BornAgain  1.19.79
Open-source research software to simulate and fit neutron and x-ray reflectometry and grazing-incidence small-angle scattering
ROOT::Fit::Fitter Class Reference

Description

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);

Definition at line 77 of file Fitter.h.

Collaboration diagram for ROOT::Fit::Fitter:
[legend]

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
 
template<class T >
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 ()
 
FitConfigConfig ()
 
const FitConfigConfig () 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)
 
template<class Function >
bool FitFCN (unsigned int npar, Function &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false)
 
ROOT::Math::IMultiGenFunctionGetFCN () const
 
ROOT::Math::MinimizerGetMinimizer () 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 FitResultResult () 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 &)
 
Fitteroperator= (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< IModelFunctionfFunc
 copy of the fitted function containing on output the fit result More...
 
std::shared_ptr< IModelFunction_vfFunc_v
 
std::shared_ptr< ROOT::Math::MinimizerfMinimizer
 pointer to the object containing the result of the fit More...
 
std::shared_ptr< ROOT::Math::IMultiGenFunctionfObjFunction
 pointer to the fit data (binned or unbinned data) More...
 
std::shared_ptr< ROOT::Fit::FitResultfResult
 copy of the fitted function containing on output the fit result More...
 
bool fUseGradient
 

Member Typedef Documentation

◆ BaseFunc

◆ BaseGradFunc

◆ IGradModel1DFunction

◆ IGradModelFunction

◆ IGradModelFunction_v

◆ IModel1DFunction

◆ IModelFunction

◆ IModelFunction_v

◆ IModelFunctionTempl

Definition at line 83 of file Fitter.h.

◆ MinuitFCN_t

typedef void(* ROOT::Fit::Fitter::MinuitFCN_t) (int &npar, double *gin, double &f, double *u, int flag)

fit 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

Definition at line 310 of file Fitter.h.

Constructor & Destructor Documentation

◆ Fitter() [1/3]

ROOT::Fit::Fitter::Fitter ( )

Default constructor

◆ Fitter() [2/3]

ROOT::Fit::Fitter::Fitter ( const std::shared_ptr< FitResult > &  result)

Constructor from a result

◆ ~Fitter()

ROOT::Fit::Fitter::~Fitter ( )

Destructor

◆ Fitter() [3/3]

ROOT::Fit::Fitter::Fitter ( const Fitter )
private

Copy constructor (disabled, class is not copyable)

Member Function Documentation

◆ ApplyWeightCorrection()

bool ROOT::Fit::Fitter::ApplyWeightCorrection ( const ROOT::Math::IMultiGenFunction loglw2,
bool  minimizeW2L = false 
)

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)

◆ CalculateHessErrors()

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

◆ CalculateMinosErrors()

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

◆ Config() [1/2]

FitConfig& ROOT::Fit::Fitter::Config ( )
inline

access to the configuration (non const method)

Definition at line 398 of file Fitter.h.

398 { return fConfig; }
FitConfig fConfig
Definition: Fitter.h:504

References fConfig.

◆ Config() [2/2]

const FitConfig& ROOT::Fit::Fitter::Config ( ) const
inline

access to the fit configuration (const method)

Definition at line 393 of file Fitter.h.

393 { return fConfig; }

References fConfig.

◆ DoBinnedLikelihoodFit()

bool ROOT::Fit::Fitter::DoBinnedLikelihoodFit ( bool  extended = true,
const ROOT::Fit::ExecutionPolicy &  executionPolicy = ROOT::Fit::ExecutionPolicy::kSerial 
)
protected

binned likelihood fit

Referenced by LikelihoodFit().

◆ DoInitMinimizer()

bool ROOT::Fit::Fitter::DoInitMinimizer ( )
protected

◆ DoLeastSquareFit()

bool ROOT::Fit::Fitter::DoLeastSquareFit ( const ROOT::Fit::ExecutionPolicy &  executionPolicy = ROOT::Fit::ExecutionPolicy::kSerial)
protected

least square fit

Referenced by Fit().

◆ DoLinearFit()

bool ROOT::Fit::Fitter::DoLinearFit ( )
protected

linear least square fit

Referenced by LinearFit().

◆ DoMinimization() [1/2]

bool ROOT::Fit::Fitter::DoMinimization ( const BaseFunc f,
const ROOT::Math::IMultiGenFunction chifunc = 0 
)
protected

do minimization

◆ DoMinimization() [2/2]

bool ROOT::Fit::Fitter::DoMinimization ( const ROOT::Math::IMultiGenFunction chifunc = 0)
protected

◆ DoUnbinnedLikelihoodFit()

bool ROOT::Fit::Fitter::DoUnbinnedLikelihoodFit ( bool  extended = false,
const ROOT::Fit::ExecutionPolicy &  executionPolicy = ROOT::Fit::ExecutionPolicy::kSerial 
)
protected

un-binned likelihood fit

Referenced by Fit(), and LikelihoodFit().

