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ROOT::Math::GSLSimAnMinimizer Class Reference

GSLSimAnMinimizer class for minimization using simulated annealing using the algorithm from GSL.

It implements the ROOT::Minimizer interface and a plug-in (name "GSLSimAn") exists to instantiate this class via the plug-in manager Configuration (Setting/getting) the options is done through the methods defined in the ROOT::Math::Minimizer class. The user needs to call the base class method ROOT::Math::Minimizer::SetOptions to set the corresponding options. Here is some code example for increasing n_tries from 200 (default) to 1000

simanOpt.SetValue("n_tries", 1000);
class implementing generic options for a numerical algorithm Just store the options in a map of strin...
void SetValue(const char *name, double val)
generic methods for retrieving options
Definition IOptions.h:42
void SetExtraOptions(const IOptions &opt)
set extra options (in this case pointer is cloned)

Definition at line 75 of file GSLSimAnMinimizer.h.

Public Member Functions

 GSLSimAnMinimizer (int type=0)
 Default constructor.
 ~GSLSimAnMinimizer () override
 Destructor (no operations)
bool Minimize () override
 method to perform the minimization
const GSLSimAnParamsMinimizerParameters () const
 Get current minimizer option parameters.
unsigned int NCalls () const override
 number of calls
void SetParameters (const GSLSimAnParams &params)
 set new minimizer option parameters using directly the GSLSimAnParams structure
- Public Member Functions inherited from ROOT::Math::BasicMinimizer
 BasicMinimizer ()
 Default constructor.
 ~BasicMinimizer () override
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 )
void SetFunction (const ROOT::Math::IMultiGenFunction &func) override
 set the function to minimize
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.
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
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
virtual double Edm () const
 return expected distance reached from the minimum (re-implement if minimizer provides it
double ErrorDef () const
 return the statistical scale used for calculate the error is typically 1 for Chi2 and 0.5 for likelihood minimization
virtual const doubleErrors () const
 return errors at the minimum
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 const doubleMinGradient () const
 return pointer to gradient values at the minimum
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 ProvidesError () const
 minimizer provides error and error matrix
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
double Tolerance () const
 absolute tolerance

Protected Member Functions

void DoSetMinimOptions (const GSLSimAnParams &params)
 Set the Minimizer options from the simulated annealing parameters.
void DoSetSimAnParameters (const MinimizerOptions &opt)
 set minimizer option parameters from stored ROOT::Math::MinimizerOptions (fOpt)
- 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

 GSLSimAnMinimizer (const GSLSimAnMinimizer &)
 Copy constructor.
GSLSimAnMinimizeroperator= (const GSLSimAnMinimizer &rhs)
 Assignment operator.

Private Attributes

ROOT::Math::GSLSimAnnealing fSolver

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/GSLSimAnMinimizer.h>

Inheritance diagram for ROOT::Math::GSLSimAnMinimizer:

Constructor & Destructor Documentation

◆ GSLSimAnMinimizer() [1/2]

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

Default constructor.

Definition at line 33 of file GSLSimAnMinimizer.cxx.

◆ ~GSLSimAnMinimizer()

ROOT::Math::GSLSimAnMinimizer::~GSLSimAnMinimizer ( )

Destructor (no operations)

Definition at line 53 of file GSLSimAnMinimizer.cxx.

◆ GSLSimAnMinimizer() [2/2]

ROOT::Math::GSLSimAnMinimizer::GSLSimAnMinimizer ( const GSLSimAnMinimizer )

Copy constructor.

Definition at line 94 of file GSLSimAnMinimizer.h.

Member Function Documentation

◆ DoSetMinimOptions()

void ROOT::Math::GSLSimAnMinimizer::DoSetMinimOptions ( const GSLSimAnParams params)

Set the Minimizer options from the simulated annealing parameters.

Definition at line 149 of file GSLSimAnMinimizer.cxx.

◆ DoSetSimAnParameters()

void ROOT::Math::GSLSimAnMinimizer::DoSetSimAnParameters ( const MinimizerOptions opt)

set minimizer option parameters from stored ROOT::Math::MinimizerOptions (fOpt)

Definition at line 165 of file GSLSimAnMinimizer.cxx.

◆ Minimize()

bool ROOT::Math::GSLSimAnMinimizer::Minimize ( )

method to perform the minimization

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 57 of file GSLSimAnMinimizer.cxx.

◆ MinimizerParameters()

const GSLSimAnParams & ROOT::Math::GSLSimAnMinimizer::MinimizerParameters ( ) const

Get current minimizer option parameters.

Definition at line 114 of file GSLSimAnMinimizer.h.

◆ NCalls()

unsigned int ROOT::Math::GSLSimAnMinimizer::NCalls ( ) const

number of calls

Reimplemented from ROOT::Math::Minimizer.

Definition at line 139 of file GSLSimAnMinimizer.cxx.

◆ operator=()

GSLSimAnMinimizer & ROOT::Math::GSLSimAnMinimizer::operator= ( const GSLSimAnMinimizer rhs)

Assignment operator.

Definition at line 99 of file GSLSimAnMinimizer.h.

◆ SetParameters()

void ROOT::Math::GSLSimAnMinimizer::SetParameters ( const GSLSimAnParams params)

set new minimizer option parameters using directly the GSLSimAnParams structure

Definition at line 117 of file GSLSimAnMinimizer.h.

Member Data Documentation

◆ fSolver

ROOT::Math::GSLSimAnnealing ROOT::Math::GSLSimAnMinimizer::fSolver

Definition at line 131 of file GSLSimAnMinimizer.h.

Libraries for ROOT::Math::GSLSimAnMinimizer:

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