/*
* this function tries to be a 1:1 C++ reimplementation of the Perl function
* 'read_mcstas_res' of the McStas 'mcresplot' program
*/
Resolution calc_res(std::vector<vector<t_real>>&& Q_vec,
const vector<t_real>& Q_avg, const std::vector<t_real>* pp_vec)
{
vector<t_real> Q_dir = tl::make_vec({Q_avg[0], Q_avg[1], Q_avg[2]});
Q_dir = Q_dir / norm_2(Q_dir);
vector<t_real> Q_perp = tl::make_vec({-Q_dir[1], Q_dir[0], Q_dir[2]});
vector<t_real> vecUp = tl::cross_3(Q_dir, Q_perp);
/*
* transformation from the <Q_x, Q_y, Q_z, E> system
* into the <Q_avg, Q_perp, Q_z, E> system,
* i.e. rotate by the (ki,Q) angle
*/
matrix<t_real> trafo = identity_matrix<t_real>(4);
tl::set_column(trafo, 0, Q_dir);
tl::set_column(trafo, 1, Q_perp);
tl::set_column(trafo, 2, vecUp);
tl::log_info("Transformation: ", trafo);
Resolution reso;
reso.Q_avg_notrafo = Q_avg;
reso.Q_avg = prod(trans(trafo), Q_avg);
tl::log_info("Transformed average Q vector: ", reso.Q_avg);
reso.res.resize(4,4,0);
reso.cov.resize(4,4,0);
reso.cov = tl::covariance(Q_vec, pp_vec);
reso.cov = tl::transform<matrix<t_real>>(reso.cov, trafo, true);
tl::log_info("Covariance matrix: ", reso.cov);
if(!(reso.bHasRes = tl::inverse(reso.cov, reso.res)))
tl::log_err("Covariance matrix could not be inverted!");
if(reso.bHasRes)
{
reso.dQ.resize(4, 0);
for(int iQ=0; iQ<4; ++iQ)
reso.dQ[iQ] = tl::get_SIGMA2HWHM<t_real>()/sqrt(reso.res(iQ,iQ));
tl::log_info("Resolution matrix: ", reso.res);
std::ostringstream ostrVals;
ostrVals << "Gaussian HWHM values: ";
std::copy(reso.dQ.begin(), reso.dQ.end(),
std::ostream_iterator<t_real>(ostrVals, ", "));
std::ostringstream ostrElli;
ostrElli << "Ellipsoid offsets: ";
std::copy(reso.Q_avg.begin(), reso.Q_avg.end(),
std::ostream_iterator<t_real>(ostrElli, ", "));
reso.vecQ = std::move(Q_vec);
tl::log_info(ostrVals.str());
tl::log_info(ostrElli.str());
}
return reso;
}
