void sym_sparse_matrix_to_stl(MatrixType const & A, std::vector<std::map<unsigned int, ScalarType> > & STL_A)
{
STL_A.resize(A.size1());
for (typename MatrixType::const_iterator1 row_it = A.begin1();
row_it != A.end1();
++row_it)
{
for (typename MatrixType::const_iterator2 col_it = row_it.begin();
col_it != row_it.end();
++col_it)
{
if (col_it.index1() >= col_it.index2())
STL_A[col_it.index1()][static_cast<unsigned int>(col_it.index2())] = *col_it;
else
break; //go to next row
}
}
}
void generateJ(MatrixType const & A, std::vector<std::vector<vcl_size_t> > & J)
{
for (typename MatrixType::const_iterator1 row_it = A.begin1();
row_it != A.end1();
++row_it)
{
for (typename MatrixType::const_iterator2 col_it = row_it.begin();
col_it != row_it.end();
++col_it)
{
if (col_it.index1() > col_it.index2()) //Matrix is symmetric, thus only work on lower triangular part
{
J[col_it.index2()].push_back(col_it.index1());
J[col_it.index1()].push_back(col_it.index2());
}
else
break; //go to next row
}
}
}
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)
{
diag_A.resize(viennacl::traits::size1(mat)); //resize without preserving values
for (typename MatrixType::const_iterator1 row_it = mat.begin1();
row_it != mat.end1();
++row_it)
{
bool diag_found = false;
for (typename MatrixType::const_iterator2 col_it = row_it.begin();
col_it != row_it.end();
++col_it)
{
if (col_it.index1() == col_it.index2())
{
diag_A[col_it.index1()] = *col_it;
diag_found = true;
}
}
if (!diag_found)
throw "ViennaCL: Zero in diagonal encountered while setting up Jacobi preconditioner!";
}
}
jacobi_precond(MatrixType const & mat, jacobi_tag const & tag) : system_matrix(mat)
{
assert(mat.size1() == mat.size2());
diag_A_inv.resize(mat.size1()); //resize without preserving values
for (typename MatrixType::const_iterator1 row_it = system_matrix.begin1();
row_it != system_matrix.end1();
++row_it)
{
bool diag_found = false;
for (typename MatrixType::const_iterator2 col_it = row_it.begin();
col_it != row_it.end();
++col_it)
{
if (col_it.index1() == col_it.index2())
{
diag_A_inv[col_it.index1()] = static_cast<ScalarType>(1.0) / *col_it;
diag_found = true;
}
}
if (!diag_found)
throw "ViennaCL: Zero in diagonal encountered while setting up Jacobi preconditioner!";
}
}
