ROOT 6.08/07 Reference Guide |
Abstract Minimizer class, defining the interface for the various minimizer (like Minuit2, Minuit, GSL, etc..) Plug-in's exist in ROOT to be able to instantiate the derived classes like ROOT::Math::GSLMinimizer or ROOT::Math::Minuit2Minimizer via the plug-in manager.
Provides interface for setting the function to be minimized. The function must implemente the multi-dimensional generic interface ROOT::Math::IBaseFunctionMultiDim. If the function provides gradient calculation (implements the ROOT::Math::IGradientFunctionMultiDim interface) this will be used by the Minimizer.
It Defines also interface for setting the initial values for the function variables (which are the parameters in of the model function in case of solving for fitting) and especifying their limits.
It defines the interface to set and retrieve basic minimization parameters (for specific Minimizer parameters one must use the derived classes).
Then it defines the interface to retrieve the result of minimization ( minimum X values, function value, gradient, error on the mimnimum, etc...)
Definition at line 86 of file Minimizer.h.
Public Member Functions | |
Minimizer () | |
Default constructor. More... | |
virtual | ~Minimizer () |
Destructor (no operations) More... | |
virtual void | Clear () |
reset for consecutive minimizations - implement if needed 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 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 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... | |
virtual double | Edm () const |
return expected distance reached from the minimum (re-implement if minimizer provides it 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 const double * | Errors () const |
return errors at the minimum 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 const double * | MinGradient () const |
return pointer to gradient values at the minimum More... | |
virtual bool | Minimize ()=0 |
method to perform the minimization More... | |
virtual double | MinValue () const =0 |
return minimum function value More... | |
virtual unsigned int | NCalls () const |
number of function calls to reach the minimum More... | |
virtual unsigned int | NDim () const =0 |
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 unsigned int | NIterations () const |
number of iterations to reach the minimum More... | |
virtual MinimizerOptions | Options () const |
retrieve the minimizer options (implement derived class if needed) 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 | ProvidesError () const |
minimizer provides error and error matrix 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 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)=0 |
set the function to minimize More... | |
virtual void | SetFunction (const ROOT::Math::IMultiGradFunction &func) |
set a function to minimize using gradient More... | |
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 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 | SetVariable (unsigned int ivar, const std::string &name, double val, double step)=0 |
set a new free variable 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... | |
virtual const double * | X () const =0 |
return pointer to X values at the minimum More... | |
Protected Attributes | |
MinimizerOptions | fOptions |
int | fStatus |
bool | fValidError |
Private Member Functions | |
Minimizer (const Minimizer &) | |
Copy constructor. More... | |
Minimizer & | operator= (const Minimizer &rhs) |
Assignment operator. More... | |
#include <Math/Minimizer.h>
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Default constructor.
Definition at line 93 of file Minimizer.h.
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Destructor (no operations)
Definition at line 101 of file Minimizer.h.
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Copy constructor.
Definition at line 112 of file Minimizer.h.
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reset for consecutive minimizations - implement if needed
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::GeneticMinimizer.
Definition at line 125 of file Minimizer.h.
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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 ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 387 of file Minimizer.h.
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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 334 of file Minimizer.h.
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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 ROOT::Math::GSLNLSMinimizer, ROOT::Minuit2::Minuit2Minimizer, TMinuitMinimizer, ROOT::Math::GSLMinimizer, TFumiliMinimizer, TLinearMinimizer, ROOT::Math::GeneticMinimizer, and ROOT::Math::RMinimizer.
Definition at line 292 of file Minimizer.h.
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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 ROOT::Math::GSLNLSMinimizer, ROOT::Minuit2::Minuit2Minimizer, TMinuitMinimizer, TFumiliMinimizer, and TLinearMinimizer.
Definition at line 326 of file Minimizer.h.
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return expected distance reached from the minimum (re-implement if minimizer provides it
Reimplemented in ROOT::Math::GSLNLSMinimizer, ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::GSLMinimizer, TMinuitMinimizer, TFumiliMinimizer, TLinearMinimizer, and ROOT::Math::GeneticMinimizer.
Definition at line 262 of file Minimizer.h.
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return the statistical scale used for calculate the error is typically 1 for Chi2 and 0.5 for likelihood minimization
Definition at line 442 of file Minimizer.h.