◆ DoUpdateFitConfig()

void ROOT::Fit::Fitter::DoUpdateFitConfig ( )
protected

◆ EvalFCN()

bool ROOT::Fit::Fitter::EvalFCN ( )

Perform a simple FCN evaluation. FitResult will be modified and contain the value of the FCN

◆ ExamineFCN()

void ROOT::Fit::Fitter::ExamineFCN ( )
protected

look at the user provided FCN and get data and model function is they derive from ROOT::Fit FCN classes

◆ Fit() [1/4]

bool ROOT::Fit::Fitter::Fit ( const BinData data,
const ROOT::Fit::ExecutionPolicy &  executionPolicy = ROOT::Fit::ExecutionPolicy::kSerial 
)
inline

Fit a binned data set using a least square fit (default method)

Definition at line 151 of file Fitter.h.

151  {
152  SetData(data);
153  return DoLeastSquareFit(executionPolicy);
154  }
void SetData(const FitData &data)
Definition: Fitter.h:465
bool DoLeastSquareFit(const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial)
least square fit

References DoLeastSquareFit(), and SetData().

Here is the call graph for this function:

◆ Fit() [2/4]

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 ROOT::Fit::Fitter::Fit ( const Data &  data,
const Function &  func,
const ROOT::Fit::ExecutionPolicy &  executionPolicy = ROOT::Fit::ExecutionPolicy::kSerial 
)
inline

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.

143  {
144  SetFunction(func);
145  return Fit(data, executionPolicy);
146  }
void SetFunction(const IModelFunction &func, bool useGradient=false)
bool Fit(const Data &data, const Function &func, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial)
Definition: Fitter.h:141

References SetFunction().

Referenced by LeastSquareFit().

Here is the call graph for this function:

◆ Fit() [3/4]

bool ROOT::Fit::Fitter::Fit ( const std::shared_ptr< BinData > &  data,
const ROOT::Fit::ExecutionPolicy &  executionPolicy = ROOT::Fit::ExecutionPolicy::kSerial 
)
inline

Definition at line 155 of file Fitter.h.

155  {
156  SetData(data);
157  return DoLeastSquareFit(executionPolicy);
158  }

References DoLeastSquareFit(), and SetData().

Here is the call graph for this function:

◆ Fit() [4/4]

bool ROOT::Fit::Fitter::Fit ( const UnBinData data,
bool  extended = false,
const ROOT::Fit::ExecutionPolicy &  executionPolicy = ROOT::Fit::ExecutionPolicy::kSerial 
)
inline

fit an unbinned data set using loglikelihood method

Definition at line 170 of file Fitter.h.

170  {
171  SetData(data);
172  return DoUnbinnedLikelihoodFit(extended, executionPolicy);
173  }
bool DoUnbinnedLikelihoodFit(bool extended=false, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial)
un-binned likelihood fit

References DoUnbinnedLikelihoodFit(), and SetData().

Here is the call graph for this function:

◆ FitFCN() [1/7]

bool ROOT::Fit::Fitter::FitFCN ( )

Perform a fit with the previously set FCN function. Require SetFCN before

Referenced by FitFCN().

◆ FitFCN() [2/7]

bool ROOT::Fit::Fitter::FitFCN ( const ROOT::Math::FitMethodFunction fcn,
const double *  params = 0 
)

Fit using a FitMethodFunction interface. Same as method above, but now extra information can be taken from the function class

◆ FitFCN() [3/7]

bool ROOT::Fit::Fitter::FitFCN ( const ROOT::Math::FitMethodGradFunction fcn,
const double *  params = 0 
)

Fit using a FitMethodGradFunction interface. Same as method above, but now extra information can be taken from the function class

◆ FitFCN() [4/7]

bool ROOT::Fit::Fitter::FitFCN ( const ROOT::Math::IMultiGenFunction fcn,
const double *  params = 0,
unsigned int  dataSize = 0,
bool  chi2fit = false 
)

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) )

◆ FitFCN() [5/7]

bool ROOT::Fit::Fitter::FitFCN ( const ROOT::Math::IMultiGradFunction fcn,
const double *  params = 0,
unsigned int  dataSize = 0,
bool  chi2fit = false 
)

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

◆ FitFCN() [6/7]

bool ROOT::Fit::Fitter::FitFCN ( MinuitFCN_t  fcn,
int  npar = 0,
const double *  params = 0,
unsigned int  dataSize = 0,
bool  chi2fit = false 
)

◆ FitFCN() [7/7]

template<class Function >
bool ROOT::Fit::Fitter::FitFCN ( unsigned int  npar,
Function &  fcn,
const double *  params = 0,
unsigned int  dataSize = 0,
bool  chi2fit = false 
)

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.

