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Reference Guide
ROOT::Math::GSLNLSMinimizer Class Reference

GSLNLSMinimizer class for Non Linear Least Square fitting It Uses the Levemberg-Marquardt algorithm from GSL Non Linear Least Square fitting.

Definition at line 152 of file GSLNLSMinimizer.h.

Public Member Functions

 GSLNLSMinimizer (int type=0)
 Default constructor. More...
 
 ~GSLNLSMinimizer ()
 Destructor (no operations) More...
 
virtual 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 More...
 
virtual int CovMatrixStatus () const
 return covariance matrix status More...
 
virtual double Edm () const
 return expected distance reached from the minimum More...
 
virtual const double * Errors () const
 return errors at the minimum More...
 
virtual const double * MinGradient () const
 return pointer to gradient values at the minimum More...
 
virtual bool Minimize ()
 method to perform the minimization More...
 
virtual unsigned int NCalls () const
 number of function calls to reach the minimum More...
 
virtual bool ProvidesError () const
 number of free variables (real dimension of the problem) this is <= Function().NDim() which is the total More...
 
virtual void SetFunction (const ROOT::Math::IMultiGenFunction &func)
 set the function to minimize More...
 
virtual void SetFunction (const ROOT::Math::IMultiGradFunction &func)
 set gradient the function to minimize More...
 
- Public Member Functions inherited from ROOT::Math::BasicMinimizer
 BasicMinimizer ()
 Default constructor. More...
 
virtual ~BasicMinimizer ()
 Destructor. More...
 
virtual bool FixVariable (unsigned int ivar)
 fix an existing variable More...
 
virtual bool GetVariableSettings (unsigned int ivar, ROOT::Fit::ParameterSettings &varObj) const
 get variable settings in a variable object (like ROOT::Fit::ParamsSettings) More...
 
const ROOT::Math::IMultiGradFunctionGradObjFunction () const
 return pointer to used gradient object function (NULL if gradient is not supported) More...
 
virtual bool IsFixedVariable (unsigned int ivar) const
 query if an existing variable is fixed (i.e. More...
 
virtual double MinValue () const
 return minimum function value More...
 
virtual unsigned int NDim () const
 number of dimensions More...
 
virtual unsigned int NFree () const
 number of free variables (real dimension of the problem) More...
 
virtual unsigned int NPar () const
 total number of parameter defined More...
 
const ROOT::Math::IMultiGenFunctionObjFunction () const
 return pointer to used objective function More...
 
void PrintResult () const
 print result of minimization More...
 
virtual bool ReleaseVariable (unsigned int ivar)
 release an existing variable More...
 
virtual bool SetFixedVariable (unsigned int, const std::string &, double)
 set fixed variable (override if minimizer supports them ) More...
 
virtual bool SetLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double, double)
 set upper/lower limited variable (override if minimizer supports them ) More...
 
virtual bool SetLowerLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double lower)
 set lower limit variable (override if minimizer supports them ) More...
 
virtual bool SetUpperLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double upper)
 set upper limit variable (override if minimizer supports them ) More...
 
virtual bool SetVariable (unsigned int ivar, const std::string &name, double val, double step)
 set free variable More...
 
virtual bool SetVariableLimits (unsigned int ivar, double lower, double upper)
 set the limits of an already existing variable More...
 
virtual bool SetVariableLowerLimit (unsigned int ivar, double lower)
 set the lower-limit of an already existing variable More...
 
virtual bool SetVariableStepSize (unsigned int ivar, double step)
 set the step size of an already existing variable More...
 
virtual bool SetVariableUpperLimit (unsigned int ivar, double upper)
 set the upper-limit of an already existing variable More...
 
virtual bool SetVariableValue (unsigned int ivar, double val)
 set the value of an existing variable More...
 
virtual bool SetVariableValues (const double *x)
 set the values of all existing variables (array must be dimensioned to the size of existing parameters) More...
 
virtual const double * StepSizes () const
 accessor methods More...
 
const ROOT::Math::MinimTransformFunctionTransformFunction () const
 return transformation function (NULL if not having a transformation) More...
 
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 More...
 
virtual std::string VariableName (unsigned int ivar) const
 get name of variables (override if minimizer support storing of variable names) More...
 
virtual const double * X () const
 return pointer to X values at the minimum More...
 
