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

Protected Member Functions

template<class Func >
bool DoMinimize (const Func &f)
 Internal method to perform minimization template on the type of method function.
 
- Protected Member Functions inherited from ROOT::Math::BasicMinimizer
bool CheckDimension () const
 
bool CheckObjFunction () const
 
MinimTransformFunctionCreateTransformation (std::vector< double > &startValues, const ROOT::Math::IMultiGradFunction *func=nullptr)
 
void SetFinalValues (const double *x, const MinimTransformFunction *func=nullptr)
 
void SetMinValue (double val)
 

Private Member Functions

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

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
 
int fStatus
 status of minimizer
 
bool fValidError
 flag to control if errors have been validated (Hesse has been run in case of Minuit)
 

#include <Math/GSLNLSMinimizer.h>

Inheritance diagram for ROOT::Math::GSLNLSMinimizer:
[legend]

Constructor & Destructor Documentation

◆ GSLNLSMinimizer() [1/2]

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

Default constructor.

Definition at line 206 of file GSLNLSMinimizer.cxx.

◆ ~GSLNLSMinimizer()

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

Destructor (no operations)

Definition at line 228 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 100 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 117 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 107 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 114 of file GSLNLSMinimizer.h.

◆ SetFunction()

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

set the function to minimize

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 235 of file GSLNLSMinimizer.cxx.

Member Data Documentation

◆ fCovMatrix

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

Definition at line 152 of file GSLNLSMinimizer.h.

◆ fEdm

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

Definition at line 149 of file GSLNLSMinimizer.h.

◆ fErrors

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

Definition at line 151 of file GSLNLSMinimizer.h.

◆ fGSLMultiFit

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

Definition at line 147 of file GSLNLSMinimizer.h.

◆ fLSTolerance

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

Definition at line 150 of file GSLNLSMinimizer.h.

◆ fNCalls

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

Definition at line 145 of file GSLNLSMinimizer.h.

◆ fNFree

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

Definition at line 144 of file GSLNLSMinimizer.h.

◆ fUseGradFunction

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

Definition at line 143 of file GSLNLSMinimizer.h.

Libraries for ROOT::Math::GSLNLSMinimizer:

The documentation for this class was generated from the following files: