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 double * | Errors () const override |
return errors at the minimum | |
const double * | MinGradient () const override |
return pointer to gradient values at the minimum | |
bool | Minimize () override |
method to perform the minimization | |
const GeneticMinimizerParameters & | MinimizerParameters () 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 ¶ms) |
void | SetRandomSeed (int seed) |
bool | SetVariable (unsigned int ivar, const std::string &name, double val, double step) override |
set a new free variable | |
const double * | X () const override |
return pointer to X values at the minimum | |
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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::IFitterTarget * | fFitness |
double | fMinValue |
GeneticMinimizerParameters | fParameters |
std::vector< TMVA::Interval * > | fRanges |
std::vector< double > | fResult |
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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>
ROOT::Math::GeneticMinimizer::GeneticMinimizer | ( | int | i = 0 | ) |
Definition at line 99 of file GeneticMinimizer.cxx.
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override |
Definition at line 118 of file GeneticMinimizer.cxx.
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overridevirtual |
reset for consecutive minimization - implement if needed
Reimplemented from ROOT::Math::Minimizer.
Definition at line 127 of file GeneticMinimizer.cxx.
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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.
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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.
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overridevirtual |
return errors at the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 367 of file GeneticMinimizer.cxx.
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Definition at line 192 of file GeneticMinimizer.cxx.
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return pointer to gradient values at the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 365 of file GeneticMinimizer.cxx.
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overridevirtual |
method to perform the minimization
Implements ROOT::Math::Minimizer.
Definition at line 253 of file GeneticMinimizer.cxx.
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inline |
Definition at line 96 of file GeneticMinimizer.h.
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overridevirtual |
return minimum function value
Implements ROOT::Math::Minimizer.
Definition at line 332 of file GeneticMinimizer.cxx.
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overridevirtual |
number of function calls to reach the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 341 of file GeneticMinimizer.cxx.
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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.
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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.
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overridevirtual |
retrieve the minimizer options (implement derived class if needed)
Reimplemented from ROOT::Math::Minimizer.
Definition at line 186 of file GeneticMinimizer.cxx.
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overridevirtual |
minimizer provides error and error matrix
Reimplemented from ROOT::Math::Minimizer.
Definition at line 366 of file GeneticMinimizer.cxx.
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overridevirtual |
set a new fixed variable (override if minimizer supports them )
Reimplemented from ROOT::Math::Minimizer.
Definition at line 166 of file GeneticMinimizer.cxx.
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overridevirtual |
set the function to minimize
Implements ROOT::Math::Minimizer.
Definition at line 138 of file GeneticMinimizer.cxx.
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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.
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Definition at line 218 of file GeneticMinimizer.cxx.
void ROOT::Math::GeneticMinimizer::SetParameters | ( | const GeneticMinimizerParameters & | params | ) |
Definition at line 178 of file GeneticMinimizer.cxx.
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inline |
Definition at line 94 of file GeneticMinimizer.h.
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overridevirtual |
set a new free variable
Implements ROOT::Math::Minimizer.
Definition at line 154 of file GeneticMinimizer.cxx.
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overridevirtual |
return pointer to X values at the minimum
Implements ROOT::Math::Minimizer.
Definition at line 337 of file GeneticMinimizer.cxx.
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Definition at line 107 of file GeneticMinimizer.h.
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Definition at line 108 of file GeneticMinimizer.h.
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Definition at line 111 of file GeneticMinimizer.h.
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Definition at line 106 of file GeneticMinimizer.h.
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Definition at line 109 of file GeneticMinimizer.h.