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="">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)

virtual voidROOT::Math::Minimizer::Clear()
virtual doubleCovMatrix(unsigned int, unsigned int) const
virtual doubleEdm() const
virtual const double*Errors() const
doubleROOT::Math::Minimizer::ErrorUp() const
virtual boolGetMinosError(unsigned int, double&, double&)
ROOT::Math::GSLMinimizerGSLMinimizer(ROOT::Math::EGSLMinimizerType type = ROOT::Math::kConjugateFR)
ROOT::Math::GSLMinimizerGSLMinimizer(const char* type)
unsigned intROOT::Math::Minimizer::MaxFunctionCalls()
unsigned intROOT::Math::Minimizer::MaxIterations()
virtual const double*MinGradient() const
virtual boolMinimize()
virtual doubleMinValue() const
virtual unsigned intNCalls() const
virtual unsigned intNDim() const
virtual unsigned intNFree() const
intROOT::Math::Minimizer::PrintLevel() const
virtual boolProvidesError() const
voidROOT::Math::Minimizer::SetErrorUp(double up)
virtual boolROOT::Math::Minimizer::SetFixedVariable(unsigned int ivar, const string& name, double val)
virtual voidSetFunction(const ROOT::Math::Minimizer::IObjFunction& func)
virtual voidSetFunction(const ROOT::Math::Minimizer::IGradObjFunction& func)
virtual boolROOT::Math::Minimizer::SetLimitedVariable(unsigned int ivar, const string& name, double val, double step, double, double)
virtual boolROOT::Math::Minimizer::SetLowerLimitedVariable(unsigned int ivar, const string& name, double val, double step, double lower)
voidROOT::Math::Minimizer::SetMaxFunctionCalls(unsigned int maxfcn)
voidROOT::Math::Minimizer::SetMaxIterations(unsigned int maxiter)
voidROOT::Math::Minimizer::SetPrintLevel(int level)
voidROOT::Math::Minimizer::SetStrategy(int strategyLevel)
voidROOT::Math::Minimizer::SetTolerance(double tol)
virtual boolROOT::Math::Minimizer::SetUpperLimitedVariable(unsigned int ivar, const string& name, double val, double step, double upper)
virtual boolSetVariable(unsigned int ivar, const string& name, double val, double step)
intROOT::Math::Minimizer::Strategy() const
doubleROOT::Math::Minimizer::Tolerance() const
virtual const double*X() const
ROOT::Math::GSLMinimizerGSLMinimizer(const ROOT::Math::GSLMinimizer&)
ROOT::Math::GSLMinimizer&operator=(const ROOT::Math::GSLMinimizer& rhs)

Data Members

intROOT::Math::Minimizer::fDebugprint level
unsigned intROOT::Math::Minimizer::fMaxCallsmax number of funciton calls
unsigned intROOT::Math::Minimizer::fMaxItermax number or iterations used to find the minimum
intROOT::Math::Minimizer::fStrategyminimizer strategy
doubleROOT::Math::Minimizer::fToltolerance (absolute)
doubleROOT::Math::Minimizer::fUperror scale
unsigned intfDim
doublefLSToleranceLine Search Tolerance
const ROOT::Math::Minimizer::IGradObjFunction*fObjFunc

Class Charts

Inheritance Inherited Members Includes Libraries
Class Charts

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()

GSLMinimizer(const GSLMinimizer &)
 usually copying is non trivial, so we make this unaccessible

Copy constructor

void SetFunction(const Minimizer::IObjFunction & func)
 set the function to minimize
void SetFunction(const Minimizer::IGradObjFunction & func)
 set gradient the function to minimize
bool SetVariable(unsigned int ivar, const string& name, double val, double step)
 set free variable
bool Minimize()
 method to perform the minimization
double MinValue()
 return minimum function value
{ return fMinVal; }
double Edm()
 return expected distance reached from the minimum
const double * X()
 return  pointer to X values at the minimum
{ return &fValues.front(); }
const double * MinGradient()
 return pointer to gradient values at the minimum
unsigned int NCalls()
 number of function calls to reach the minimum
{ return 0; }
unsigned int NDim()
 this is <= Function().NDim() which is the total
 number of variables (free+ constrained ones)
{ return fDim; }
unsigned int NFree()
 number of free variables (real dimension of the problem)
 this is <= Function().NDim() which is the total
{ return fDim; }
bool ProvidesError()
 minimizer provides error and error matrix
{ return true; }
const double * Errors()
 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; }
bool GetMinosError(unsigned int , double& , double& )
 minos error for variable i, return false if Minos failed
{ return false; }

Author: L. Moneta Wed Oct 18 11:48:00 2006
Last update: root/mathmore:$Id: GSLMinimizer.h 21553 2007-12-21 10:55:46Z moneta $
Copyright (c) 2006 LCG ROOT Math Team, CERN/PH-SFT *

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