590  {
592  return FitFCN(wf,par,datasize,chi2fit);
593 }

References FitFCN().

Here is the call graph for this function:

◆ GetDataFromFCN()

template<class ObjFuncType >
bool ROOT::Fit::Fitter::GetDataFromFCN
protected

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.

524  {
525  ObjFuncType * objfunc = dynamic_cast<ObjFuncType*>(fObjFunction.get() );
526  if (objfunc) {
527  fFunc = objfunc->ModelFunctionPtr();
528  fData = objfunc->DataPtr();
529  return true;
530  }
531  else {
532  return false;
533  }
534 }
std::shared_ptr< ROOT::Fit::FitData > fData
pointer to used minimizer
Definition: Fitter.h:514
std::shared_ptr< ROOT::Math::IMultiGenFunction > fObjFunction
pointer to the fit data (binned or unbinned data)
Definition: Fitter.h:516
std::shared_ptr< IModelFunction > fFunc
copy of the fitted function containing on output the fit result
Definition: Fitter.h:508

References fData, fFunc, and fObjFunction.

◆ GetFCN()

ROOT::Math::IMultiGenFunction* ROOT::Fit::Fitter::GetFCN ( ) const
inline

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.

426 { return fObjFunction.get(); }

References fObjFunction.

◆ GetMinimizer()

ROOT::Math::Minimizer* ROOT::Fit::Fitter::GetMinimizer ( ) const
inline

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.

415 { return fMinimizer.get(); }
std::shared_ptr< ROOT::Math::Minimizer > fMinimizer
pointer to the object containing the result of the fit
Definition: Fitter.h:512

References fMinimizer.

◆ GetNCallsFromFCN()

int ROOT::Fit::Fitter::GetNCallsFromFCN ( )
protected

◆ IsBinFit()

bool ROOT::Fit::Fitter::IsBinFit ( ) const
inline

query if fit is binned. In cse of false teh fit can be unbinned or is not defined (like in case of fitting through a ::FitFCN)

Definition at line 404 of file Fitter.h.

404 { return fBinFit; }

References fBinFit.

◆ LeastSquareFit()

bool ROOT::Fit::Fitter::LeastSquareFit ( const BinData data)
inline

Fit a binned data set using a least square fit

Definition at line 163 of file Fitter.h.

163  {
164  return Fit(data);
165  }

References Fit().

Here is the call graph for this function:

◆ LikelihoodFit() [1/5]

bool ROOT::Fit::Fitter::LikelihoodFit ( const BinData data,
bool  extended = true,
const ROOT::Fit::ExecutionPolicy &  executionPolicy = ROOT::Fit::ExecutionPolicy::kSerial 
)
inline

Binned Likelihood fit. Default is extended

Definition at line 178 of file Fitter.h.

179  {
180  SetData(data);
181  return DoBinnedLikelihoodFit(extended, executionPolicy);
182  }
bool DoBinnedLikelihoodFit(bool extended=true, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial)
binned likelihood fit

References DoBinnedLikelihoodFit(), and SetData().

Referenced by LikelihoodFit().

Here is the call graph for this function:

◆ LikelihoodFit() [2/5]

template<class Data , class Function >
bool ROOT::Fit::Fitter::LikelihoodFit ( const Data &  data,
const Function &  func,
bool  extended 
)
inline

fit a data set using any generic model function Pre-requisite on the function:

Definition at line 207 of file Fitter.h.

207  {
208  SetFunction(func);
209  return LikelihoodFit(data, extended);
210  }
bool LikelihoodFit(const BinData &data, bool extended=true, const ROOT::Fit::ExecutionPolicy &executionPolicy=ROOT::Fit::ExecutionPolicy::kSerial)
Definition: Fitter.h:178

References LikelihoodFit(), and SetFunction().

Here is the call graph for this function:

◆ LikelihoodFit() [3/5]

bool ROOT::Fit::Fitter::LikelihoodFit ( const std::shared_ptr< BinData > &  data,
bool  extended = true,
const ROOT::Fit::ExecutionPolicy &  executionPolicy = ROOT::Fit::ExecutionPolicy::kSerial 
)
inline

Definition at line 184 of file Fitter.h.

