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ROOT::Math::GeneticMinimizer Class Reference

GeneticMinimizer.

Minimizer class based on the Gentic algorithm implemented in TMVA

Definition at line 61 of file GeneticMinimizer.h.

Public Member Functions

 GeneticMinimizer (int i=0)
 
 ~GeneticMinimizer () override
 
void Clear () override
 reset for consecutive minimization - implement if needed
 
double CovMatrix (unsigned int i, unsigned int j) const override
 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
 
double Edm () const override
 return expected distance reached from the minimum (re-implement if minimizer provides it
 
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
 
const GeneticMinimizerParametersMinimizerParameters () const
 
double MinValue () const override
 return minimum function value
 
unsigned int NCalls () const override
 number of function calls to reach the minimum
 
unsigned int NDim () const override
 this is <= Function().NDim() which is the total number of variables (free+ constrained ones)
 
unsigned int NFree () const override
 number of free variables (real dimension of the problem) this is <= Function().NDim() which is the total (re-implement if minimizer supports bounded parameters)
 
ROOT::Math::MinimizerOptions Options () const override
 retrieve the minimizer options (implement derived class if needed)
 
bool ProvidesError () const override
 minimizer provides error and error matrix
 
bool SetFixedVariable (unsigned int ivar, const std::string &name, double val) override
 set a new fixed variable (override if minimizer supports them )
 
void SetFunction (const ROOT::Math::IMultiGenFunction &func) override
 set the function to minimize
 
bool SetLimitedVariable (unsigned int, const std::string &, double, double, double, double) override
 set a new upper/lower limited variable (override if minimizer supports them ) otherwise as default set an unlimited variable
 
virtual void SetOptions (const ROOT::Math::MinimizerOptions &opt)
 
void SetParameters (const GeneticMinimizerParameters &params)
 
void SetRandomSeed (int seed)
 
bool SetVariable (unsigned int ivar, const std::string &name, double val, double step) override
 set a new free variable
 
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 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 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
 
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 FixVariable (unsigned int ivar)
 fix an existing variable
 
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 bool GetVariableSettings (unsigned int ivar, ROOT::Fit::ParameterSettings &pars) const
 get variable settings in a variable object (like ROOT::Fit::ParamsSettings)
 
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
 
virtual bool IsFixedVariable (unsigned int ivar) const
 query if an existing variable is fixed (i.e.
 
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
 
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 ReleaseVariable (unsigned int ivar)
 release an existing variable
 
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)
 
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 )
 
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
 
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 )
 
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
 
virtual bool SetVariableLimits (unsigned int ivar, double lower, double upper)
 set the limits of an already existing variable
 
virtual bool SetVariableLowerLimit (unsigned int ivar, double lower)
 set the lower-limit of an already existing variable
 
template<class VariableIterator >
int SetVariables (const VariableIterator &begin, const VariableIterator &end)
 add variables . Return number of variables successfully added
 
virtual bool SetVariableStepSize (unsigned int ivar, double value)
 set the step size of an already existing variable
 
virtual bool SetVariableUpperLimit (unsigned int ivar, double upper)
 set the upper-limit of an already existing variable
 
virtual bool SetVariableValue (unsigned int ivar, double value)
 set the value of an already existing variable
 
virtual bool SetVariableValues (const double *x)
 set the values of all existing variables (array must be dimensioned to the size of the existing parameters)
 
int Status () const
 status code of minimizer
 
int Strategy () const
 strategy
 
double Tolerance () const
 absolute tolerance
 
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
 
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
 

Protected Member Functions

void GetGeneticOptions (ROOT::Math::MinimizerOptions &opt) const
 

Protected Attributes

TMVA::IFitterTargetfFitness
 
double fMinValue
 
GeneticMinimizerParameters fParameters
 
std::vector< TMVA::Interval * > fRanges
 
std::vector< doublefResult
 
- 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/GeneticMinimizer.h>

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

Constructor & Destructor Documentation

◆ GeneticMinimizer()

ROOT::Math::GeneticMinimizer::GeneticMinimizer ( int  i = 0)

Definition at line 99 of file GeneticMinimizer.cxx.

◆ ~GeneticMinimizer()

ROOT::Math::GeneticMinimizer::~GeneticMinimizer ( )
override

Definition at line 118 of file GeneticMinimizer.cxx.

Member Function Documentation

◆ Clear()

void ROOT::Math::GeneticMinimizer::Clear ( )
overridevirtual

reset for consecutive minimization - implement if needed

Reimplemented from ROOT::Math::Minimizer.

Definition at line 127 of file GeneticMinimizer.cxx.

◆ CovMatrix()

double ROOT::Math::GeneticMinimizer::CovMatrix ( unsigned int  ivar,
unsigned int  jvar 
) const
overridevirtual

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

Reimplemented from ROOT::Math::Minimizer.

Definition at line 369 of file GeneticMinimizer.cxx.

◆ Edm()

double ROOT::Math::GeneticMinimizer::Edm ( ) const
overridevirtual

return expected distance reached from the minimum (re-implement if minimizer provides it

Reimplemented from ROOT::Math::Minimizer.

Definition at line 368 of file GeneticMinimizer.cxx.

◆ Errors()

const double * ROOT::Math::GeneticMinimizer::Errors ( ) const
overridevirtual

return errors at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 367 of file GeneticMinimizer.cxx.

