Abstract Minimizer class, defining the interface for the various minimizer (like Minuit2, Minuit, GSL, etc..) in ROOT.
Plug-in's exist in ROOT to be able to instantiate the derived classes without linking the library using the static function ROOT::Math::Factory::CreateMinimizer.
Here is the list of all possible minimizers and their respective methods (algorithms) that can be instantiated: The name shown below can be used to create them. More documentation can be found in the respective class
mathmore
supportmathmore
supportmathmore
supportr
supportoptimix
of the optmix R packageThe Minimizer class provides the interface to perform the minimization including
In addition to provide the API for function minimization (via ROOT::Math::Minimizer::Minimize) the Minimizer class provides:
ROOT::Math::Functor
class and the ROOT::Math::GradFunctor
class for wrapping functions providing both evaluation and gradient. Some methods, like Fumili, Fumili2 and GSLMultiFit are specialized method for least-square and also likelihood minimizations. They require then that the given function implements in addition the ROOT::Math::FitMethodFunction
interface.ROOT::Math::MinimizerOptions
. When no parameters are specified the default ones are used. Specific Minimizer options can also be passed via the MinimizerOptions
class. For the list of the available option parameter one must look at the documentation of the corresponding derived class.An example on how to use this interface is the tutorial NumericalMinimization.C in the tutorials/fit directory.
Definition at line 119 of file Minimizer.h.
Public Member Functions | |
Minimizer () | |
Default constructor. | |
Minimizer (Minimizer &&)=delete | |
Minimizer (Minimizer const &)=delete | |
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 double * | Errors () const |
return errors at the minimum | |
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 const double * | MinGradient () const |
return pointer to gradient values at the minimum | |
virtual bool | Minimize ()=0 |
method to perform the minimization | |
virtual int | MinosStatus () const |
status code of Minos (to be re-implemented by the minimizers supporting Minos) | |
virtual double | MinValue () const =0 |
return minimum function value | |
virtual unsigned int | NCalls () const |
number of function calls to reach the minimum | |
virtual unsigned int | NDim () const =0 |
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 unsigned int | NIterations () const |
number of iterations to reach the minimum | |
Minimizer & | operator= (Minimizer &&)=delete |
Minimizer & | operator= (Minimizer const &)=delete |
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 | 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 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)=0 |
set the function to minimize | |
virtual void | SetHessianFunction (std::function< bool(std::span< const double >, double *)>) |
set the function implementing Hessian computation (re-implemented by Minimizer using it) | |
virtual bool | SetLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double lower, double upper) |
set a new upper/lower limited variable (override if minimizer supports them ) otherwise as default set an unlimited variable | |
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 | SetVariable (unsigned int ivar, const std::string &name, double val, double step)=0 |
set a new free variable | |
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 | |
virtual const double * | X () const =0 |
return pointer to X values at the minimum | |
Protected Attributes | |
MinimizerOptions | fOptions |
minimizer options | |
int | fStatus = -1 |
status of minimizer | |
bool | fValidError = false |
flag to control if errors have been validated (Hesse has been run in case of Minuit) | |
#include <Math/Minimizer.h>
|
inline |
Default constructor.
Definition at line 124 of file Minimizer.h.
|
inlinevirtual |
Destructor (no operations).
Definition at line 127 of file Minimizer.h.
|
delete |
|
delete |
|
inlinevirtual |
reset for consecutive minimization - implement if needed
Reimplemented in ROOT::Math::GeneticMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 136 of file Minimizer.h.
|
virtual |
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();
Reimplemented in TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 192 of file Minimizer.cxx.
|
inlinevirtual |
return correlation coefficient between variable i and j.
If the variable is fixed or const the return value is zero
Reimplemented in ROOT::Minuit2::Minuit2Minimizer.
Definition at line 259 of file Minimizer.h.
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 in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, TLinearMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::RMinimizer, ROOT::Math::GSLMinimizer, and ROOT::Math::GSLNLSMinimizer.
Definition at line 101 of file Minimizer.cxx.
|
inlinevirtual |
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
Reimplemented in TFumiliMinimizer, ROOT::Math::GSLNLSMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 251 of file Minimizer.h.
|
inlinevirtual |
return expected distance reached from the minimum (re-implement if minimizer provides it
Reimplemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 217 of file Minimizer.h.
|
inline |
return the statistical scale used for calculate the error is typically 1 for Chi2 and 0.5 for likelihood minimization
Definition at line 312 of file Minimizer.h.
|
inlinevirtual |
return errors at the minimum
Reimplemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, TLinearMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::RMinimizer.