185  {
186  SetData(data);
187  return DoBinnedLikelihoodFit(extended, executionPolicy);
188  }

References DoBinnedLikelihoodFit(), and SetData().

Here is the call graph for this function:

◆ LikelihoodFit() [4/5]

bool ROOT::Fit::Fitter::LikelihoodFit ( const std::shared_ptr< UnBinData > &  data,
bool  extended = false,
const ROOT::Fit::ExecutionPolicy &  executionPolicy = ROOT::Fit::ExecutionPolicy::kSerial 
)
inline

Definition at line 196 of file Fitter.h.

196  {
197  SetData(data);
198  return DoUnbinnedLikelihoodFit(extended, executionPolicy);
199  }

References DoUnbinnedLikelihoodFit(), and SetData().

Here is the call graph for this function:

◆ LikelihoodFit() [5/5]

bool ROOT::Fit::Fitter::LikelihoodFit ( const UnBinData data,
bool  extended = false,
const ROOT::Fit::ExecutionPolicy &  executionPolicy = ROOT::Fit::ExecutionPolicy::kSerial 
)
inline

Unbinned Likelihood fit. Default is not extended

Definition at line 192 of file Fitter.h.

192  {
193  SetData(data);
194  return DoUnbinnedLikelihoodFit(extended, executionPolicy);
195  }

References DoUnbinnedLikelihoodFit(), and SetData().

Here is the call graph for this function:

◆ LinearFit() [1/2]

bool ROOT::Fit::Fitter::LinearFit ( const BinData data)
inline

do a linear fit on a set of bin-data

Definition at line 215 of file Fitter.h.

215  {
216  SetData(data);
217  return DoLinearFit();
218  }
bool DoLinearFit()
linear least square fit

References DoLinearFit(), and SetData().

Here is the call graph for this function:

◆ LinearFit() [2/2]

bool ROOT::Fit::Fitter::LinearFit ( const std::shared_ptr< BinData > &  data)
inline

Definition at line 219 of file Fitter.h.

219  {
220  SetData(data);
221  return DoLinearFit();
222  }

References DoLinearFit(), and SetData().

Here is the call graph for this function:

◆ operator=()

Fitter& ROOT::Fit::Fitter::operator= ( const Fitter rhs)
private

Assignment operator (disabled, class is not copyable)

◆ Result()

const FitResult& ROOT::Fit::Fitter::Result ( ) const
inline

get fit result

Definition at line 365 of file Fitter.h.

365  {
366  assert( fResult.get() );
367  return *fResult;
368  }
std::shared_ptr< ROOT::Fit::FitResult > fResult
copy of the fitted function containing on output the fit result
Definition: Fitter.h:510

References fResult.

◆ SetData() [1/2]

void ROOT::Fit::Fitter::SetData ( const FitData &  data)
inlineprotected

Definition at line 465 of file Fitter.h.

465  {
466  fData = std::shared_ptr<FitData>(const_cast<FitData*>(&data),DummyDeleter<FitData>());
467  }

References fData.

Referenced by Fit(), LikelihoodFit(), LinearFit(), and SetFunctionAndData().

◆ SetData() [2/2]

template<class Data >
void ROOT::Fit::Fitter::SetData ( const std::shared_ptr< Data > &  data)
inlineprotected

Definition at line 477 of file Fitter.h.

477  {
478  fData = std::static_pointer_cast<Data>(data);
479  }

References fData.

◆ SetFCN() [1/6]

bool ROOT::Fit::Fitter::SetFCN ( const ROOT::Math::FitMethodFunction fcn,
const double *  params = 0 
)

Set the objective function (FCN) using a FitMethodFunction interface. Same as method above, but now extra information can be taken from the function class

◆ SetFCN() [2/6]

bool ROOT::Fit::Fitter::SetFCN ( const ROOT::Math::FitMethodGradFunction fcn,
const double *  params = 0 
)

Set the objective function (FCN) using a FitMethodGradFunction interface. Same as method above, but now extra information can be taken from the function class

◆ SetFCN() [3/6]

bool ROOT::Fit::Fitter::SetFCN ( const ROOT::Math::IMultiGenFunction fcn,
const double *  params = 0,
unsigned int  dataSize = 0,
bool  chi2fit = false 
)

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

◆ SetFCN() [4/6]

bool ROOT::Fit::Fitter::SetFCN ( const ROOT::Math::IMultiGradFunction fcn,
const double *  params = 0,
unsigned int  dataSize = 0,
bool  chi2fit = false 
)

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

◆ SetFCN() [5/6]

bool ROOT::Fit::Fitter::SetFCN ( MinuitFCN_t  fcn,
int  npar = 0,
const double *  params = 0,
unsigned int  dataSize = 0,
bool  chi2fit = false 
)

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

◆ SetFCN() [6/6]

template<class Function >
bool ROOT::Fit::Fitter::SetFCN ( unsigned int  npar,
Function &  fcn,
const double *  params = 0,
unsigned int  dataSize = 0,
bool  chi2fit = false 
)

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.

