BornAgain
1.19.79
Open-source research software to simulate and fit neutron and x-ray reflectometry and grazing-incidence small-angle scattering
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Fitter class, entry point for performing all type of fits. Fits are performed using the generic ROOT::Fit::Fitter::Fit method. The inputs are the data points and a model function (using a ROOT::Math::IParamFunction) The result of the fit is returned and kept internally in the ROOT::Fit::FitResult class. The configuration of the fit (parameters, options, etc...) are specified in the ROOT::Math::FitConfig class. After fitting the config of the fit will be modified to have the new values the resulting parameter of the fit with step sizes equal to the errors. FitConfig can be preserved with initial parameters by calling FitConfig.SetUpdateAfterFit(false);
Public Types | |
typedef ROOT::Math::IMultiGenFunction | BaseFunc |
typedef ROOT::Math::IMultiGradFunction | BaseGradFunc |
typedef ROOT::Math::IParamGradFunction | IGradModel1DFunction |
typedef ROOT::Math::IParamMultiGradFunction | IGradModelFunction |
typedef ROOT::Math::IParamMultiGradFunction | IGradModelFunction_v |
typedef ROOT::Math::IParamFunction | IModel1DFunction |
typedef ROOT::Math::IParamMultiFunction | IModelFunction |
typedef ROOT::Math::IParamMultiFunction | IModelFunction_v |
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using | IModelFunctionTempl = ROOT::Math::IParamMultiFunctionTempl< T > |
typedef void(* | MinuitFCN_t) (int &npar, double *gin, double &f, double *u, int flag) |
Public Member Functions | |
Fitter () | |
Fitter (const std::shared_ptr< FitResult > &result) | |
~Fitter () | |
bool | ApplyWeightCorrection (const ROOT::Math::IMultiGenFunction &loglw2, bool minimizeW2L=false) |
bool | CalculateHessErrors () |
bool | CalculateMinosErrors () |
FitConfig & | Config () |
const FitConfig & | Config () const |
bool | EvalFCN () |
bool | Fit (const BinData &data, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial) |
template<class Data , class Function , class cond = typename std::enable_if<!(std::is_same<Function, ROOT::Fit::ExecutionPolicy>::value || std::is_same<Function, int>::value), Function>::type> | |
bool | Fit (const Data &data, const Function &func, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial) |
bool | Fit (const std::shared_ptr< BinData > &data, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial) |
bool | Fit (const UnBinData &data, bool extended=false, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial) |
bool | FitFCN () |
bool | FitFCN (const ROOT::Math::FitMethodFunction &fcn, const double *params=0) |
bool | FitFCN (const ROOT::Math::FitMethodGradFunction &fcn, const double *params=0) |
bool | FitFCN (const ROOT::Math::IMultiGenFunction &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false) |
bool | FitFCN (const ROOT::Math::IMultiGradFunction &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false) |
bool | FitFCN (MinuitFCN_t fcn, int npar=0, const double *params=0, unsigned int dataSize=0, bool chi2fit=false) |
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bool | FitFCN (unsigned int npar, Function &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false) |
ROOT::Math::IMultiGenFunction * | GetFCN () const |
ROOT::Math::Minimizer * | GetMinimizer () const |
bool | IsBinFit () const |
bool | LeastSquareFit (const BinData &data) |
bool | LikelihoodFit (const BinData &data, bool extended=true, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial) |
template<class Data , class Function > | |
bool | LikelihoodFit (const Data &data, const Function &func, bool extended) |
bool | LikelihoodFit (const std::shared_ptr< BinData > &data, bool extended=true, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial) |
bool | LikelihoodFit (const std::shared_ptr< UnBinData > &data, bool extended=false, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial) |
bool | LikelihoodFit (const UnBinData &data, bool extended=false, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial) |
bool | LinearFit (const BinData &data) |
bool | LinearFit (const std::shared_ptr< BinData > &data) |
const FitResult & | Result () const |
bool | SetFCN (const ROOT::Math::FitMethodFunction &fcn, const double *params=0) |
bool | SetFCN (const ROOT::Math::FitMethodGradFunction &fcn, const double *params=0) |
bool | SetFCN (const ROOT::Math::IMultiGenFunction &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false) |
bool | SetFCN (const ROOT::Math::IMultiGradFunction &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false) |
bool | SetFCN (MinuitFCN_t fcn, int npar=0, const double *params=0, unsigned int dataSize=0, bool chi2fit=false) |
template<class Function > | |
bool | SetFCN (unsigned int npar, Function &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false) |
void | SetFunction (const IGradModel1DFunction &func, bool useGradient=true) |
void | SetFunction (const IGradModelFunction &func, bool useGradient=true) |
void | SetFunction (const IModel1DFunction &func, bool useGradient=false) |
void | SetFunction (const IModelFunction &func, bool useGradient=false) |
Protected Member Functions | |
bool | DoBinnedLikelihoodFit (bool extended=true, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial) |
binned likelihood fit More... | |
bool | DoInitMinimizer () |
bool | DoLeastSquareFit (const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial) |
least square fit More... | |
bool | DoLinearFit () |
linear least square fit More... | |
bool | DoMinimization (const BaseFunc &f, const ROOT::Math::IMultiGenFunction *chifunc=0) |
do minimization More... | |
bool | DoMinimization (const ROOT::Math::IMultiGenFunction *chifunc=0) |
bool | DoUnbinnedLikelihoodFit (bool extended=false, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial) |
un-binned likelihood fit More... | |
void | DoUpdateFitConfig () |
void | ExamineFCN () |
look at the user provided FCN and get data and model function is they derive from ROOT::Fit FCN classes More... | |
template<class ObjFuncType > | |
bool | GetDataFromFCN () |
internal functions to get data set and model function from FCN useful for fits done with customized FCN classes More... | |
int | GetNCallsFromFCN () |
void | SetData (const FitData &data) |
template<class Data > | |
void | SetData (const std::shared_ptr< Data > &data) |
template<class T > | |
void | SetFunctionAndData (const IModelFunctionTempl< T > &func, const FitData &data) |
Private Member Functions | |
Fitter (const Fitter &) | |
Fitter & | operator= (const Fitter &rhs) |
Private Attributes | |
bool | fBinFit |
FitConfig | fConfig |
std::shared_ptr< ROOT::Fit::FitData > | fData |
pointer to used minimizer More... | |
int | fDataSize |
int | fFitType |
std::shared_ptr< IModelFunction > | fFunc |
copy of the fitted function containing on output the fit result More... | |
std::shared_ptr< IModelFunction_v > | fFunc_v |
std::shared_ptr< ROOT::Math::Minimizer > | fMinimizer |
pointer to the object containing the result of the fit More... | |
std::shared_ptr< ROOT::Math::IMultiGenFunction > | fObjFunction |
pointer to the fit data (binned or unbinned data) More... | |
std::shared_ptr< ROOT::Fit::FitResult > | fResult |
copy of the fitted function containing on output the fit result More... | |
bool | fUseGradient |
using ROOT::Fit::Fitter::IModelFunctionTempl = ROOT::Math::IParamMultiFunctionTempl<T> |
typedef void(* ROOT::Fit::Fitter::MinuitFCN_t) (int &npar, double *gin, double &f, double *u, int flag) |
ROOT::Fit::Fitter::Fitter | ( | ) |
Default constructor
ROOT::Fit::Fitter::Fitter | ( | const std::shared_ptr< FitResult > & | result | ) |
Constructor from a result
ROOT::Fit::Fitter::~Fitter | ( | ) |
Destructor
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Copy constructor (disabled, class is not copyable)
bool ROOT::Fit::Fitter::ApplyWeightCorrection | ( | const ROOT::Math::IMultiGenFunction & | loglw2, |
bool | minimizeW2L = false |
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apply correction in the error matrix for the weights for likelihood fits This method can be called only after a fit. The passed function (loglw2) is a log-likelihood function impelemented using the sum of weight squared When using FitConfig.SetWeightCorrection() this correction is applied automatically when doing a likelihood fit (binned or unbinned)
bool ROOT::Fit::Fitter::CalculateHessErrors | ( | ) |
perform an error analysis on the result using the Hessian Errors are obtaied from the inverse of the Hessian matrix To be called only after fitting and when a minimizer supporting the Hessian calculations is used otherwise an error (false) is returned. A new FitResult with the Hessian result will be produced
bool ROOT::Fit::Fitter::CalculateMinosErrors | ( | ) |
perform an error analysis on the result using MINOS To be called only after fitting and when a minimizer supporting MINOS is used otherwise an error (false) is returned. The result will be appended in the fit result class Optionally a vector of parameter indeces can be passed for selecting the parameters to analyse using FitConfig::SetMinosErrors
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binned likelihood fit
Referenced by LikelihoodFit().
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least square fit
Referenced by Fit().
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linear least square fit
Referenced by LinearFit().
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do minimization
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un-binned likelihood fit
Referenced by Fit(), and LikelihoodFit().
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bool ROOT::Fit::Fitter::EvalFCN | ( | ) |
Perform a simple FCN evaluation. FitResult will be modified and contain the value of the FCN
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look at the user provided FCN and get data and model function is they derive from ROOT::Fit FCN classes
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Fit a binned data set using a least square fit (default method)
Definition at line 151 of file Fitter.h.
References DoLeastSquareFit(), and SetData().
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fit a data set using any generic model function If data set is binned a least square fit is performed If data set is unbinned a maximum likelihood fit (not extended) is done Pre-requisite on the function: it must implement the 1D or multidimensional parametric function interface
Definition at line 141 of file Fitter.h.
References SetFunction().
Referenced by LeastSquareFit().
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Definition at line 155 of file Fitter.h.
References DoLeastSquareFit(), and SetData().
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fit an unbinned data set using loglikelihood method
Definition at line 170 of file Fitter.h.
References DoUnbinnedLikelihoodFit(), and SetData().
bool ROOT::Fit::Fitter::FitFCN | ( | ) |
Perform a fit with the previously set FCN function. Require SetFCN before
Referenced by FitFCN().
bool ROOT::Fit::Fitter::FitFCN | ( | const ROOT::Math::FitMethodFunction & | fcn, |
const double * | params = 0 |
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Fit using a FitMethodFunction interface. Same as method above, but now extra information can be taken from the function class
bool ROOT::Fit::Fitter::FitFCN | ( | const ROOT::Math::FitMethodGradFunction & | fcn, |
const double * | params = 0 |
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Fit using a FitMethodGradFunction interface. Same as method above, but now extra information can be taken from the function class
bool ROOT::Fit::Fitter::FitFCN | ( | const ROOT::Math::IMultiGenFunction & | fcn, |
const double * | params = 0 , |
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unsigned int | dataSize = 0 , |
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bool | chi2fit = false |
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Fit using the given FCN function represented by a multi-dimensional function interface (ROOT::Math::IMultiGenFunction). Give optionally the initial arameter values, data size to have the fit Ndf correctly set in the FitResult and flag specifying if it is a chi2 fit. Note that if the parameters values are not given (params=0) the current parameter settings are used. The parameter settings can be created before by using the FitConfig::SetParamsSetting. If they have not been created they are created automatically when the params pointer is not zero. Note that passing a params != 0 will set the parameter settings to the new value AND also the step sizes to some pre-defined value (stepsize = 0.3 * abs(parameter_value) )
bool ROOT::Fit::Fitter::FitFCN | ( | const ROOT::Math::IMultiGradFunction & | fcn, |
const double * | params = 0 , |
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unsigned int | dataSize = 0 , |
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bool | chi2fit = false |
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Fit using the given FCN function representing a multi-dimensional gradient function interface (ROOT::Math::IMultiGradFunction). In this case the minimizer will use the gradient information provided by the function. For the options same consideration as in the previous method
bool ROOT::Fit::Fitter::FitFCN | ( | MinuitFCN_t | fcn, |
int | npar = 0 , |
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const double * | params = 0 , |
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unsigned int | dataSize = 0 , |
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bool | chi2fit = false |
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bool ROOT::Fit::Fitter::FitFCN | ( | unsigned int | npar, |
Function & | fcn, | ||
const double * | params = 0 , |
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unsigned int | dataSize = 0 , |
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bool | chi2fit = false |
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Fit using the a generic FCN function as a C++ callable object implementing double () (const double *) Note that the function dimension (i.e. the number of parameter) is needed in this case For the options see documentation for following methods FitFCN(IMultiGenFunction & fcn,..)
Definition at line 590 of file Fitter.h.
References FitFCN().
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internal functions to get data set and model function from FCN useful for fits done with customized FCN classes
Definition at line 524 of file Fitter.h.
References fData, fFunc, and fObjFunction.
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return pointer to last used objective function (is NULL in case fit is not yet done) This pointer will be valid as far as the fitter class has not been deleted. To be used after the fitting. The pointer should not be stored and will be invalided after performing a new fitting. In this case a new instance of the function pointer will be re-created and can be obtained calling again GetFCN()
Definition at line 426 of file Fitter.h.
References fObjFunction.
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return pointer to last used minimizer (is NULL in case fit is not yet done) This pointer is guranteed to be valid as far as the fitter class is valid and a new fit is not redone. To be used only after fitting. The pointer should not be stored and will be invalided after performing a new fitting. In this case a new instance of ROOT::Math::Minimizer will be re-created and can be obtained calling again GetMinimizer()
Definition at line 415 of file Fitter.h.
References fMinimizer.
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Binned Likelihood fit. Default is extended
Definition at line 178 of file Fitter.h.
References DoBinnedLikelihoodFit(), and SetData().
Referenced by LikelihoodFit().
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fit a data set using any generic model function Pre-requisite on the function:
Definition at line 207 of file Fitter.h.
