//-----------------------------------------------------------------------------
CoordinateMatrix::CoordinateMatrix(const GenericMatrix& A, bool symmetric,
bool base_one)
: _symmetric(symmetric), _base_one(base_one)
{
_size[0] = A.size(0);
_size[1] = A.size(1);
// Iterate over local rows
const std::pair<std::size_t, std::size_t> local_row_range = A.local_range(0);
if (!_symmetric)
{
for (std::size_t i = local_row_range.first; i < local_row_range.second; ++i)
{
// Get column and value data for row
std::vector<std::size_t> columns;
std::vector<double> values;
A.getrow(i, columns, values);
// Insert data at end
_rows.insert(_rows.end(), columns.size(), i);
_cols.insert(_cols.end(), columns.begin(), columns.end());
_vals.insert(_vals.end(), values.begin(), values.end());
}
assert(_rows.size() == _cols.size());
}
else
{
assert(_size[0] == _size[1]);
for (std::size_t i = local_row_range.first; i < local_row_range.second; ++i)
{
// Get column and value data for row
std::vector<std::size_t> columns;
std::vector<double> values;
A.getrow(i, columns, values);
for (std::size_t j = 0; j < columns.size(); ++j)
{
if (columns[j] >= i)
{
_rows.push_back(i);
_cols.push_back(columns[j]);
_vals.push_back(values[j]);
}
}
}
assert(_rows.size() == _cols.size());
}
// Add 1 for Fortran-style indices
if (base_one)
{
for (std::size_t i = 0; i < _cols.size(); ++i)
{
_rows[i]++;
_cols[i]++;
}
}
}
void compute_DG0_to_CG_weight_matrix(GenericMatrix& A, Function& DG)
{
compute_weight(DG);
std::vector<std::size_t> columns;
std::vector<double> values;
std::vector<std::vector<std::size_t> > allcolumns;
std::vector<std::vector<double> > allvalues;
const std::pair<std::size_t, std::size_t> row_range = A.local_range(0);
const std::size_t m = row_range.second - row_range.first;
GenericVector& weight = *DG.vector();
const std::pair<std::size_t, std::size_t> weight_range = weight.local_range();
std::vector<std::size_t> weight_range_vec(2);
weight_range_vec[0] = weight_range.first;
weight_range_vec[1] = weight_range.second;
int dm = weight_range.second-weight_range.first;
const MPI_Comm mpi_comm = DG.function_space()->mesh()->mpi_comm();
// Communicate local_ranges of weights
std::vector<std::vector<std::size_t> > all_ranges;
MPI::all_gather(mpi_comm, weight_range_vec, all_ranges);
// Number of MPI processes
std::size_t num_processes = MPI::size(mpi_comm);
// Some weights live on other processes and need to be communicated
// Create list of off-process weights
std::vector<std::vector<std::size_t> > dofs_needed(num_processes);
for (std::size_t row = 0; row < m; row++)
{
// Get global row number
const std::size_t global_row = row + row_range.first;
A.getrow(global_row, columns, values);
for (std::size_t i = 0; i < columns.size(); i++)
{
std::size_t dof = columns[i];
if (dof < weight_range.first || dof >= weight_range.second)
{
std::size_t owner = dof_owner(all_ranges, dof);
dofs_needed[owner].push_back(dof);
}
}
}
// Communicate to all which weights are needed by the process
std::vector<std::vector<std::size_t> > dofs_needed_recv;
MPI::all_to_all(mpi_comm, dofs_needed, dofs_needed_recv);
// Fetch the weights that must be communicated
std::vector<std::vector<double> > weights_to_send(num_processes);
for (std::size_t p = 0; p < num_processes; p++)
{
if (p == MPI::rank(mpi_comm))
continue;
std::vector<std::size_t> dofs = dofs_needed_recv[p];
std::map<std::size_t, double> send_weights;
for (std::size_t k = 0; k < dofs.size(); k++)
{
weights_to_send[p].push_back(weight[dofs[k]-weight_range.first]);
}
}
std::vector<std::vector<double> > weights_to_send_recv;