595  {
597  return SetFCN(wf,par,datasize,chi2fit);
598 }
bool SetFCN(unsigned int npar, Function &fcn, const double *params=0, unsigned int dataSize=0, bool chi2fit=false)
Definition: Fitter.h:595

◆ SetFunction() [1/4]

void ROOT::Fit::Fitter::SetFunction ( const IGradModel1DFunction func,
bool  useGradient = true 
)

Set the fitted function from 1D gradient parametric function interface

◆ SetFunction() [2/4]

void ROOT::Fit::Fitter::SetFunction ( const IGradModelFunction func,
bool  useGradient = true 
)

Set the fitted function (model function) from a parametric gradient function interface

◆ SetFunction() [3/4]

void ROOT::Fit::Fitter::SetFunction ( const IModel1DFunction func,
bool  useGradient = false 
)

Set the fitted function (model function) from a vectorized parametric function interface Set the fitted function from a parametric 1D function interface

◆ SetFunction() [4/4]

void ROOT::Fit::Fitter::SetFunction ( const IModelFunction func,
bool  useGradient = false 
)

Set the fitted function (model function) from a parametric function interface

Referenced by Fit(), and LikelihoodFit().

◆ SetFunctionAndData()

template<class T >
void ROOT::Fit::Fitter::SetFunctionAndData ( const IModelFunctionTempl< T > &  func,
const FitData &  data 
)
inlineprotected

Definition at line 470 of file Fitter.h.

470  {
471  SetData(data);
472  fFunc = std::shared_ptr<IModelFunctionTempl<T>>(const_cast<IModelFunctionTempl<T>*>(&func),DummyDeleter<IModelFunctionTempl<T>>());
473  }

References fFunc, and SetData().

Here is the call graph for this function:

Member Data Documentation

◆ fBinFit

bool ROOT::Fit::Fitter::fBinFit
private

Definition at line 496 of file Fitter.h.

Referenced by IsBinFit().

◆ fConfig

FitConfig ROOT::Fit::Fitter::fConfig
private

Definition at line 504 of file Fitter.h.

Referenced by Config().

◆ fData

std::shared_ptr<ROOT::Fit::FitData> ROOT::Fit::Fitter::fData
private

pointer to used minimizer

Definition at line 514 of file Fitter.h.

Referenced by GetDataFromFCN(), and SetData().

◆ fDataSize

int ROOT::Fit::Fitter::fDataSize
private

Definition at line 502 of file Fitter.h.

◆ fFitType

int ROOT::Fit::Fitter::fFitType
private

Definition at line 500 of file Fitter.h.

◆ fFunc

std::shared_ptr<IModelFunction> ROOT::Fit::Fitter::fFunc
private

copy of the fitted function containing on output the fit result

Definition at line 508 of file Fitter.h.

Referenced by GetDataFromFCN(), and SetFunctionAndData().

◆ fFunc_v

std::shared_ptr<IModelFunction_v> ROOT::Fit::Fitter::fFunc_v
private

Definition at line 506 of file Fitter.h.

◆ fMinimizer

std::shared_ptr<ROOT::Math::Minimizer> ROOT::Fit::Fitter::fMinimizer
private

pointer to the object containing the result of the fit

Definition at line 512 of file Fitter.h.

Referenced by GetMinimizer().

◆ fObjFunction

std::shared_ptr<ROOT::Math::IMultiGenFunction> ROOT::Fit::Fitter::fObjFunction
private

pointer to the fit data (binned or unbinned data)

Definition at line 516 of file Fitter.h.

Referenced by GetDataFromFCN(), and GetFCN().

◆ fResult

std::shared_ptr<ROOT::Fit::FitResult> ROOT::Fit::Fitter::fResult
private

copy of the fitted function containing on output the fit result

Definition at line 510 of file Fitter.h.

Referenced by Result().

◆ fUseGradient

bool ROOT::Fit::Fitter::fUseGradient
private

Definition at line 494 of file Fitter.h.


The documentation for this class was generated from the following file: