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 33 of file RMinimizer.h.
Public Member Functions | |
RMinimizer (Option_t *method) | |
Default constructor. | |
~RMinimizer () override | |
Destructor. | |
double | CovMatrix (unsigned int ivar, unsigned int jvar) 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 | |
const double * | Errors () const override |
return errors at the minimum | |
bool | GetCovMatrix (double *covMat) const override |
Fill the passed array with the covariance matrix elements if the variable is fixed or const the value is zero. | |
double | HessMatrix (unsigned int i, unsigned int j) const |
Returns the ith jth component of the Hessian matrix. | |
bool | Minimize () override |
Function to find the minimum. | |
unsigned int | NCalls () const override |
Returns the number of function calls. | |
bool | ProvidesError () const override |
minimizer provides error and error matrix | |
Public Member Functions inherited from ROOT::Math::BasicMinimizer | |
BasicMinimizer () | |
Default constructor. | |
~BasicMinimizer () override | |
Destructor. | |
bool | FixVariable (unsigned int ivar) override |
fix an existing variable | |
bool | GetVariableSettings (unsigned int ivar, ROOT::Fit::ParameterSettings &varObj) const override |
get variable settings in a variable object (like ROOT::Fit::ParamsSettings) | |
const ROOT::Math::IMultiGradFunction * | GradObjFunction () const |
return pointer to used gradient object function (NULL if gradient is not supported) | |
bool | IsFixedVariable (unsigned int ivar) const override |
query if an existing variable is fixed (i.e. | |
double | MinValue () const override |
return minimum function value | |
unsigned int | NDim () const override |
number of dimensions | |
unsigned int | NFree () const override |
number of free variables (real dimension of the problem) | |
virtual unsigned int | NPar () const |
total number of parameter defined | |
const ROOT::Math::IMultiGenFunction * | ObjFunction () const |
return pointer to used objective function | |
void | PrintResult () const |
print result of minimization | |
bool | ReleaseVariable (unsigned int ivar) override |
release an existing variable | |
bool | SetFixedVariable (unsigned int, const std::string &, double) override |
set fixed variable (override if minimizer supports them ) | |
void | SetFunction (const ROOT::Math::IMultiGenFunction &func) override |
set the function to minimize | |
bool | SetLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double, double) override |
set upper/lower limited variable (override if minimizer supports them ) | |
bool | SetLowerLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double lower) override |
set lower limit variable (override if minimizer supports them ) | |
bool | SetUpperLimitedVariable (unsigned int ivar, const std::string &name, double val, double step, double upper) override |
set upper limit variable (override if minimizer supports them ) | |
bool | SetVariable (unsigned int ivar, const std::string &name, double val, double step) override |
set free variable | |
bool | SetVariableLimits (unsigned int ivar, double lower, double upper) override |
set the limits of an already existing variable | |
bool | SetVariableLowerLimit (unsigned int ivar, double lower) override |
set the lower-limit of an already existing variable | |
bool | SetVariableStepSize (unsigned int ivar, double step) override |
set the step size of an already existing variable | |
bool | SetVariableUpperLimit (unsigned int ivar, double upper) override |
set the upper-limit of an already existing variable | |
bool | SetVariableValue (unsigned int ivar, double val) override |
set the value of an existing variable | |
bool | SetVariableValues (const double *x) override |
set the values of all existing variables (array must be dimensioned to the size of existing parameters) | |
virtual const double * | StepSizes () const |
accessor methods | |
int | VariableIndex (const std::string &name) const override |
get index of variable given a variable given a name return -1 if variable is not found | |
std::string | VariableName (unsigned int ivar) const override |
get name of variables (override if minimizer support storing of variable names) | |
const double * | X () const override |
return pointer to X values at the minimum | |
Public Member Functions inherited from ROOT::Math::Minimizer | |
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 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 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 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 | |
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 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 | |
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 | Scan (unsigned int ivar, unsigned int &nstep, double *x, double *y, double xmin=0, double xmax=0) |
scan function minimum for variable i. | |
virtual bool | SetCovariance (std::span< const double > cov, unsigned int nrow) |
set initial covariance matrix | |
virtual bool | SetCovarianceDiag (std::span< const double > d2, unsigned int n) |
set initial second derivatives | |
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(std::span< const double >, double *)>) |
set the function implementing Hessian computation (re-implemented by Minimizer using it) | |
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 | |
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 | |
template<class VariableIterator > | |
int | SetVariables (const VariableIterator &begin, const VariableIterator &end) |
add variables . Return number of variables successfully added | |
int | Status () const |
status code of minimizer | |
int | Strategy () const |
strategy | |
double | Tolerance () const |
absolute tolerance | |
Protected Attributes | |
std::string | fMethod |
minimizer method to be used, must be of a type listed in R optim or optimx descriptions | |
Protected Attributes inherited from ROOT::Math::Minimizer | |
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) | |
Private Attributes | |
TMatrixD | fCovMatrix |
covariant matrix | |
std::vector< double > | fErrors |
vector of parameter errors | |
TMatrixD | fHessMatrix |
Hessian matrix. | |
Additional Inherited Members | |
Protected Member Functions inherited from ROOT::Math::BasicMinimizer | |
bool | CheckDimension () const |
bool | CheckObjFunction () const |
MinimTransformFunction * | CreateTransformation (std::vector< double > &startValues, const ROOT::Math::IMultiGradFunction *func=nullptr) |
void | SetFinalValues (const double *x, const MinimTransformFunction *func=nullptr) |
void | SetMinValue (double val) |
#include <Math/RMinimizer.h>
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.
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Destructor.
Definition at line 53 of file RMinimizer.h.
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inlineoverridevirtual |
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 68 of file RMinimizer.h.
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inlineoverridevirtual |
return errors at the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 63 of file RMinimizer.h.
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 79 of file RMinimizer.h.
Returns the ith jth component of the Hessian matrix.
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Function to find the minimum.
function for finding the minimum
Reimplemented from ROOT::Math::BasicMinimizer.
Definition at line 47 of file RMinimizer.cxx.
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Returns the number of function calls.
returns number of function calls
Reimplemented from ROOT::Math::Minimizer.
Definition at line 44 of file RMinimizer.cxx.
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inlineoverridevirtual |
minimizer provides error and error matrix
Reimplemented from ROOT::Math::Minimizer.
Definition at line 61 of file RMinimizer.h.
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private |
covariant matrix
Definition at line 39 of file RMinimizer.h.
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private |
vector of parameter errors
Definition at line 38 of file RMinimizer.h.
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private |
Hessian matrix.
Definition at line 40 of file RMinimizer.h.
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protected |
minimizer method to be used, must be of a type listed in R optim or optimx descriptions
Definition at line 35 of file RMinimizer.h.