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ROOT » MATH » MATHMORE » ROOT::Math::GSLMinimizer

class ROOT::Math::GSLMinimizer: public ROOT::Math::Minimizer


   GSLMinimizer class.
   Implementation of the ROOT::Math::Minimizer interface using the GSL multi-dimensional
   minimization algorithms.

   See <A HREF="http://www.gnu.org/software/gsl/manual/html_node/Multidimensional-Minimization.html">GSL doc</A>
   from more info on the GSL minimization algorithms.

   The class implements the ROOT::Math::Minimizer interface and can be instantiated using the
   ROOT plugin manager (plugin name is "GSLMultiMin"). The varius minimization algorithms
   (conjugatefr, conjugatepr, bfgs, etc..) can be passed as enumerations and also as a string.
   The default algorithm is conjugatefr (Fletcher-Reeves conjugate gradient algorithm).

   @ingroup MultiMin

Function Members (Methods)

public:

virtual	~GSLMinimizer()
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	ROOT::Math::Minimizer::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::GSLMinimizer	GSLMinimizer(ROOT::Math::EGSLMinimizerType type = ROOT::Math::kConjugateFR)
ROOT::Math::GSLMinimizer	GSLMinimizer(const char* type)
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
const ROOT::Math::IMultiGradFunction*	ObjFunction() 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, const string&, double)
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, double)
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
const ROOT::Math::MinimTransformFunction*	TransformFunction() 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::GSLMinimizer	GSLMinimizer(const ROOT::Math::GSLMinimizer&)
ROOT::Math::GSLMinimizer&	operator=(const ROOT::Math::GSLMinimizer& 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
unsigned int	fDim
ROOT::Math::GSLMultiMinimizer*	fGSLMultiMin
double	fLSTolerance	Line Search Tolerance
double	fMinVal
vector<std::string>	fNames
const ROOT::Math::IMultiGradFunction*	fObjFunc
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

GSLMinimizer(ROOT::Math::EGSLMinimizerType type = ROOT::Math::kConjugateFR)

      Default constructor

GSLMinimizer(const char* type)

      Constructor with a string giving name of algorithm

virtual ~GSLMinimizer()

      Destructor

GSLMinimizer(const ROOT::Math::GSLMinimizer& )

 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 limit variable  (override if minimizer supports them )

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

 set upper limit variable (override if minimizer supports them )

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

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

bool SetFixedVariable(unsigned int , const string& , double )

 set fixed variable (override if minimizer supports them )

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

unsigned int NDim() const

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

{ return fValues.size(); }

unsigned int NFree() const

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

{ return fObjFunc->NDim(); }

bool ProvidesError() const

 minimizer provides error and error matrix

{ return false; }

const double * Errors() const

 return errors at the minimum

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

{ return 0; }

const ROOT::Math::IMultiGradFunction * ObjFunction() const

 method of only GSL  minimizer (not inherited from interface)
 return pointer to used objective gradient function

{ return fObjFunc; }