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Reference Guide
ROOT::Math::GeneticMinimizer Class Reference

GeneticMinimizer.

Minimizer class based on the Gentic algorithm implemented in TMVA

Definition at line 60 of file GeneticMinimizer.h.

Public Member Functions

 GeneticMinimizer (int i=0)
 
virtual ~GeneticMinimizer ()
 
virtual void Clear ()
 reset for consecutive minimizations - implement if needed More...
 
virtual double CovMatrix (unsigned int i, unsigned int j) 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 double Edm () const
 return expected distance reached from the minimum (re-implement if minimizer provides it 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...
 
const GeneticMinimizerParametersMinimizerParameters () const
 
virtual double MinValue () const
 return minimum function value More...
 
virtual unsigned int NCalls () const
 number of function calls to reach the minimum More...
 
virtual unsigned int NDim () const
 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 ROOT::Math::MinimizerOptions Options () const
 retrieve the minimizer options (implement derived class if needed) More...
 
virtual bool ProvidesError () const
 minimizer provides error and error matrix 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)
 set the function to minimize More...
 
virtual bool SetLimitedVariable (unsigned int, const std::string &, double, double, double, double)
 set a new upper/lower limited variable (override if minimizer supports them ) otherwise as default set an unlimited variable More...
 
virtual void SetOptions (const ROOT::Math::MinimizerOptions &opt)
 
void SetParameters (const GeneticMinimizerParameters &params)
 
void SetRandomSeed (int seed)
 
virtual bool SetVariable (unsigned int ivar, const std::string &name, double val, double step)
 set a new free variable 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 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 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...
 
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 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 (This feature is not yet implemented) 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 unsigned int NIterations () const
 number of iterations to reach the minimum 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 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 defaut options (defined in MinimizerOptions) More...
 
void SetErrorDef (double up)
 set scale for calculating the errors More...
 
virtual void SetFunction (const ROOT::Math::IMultiGradFunction &func)
 set a function to minimize using gradient 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 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...
 

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< double > fResult
 
- Protected Attributes inherited from ROOT::Math::Minimizer
MinimizerOptions fOptions
 
int fStatus
 
bool fValidError
 

#include <Math/GeneticMinimizer.h>

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

◆ GeneticMinimizer()

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

Definition at line 99 of file GeneticMinimizer.cxx.

◆ ~GeneticMinimizer()

ROOT::Math::GeneticMinimizer::~GeneticMinimizer ( )
virtual

Definition at line 118 of file GeneticMinimizer.cxx.

Member Function Documentation

◆ Clear()

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

reset for consecutive minimizations - 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
virtual

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
virtual

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
virtual

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
virtual

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 ( )
virtual

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 95 of file GeneticMinimizer.h.

◆ MinValue()

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

return minimum function value

Implements ROOT::Math::Minimizer.

Definition at line 332 of file GeneticMinimizer.cxx.

◆ NCalls()

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

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
virtual

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
virtual

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
virtual

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
virtual

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 
)
virtual

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)
virtual

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 
)
virtual

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 93 of file GeneticMinimizer.h.

◆ SetVariable()

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

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
virtual

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 106 of file GeneticMinimizer.h.

◆ fMinValue

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

Definition at line 107 of file GeneticMinimizer.h.

◆ fParameters

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

Definition at line 110 of file GeneticMinimizer.h.

◆ fRanges

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

Definition at line 105 of file GeneticMinimizer.h.

◆ fResult

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

Definition at line 108 of file GeneticMinimizer.h.

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