LMU/musrfit
LMU/musrfit
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reduced some calculation overhead

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root 2008-02-27 10:10:25 +00:00
parent b3807450b1
commit dd2cbac068
3 changed files with 10 additions and 6 deletions
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4
src/classes/PFitterFcn.cpp
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@ -53,7 +53,7 @@ PFitterFcn::PFitterFcn(PRunListCollection *runList, bool useChi2)
fUp = 0.5; fUp = 0.5;
fRunListCollection = runList; fRunListCollection = runList;
// check if max likelihood is used together with asymmetry/RRF/nonMusr data. // check if max likelihood is used together with asymmetry/RRF/nonMusr data.
// if yes place a warning since this option is not implemented and a fall back // if yes place a warning since this option is not implemented and a fall back
// to chi2 will be used. // to chi2 will be used.
@ -64,7 +64,7 @@ PFitterFcn::PFitterFcn(PRunListCollection *runList, bool useChi2)
cout << endl << "**WARNING**: Maximum Log Likelihood Fit is only implemented for Single Histogram Fit"; cout << endl << "**WARNING**: Maximum Log Likelihood Fit is only implemented for Single Histogram Fit";
cout << endl << " Will fall back to Chi Square Fit."; cout << endl << " Will fall back to Chi Square Fit.";
cout << endl; cout << endl;
} }
} }
} }

1
src/classes/PRunSingleHisto.cpp
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@ -153,6 +153,7 @@ double PRunSingleHisto::CalcChiSquare(const std::vector<double>& par)
// counter++; // counter++;
// if (counter == 4) exit(0); // if (counter == 4) exit(0);
//cout << endl << ">> " << chisq*fRunInfo->fPacking;
return chisq*fRunInfo->fPacking; return chisq*fRunInfo->fPacking;
} }

11
src/classes/PTheory.cpp
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@ -40,6 +40,9 @@ using namespace std;
#include "PMsrHandler.h" #include "PMsrHandler.h"
#include "PTheory.h" #include "PTheory.h"
#define SQRT_TWO 1.41421356237
#define SQRT_PI 1.77245385091
//-------------------------------------------------------------------------- //--------------------------------------------------------------------------
// Constructor // Constructor
//-------------------------------------------------------------------------- //--------------------------------------------------------------------------
@ -1005,8 +1008,8 @@ double PTheory::SkewedGauss(register double t, const vector<double>& paramValues
// val[2] = sigma-, val[3] = sigma+ // val[2] = sigma-, val[3] = sigma+
double z1 = val[3]*t/TMath::Sqrt(2.0); // sigma+ double z1 = val[3]*t/SQRT_TWO; // sigma+
double z2 = val[2]*t/TMath::Sqrt(2.0); // sigma- double z2 = val[2]*t/SQRT_TWO; // sigma-
double g1 = TMath::Exp(-0.5*TMath::Power(t*val[3], 2.0)); // gauss sigma+ double g1 = TMath::Exp(-0.5*TMath::Power(t*val[3], 2.0)); // gauss sigma+
double g2 = TMath::Exp(-0.5*TMath::Power(t*val[2], 2.0)); // gauss sigma- double g2 = TMath::Exp(-0.5*TMath::Power(t*val[2], 2.0)); // gauss sigma-
@ -1016,8 +1019,8 @@ double PTheory::SkewedGauss(register double t, const vector<double>& paramValues
skg = 0.5*TMath::Cos(DEG_TO_RAD*val[0]+TWO_PI*val[1]*t) * ( g1 + g2 ) - skg = 0.5*TMath::Cos(DEG_TO_RAD*val[0]+TWO_PI*val[1]*t) * ( g1 + g2 ) -
0.5*TMath::Sin(DEG_TO_RAD*val[0]+TWO_PI*val[1]*t) * 0.5*TMath::Sin(DEG_TO_RAD*val[0]+TWO_PI*val[1]*t) *
( (
g1*2.0*z1/TMath::Sqrt(TMath::Pi())*gsl_sf_hyperg_1F1(0.5,1.5,z1*z1) - g1*2.0*z1/SQRT_PI*gsl_sf_hyperg_1F1(0.5,1.5,z1*z1) -
g2*2.0*z2/TMath::Sqrt(TMath::Pi())*gsl_sf_hyperg_1F1(0.5,1.5,z2*z2) g2*2.0*z2/SQRT_PI*gsl_sf_hyperg_1F1(0.5,1.5,z2*z2)
); );
return skg; return skg;