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Reference Guide
ROOT::Math::RMinimizer Class Reference

RMinimizer class.

Minimizer class that uses the ROOT/R interface to pass functions and minimize them in R.

The class implements the ROOT::Math::Minimizer interface and can be instantiated using the ROOT plugin manager (plugin name is "RMinimizer"). The various minimization algorithms (BFGS, Nelder-Mead, SANN, etc..) can be passed as an option. The default algorithm is BFGS.

The library for this and future R/ROOT classes is currently libRtools.so

Definition at line 31 of file RMinimizer.h.

Public Member Functions

 RMinimizer (Option_t *method)
 Default constructor. More...
 
virtual ~RMinimizer ()
 Destructor. 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 const double * Errors () const
 return errors at the minimum 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...
 
double HessMatrix (unsigned int i, unsigned int j) const
 Returns the ith jth component of the Hessian matrix. More...
 
virtual bool Minimize ()
 Function to find the minimum. More...
 
virtual unsigned int NCalls () const
 Returns the number of function calls. More...
 
virtual bool ProvidesError () const
 minimizer provides error and error matrix More...
 
- Public Member Functions inherited from ROOT::Math::BasicMinimizer
 BasicMinimizer ()
 Default constructor. More...
 
virtual ~BasicMinimizer ()
 Destructor. More...
 
virtual bool FixVariable (unsigned int ivar)
 fix an existing variable More...
 
virtual bool GetVariableSettings (unsigned int ivar, ROOT::Fit::ParameterSettings &varObj) const
 get variable settings in a variable object (like ROOT::Fit::ParamsSettings) More...
 
const ROOT::Math::IMultiGradFunctionGradObjFunction () const
 return pointer to used gradient object function (NULL if gradient is not supported) More...
 
virtual bool IsFixedVariable (unsigned int ivar) const
 query if an existing variable is fixed (i.e. More...
 
virtual double MinValue () const
 return minimum function value More...
 
virtual unsigned int NDim () const
 number of dimensions More...
 
virtual unsigned int NFree () const
 number of free variables (real dimension of the problem) More...
 
virtual unsigned int NPar () const
 total number of parameter defined More...
 
const ROOT::Math::IMultiGenFunctionObjFunction () const
 return pointer to used objective function More...
 
void PrintResult () const
 print result of minimization More...
 
virtual bool ReleaseVariable (unsigned int ivar)
 release an existing variable More...
 
virtual bool SetFixedVariable (unsigned int, const std::string &, double)
 set fixed variable (override if minimizer supports them ) More...
 
virtual void SetFunction (const ROOT::Math::IMultiGenFunction &func)
 set the function to minimize More...
 
virtual void SetFunction (const ROOT::Math::IMultiGradFunction &func)
 set gradient the function to minimize More...
 
virtual bool SetLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double, double)
 set upper/lower limited variable (override if minimizer supports them ) More...
 
virtual bool SetLowerLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double lower)
 set lower limit variable (override if minimizer supports them ) More...
 
virtual bool SetUpperLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double upper)
 set upper limit variable (override if minimizer supports them ) More...
 
virtual bool SetVariable (unsigned int ivar, const std::string &name, double val, double step)
 set free 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...
 
virtual bool SetVariableStepSize (unsigned int ivar, double step)
 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 val)
 set the value of an existing variable More...
 
virtual bool SetVariableValues (const double *x)
 set the values of all existing variables (array must be dimensioned to the size of existing parameters) More...
 
virtual const double * StepSizes () const
 accessor methods More...
 
const ROOT::Math::MinimTransformFunctionTransformFunction () const
 return transformation function (NULL if not having a transformation) 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) 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 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 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 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 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...
 
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 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 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...
 
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...
 
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...
 
template<class VariableIterator >
int SetVariables (const VariableIterator &begin, const VariableIterator &end)
 add variables . Return number of variables successfully added More...
 
int Status () const
 status code of minimizer More...
 
int Strategy () const
 strategy More...
 
double Tolerance () const
 absolute tolerance More...
 

