void init(MatrixType const & mat, row_scaling_tag const & tag)
{
diag_M.resize(mat.size1()); //resize without preserving values
for (typename MatrixType::const_iterator1 row_it = mat.begin1();
row_it != mat.end1();
++row_it)
{
for (typename MatrixType::const_iterator2 col_it = row_it.begin();
col_it != row_it.end();
++col_it)
{
if (tag.norm() == 0)
diag_M[col_it.index1()] = std::max<ScalarType>(diag_M[col_it.index1()], std::fabs(*col_it));
else if (tag.norm() == 1)
diag_M[col_it.index1()] += std::fabs(*col_it);
else if (tag.norm() == 2)
diag_M[col_it.index1()] += (*col_it) * (*col_it);
}
if (!diag_M[row_it.index1()])
throw zero_on_diagonal_exception("ViennaCL: Zero row encountered while setting up row scaling preconditioner!");
if (tag.norm() == 2)
diag_M[row_it.index1()] = std::sqrt(diag_M[row_it.index1()]);
}
}
void init(MatrixType const & mat, row_scaling_tag const & tag)
{
switch (tag.norm())
{
case 0:
detail::row_info(mat, diag_M, detail::SPARSE_ROW_NORM_INF);
break;
case 1:
detail::row_info(mat, diag_M, detail::SPARSE_ROW_NORM_1);
break;
case 2:
detail::row_info(mat, diag_M, detail::SPARSE_ROW_NORM_2);
break;
default:
throw unknown_norm_exception("Unknown norm when initializing row_scaling preconditioner!");
}
}
void init(MatrixType const & mat, row_scaling_tag const & tag)
{
switch (tag.norm())
{
case 0:
detail::row_info(mat, diag_M, detail::SPARSE_ROW_NORM_INF);
break;
case 1:
detail::row_info(mat, diag_M, detail::SPARSE_ROW_NORM_1);
break;
case 2:
detail::row_info(mat, diag_M, detail::SPARSE_ROW_NORM_2);
break;
default:
throw "Unknown norm!";
}
}