◆ GetGeneticOptions()

void ROOT::Math::GeneticMinimizer::GetGeneticOptions ( ROOT::Math::MinimizerOptions opt) const
protected

Definition at line 192 of file GeneticMinimizer.cxx.

◆ MinGradient()

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

return pointer to gradient values at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 365 of file GeneticMinimizer.cxx.

◆ Minimize()

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

method to perform the minimization

Implements ROOT::Math::Minimizer.

Definition at line 253 of file GeneticMinimizer.cxx.

◆ MinimizerParameters()

const GeneticMinimizerParameters & ROOT::Math::GeneticMinimizer::MinimizerParameters ( ) const
inline

Definition at line 96 of file GeneticMinimizer.h.

◆ MinValue()

double ROOT::Math::GeneticMinimizer::MinValue ( ) const
overridevirtual

return minimum function value

Implements ROOT::Math::Minimizer.

Definition at line 332 of file GeneticMinimizer.cxx.

◆ NCalls()

unsigned int ROOT::Math::GeneticMinimizer::NCalls ( ) const
overridevirtual

number of function calls to reach the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 341 of file GeneticMinimizer.cxx.

◆ NDim()

unsigned int ROOT::Math::GeneticMinimizer::NDim ( ) const
overridevirtual

this is <= Function().NDim() which is the total number of variables (free+ constrained ones)

Implements ROOT::Math::Minimizer.

Definition at line 349 of file GeneticMinimizer.cxx.

◆ NFree()

unsigned int ROOT::Math::GeneticMinimizer::NFree ( ) const
overridevirtual

number of free variables (real dimension of the problem) this is <= Function().NDim() which is the total (re-implement if minimizer supports bounded parameters)

Reimplemented from ROOT::Math::Minimizer.

Definition at line 356 of file GeneticMinimizer.cxx.

◆ Options()

ROOT::Math::MinimizerOptions ROOT::Math::GeneticMinimizer::Options ( ) const
overridevirtual

retrieve the minimizer options (implement derived class if needed)

Reimplemented from ROOT::Math::Minimizer.

Definition at line 186 of file GeneticMinimizer.cxx.

◆ ProvidesError()

bool ROOT::Math::GeneticMinimizer::ProvidesError ( ) const
overridevirtual

minimizer provides error and error matrix

Reimplemented from ROOT::Math::Minimizer.

Definition at line 366 of file GeneticMinimizer.cxx.

◆ SetFixedVariable()

bool ROOT::Math::GeneticMinimizer::SetFixedVariable ( unsigned int  ivar,
const std::string &  name,
double  val 
)
overridevirtual

set a new fixed variable (override if minimizer supports them )

Reimplemented from ROOT::Math::Minimizer.

Definition at line 166 of file GeneticMinimizer.cxx.

◆ SetFunction()

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

set the function to minimize

Implements ROOT::Math::Minimizer.

Definition at line 138 of file GeneticMinimizer.cxx.

◆ SetLimitedVariable()

bool ROOT::Math::GeneticMinimizer::SetLimitedVariable ( unsigned int  ivar,
const std::string &  name,
double  val,
double  step,
double  lower,
double  upper 
)
overridevirtual

set a new upper/lower limited variable (override if minimizer supports them ) otherwise as default set an unlimited variable

Reimplemented from ROOT::Math::Minimizer.

Definition at line 147 of file GeneticMinimizer.cxx.

◆ SetOptions()

void ROOT::Math::GeneticMinimizer::SetOptions ( const ROOT::Math::MinimizerOptions opt)
virtual

Definition at line 218 of file GeneticMinimizer.cxx.

◆ SetParameters()

void ROOT::Math::GeneticMinimizer::SetParameters ( const GeneticMinimizerParameters params)

Definition at line 178 of file GeneticMinimizer.cxx.

◆ SetRandomSeed()

void ROOT::Math::GeneticMinimizer::SetRandomSeed ( int  seed)
inline

Definition at line 94 of file GeneticMinimizer.h.

◆ SetVariable()

bool ROOT::Math::GeneticMinimizer::SetVariable ( unsigned int  ivar,
const std::string &  name,
double  val,
double  step 
)
overridevirtual

set a new free variable

Implements ROOT::Math::Minimizer.

Definition at line 154 of file GeneticMinimizer.cxx.

◆ X()

const double * ROOT::Math::GeneticMinimizer::X ( ) const
overridevirtual

return pointer to X values at the minimum

Implements ROOT::Math::Minimizer.

Definition at line 337 of file GeneticMinimizer.cxx.

Member Data Documentation

◆ fFitness

TMVA::IFitterTarget* ROOT::Math::GeneticMinimizer::fFitness
protected

Definition at line 107 of file GeneticMinimizer.h.

◆ fMinValue

double ROOT::Math::GeneticMinimizer::fMinValue
protected

Definition at line 108 of file GeneticMinimizer.h.

◆ fParameters

GeneticMinimizerParameters ROOT::Math::GeneticMinimizer::fParameters
protected

Definition at line 111 of file GeneticMinimizer.h.

◆ fRanges

std::vector<TMVA::Interval*> ROOT::Math::GeneticMinimizer::fRanges
protected

Definition at line 106 of file GeneticMinimizer.h.

◆ fResult

std::vector<double> ROOT::Math::GeneticMinimizer::fResult
protected

Definition at line 109 of file GeneticMinimizer.h.

Libraries for ROOT::Math::GeneticMinimizer:

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