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ROOT 6.12/07 Reference Guide |
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... | |
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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::IMultiGradFunction * | GradObjFunction () 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::IMultiGenFunction * | ObjFunction () 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::MinimTransformFunction * | TransformFunction () 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... | |
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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... | |
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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 | |
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bool | CheckDimension () const |
bool | CheckObjFunction () const |
MinimTransformFunction * | CreateTransformation (std::vector< double > &startValues, const ROOT::Math::IMultiGradFunction *func=0) |
void | SetFinalValues (const double *x) |
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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inlinevirtual |
Destructor.
Definition at line 51 of file RMinimizer.h.
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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.
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inlinevirtual |
return errors at the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 61 of file RMinimizer.h.
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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.
double ROOT::Math::RMinimizer::HessMatrix | ( | unsigned int | i, |
unsigned int | j | ||
) | const |
Returns the ith jth component of the Hessian matrix.
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virtual |
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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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.
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inlinevirtual |
minimizer provides error and error matrix
Reimplemented from ROOT::Math::Minimizer.
Definition at line 59 of file RMinimizer.h.
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private |
covariant matrix
Definition at line 37 of file RMinimizer.h.
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private |
vector of parameter errors
Definition at line 36 of file RMinimizer.h.
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private |
Hessian matrix.
Definition at line 38 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 33 of file RMinimizer.h.