#include <UnbinnedLikelihoodFit.h>

Public Member Functions
int32_t	fit (int32_t verbosity=-1)
int32_t	fit (int32_t n, double *x, int32_t verbosity=-1)
TF1 *	getFunction () const
double	getParameterError (uint32_t i)
double *	getParameterErrors ()
double	getParameterValue (uint32_t i)
double *	getParameterValues ()
void	setData (uint32_t n, double *x)
void	setFunction (TF1 *f)
void	setMaxIterations (uint32_t n)
void	setTolerance (double tol)
	UnbinnedLikelihoodFit ()
	~UnbinnedLikelihoodFit ()
Private Member Functions
double	logL (const double *x) const
Private Attributes
double	arglist_ [10]
uint32_t	datasize_
TF1 *	function_
uint32_t	maxIterations_
TVirtualFitter *	min
uint32_t	nparameters_
double	tolerance_
double *	x_
Friends
void	UnbinnedLL (Int_t &npar, Double_t gin, Double_t &val, Double_t par, Int_t iflag)

Detailed Description

Definition at line 24 of file UnbinnedLikelihoodFit.h.

Constructor & Destructor Documentation

UnbinnedLikelihoodFit::UnbinnedLikelihoodFit ( )

Definition at line 30 of file UnbinnedLikelihoodFit.cc.

References datasize_, maxIterations_, min, nparameters_, NULL, tolerance_, and x_.

                                             {
  nparameters_ = 0;
  datasize_ = 0;
  x_ = NULL;
  min = NULL;
  tolerance_ = 0.01;
  maxIterations_ = 1000;
}

UnbinnedLikelihoodFit::~UnbinnedLikelihoodFit ( )

Definition at line 40 of file UnbinnedLikelihoodFit.cc.

{
}

Member Function Documentation

int32_t UnbinnedLikelihoodFit::fit ( int32_t verbosity = -1 )

Definition at line 57 of file UnbinnedLikelihoodFit.cc.

References arglist_, ExpressReco_HICollisions_FallBack::Fitter, function_, i, maxIterations_, min, nparameters_, ntuplemaker::status, tolerance_, UnbinnedLL, and verbosity.

Referenced by UnbinnedFitDeDxEstimator::dedx().

                                                    {
  // creates a fitter 
  min = TVirtualFitter::Fitter(this,nparameters_);
  min->SetFCN(UnbinnedLL);
  
  // set print level: no output
  arglist_[0] = 0;
  min->ExecuteCommand("SET NOWarnings",arglist_,1);
  arglist_[0] = verbosity;
  min->ExecuteCommand("SET PRINT",arglist_,1);
  
  // initial values, error, range
  double parmin,parmax;
  for(uint32_t i=0;i<nparameters_;++i) {
    function_->GetParLimits(i, parmin, parmax);
    min->SetParameter(i,
                      function_->GetParName(i),
                      function_->GetParameter(i),
                      tolerance_,
                      parmin, parmax);
  }

  // run MIGRAD
  arglist_[0] = maxIterations_; // number of function calls
  arglist_[1] = tolerance_;     // tolerance
  int32_t status = min->ExecuteCommand("MIGRAD",arglist_,2);

  // get fit parameters and errors
  for(uint32_t i=0;i<nparameters_;++i) {
    function_->SetParameter(i, min->GetParameter(i));
    function_->SetParError( i, min->GetParError(i) );
  }

  // returns the status
  return status;
}

int32_t UnbinnedLikelihoodFit::fit	(	int32_t	n,
		double *	x,
		int32_t	verbosity = `-1`
	)		`[inline]`

Definition at line 43 of file UnbinnedLikelihoodFit.h.

References fit(), setData(), and verbosity.

Referenced by fit().

{ setData(n,x); return fit(verbosity); }

TF1* UnbinnedLikelihoodFit::getFunction ( ) const [inline]

Definition at line 46 of file UnbinnedLikelihoodFit.h.

References function_.

{ return function_; }

double UnbinnedLikelihoodFit::getParameterError ( uint32_t i ) [inline]

Definition at line 48 of file UnbinnedLikelihoodFit.h.

References function_.

{ return function_ ? function_->GetParError(i)  : 0; }

double* UnbinnedLikelihoodFit::getParameterErrors ( ) [inline]

Definition at line 50 of file UnbinnedLikelihoodFit.h.

References function_, and NULL.

{ return function_ ? function_->GetParErrors()  : NULL; }

double UnbinnedLikelihoodFit::getParameterValue ( uint32_t i ) [inline]

Definition at line 47 of file UnbinnedLikelihoodFit.h.

References function_.

{ return function_ ? function_->GetParameter(i) : 0; }

double* UnbinnedLikelihoodFit::getParameterValues ( ) [inline]

Definition at line 49 of file UnbinnedLikelihoodFit.h.

References function_, and NULL.

{ return function_ ? function_->GetParameters() : NULL; }

double UnbinnedLikelihoodFit::logL ( const double * x ) const [private]

Definition at line 95 of file UnbinnedLikelihoodFit.cc.

References datasize_, function_, i, and x_.

                                                                 {
  double val=0;
  if(!function_) return val;
  for (uint32_t i=0;i<datasize_;++i){
    val += TMath::Log(function_->EvalPar(&(x_[i]),parameters));
  }
  return val; 
}

void UnbinnedLikelihoodFit::setData	(	uint32_t	n,
		double *	x
	)

Definition at line 45 of file UnbinnedLikelihoodFit.cc.

References datasize_, n, ExpressReco_HICollisions_FallBack::x, and x_.

Referenced by fit().

                                                         {
  datasize_ = n;
  x_ = x;
}

void UnbinnedLikelihoodFit::setFunction ( TF1 * f )

Definition at line 51 of file UnbinnedLikelihoodFit.cc.

References f, function_, and nparameters_.

Referenced by UnbinnedFitDeDxEstimator::UnbinnedFitDeDxEstimator().

                                              {
  function_ = f;
  nparameters_ = function_ ? function_->GetNpar() : 0;
}

void UnbinnedLikelihoodFit::setMaxIterations ( uint32_t n ) [inline]

Definition at line 39 of file UnbinnedLikelihoodFit.h.

References maxIterations_, and n.

{ maxIterations_ = n; }

void UnbinnedLikelihoodFit::setTolerance ( double tol ) [inline]

Definition at line 38 of file UnbinnedLikelihoodFit.h.

References tolerance_.

{ tolerance_ = tol; }

Friends And Related Function Documentation

void UnbinnedLL	(	Int_t &	npar,
		Double_t *	gin,
		Double_t &	val,
		Double_t *	par,
		Int_t	iflag
	)		`[friend]`

Definition at line 22 of file UnbinnedLikelihoodFit.cc.

Referenced by fit().

                                                                        {
  // retrieve the data object (it's also the fitter)
  // - sign to have a minimum
  // factor 2 to have the right errors (see for example the pdg)
  val = -2*((dynamic_cast<const UnbinnedLikelihoodFit*>((TVirtualFitter::GetFitter())->GetObjectFit()))->logL(par));
}