	fGSLMultiFit	pointer to GSL multi fit solver
double	fLSTolerance	Line Search Tolerance
double	fMinVal	minimum function value
unsigned int	fNFree	dimension of the internal function to be minimized
vector<std::string>	fNames
const ROOT::Math::FitMethodFunction*	fObjFunc	pointer to Least square function
vector<LSResidualFunc>	fResiduals	! transient Vector of the residual functions
unsigned int	fSize	number of fit points (residuals)
vector<double>	fSteps
vector<double>	fValues
vector<ROOT::Math::EMinimVariableType>	fVarTypes	vector specifyng the type of variables

Class Charts

Inheritance Inherited Members Includes Libraries

Function documentation

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

unsigned int NDim() const

{ return fChi2->NDim(); }

GSLNLSMinimizer(int type = 0)

      Default constructor

~GSLNLSMinimizer()

      Destructor (no operations)

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

 usually copying is non trivial, so we make this unaccessible

      Copy constructor

{}

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

 set the function to minimize

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

 set gradient the function to minimize

bool SetVariable(unsigned int ivar, const string& name, double val, double step)

 set free variable

bool SetLowerLimitedVariable(unsigned int ivar, const string& name, double val, double step, double lower)

 set lower limited variable

bool SetUpperLimitedVariable(unsigned int ivar, const string& name, double val, double step, double upper)

 set upper limited variable

bool SetLimitedVariable(unsigned int ivar, const string& name, double val, double step, double lower, double upper)

 set upper/lower limited variable

bool SetFixedVariable(unsigned int ivar, const string& name, double val)

 set fixed variable

bool SetVariableValue(unsigned int ivar, double val)

 set the value of an existing variable

bool SetVariableValues(const double* x)

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

bool Minimize()

 method to perform the minimization

double MinValue() const

 return minimum function value

{ return fMinVal; }

double Edm() const

 return expected distance reached from the minimum

const double * X() const

 return  pointer to X values at the minimum

{ return &fValues.front(); }

const double * MinGradient() const

 return pointer to gradient values at the minimum

unsigned int NCalls() const

 number of function calls to reach the minimum

{ return (fObjFunc) ? fObjFunc->NCalls() : 0; }

unsigned int NFree() const

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

{ return fNFree; }

bool ProvidesError() const

 minimizer provides error and error matrix

{ return true; }

const double * Errors() const

 return errors at the minimum

{ return (fErrors.size() > 0) ? &fErrors.front() : 0; }

double CovMatrix(unsigned int , unsigned int ) const

  {
       static std::vector<double> err;
       err.resize(fDim);
       return &err.front();
    }
 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

 return covariance matrix status