- Public Member Functions inherited from ROOT::Math::Minimizer
 Minimizer ()
 Default constructor. More...
 
virtual ~Minimizer ()
 Destructor (no operations) More...
 
virtual void Clear ()
 reset for consecutive minimizations - implement if needed More...
 
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(); More...
 
virtual double Correlation (unsigned int i, unsigned int j) const
 return correlation coefficient between variable i and j. More...
 
double ErrorDef () const
 return the statistical scale used for calculate the error is typically 1 for Chi2 and 0.5 for likelihood minimization More...
 
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. More...
 
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. More...
 
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 (This feature is not yet implemented) More...
 
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. More...
 
virtual bool Hesse ()
 perform a full calculation of the Hessian matrix for error calculation More...
 
bool IsValidError () const
 return true if Minimizer has performed a detailed error validation (e.g. run Hesse for Minuit) More...
 
unsigned int MaxFunctionCalls () const
 max number of function calls More...
 
unsigned int MaxIterations () const
 max iterations More...
 
virtual unsigned int NIterations () const
 number of iterations to reach the minimum More...
 
virtual MinimizerOptions Options () const
 retrieve the minimizer options (implement derived class if needed) More...
 
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) More...
 
int PrintLevel () const
 minimizer configuration parameters More...
 
virtual void PrintResults ()
 return reference to the objective function virtual const ROOT::Math::IGenFunction & Function() const = 0; More...
 
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. More...
 
void SetDefaultOptions ()
 reset the defaut options (defined in MinimizerOptions) More...
 
void SetErrorDef (double up)
 set scale for calculating the errors More...
 
void SetMaxFunctionCalls (unsigned int maxfcn)
 set maximum of function calls More...
 
void SetMaxIterations (unsigned int maxiter)
 set maximum iterations (one iteration can have many function calls) More...
 
void SetOptions (const MinimizerOptions &opt)
 set all options in one go More...
 
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. More...
 
void SetPrintLevel (int level)
 set print level More...
 
void SetStrategy (int strategyLevel)
 set the strategy More...
 
void SetTolerance (double tol)
 set the tolerance More...
 
void SetValidError (bool on)
 flag to check if minimizer needs to perform accurate error analysis (e.g. run Hesse for Minuit) More...
 
virtual bool SetVariableInitialRange (unsigned int, double, double)
 set the initial range of an existing variable More...
 
template<class VariableIterator >
int SetVariables (const VariableIterator &begin, const VariableIterator &end)
 add variables . Return number of variables successfully added More...
 
int Status () const
 status code of minimizer More...
 
int Strategy () const
 strategy More...
 
double Tolerance () const
 absolute tolerance More...
 

Private Member Functions

 GSLNLSMinimizer (const GSLNLSMinimizer &)
 Copy constructor. More...
 
GSLNLSMinimizeroperator= (const GSLNLSMinimizer &rhs)
 Assignment operator. More...
 

Private Attributes

const ROOT::Math::FitMethodFunctionfChi2Func
 
std::vector< double > fCovMatrix
 
double fEdm
 
std::vector< double > fErrors
 
ROOT::Math::GSLMultiFitfGSLMultiFit
 
double fLSTolerance
 
unsigned int fNFree
 
std::vector< LSResidualFuncfResiduals
 
unsigned int fSize
 

Additional Inherited Members

- Protected Member Functions inherited from ROOT::Math::BasicMinimizer
bool CheckDimension () const
 
bool CheckObjFunction () const
 
MinimTransformFunctionCreateTransformation (std::vector< double > &startValues, const ROOT::Math::IMultiGradFunction *func=0)
 
void SetFinalValues (const double *x)
 
void SetMinValue (double val)
 
- Protected Attributes inherited from ROOT::Math::Minimizer
MinimizerOptions fOptions
 
int fStatus
 
bool fValidError
 

#include <Math/GSLNLSMinimizer.h>

Inheritance diagram for ROOT::Math::GSLNLSMinimizer:
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Constructor & Destructor Documentation

◆ GSLNLSMinimizer() [1/2]

ROOT::Math::GSLNLSMinimizer::GSLNLSMinimizer ( int  type = 0)

Default constructor.

Definition at line 136 of file GSLNLSMinimizer.cxx.

◆ ~GSLNLSMinimizer()

ROOT::Math::GSLNLSMinimizer::~GSLNLSMinimizer ( )

Destructor (no operations)

Definition at line 161 of file GSLNLSMinimizer.cxx.

