GSLMinimizer class.
Implementation of the ROOT::Math::Minimizer interface using the GSL multi-dimensional minimization algorithms.
See GSL doc from more info on the GSL minimization algorithms.
The class implements the ROOT::Math::Minimizer interface and can be instantiated using the ROOT plugin manager (plugin name is "GSLMultiMin"). The varius minimization algorithms (conjugatefr, conjugatepr, bfgs, etc..) can be passed as enumerations and also as a string. The default algorithm is conjugatefr (Fletcher-Reeves conjugate gradient algorithm).
Definition at line 79 of file GSLMinimizer.h.
Public Member Functions | |
GSLMinimizer (const char *type) | |
Constructor with a string giving name of algorithm. | |
GSLMinimizer (ROOT::Math::EGSLMinimizerType type=ROOT::Math::kConjugateFR) | |
Default constructor. | |
virtual | ~GSLMinimizer () |
Destructor. | |
virtual double | CovMatrix (unsigned int, unsigned int) const |
return covariance matrices elements if the variable is fixed the matrix is zero The ordering of the variables is the same as in errors | |
virtual double | Edm () const |
return expected distance reached from the minimum | |
virtual const double * | Errors () const |
return errors at the minimum | |
virtual const double * | MinGradient () const |
return pointer to gradient values at the minimum | |
virtual bool | Minimize () |
method to perform the minimization | |
virtual unsigned int | NCalls () const |
number of function calls to reach the minimum | |
virtual bool | ProvidesError () const |
minimizer provides error and error matrix | |
virtual void | SetFunction (const ROOT::Math::IMultiGenFunction &func) |
set the function to minimize | |
virtual void | SetFunction (const ROOT::Math::IMultiGradFunction &func) |
set the function to minimize | |
Public Member Functions inherited from ROOT::Math::BasicMinimizer | |
BasicMinimizer () | |
Default constructor. | |
virtual | ~BasicMinimizer () |
Destructor. | |
virtual bool | FixVariable (unsigned int ivar) |
fix an existing variable | |
virtual bool | GetVariableSettings (unsigned int ivar, ROOT::Fit::ParameterSettings &varObj) const |
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) | |
virtual bool | IsFixedVariable (unsigned int ivar) const |
query if an existing variable is fixed (i.e. | |
virtual double | MinValue () const |
return minimum function value | |
virtual unsigned int | NDim () const |
number of dimensions | |
virtual unsigned int | NFree () const |
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 | |
virtual bool | ReleaseVariable (unsigned int ivar) |
release an existing variable | |
virtual bool | SetFixedVariable (unsigned int, const std::string &, double) |
set fixed variable (override if minimizer supports them ) | |
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 ) | |
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 ) | |
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 ) | |
virtual bool | SetVariable (unsigned int ivar, const std::string &name, double val, double step) |
set free 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 | |
virtual bool | SetVariableStepSize (unsigned int ivar, double step) |
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 val) |
set the value of an existing variable | |
virtual bool | SetVariableValues (const double *x) |
set the values of all existing variables (array must be dimensioned to the size of existing parameters) | |
virtual const double * | StepSizes () const |
accessor methods | |
const ROOT::Math::MinimTransformFunction * | TransformFunction () const |
return transformation function (NULL if not having a transformation) | |
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) | |
virtual const double * | X () const |
return pointer to X values at the minimum | |
Public Member Functions inherited from ROOT::Math::Minimizer | |
Minimizer () | |
Default constructor. | |
virtual | ~Minimizer () |
Destructor (no operations) | |
virtual void | Clear () |
reset for consecutive minimizations - 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 | |
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 | 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 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 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 | |
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. | |
void | SetDefaultOptions () |
reset the defaut options (defined in MinimizerOptions) | |
void | SetErrorDef (double up) |
set scale for calculating the errors | |
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 | |
Private Member Functions | |
GSLMinimizer (const GSLMinimizer &) | |
Copy constructor. | |
GSLMinimizer & | operator= (const GSLMinimizer &rhs) |
Assignment operator. | |
Private Attributes | |
ROOT::Math::GSLMultiMinimizer * | fGSLMultiMin |
double | fLSTolerance |
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=0) |
void | SetFinalValues (const double *x) |
void | SetMinValue (double val) |
Protected Attributes inherited from ROOT::Math::Minimizer | |
MinimizerOptions | fOptions |
int | fStatus |
bool | fValidError |
#include <Math/GSLMinimizer.h>
ROOT::Math::GSLMinimizer::GSLMinimizer | ( | ROOT::Math::EGSLMinimizerType | type = ROOT::Math::kConjugateFR | ) |
Default constructor.
Definition at line 51 of file GSLMinimizer.cxx.
ROOT::Math::GSLMinimizer::GSLMinimizer | ( | const char * | type | ) |
Constructor with a string giving name of algorithm.
Definition at line 66 of file GSLMinimizer.cxx.
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virtual |
Destructor.
Definition at line 93 of file GSLMinimizer.cxx.
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inlineprivate |
Copy constructor.
Definition at line 104 of file GSLMinimizer.h.
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inlinevirtual |
return covariance matrices elements if the variable is fixed the matrix is zero The ordering of the variables is the same as in errors
Reimplemented from ROOT::Math::Minimizer.
Definition at line 149 of file GSLMinimizer.h.
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return expected distance reached from the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 127 of file GSLMinimizer.h.
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inlinevirtual |
return errors at the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 141 of file GSLMinimizer.h.
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return pointer to gradient values at the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 288 of file GSLMinimizer.cxx.
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method to perform the minimization
Reimplemented from ROOT::Math::BasicMinimizer.
Definition at line 123 of file GSLMinimizer.cxx.
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number of function calls to reach the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 112 of file GSLMinimizer.cxx.
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inlineprivate |
Assignment operator.
Definition at line 109 of file GSLMinimizer.h.
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inlinevirtual |
minimizer provides error and error matrix
Reimplemented from ROOT::Math::Minimizer.
Definition at line 138 of file GSLMinimizer.h.
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virtual |
set the function to minimize
Reimplemented from ROOT::Math::BasicMinimizer.
Definition at line 100 of file GSLMinimizer.cxx.
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inlinevirtual |
set the function to minimize
Reimplemented from ROOT::Math::BasicMinimizer.
Definition at line 120 of file GSLMinimizer.h.
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private |
Definition at line 159 of file GSLMinimizer.h.
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private |
Definition at line 161 of file GSLMinimizer.h.