Definition at line 241 of file Minimizer.h.
fix an existing variable
Reimplemented in ROOT::Math::BasicMinimizer, ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 68 of file Minimizer.cxx.
Fill the passed array with the covariance matrix elements if the variable is fixed or const the value is zero.
The array will be filled as cov[i *ndim + j] The ordering of the variables is the same as in errors and parameter value. This is different from the direct interface of Minuit2 or TMinuit where the values were obtained only to variable parameters
Reimplemented in TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::RMinimizer.
Definition at line 116 of file Minimizer.cxx.
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.
The array will be filled as h[i *ndim + j]
Reimplemented in TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 129 of file Minimizer.cxx.
|
virtual |
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
Reimplemented in TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 153 of file Minimizer.cxx.
|
virtual |
get variable settings in a variable object (like ROOT::Fit::ParamsSettings)
Reimplemented in ROOT::Math::BasicMinimizer, ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 90 of file Minimizer.cxx.
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.
Minimizer must overload method if implemented
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 142 of file Minimizer.cxx.
|
virtual |
perform a full calculation of the Hessian matrix for error calculation
Reimplemented in TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 166 of file Minimizer.cxx.
query if an existing variable is fixed (i.e.
considered constant in the minimization) note that by default all variables are not fixed
Reimplemented in ROOT::Math::BasicMinimizer, ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 83 of file Minimizer.cxx.
|
inline |
return true if Minimizer has performed a detailed error validation (e.g. run Hesse for Minuit)
Definition at line 315 of file Minimizer.h.
|
inline |
max number of function calls
Definition at line 289 of file Minimizer.h.
|
inline |
max iterations
Definition at line 292 of file Minimizer.h.
|
inlinevirtual |
return pointer to gradient values at the minimum
Reimplemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 220 of file Minimizer.h.
|
pure virtual |
method to perform the minimization
Implemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, ROOT::Math::GSLSimAnMinimizer, TLinearMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::RMinimizer.
|
inlinevirtual |
status code of Minos (to be re-implemented by the minimizers supporting Minos)
Reimplemented in TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 308 of file Minimizer.h.
|
pure virtual |
return minimum function value
Implemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
|
inlinevirtual |
number of function calls to reach the minimum
Reimplemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, ROOT::Math::GSLSimAnMinimizer, TLinearMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::RMinimizer.
Definition at line 223 of file Minimizer.h.
|
pure virtual |
this is <= Function().NDim() which is the total number of variables (free+ constrained ones)
Implemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
|
inlinevirtual |
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 in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 235 of file Minimizer.h.
|
inlinevirtual |
number of iterations to reach the minimum
Definition at line 226 of file Minimizer.h.
|
inlinevirtual |
retrieve the minimizer options (implement derived class if needed)
Reimplemented in ROOT::Math::GeneticMinimizer.
Definition at line 318 of file Minimizer.h.
|
inline |
precision of minimizer in the evaluation of the objective function ( a value <=0 corresponds to the let the minimizer choose its default one)
Definition at line 299 of file Minimizer.h.
|
inline |
|
inlinevirtual |
return reference to the objective function virtual const ROOT::Math::IGenFunction & Function() const = 0;
print the result according to set level (implemented for TMinuit for maintaining Minuit-style printing)
Reimplemented in TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 277 of file Minimizer.h.
|
inlinevirtual |
minimizer provides error and error matrix
Reimplemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, TLinearMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::RMinimizer.
Definition at line 238 of file Minimizer.h.
release an existing variable
Reimplemented in ROOT::Math::BasicMinimizer, ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 75 of file Minimizer.cxx.
|
virtual |
scan function minimum for variable i.
Variable and function must be set before using Scan Return false if an error or if minimizer does not support this functionality
Reimplemented in TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 176 of file Minimizer.cxx.
|
inline |
reset the default options (defined in MinimizerOptions)
Definition at line 356 of file Minimizer.h.
|
inline |
set scale for calculating the errors
Definition at line 342 of file Minimizer.h.
|
inline |
set only the extra options
Definition at line 353 of file Minimizer.h.
|
virtual |
set a new fixed variable (override if minimizer supports them )
Reimplemented in ROOT::Math::GeneticMinimizer, TFumiliMinimizer, ROOT::Math::BasicMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 25 of file Minimizer.cxx.
|
pure virtual |
set the function to minimize
Implemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, ROOT::Math::GSLMinimizer, ROOT::Math::GSLNLSMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
|
inlinevirtual |
set the function implementing Hessian computation (re-implemented by Minimizer using it)
Reimplemented in ROOT::Minuit2::Minuit2Minimizer.
Definition at line 142 of file Minimizer.h.
|
virtual |
set a new upper/lower limited variable (override if minimizer supports them ) otherwise as default set an unlimited variable
Reimplemented in TFumiliMinimizer, ROOT::Math::BasicMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::GeneticMinimizer.
Definition at line 15 of file Minimizer.cxx.
|
inlinevirtual |
set a new lower limit variable (override if minimizer supports them )
Reimplemented in ROOT::Math::BasicMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 170 of file Minimizer.h.
|
inline |
set maximum of function calls
Definition at line 326 of file Minimizer.h.
|
inline |
set maximum iterations (one iteration can have many function calls)
Definition at line 329 of file Minimizer.h.
|
inline |
set all options in one go
Definition at line 348 of file Minimizer.h.
|
inline |
set in the minimizer the objective function evaluation precision ( a value <=0 means the minimizer will choose its optimal value automatically, i.e.
default case)
Definition at line 336 of file Minimizer.h.
|
inline |
set print level
Definition at line 323 of file Minimizer.h.
|
inline |
set the strategy
Definition at line 339 of file Minimizer.h.
|
inline |
set the tolerance
Definition at line 332 of file Minimizer.h.
|
inlinevirtual |
set a new upper limit variable (override if minimizer supports them )
Reimplemented in ROOT::Math::BasicMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 174 of file Minimizer.h.
|
inline |
flag to check if minimizer needs to perform accurate error analysis (e.g. run Hesse for Minuit)
Definition at line 345 of file Minimizer.h.
|
pure virtual |
set a new free variable
Implemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and TLinearMinimizer.
|
inlinevirtual |
set the initial range of an existing variable
Definition at line 203 of file Minimizer.h.
|
inlinevirtual |
set the limits of an already existing variable
Reimplemented in ROOT::Math::BasicMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 194 of file Minimizer.h.
set the lower-limit of an already existing variable
Reimplemented in ROOT::Math::BasicMinimizer, ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 51 of file Minimizer.cxx.
|
inline |
add variables . Return number of variables successfully added
Definition at line 146 of file Minimizer.h.
set the step size of an already existing variable
Reimplemented in ROOT::Math::BasicMinimizer, ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 43 of file Minimizer.cxx.
set the upper-limit of an already existing variable
Reimplemented in ROOT::Math::BasicMinimizer, ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 59 of file Minimizer.cxx.
set the value of an already existing variable
Reimplemented in TFumiliMinimizer, ROOT::Math::BasicMinimizer, ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 34 of file Minimizer.cxx.
set the values of all existing variables (array must be dimensioned to the size of the existing parameters)
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::BasicMinimizer.
Definition at line 182 of file Minimizer.h.
|
inline |
status code of minimizer
Definition at line 305 of file Minimizer.h.
|
inline |
strategy
Definition at line 302 of file Minimizer.h.
|
inline |
absolute tolerance
Definition at line 295 of file Minimizer.h.
|
virtual |
get index of variable given a variable given a name return -1 if variable is not found
Reimplemented in ROOT::Math::BasicMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 213 of file Minimizer.cxx.
|
virtual |
get name of variables (override if minimizer support storing of variable names) return an empty string if variable is not found
Reimplemented in ROOT::Math::BasicMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
Definition at line 205 of file Minimizer.cxx.
|
pure virtual |
return pointer to X values at the minimum
Implemented in TFumiliMinimizer, ROOT::Math::GeneticMinimizer, ROOT::Math::BasicMinimizer, TLinearMinimizer, TMinuitMinimizer, and ROOT::Minuit2::Minuit2Minimizer.
|
protected |
minimizer options
Definition at line 365 of file Minimizer.h.
|
protected |
status of minimizer
Definition at line 366 of file Minimizer.h.
|
protected |
flag to control if errors have been validated (Hesse has been run in case of Minuit)
Definition at line 364 of file Minimizer.h.