References LikelihoodFit(), and SetFunction().
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Definition at line 184 of file Fitter.h.
References DoBinnedLikelihoodFit(), and SetData().
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Definition at line 196 of file Fitter.h.
References DoUnbinnedLikelihoodFit(), and SetData().
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Unbinned Likelihood fit. Default is not extended
Definition at line 192 of file Fitter.h.
References DoUnbinnedLikelihoodFit(), and SetData().
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do a linear fit on a set of bin-data
Definition at line 215 of file Fitter.h.
References DoLinearFit(), and SetData().
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Definition at line 219 of file Fitter.h.
References DoLinearFit(), and SetData().
Assignment operator (disabled, class is not copyable)
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get fit result
Definition at line 365 of file Fitter.h.
References fResult.
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Definition at line 465 of file Fitter.h.
References fData.
Referenced by Fit(), LikelihoodFit(), LinearFit(), and SetFunctionAndData().
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bool ROOT::Fit::Fitter::SetFCN | ( | const ROOT::Math::FitMethodFunction & | fcn, |
const double * | params = 0 |
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Set the objective function (FCN) using a FitMethodFunction interface. Same as method above, but now extra information can be taken from the function class
bool ROOT::Fit::Fitter::SetFCN | ( | const ROOT::Math::FitMethodGradFunction & | fcn, |
const double * | params = 0 |
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Set the objective function (FCN) using a FitMethodGradFunction interface. Same as method above, but now extra information can be taken from the function class
bool ROOT::Fit::Fitter::SetFCN | ( | const ROOT::Math::IMultiGenFunction & | fcn, |
const double * | params = 0 , |
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unsigned int | dataSize = 0 , |
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bool | chi2fit = false |
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Set the FCN function represented by a multi-dimensional function interface (ROOT::Math::IMultiGenFunction) and optionally the initial parameters See also note above for the initial parameters for FitFCN
bool ROOT::Fit::Fitter::SetFCN | ( | const ROOT::Math::IMultiGradFunction & | fcn, |
const double * | params = 0 , |
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unsigned int | dataSize = 0 , |
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bool | chi2fit = false |
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Set the FCN function represented by a multi-dimensional gradient function interface (ROOT::Math::IMultiGenFunction) and optionally the initial parameters See also note above for the initial parameters for FitFCN
bool ROOT::Fit::Fitter::SetFCN | ( | MinuitFCN_t | fcn, |
int | npar = 0 , |
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const double * | params = 0 , |
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unsigned int | dataSize = 0 , |
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bool | chi2fit = false |
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set objective function using user provided FCN with Minuit-like interface If npar = 0 it is assumed that the parameters are specified in the parameter settings created before For the options same consideration as in the previous method
bool ROOT::Fit::Fitter::SetFCN | ( | unsigned int | npar, |
Function & | fcn, | ||
const double * | params = 0 , |
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unsigned int | dataSize = 0 , |
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bool | chi2fit = false |
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Set a generic FCN function as a C++ callable object implementing double () (const double *) Note that the function dimension (i.e. the number of parameter) is needed in this case For the options see documentation for following methods FitFCN(IMultiGenFunction & fcn,..)
Definition at line 595 of file Fitter.h.
void ROOT::Fit::Fitter::SetFunction | ( | const IGradModel1DFunction & | func, |
bool | useGradient = true |
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Set the fitted function from 1D gradient parametric function interface
void ROOT::Fit::Fitter::SetFunction | ( | const IGradModelFunction & | func, |
bool | useGradient = true |
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Set the fitted function (model function) from a parametric gradient function interface
void ROOT::Fit::Fitter::SetFunction | ( | const IModel1DFunction & | func, |
bool | useGradient = false |
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Set the fitted function (model function) from a vectorized parametric function interface Set the fitted function from a parametric 1D function interface
void ROOT::Fit::Fitter::SetFunction | ( | const IModelFunction & | func, |
bool | useGradient = false |
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Set the fitted function (model function) from a parametric function interface
Referenced by Fit(), and LikelihoodFit().
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Definition at line 496 of file Fitter.h.
Referenced by IsBinFit().
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pointer to used minimizer
Definition at line 514 of file Fitter.h.
Referenced by GetDataFromFCN(), and SetData().
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copy of the fitted function containing on output the fit result
Definition at line 508 of file Fitter.h.
Referenced by GetDataFromFCN(), and SetFunctionAndData().
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pointer to the object containing the result of the fit
Definition at line 512 of file Fitter.h.
Referenced by GetMinimizer().
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pointer to the fit data (binned or unbinned data)
Definition at line 516 of file Fitter.h.
Referenced by GetDataFromFCN(), and GetFCN().
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