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return errors at the minimum
Reimplemented in ROOT::Math::GSLNLSMinimizer, ROOT::Minuit2::Minuit2Minimizer, TMinuitMinimizer, ROOT::Math::GSLMinimizer, TFumiliMinimizer, TLinearMinimizer, ROOT::Math::GeneticMinimizer, and ROOT::Math::RMinimizer.
Definition at line 286 of file Minimizer.h.
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fix an existing variable
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, and TMinuitMinimizer.
Definition at line 221 of file Minimizer.h.
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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 ROOT::Minuit2::Minuit2Minimizer, TMinuitMinimizer, and ROOT::Math::RMinimizer.
Definition at line 305 of file Minimizer.h.
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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 ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 317 of file Minimizer.h.
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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)
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 357 of file Minimizer.h.
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get variable settings in a variable object (like ROOT::Fit::ParamsSettings)
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, and TMinuitMinimizer.
Definition at line 240 of file Minimizer.h.
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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 346 of file Minimizer.h.
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perform a full calculation of the Hessian matrix for error calculation
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 366 of file Minimizer.h.
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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::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, and TMinuitMinimizer.
Definition at line 234 of file Minimizer.h.
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return true if Minimizer has performed a detailed error validation (e.g. run Hesse for Minuit)
Definition at line 445 of file Minimizer.h.
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max number of function calls
Definition at line 422 of file Minimizer.h.
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max iterations
Definition at line 425 of file Minimizer.h.
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return pointer to gradient values at the minimum
Reimplemented in ROOT::Math::GSLNLSMinimizer, ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::GSLMinimizer, TMinuitMinimizer, TFumiliMinimizer, TLinearMinimizer, and ROOT::Math::GeneticMinimizer.
Definition at line 265 of file Minimizer.h.
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method to perform the minimization
Implemented in ROOT::Math::GSLNLSMinimizer, ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, ROOT::Math::GSLMinimizer, TMinuitMinimizer, ROOT::Math::GSLSimAnMinimizer, TFumiliMinimizer, TLinearMinimizer, ROOT::Math::GeneticMinimizer, and ROOT::Math::RMinimizer.
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return minimum function value
Implemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, TMinuitMinimizer, TFumiliMinimizer, TLinearMinimizer, and ROOT::Math::GeneticMinimizer.
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number of function calls to reach the minimum
Reimplemented in ROOT::Math::GSLNLSMinimizer, ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::GSLMinimizer, TMinuitMinimizer, TFumiliMinimizer, ROOT::Math::GSLSimAnMinimizer, TLinearMinimizer, ROOT::Math::GeneticMinimizer, and ROOT::Math::RMinimizer.
Definition at line 268 of file Minimizer.h.
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this is <= Function().NDim() which is the total number of variables (free+ constrained ones)
Implemented in ROOT::Minuit2::Minuit2Minimizer, TMinuitMinimizer, ROOT::Math::BasicMinimizer, TFumiliMinimizer, TLinearMinimizer, and ROOT::Math::GeneticMinimizer.
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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 ROOT::Minuit2::Minuit2Minimizer, TMinuitMinimizer, ROOT::Math::BasicMinimizer, TFumiliMinimizer, TLinearMinimizer, and ROOT::Math::GeneticMinimizer.
Definition at line 280 of file Minimizer.h.
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number of iterations to reach the minimum
Definition at line 271 of file Minimizer.h.
Assignment operator.
Definition at line 117 of file Minimizer.h.
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retrieve the minimizer options (implement derived class if needed)
Reimplemented in ROOT::Math::GeneticMinimizer.
Definition at line 448 of file Minimizer.h.
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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 432 of file Minimizer.h.
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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 mantaining Minuit-style printing)
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 399 of file Minimizer.h.
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minimizer provides error and error matrix
Reimplemented in ROOT::Math::GSLNLSMinimizer, ROOT::Minuit2::Minuit2Minimizer, TMinuitMinimizer, ROOT::Math::GSLMinimizer, TFumiliMinimizer, TLinearMinimizer, ROOT::Math::GeneticMinimizer, and ROOT::Math::RMinimizer.
Definition at line 283 of file Minimizer.h.
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release an existing variable
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, and TMinuitMinimizer.
Definition at line 227 of file Minimizer.h.
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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 ROOT::Minuit2::Minuit2Minimizer, and TMinuitMinimizer.