Protected Attributes

std::string fMethod
 minimizer method to be used, must be of a type listed in R optim or optimx descriptions More...
 
- Protected Attributes inherited from ROOT::Math::Minimizer
MinimizerOptions fOptions
 
int fStatus
 
bool fValidError
 

Private Attributes

TMatrixD fCovMatrix
 covariant matrix More...
 
std::vector< double > fErrors
 vector of parameter errors More...
 
TMatrixD fHessMatrix
 Hessian matrix. More...
 

Additional Inherited Members

- Protected Member Functions inherited from ROOT::Math::BasicMinimizer
bool CheckDimension () const
 
bool CheckObjFunction () const
 
MinimTransformFunctionCreateTransformation (std::vector< double > &startValues, const ROOT::Math::IMultiGradFunction *func=0)
 
void SetFinalValues (const double *x)
 
void SetMinValue (double val)
 

#include <Math/RMinimizer.h>

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

◆ RMinimizer()

ROOT::Math::RMinimizer::RMinimizer ( Option_t method)

Default constructor.

Default constructor with option for the method of minimization, can be any of the following: "Nelder-Mead", "BFGS", "CG", "L-BFGS-B", "SANN", "Brent" (Brent only for 1D minimization)

See R optim or optimx descriptions for more details and options.

Definition at line 38 of file RMinimizer.cxx.

◆ ~RMinimizer()

virtual ROOT::Math::RMinimizer::~RMinimizer ( )
inlinevirtual

Destructor.

Definition at line 51 of file RMinimizer.h.

Member Function Documentation

◆ CovMatrix()

virtual double ROOT::Math::RMinimizer::CovMatrix ( unsigned int  ivar,
unsigned int  jvar 
) const
inlinevirtual

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 66 of file RMinimizer.h.

◆ Errors()

virtual const double* ROOT::Math::RMinimizer::Errors ( ) const
inlinevirtual

return errors at the minimum

Reimplemented from ROOT::Math::Minimizer.

Definition at line 61 of file RMinimizer.h.

◆ GetCovMatrix()

virtual bool ROOT::Math::RMinimizer::GetCovMatrix ( double *  covMat) const
inlinevirtual


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 from ROOT::Math::Minimizer.

Definition at line 77 of file RMinimizer.h.

◆ HessMatrix()

double ROOT::Math::RMinimizer::HessMatrix ( unsigned int  i,
unsigned int  j 
) const

Returns the ith jth component of the Hessian matrix.

◆ Minimize()

bool ROOT::Math::RMinimizer::Minimize ( )
virtual

Function to find the minimum.

function for finding the minimum

Reimplemented from ROOT::Math::BasicMinimizer.

Definition at line 47 of file RMinimizer.cxx.

◆ NCalls()

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

Returns the number of function calls.

returns number of function calls

Reimplemented from ROOT::Math::Minimizer.

Definition at line 44 of file RMinimizer.cxx.

◆ ProvidesError()

virtual bool ROOT::Math::RMinimizer::ProvidesError ( ) const
inlinevirtual

minimizer provides error and error matrix

Reimplemented from ROOT::Math::Minimizer.

Definition at line 59 of file RMinimizer.h.

Member Data Documentation

◆ fCovMatrix

TMatrixD ROOT::Math::RMinimizer::fCovMatrix
private

covariant matrix

Definition at line 37 of file RMinimizer.h.

◆ fErrors

std::vector<double> ROOT::Math::RMinimizer::fErrors
private

vector of parameter errors

Definition at line 36 of file RMinimizer.h.

◆ fHessMatrix

TMatrixD ROOT::Math::RMinimizer::fHessMatrix
private

Hessian matrix.

Definition at line 38 of file RMinimizer.h.

◆ fMethod

std::string ROOT::Math::RMinimizer::fMethod
protected

minimizer method to be used, must be of a type listed in R optim or optimx descriptions

Definition at line 33 of file RMinimizer.h.

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