![]() |
ROOT 6.14/05 Reference Guide |
GSLNLSMinimizer class for Non Linear Least Square fitting It Uses the Levemberg-Marquardt algorithm from GSL Non Linear Least Square fitting.
Definition at line 152 of file GSLNLSMinimizer.h.
Public Member Functions | |
GSLNLSMinimizer (int type=0) | |
Default constructor. More... | |
~GSLNLSMinimizer () | |
Destructor (no operations) More... | |
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 More... | |
virtual int | CovMatrixStatus () const |
return covariance matrix status More... | |
virtual double | Edm () const |
return expected distance reached from the minimum More... | |
virtual const double * | Errors () const |
return errors at the minimum More... | |
virtual const double * | MinGradient () const |
return pointer to gradient values at the minimum More... | |
virtual bool | Minimize () |
method to perform the minimization More... | |
virtual unsigned int | NCalls () const |
number of function calls to reach the minimum More... | |
virtual bool | ProvidesError () const |
number of free variables (real dimension of the problem) this is <= Function().NDim() which is the total 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... | |
![]() | |
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 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... | |
![]() | |
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... | |
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 | 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 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 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... | |
Private Member Functions | |
GSLNLSMinimizer (const GSLNLSMinimizer &) | |
Copy constructor. More... | |
GSLNLSMinimizer & | operator= (const GSLNLSMinimizer &rhs) |
Assignment operator. More... | |
Private Attributes | |
const ROOT::Math::FitMethodFunction * | fChi2Func |
std::vector< double > | fCovMatrix |
double | fEdm |
std::vector< double > | fErrors |
ROOT::Math::GSLMultiFit * | fGSLMultiFit |
double | fLSTolerance |
unsigned int | fNFree |
std::vector< LSResidualFunc > | fResiduals |
unsigned int | fSize |
Additional Inherited Members | |
![]() | |
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) |
![]() | |
MinimizerOptions | fOptions |
int | fStatus |
bool | fValidError |
#include <Math/GSLNLSMinimizer.h>
ROOT::Math::GSLNLSMinimizer::GSLNLSMinimizer | ( | int | type = 0 | ) |
Default constructor.
Definition at line 136 of file GSLNLSMinimizer.cxx.
ROOT::Math::GSLNLSMinimizer::~GSLNLSMinimizer | ( | ) |
Destructor (no operations)
Definition at line 161 of file GSLNLSMinimizer.cxx.
|
inlineprivate |
Copy constructor.
Definition at line 172 of file GSLNLSMinimizer.h.
|
virtual |
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 371 of file GSLNLSMinimizer.cxx.
|
virtual |
return covariance matrix status
Reimplemented from ROOT::Math::Minimizer.
Definition at line 379 of file GSLNLSMinimizer.cxx.
|
inlinevirtual |
return expected distance reached from the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 196 of file GSLNLSMinimizer.h.
|
inlinevirtual |
return errors at the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 213 of file GSLNLSMinimizer.h.
|
virtual |
return pointer to gradient values at the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 365 of file GSLNLSMinimizer.cxx.
|
virtual |
method to perform the minimization
Reimplemented from ROOT::Math::BasicMinimizer.
Definition at line 200 of file GSLNLSMinimizer.cxx.
|
inlinevirtual |
number of function calls to reach the minimum
Reimplemented from ROOT::Math::Minimizer.
Definition at line 203 of file GSLNLSMinimizer.h.
|
inlineprivate |
Assignment operator.
Definition at line 177 of file GSLNLSMinimizer.h.
|
inlinevirtual |
number of free variables (real dimension of the problem) this is <= Function().NDim() which is the total
minimizer provides error and error matrix
Reimplemented from ROOT::Math::Minimizer.
Definition at line 210 of file GSLNLSMinimizer.h.
|
virtual |
set the function to minimize
Reimplemented from ROOT::Math::BasicMinimizer.
Definition at line 168 of file GSLNLSMinimizer.cxx.
|
virtual |
set gradient the function to minimize
Reimplemented from ROOT::Math::BasicMinimizer.
Definition at line 193 of file GSLNLSMinimizer.cxx.
|
private |
Definition at line 238 of file GSLNLSMinimizer.h.
|
private |
Definition at line 243 of file GSLNLSMinimizer.h.
|
private |
Definition at line 240 of file GSLNLSMinimizer.h.
|
private |
Definition at line 242 of file GSLNLSMinimizer.h.
|
private |
Definition at line 237 of file GSLNLSMinimizer.h.
|
private |
Definition at line 241 of file GSLNLSMinimizer.h.
|
private |
Definition at line 234 of file GSLNLSMinimizer.h.
|
private |
Definition at line 244 of file GSLNLSMinimizer.h.
|
private |
Definition at line 235 of file GSLNLSMinimizer.h.