ROOT   Reference Guide
Searching...
No Matches
ROOT::Math::GeneticMinimizer Class Reference

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)

virtual ~GeneticMinimizer ()

virtual void Clear ()
reset for consecutive minimizations - implement if needed

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

virtual double Edm () const
return expected distance reached from the minimum (re-implement if minimizer provides it

virtual const doubleErrors () const
return errors at the minimum

return pointer to gradient values at the minimum

virtual bool Minimize ()
method to perform the minimization

const GeneticMinimizerParametersMinimizerParameters () const

virtual double MinValue () const
return minimum function value

virtual unsigned int NCalls () const
number of function calls to reach the minimum

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

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)

virtual ROOT::Math::MinimizerOptions Options () const
retrieve the minimizer options (implement derived class if needed)

virtual bool ProvidesError () const
minimizer provides error and error matrix

virtual bool SetFixedVariable (unsigned int ivar, const std::string &name, double val)
set a new fixed variable (override if minimizer supports them )

virtual void SetFunction (const ROOT::Math::IMultiGenFunction &func)
set the function to minimize

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

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

virtual const doubleX () const
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 defaut options (defined in MinimizerOptions)

void SetErrorDef (double up)
set scale for calculating the errors

virtual void SetFunction (const ROOT::Math::IMultiGradFunction &func)
set a function to minimize using gradient

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)

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

int fStatus

bool fValidError

#include <Math/GeneticMinimizer.h>

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

## ◆ 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.

## ◆ 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.

 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 96 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 94 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.

## ◆ 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 ROOT::Math::GeneticMinimizer::fRanges
protected

Definition at line 106 of file GeneticMinimizer.h.

## ◆ fResult

 std::vector 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: