void MultivariateGaussianComptonProfile::massProfile(
double *result, const size_t nData, const double amplitude) const {
std::vector<double> s2Cache;
buildS2Cache(s2Cache);
const double sigmaX(getParameter(SIGMA_X_PARAM));
const double sigmaY(getParameter(SIGMA_Y_PARAM));
const double sigmaZ(getParameter(SIGMA_Z_PARAM));
const double prefactorJ =
(1.0 / (sqrt(2.0 * M_PI) * sigmaX * sigmaY * sigmaZ)) * (2.0 / M_PI);
const double prefactorFSE =
(pow(sigmaX, 4) + pow(sigmaY, 4) + pow(sigmaZ, 4)) /
(9.0 * sqrt(2.0 * M_PI) * sigmaX * sigmaY * sigmaZ);
const auto &yspace = ySpace();
const auto &modq = modQ();
for (size_t i = 0; i < nData; i++) {
const double y(yspace[i]);
const double q(modq[i]);
double j = prefactorJ * calculateJ(s2Cache, y);
double fse = (prefactorFSE / q) * calculateFSE(s2Cache, y);
result[i] = amplitude * (j + fse);
}
}
/**
* Uses a Gaussian approximation for the mass and convolutes it with the Voigt
* instrument resolution function
* @param result An pre-sized output vector that should be filled with the results
* @param lorentzFWHM The lorentz width for the resolution
* @param resolutionFWHM The sum-squared value of the resolution errors
*/
void GaussianComptonProfile::massProfile(std::vector<double> & result,const double lorentzFWHM, const double resolutionFWHM) const
{
double lorentzPos(0.0), gaussWidth(getParameter(0)), amplitude(getParameter(1));
double gaussFWHM = std::sqrt(std::pow(resolutionFWHM,2) + std::pow(2.0*STDDEV_TO_HWHM*gaussWidth,2));
const auto & yspace = ySpace();
// Gaussian already folded into Voigt
voigtApprox(result, yspace, lorentzPos, amplitude, lorentzFWHM, gaussFWHM);
std::vector<double> voigtDiffResult(yspace.size());
voigtApproxDiff(voigtDiffResult, yspace, lorentzPos, amplitude, lorentzFWHM, gaussFWHM);
const auto & modq = modQ();
const size_t nData(result.size());
for(size_t j = 0; j < nData; ++j)
{
const double factor = std::pow(gaussWidth,4.0)/(3.0*modq[j]);
result[j] -= factor*voigtDiffResult[j];
}
}