◆ GSLNLSMinimizer() [2/2]

ROOT::Math::GSLNLSMinimizer::GSLNLSMinimizer ( const GSLNLSMinimizer )
inlineprivate

Copy constructor.

Definition at line 172 of file GSLNLSMinimizer.h.

Member Function Documentation

◆ CovMatrix()

double ROOT::Math::GSLNLSMinimizer::CovMatrix ( unsigned int  i,
unsigned int  j 
) const
virtual

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 371 of file GSLNLSMinimizer.cxx.

◆ CovMatrixStatus()

int ROOT::Math::GSLNLSMinimizer::CovMatrixStatus ( ) const
virtual

return covariance matrix status

Reimplemented from ROOT::Math::Minimizer.

Definition at line 379 of file GSLNLSMinimizer.cxx.

◆ Edm()

virtual double ROOT::Math::GSLNLSMinimizer::Edm ( ) const
inlinevirtual

return expected distance reached from the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 196 of file GSLNLSMinimizer.h.

◆ Errors()

virtual const double* ROOT::Math::GSLNLSMinimizer::Errors ( ) const
inlinevirtual

return errors at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 213 of file GSLNLSMinimizer.h.

◆ MinGradient()

const double * ROOT::Math::GSLNLSMinimizer::MinGradient ( ) const
virtual

return pointer to gradient values at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 365 of file GSLNLSMinimizer.cxx.

◆ Minimize()

bool ROOT::Math::GSLNLSMinimizer::Minimize ( )
virtual

method to perform the minimization

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 200 of file GSLNLSMinimizer.cxx.

◆ NCalls()

virtual unsigned int ROOT::Math::GSLNLSMinimizer::NCalls ( ) const
inlinevirtual

number of function calls to reach the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 203 of file GSLNLSMinimizer.h.

◆ operator=()

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

Assignment operator.

Definition at line 177 of file GSLNLSMinimizer.h.

◆ ProvidesError()

virtual bool ROOT::Math::GSLNLSMinimizer::ProvidesError ( ) const
inlinevirtual

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

minimizer provides error and error matrix

Reimplemented from ROOT::Math::Minimizer.

Definition at line 210 of file GSLNLSMinimizer.h.

◆ SetFunction() [1/2]

void ROOT::Math::GSLNLSMinimizer::SetFunction ( const ROOT::Math::IMultiGenFunction func)
virtual

set the function to minimize

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 168 of file GSLNLSMinimizer.cxx.

◆ SetFunction() [2/2]

void ROOT::Math::GSLNLSMinimizer::SetFunction ( const ROOT::Math::IMultiGradFunction func)
virtual

set gradient the function to minimize

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 193 of file GSLNLSMinimizer.cxx.

Member Data Documentation

◆ fChi2Func

const ROOT::Math::FitMethodFunction* ROOT::Math::GSLNLSMinimizer::fChi2Func
private

Definition at line 238 of file GSLNLSMinimizer.h.

◆ fCovMatrix

std::vector<double> ROOT::Math::GSLNLSMinimizer::fCovMatrix
private

Definition at line 243 of file GSLNLSMinimizer.h.

◆ fEdm

double ROOT::Math::GSLNLSMinimizer::fEdm
private

Definition at line 240 of file GSLNLSMinimizer.h.

◆ fErrors

std::vector<double> ROOT::Math::GSLNLSMinimizer::fErrors
private

Definition at line 242 of file GSLNLSMinimizer.h.

◆ fGSLMultiFit

ROOT::Math::GSLMultiFit* ROOT::Math::GSLNLSMinimizer::fGSLMultiFit
private

Definition at line 237 of file GSLNLSMinimizer.h.

◆ fLSTolerance

double ROOT::Math::GSLNLSMinimizer::fLSTolerance
private

Definition at line 241 of file GSLNLSMinimizer.h.

◆ fNFree

unsigned int ROOT::Math::GSLNLSMinimizer::fNFree
private

Definition at line 234 of file GSLNLSMinimizer.h.

◆ fResiduals

std::vector<LSResidualFunc> ROOT::Math::GSLNLSMinimizer::fResiduals
private

Definition at line 244 of file GSLNLSMinimizer.h.

◆ fSize

unsigned int ROOT::Math::GSLNLSMinimizer::fSize
private

Definition at line 235 of file GSLNLSMinimizer.h.

Libraries for ROOT::Math::GSLNLSMinimizer:
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The documentation for this class was generated from the following files: