value_type iterate( matrix_type const& initial_matrix, matrix_type& result_matrix ) { triple_homotopy_fitting<value_type> thf{ug_size}; size_type const tilt_number = diag_matrix.row(); matrix_type intensity{ intensity_matrix.col(), 1 }; for ( size_type index = 0; index != tilt_number; ++index ) { std::copy( intensity_matrix.row_begin(index), intensity_matrix.row_end(index), intensity.col_begin(0) ); //TODO -- optimizaton here thf.register_entry( ar, //C1 approximation alpha(progress_ratio), make_coefficient_matrix( thickness, diag_matrix.row_begin(index), diag_matrix.row_end(index), column_index ), //C/2 * C/2 approximation beta(progress_ratio), make_coefficient_matrix( thickness/2.0, diag_matrix.row_begin(index), diag_matrix.row_end(index) ), expm( make_structure_matrix(ar, initial_matrix, diag_matrix.row_begin(index), diag_matrix.row_end(index) ), thickness/2.0, column_index ), //standard expm gamma(progress_ratio), make_scattering_matrix( ar, initial_matrix, diag_matrix.row_begin(index), diag_matrix.row_end(index), thickness, column_index ), intensity, column_index ); } result_matrix.resize( ug_size, 1 ); value_type const residual = thf.output( result_matrix.begin() ); /* std::cout << "\n current residual is " << residual << "\n"; std::cout << "\n current ug is \n" << result_matrix.transpose() << "\n"; */ return residual; }