musrfit/src/classes/PFitterFcn.cpp
2019-04-26 09:11:00 +02:00

129 lines
5.3 KiB
C++

/***************************************************************************
PFitterFcn.cpp
Author: Andreas Suter
e-mail: andreas.suter@psi.ch
***************************************************************************/
/***************************************************************************
* Copyright (C) 2007-2019 by Andreas Suter *
* andreas.suter@psi.ch *
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 2 of the License, or *
* (at your option) any later version. *
* *
* This program is distributed in the hope that it will be useful, *
* but WITHOUT ANY WARRANTY; without even the implied warranty of *
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the *
* GNU General Public License for more details. *
* *
* You should have received a copy of the GNU General Public License *
* along with this program; if not, write to the *
* Free Software Foundation, Inc., *
* 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. *
***************************************************************************/
#include "PFitterFcn.h"
//--------------------------------------------------------------------------
// Constructor
//--------------------------------------------------------------------------
/**
* <p>Constructor.
*
* \param runList run list collection
* \param useChi2 if true, a chisq fit will be performed, otherwise a log max-likelihood fit will be carried out.
*/
PFitterFcn::PFitterFcn(PRunListCollection *runList, Bool_t useChi2)
{
fUseChi2 = useChi2;
if (fUseChi2)
fUp = 1.0;
else
fUp = 0.5;
fRunListCollection = runList;
}
//--------------------------------------------------------------------------
// Destructor
//--------------------------------------------------------------------------
/**
* <p>Destructor
*/
PFitterFcn::~PFitterFcn()
{
}
//--------------------------------------------------------------------------
// operator()
//--------------------------------------------------------------------------
/**
* <p>Minuit2 interface function call routine. This is the function which should be minimized.
*
* \param par a vector with all the parameters of the function
*/
Double_t PFitterFcn::operator()(const std::vector<Double_t>& par) const
{
Double_t value = 0.0;
if (fUseChi2) { // chi square
value += fRunListCollection->GetSingleHistoChisq(par);
value += fRunListCollection->GetSingleHistoRRFChisq(par);
value += fRunListCollection->GetAsymmetryChisq(par);
value += fRunListCollection->GetAsymmetryRRFChisq(par);
value += fRunListCollection->GetAsymmetryBNMRChisq(par);
value += fRunListCollection->GetMuMinusChisq(par);
value += fRunListCollection->GetNonMusrChisq(par);
} else { // max likelihood
value += fRunListCollection->GetSingleHistoMaximumLikelihood(par);
value += fRunListCollection->GetSingleHistoRRFMaximumLikelihood(par);
value += fRunListCollection->GetAsymmetryMaximumLikelihood(par);
value += fRunListCollection->GetAsymmetryRRFMaximumLikelihood(par);
value += fRunListCollection->GetAsymmetryBNMRMaximumLikelihood(par);
value += fRunListCollection->GetMuMinusMaximumLikelihood(par);
value += fRunListCollection->GetNonMusrMaximumLikelihood(par);
}
return value;
}
//--------------------------------------------------------------------------
// CalcExpectedChiSquare()
//--------------------------------------------------------------------------
/**
* <p>Calculates the expected chisq, expected chisq per run, and chisq per run, if applicable.
*
* \param par
* \param totalExpectedChisq expected chisq for all run blocks
* \param expectedChisqPerRun expected chisq vector for all the run blocks
*/
void PFitterFcn::CalcExpectedChiSquare(const std::vector<Double_t> &par, Double_t &totalExpectedChisq, std::vector<Double_t> &expectedChisqPerRun)
{
// init expected chisq related variables
totalExpectedChisq = 0.0;
expectedChisqPerRun.clear();
Double_t value = 0.0;
if (fUseChi2) {
// single histo
for (UInt_t i=0; i<fRunListCollection->GetNoOfSingleHisto(); i++) {
value = fRunListCollection->GetSingleHistoChisqExpected(par, i); // calculate the expected chisq for single histo run block 'i'
expectedChisqPerRun.push_back(value);
totalExpectedChisq += value;
}
} else { // log max. likelihood
// single histo
for (UInt_t i=0; i<fRunListCollection->GetNoOfSingleHisto(); i++) {
value = fRunListCollection->GetSingleHistoMaximumLikelihoodExpected(par, i); // calculate the expected mlh for single histo run block 'i'
expectedChisqPerRun.push_back(value);
totalExpectedChisq += value;
}
}
}