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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 59 of file GSLNLSMinimizer.h.

Public Member Functions

 GSLNLSMinimizer (int type=0)
 Default constructor. More...
 
 ~GSLNLSMinimizer () override
 Destructor (no operations) More...
 
double CovMatrix (unsigned int, unsigned int) const override
 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...
 
int CovMatrixStatus () const override
 return covariance matrix status More...
 
double Edm () const override
 return expected distance reached from the minimum More...
 
const doubleErrors () const override
 return errors at the minimum More...
 
const doubleMinGradient () const override
 return pointer to gradient values at the minimum More...
 
bool Minimize () override
 method to perform the minimization More...
 
unsigned int NCalls () const override
 number of function calls to reach the minimum More...
 
bool ProvidesError () const override
 number of free variables (real dimension of the problem) this is <= Function().NDim() which is the total More...
 
void SetFunction (const ROOT::Math::IMultiGenFunction &func) override
 set the function to minimize More...
 
void SetFunction (const ROOT::Math::IMultiGradFunction &func) override
 set gradient the function to minimize More...
 
- Public Member Functions inherited from ROOT::Math::BasicMinimizer
 BasicMinimizer ()
 Default constructor. More...
 
 ~BasicMinimizer () override
 Destructor. More...
 
bool FixVariable (unsigned int ivar) override
 fix an existing variable More...
 
bool GetVariableSettings (unsigned int ivar, ROOT::Fit::ParameterSettings &varObj) const override
 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...
 
bool IsFixedVariable (unsigned int ivar) const override
 query if an existing variable is fixed (i.e. More...
 
bool Minimize () override
 method to perform the minimization More...
 
double MinValue () const override
 return minimum function value More...
 
unsigned int NDim () const override
 number of dimensions More...
 
unsigned int NFree () const override
 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...
 
bool ReleaseVariable (unsigned int ivar) override
 release an existing variable More...
 
bool SetFixedVariable (unsigned int, const std::string &, double) override
 set fixed variable (override if minimizer supports them ) More...
 
void SetFunction (const ROOT::Math::IMultiGenFunction &func) override
 set the function to minimize More...
 
void SetFunction (const ROOT::Math::IMultiGradFunction &func) override
 set gradient the function to minimize More...
 
bool SetLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double, double) override
 set upper/lower limited variable (override if minimizer supports them ) More...
 
bool SetLowerLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double lower) override
 set lower limit variable (override if minimizer supports them ) More...
 
bool SetUpperLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double upper) override
 set upper limit variable (override if minimizer supports them ) More...
 
bool SetVariable (unsigned int ivar, const std::string &name, double val, double step) override
 set free variable More...
 
bool SetVariableLimits (unsigned int ivar, double lower, double upper) override
 set the limits of an already existing variable More...
 
bool SetVariableLowerLimit (unsigned int ivar, double lower) override
 set the lower-limit of an already existing variable More...
 
bool SetVariableStepSize (unsigned int ivar, double step) override
 set the step size of an already existing variable More...
 
bool SetVariableUpperLimit (unsigned int ivar, double upper) override
 set the upper-limit of an already existing variable More...
 
bool SetVariableValue (unsigned int ivar, double val) override
 set the value of an existing variable More...
 
bool SetVariableValues (const double *x) override
 set the values of all existing variables (array must be dimensioned to the size of existing parameters) More...
 
virtual const doubleStepSizes () const
 accessor methods More...
 
int VariableIndex (const std::string &name) const override
 get index of variable given a variable given a name return -1 if variable is not found More...
 
std::string VariableName (unsigned int ivar) const override
 get name of variables (override if minimizer support storing of variable names) More...
 
const doubleX () const override
 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 minimization - 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...
 
virtual double CovMatrix (unsigned int ivar, unsigned int jvar) const
 return covariance matrices element for variables ivar,jvar if the variable is fixed the return value is zero The ordering of the variables is the same as in the parameter and errors vectors More...
 
virtual int CovMatrixStatus () const
 return status of covariance matrix using Minuit convention {0 not calculated 1 approximated 2 made pos def , 3 accurate} Minimizer who implements covariance matrix calculation will re-implement the method More...
 
virtual double Edm () const
 return expected distance reached from the minimum (re-implement if minimizer provides it 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 const doubleErrors () const
 return errors at the minimum More...
 
virtual bool FixVariable (unsigned int ivar)
 fix an existing variable 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 More...
 
virtual bool GetVariableSettings (unsigned int ivar, ROOT::Fit::ParameterSettings &pars) const
 get variable settings in a variable object (like ROOT::Fit::ParamsSettings) 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...
 
virtual bool IsFixedVariable (unsigned int ivar) const
 query if an existing variable is fixed (i.e. 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 const doubleMinGradient () const
 return pointer to gradient values at the minimum More...
 
virtual bool Minimize ()=0
 method to perform the minimization More...
 
virtual int MinosStatus () const
 status code of Minos (to be re-implemented by the minimizers supporting Minos) More...
 
virtual double MinValue () const =0
 return minimum function value More...
 
virtual unsigned int NCalls () const
 number of function calls to reach the minimum More...
 
virtual unsigned int NDim () const =0
 this is <= Function().NDim() which is the total number of variables (free+ constrained ones) More...
 
virtual unsigned int NFree () const
 number of free variables (real dimension of the problem) this is <= Function().NDim() which is the total (re-implement if minimizer supports bounded parameters) 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 ProvidesError () const
 minimizer provides error and error matrix More...
 
virtual bool ReleaseVariable (unsigned int ivar)
 release an existing variable 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 default options (defined in MinimizerOptions) More...
 
void SetErrorDef (double up)
 set scale for calculating the errors More...
 
void SetExtraOptions (const IOptions &extraOptions)
 set only the extra options More...
 
virtual bool SetFixedVariable (unsigned int ivar, const std::string &name, double val)
 set a new fixed variable (override if minimizer supports them ) More...
 
virtual void SetFunction (const ROOT::Math::IMultiGenFunction &func)=0
 set the function to minimize More...
 
virtual void SetFunction (const ROOT::Math::IMultiGradFunction &func)
 set a function to minimize using gradient More...
 
virtual bool SetLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double lower, double upper)
 set a new upper/lower limited variable (override if minimizer supports them ) otherwise as default set an unlimited variable More...
 
virtual bool SetLowerLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double lower)
 set a new lower limit variable (override if minimizer supports them ) 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...
 
virtual bool SetUpperLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double upper)
 set a new upper limit variable (override if minimizer supports them ) 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 SetVariable (unsigned int ivar, const std::string &name, double val, double step)=0
 set a new free variable More...
 
virtual bool SetVariableInitialRange (unsigned int, double, double)
 set the initial range of an existing 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...
 
template<class VariableIterator >
int SetVariables (const VariableIterator &begin, const VariableIterator &end)
 add variables . Return number of variables successfully added More...
 
virtual bool SetVariableStepSize (unsigned int ivar, double value)
 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 value)
 set the value of an already existing variable More...
 
virtual bool SetVariableValues (const double *x)
 set the values of all existing variables (array must be dimensioned to the size of the existing parameters) More...
 
int Status () const
 status code of minimizer More...
 
int Strategy () const
 strategy More...
 
double Tolerance () const
 absolute tolerance 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) return an empty string if variable is not found More...
 
virtual const doubleX () const =0
 return pointer to X values at the minimum More...
 

Protected Member Functions

template<class Func >
bool DoMinimize (const Func &f)
 Internal method to perform minimization template on the type of method function. More...
 
- 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, const MinimTransformFunction *func=nullptr)
 
void SetMinValue (double val)
 

Private Member Functions

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

Private Attributes

std::vector< doublefCovMatrix
 
double fEdm
 
std::vector< doublefErrors
 
ROOT::Math::GSLMultiFitfGSLMultiFit
 
double fLSTolerance
 
unsigned int fNCalls
 
unsigned int fNFree
 
bool fUseGradFunction = false
 

Additional Inherited Members

- Protected Attributes inherited from ROOT::Math::Minimizer
MinimizerOptions fOptions
 minimizer options More...
 
int fStatus
 status of minimizer More...
 
bool fValidError
 flag to control if errors have been validated (Hesse has been run in case of Minuit) More...
 

#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 200 of file GSLNLSMinimizer.cxx.

◆ ~GSLNLSMinimizer()

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

Destructor (no operations)

Definition at line 222 of file GSLNLSMinimizer.cxx.

◆ GSLNLSMinimizer() [2/2]

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

Copy constructor.

Definition at line 79 of file GSLNLSMinimizer.h.

Member Function Documentation

◆ CovMatrix()

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

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 456 of file GSLNLSMinimizer.cxx.

◆ CovMatrixStatus()

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

return covariance matrix status

Reimplemented from ROOT::Math::Minimizer.

Definition at line 464 of file GSLNLSMinimizer.cxx.

◆ DoMinimize()

template<class Func >
bool ROOT::Math::GSLNLSMinimizer::DoMinimize ( const Func &  f)
protected

Internal method to perform minimization template on the type of method function.

Definition at line 268 of file GSLNLSMinimizer.cxx.

◆ Edm()

double ROOT::Math::GSLNLSMinimizer::Edm ( ) const
inlineoverridevirtual

return expected distance reached from the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 103 of file GSLNLSMinimizer.h.

◆ Errors()

const double * ROOT::Math::GSLNLSMinimizer::Errors ( ) const
inlineoverridevirtual

return errors at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 120 of file GSLNLSMinimizer.h.

◆ MinGradient()

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

return pointer to gradient values at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 450 of file GSLNLSMinimizer.cxx.

◆ Minimize()

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

method to perform the minimization

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 247 of file GSLNLSMinimizer.cxx.

◆ NCalls()

unsigned int ROOT::Math::GSLNLSMinimizer::NCalls ( ) const
inlineoverridevirtual

number of function calls to reach the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 110 of file GSLNLSMinimizer.h.

◆ operator=()

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

Assignment operator.

Definition at line 84 of file GSLNLSMinimizer.h.

◆ ProvidesError()

bool ROOT::Math::GSLNLSMinimizer::ProvidesError ( ) const
inlineoverridevirtual

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 117 of file GSLNLSMinimizer.h.

◆ SetFunction() [1/2]

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

set the function to minimize

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 229 of file GSLNLSMinimizer.cxx.

◆ SetFunction() [2/2]

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

set gradient the function to minimize

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 240 of file GSLNLSMinimizer.cxx.

Member Data Documentation

◆ fCovMatrix

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

Definition at line 155 of file GSLNLSMinimizer.h.

◆ fEdm

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

Definition at line 152 of file GSLNLSMinimizer.h.

◆ fErrors

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

Definition at line 154 of file GSLNLSMinimizer.h.

◆ fGSLMultiFit

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

Definition at line 150 of file GSLNLSMinimizer.h.

◆ fLSTolerance

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

Definition at line 153 of file GSLNLSMinimizer.h.

◆ fNCalls

unsigned int ROOT::Math::GSLNLSMinimizer::fNCalls
private

Definition at line 148 of file GSLNLSMinimizer.h.

◆ fNFree

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

Definition at line 147 of file GSLNLSMinimizer.h.

◆ fUseGradFunction

bool ROOT::Math::GSLNLSMinimizer::fUseGradFunction = false
private

Definition at line 146 of file GSLNLSMinimizer.h.

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