Definition at line 375 of file Minimizer.h.
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reset the defaut options (defined in MinimizerOptions)
Definition at line 483 of file Minimizer.h.
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set scale for calculating the errors
Definition at line 472 of file Minimizer.h.
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set a new fixed variable (override if minimizer supports them )
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, TMinuitMinimizer, TFumiliMinimizer, TLinearMinimizer, and ROOT::Math::GeneticMinimizer.
Definition at line 178 of file Minimizer.h.
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set the function to minimize
Implemented in ROOT::Math::GSLNLSMinimizer, ROOT::Math::GSLMinimizer, ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, TMinuitMinimizer, TFumiliMinimizer, ROOT::Math::GeneticMinimizer, and TLinearMinimizer.
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set a function to minimize using gradient
Reimplemented in ROOT::Math::GSLNLSMinimizer, ROOT::Math::GSLMinimizer, ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, TMinuitMinimizer, TFumiliMinimizer, and TLinearMinimizer.
Definition at line 131 of file Minimizer.h.
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set a new upper/lower limited variable (override if minimizer supports them ) otherwise as default set an unlimited variable
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, TMinuitMinimizer, TFumiliMinimizer, and ROOT::Math::GeneticMinimizer.
Definition at line 171 of file Minimizer.h.
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set a new lower limit variable (override if minimizer supports them )
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, and TMinuitMinimizer.
Definition at line 163 of file Minimizer.h.
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set maximum of function calls
Definition at line 456 of file Minimizer.h.
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set maximum iterations (one iteration can have many function calls)
Definition at line 459 of file Minimizer.h.
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set all options in one go
Definition at line 478 of file Minimizer.h.
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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 466 of file Minimizer.h.
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set print level
Definition at line 453 of file Minimizer.h.
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set the strategy
Definition at line 469 of file Minimizer.h.
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set the tolerance
Definition at line 462 of file Minimizer.h.
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set a new upper limit variable (override if minimizer supports them )
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, and TMinuitMinimizer.
Definition at line 167 of file Minimizer.h.
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flag to check if minimizer needs to perform accurate error analysis (e.g. run Hesse for Minuit)
Definition at line 475 of file Minimizer.h.
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set a new free variable
Implemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, TMinuitMinimizer, TFumiliMinimizer, TLinearMinimizer, and ROOT::Math::GeneticMinimizer.
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set the initial range of an existing variable
Definition at line 248 of file Minimizer.h.
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set the limits of an already existing variable
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, and TMinuitMinimizer.
Definition at line 217 of file Minimizer.h.
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set the lower-limit of an already existing variable
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, and TMinuitMinimizer.
Definition at line 205 of file Minimizer.h.
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add variables . Return number of variables successfully added
Definition at line 139 of file Minimizer.h.
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set the step size of an already existing variable
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, and TMinuitMinimizer.
Definition at line 199 of file Minimizer.h.
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set the upper-limit of an already existing variable
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, and TMinuitMinimizer.
Definition at line 211 of file Minimizer.h.
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set the value of an already existing variable
Reimplemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, TMinuitMinimizer, and TFumiliMinimizer.
Definition at line 184 of file Minimizer.h.
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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 190 of file Minimizer.h.
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status code of minimizer
Definition at line 438 of file Minimizer.h.
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strategy
Definition at line 435 of file Minimizer.h.
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absolute tolerance
Definition at line 428 of file Minimizer.h.
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get index of variable given a variable given a name return -1 if variable is not found
Reimplemented in TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::BasicMinimizer.
Definition at line 410 of file Minimizer.h.
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get name of variables (override if minimizer support storing of variable names) return an empty string if variable is not found
Reimplemented in TMinuitMinimizer, ROOT::Minuit2::Minuit2Minimizer, and ROOT::Math::BasicMinimizer.
Definition at line 403 of file Minimizer.h.
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return pointer to X values at the minimum
Implemented in ROOT::Minuit2::Minuit2Minimizer, ROOT::Math::BasicMinimizer, TMinuitMinimizer, TFumiliMinimizer, TLinearMinimizer, and ROOT::Math::GeneticMinimizer.
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Definition at line 497 of file Minimizer.h.
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Definition at line 498 of file Minimizer.h.
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Definition at line 496 of file Minimizer.h.