class ROOT::Math::Minimizer

Abstract Minimizer class, defining  the interface for the various minimizer
(like Minuit2, Minuit, GSL, etc..)
Plug-in's exist in ROOT to be able to instantiate the derived classes like
ROOT::Math::GSLMinimizer or ROOT::Math::Minuit2Minimizer via the
plug-in manager.

Provides interface for setting the function to be minimized.
The function must  implemente the multi-dimensional generic interface
If the function provides gradient calculation
(implements the ROOT::Math::IGradientFunctionMultiDim interface) this will be
used by the Minimizer.

It Defines also 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 especifying their limits.

It defines the interface to set and retrieve basic minimization parameters
(for specific Minimizer parameters one must use the derived classes).

Then it defines the interface to retrieve the result of minimization ( minimum X values, function value,
gradient, error on the mimnimum, etc...)

@ingroup MultiMin

Function Members (Methods)

    This is an abstract class, constructors will not be documented.
    Look at the header to check for available constructors.

virtual voidClear()
virtual doubleCovMatrix(unsigned int i, unsigned int j) const
virtual doubleEdm() const
virtual const double*Errors() const
doubleErrorUp() const
virtual boolGetMinosError(unsigned int, double& errLow, double& errUp)
unsigned intMaxFunctionCalls()
unsigned intMaxIterations()
virtual const double*MinGradient() const
virtual boolMinimize()
virtual doubleMinValue() const
virtual unsigned intNCalls() const
virtual unsigned intNDim() const
virtual unsigned intNFree() const
intPrintLevel() const
virtual boolProvidesError() const
voidSetErrorUp(double up)
virtual boolSetFixedVariable(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 boolSetLimitedVariable(unsigned int ivar, const string& name, double val, double step, double, double)
virtual boolSetLowerLimitedVariable(unsigned int ivar, const string& name, double val, double step, double lower)
voidSetMaxFunctionCalls(unsigned int maxfcn)
voidSetMaxIterations(unsigned int maxiter)
voidSetPrintLevel(int level)
voidSetStrategy(int strategyLevel)
voidSetTolerance(double tol)
virtual boolSetUpperLimitedVariable(unsigned int ivar, const string& name, double val, double step, double upper)
virtual boolSetVariable(unsigned int ivar, const string& name, double val, double step)
intStrategy() const
doubleTolerance() const
virtual const double*X() const
ROOT::Math::Minimizer&operator=(const ROOT::Math::Minimizer& rhs)

Data Members

intfDebugprint level
unsigned intfMaxCallsmax number of funciton calls
unsigned intfMaxItermax number or iterations used to find the minimum
intfStrategyminimizer strategy
doublefToltolerance (absolute)
doublefUperror scale

Class Charts

Inheritance Inherited Members Includes Libraries
Class Charts

Function documentation

virtual ~Minimizer()
Destructor (no operations)

void Clear()
 reset for consecutive minimizations - implement if needed
void SetFunction(const IObjFunction & func)
 set the function to minimize
void SetFunction(const IGradObjFunction & func)
 set a function to minimize using gradient
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)
return SetLimitedVariable(unsigned int ivar, const string& name, double val, double step, double , double )
bool SetUpperLimitedVariable(unsigned int ivar, const string& name, double val, double step, double upper)
 set upper limit variable (override if minimizer supports them )
bool SetFixedVariable(unsigned int ivar, const string& name, double val)
 set fixed variable (override if minimizer supports them )
bool Minimize()
 method to perform the minimization
double MinValue()
 return minimum function value
double Edm()
 return expected distance reached from the minimum
const double * X()
 return  pointer to X values at the minimum
const double * MinGradient()
 return pointer to gradient values at the minimum
unsigned int NCalls()
 number of function calls to reach the minimum
unsigned int NDim()
 this is <= Function().NDim() which is the total
 number of variables (free+ constrained ones)
unsigned int NFree()
 number of free variables (real dimension of the problem)
 this is <= Function().NDim() which is the total
bool ProvidesError()
 minimizer provides error and error matrix
const double * Errors()
 return errors at the minimum
double CovMatrix(unsigned int i, unsigned int j) 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

bool GetMinosError(unsigned int , double& errLow, double& errUp)
 minos error for variable i, return false if Minos failed or not supported
int PrintLevel()
 return reference to the objective function
virtual const ROOT::Math::IGenFunction & Function() const = 0;
 minimizer configuration parameters 
 set print level
{ return fDebug; }
unsigned int MaxFunctionCalls()
  max number of function calls
{ return fMaxCalls; }
unsigned int MaxIterations()
 max iterations
{ return fMaxIter; }
double Tolerance()
 absolute tolerance
{ return fTol; }
int Strategy()
{ return fStrategy; }
double ErrorUp()
 return the statistical scale used for calculate the error
 is typically 1 for Chi2 minimizetion and 0.5 for likelihood's
{ return fUp; }
void SetPrintLevel(int level)
 set print level
{ fDebug = level; }
void SetMaxFunctionCalls(unsigned int maxfcn)
set maximum of function calls
{ if (maxfcn > 0) fMaxCalls = maxfcn; }
void SetMaxIterations(unsigned int maxiter)
 set maximum iterations (one iteration can have many function calls)
{ if (maxiter > 0) fMaxIter = maxiter; }
void SetTolerance(double tol)
 set the tolerance
{ fTol = tol; }
void SetStrategy(int strategyLevel)
set the strategy
{ fStrategy = strategyLevel; }
void SetErrorUp(double up)
 set scale for calculating the errors
{ fUp = up; }

Author: L. Moneta Fri Sep 22 15:06:47 2006
Last update: root/mathcore:$Id: Minimizer.h 21503 2007-12-19 17:34:54Z moneta $
Copyright (c) 2006 LCG ROOT Math Team, CERN/PH-SFT *

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