MPI::all_to_all(mpi_comm, weights_to_send, weights_to_send_recv);
// Create a map for looking up received weights
std::map<std::size_t, double> received_weights;
for (std::size_t p = 0; p < num_processes; p++)
{
if (p == MPI::rank(mpi_comm))
continue;
for (std::size_t k = 0; k < dofs_needed[p].size(); k++)
{
received_weights[dofs_needed[p][k]] = weights_to_send_recv[p][k];
}
}
for (std::size_t row = 0; row < m; row++)
{
// Get global row number
const std::size_t global_row = row + row_range.first;
A.getrow(global_row, columns, values);
for (std::size_t i = 0; i < values.size(); i++)
{
std::size_t dof = columns[i];
if (dof < weight_range.first || dof >= weight_range.second)
{
values[i] = received_weights[dof];
}
else
{
values[i] = weight[columns[i]-weight_range.first];
}
// values[i] = 1./values[i];
}
double s = std::accumulate(values.begin(), values.end(), 0.0);
std::transform(values.begin(), values.end(), values.begin(),
std::bind2nd(std::multiplies<double>(), 1./s));
for (std::size_t i=0; i<values.size(); i++)
{
double w;
std::size_t dof = columns[i];
if (dof < weight_range.first || dof >= weight_range.second)
{
w = received_weights[dof];
}
else
{
w = weight[dof-weight_range.first];
}
values[i] = values[i]*w;
// values[i] = values[i]*values[i];
}
allvalues.push_back(values);
allcolumns.push_back(columns);
}
for (std::size_t row = 0; row < m; row++)
{
// Get global row number
const std::size_t global_row = row + row_range.first;
A.setrow(global_row, allcolumns[row], allvalues[row]);
}
A.apply("insert");
}
//-----------------------------------------------------------------------------
void DirichletBC::zero_columns(GenericMatrix& A,
GenericVector& b,
double diag_val) const
{
// Check arguments
check_arguments(&A, &b, NULL, 1);
// A map to hold the mapping from boundary dofs to boundary values
Map bv_map;
get_boundary_values(bv_map);
// Create lookup table of dofs
//const std::size_t nrows = A.size(0); // should be equal to b.size()
const std::size_t ncols = A.size(1); // should be equal to max possible dof+1
std::pair<std::size_t, std::size_t> rows = A.local_range(0);
std::vector<char> is_bc_dof(ncols);
std::vector<double> bc_dof_val(ncols);
for (Map::const_iterator bv = bv_map.begin(); bv != bv_map.end(); ++bv)
{
is_bc_dof[bv->first] = 1;
bc_dof_val[bv->first] = bv->second;
}
// Scan through all columns of all rows, setting to zero if
// is_bc_dof[column]. At the same time, we collect corrections to
// the RHS
std::vector<std::size_t> cols;
std::vector<double> vals;
std::vector<double> b_vals;
std::vector<dolfin::la_index> b_rows;
for (std::size_t row = rows.first; row < rows.second; row++)
{
// If diag_val is nonzero, the matrix is a diagonal block
// (nrows==ncols), and we can set the whole BC row
if (diag_val != 0.0 && is_bc_dof[row])
{
A.getrow(row, cols, vals);
for (std::size_t j = 0; j < cols.size(); j++)
vals[j] = (cols[j] == row)*diag_val;
A.setrow(row, cols, vals);
A.apply("insert");
b.setitem(row, bc_dof_val[row]*diag_val);
}
else // Otherwise, we scan the row for BC columns
{
A.getrow(row, cols, vals);
bool row_changed = false;
for (std::size_t j = 0; j < cols.size(); j++)
{
const std::size_t col = cols[j];
// Skip columns that aren't BC, and entries that are zero
if (!is_bc_dof[col] || vals[j] == 0.0)
continue;
// We're going to change the row, so make room for it
if (!row_changed)
{
row_changed = true;
b_rows.push_back(row);
b_vals.push_back(0.0);
}
b_vals.back() -= bc_dof_val[col]*vals[j];
vals[j] = 0.0;
}
if (row_changed)
{
A.setrow(row, cols, vals);
A.apply("insert");
}
}
}
b.add_local(&b_vals.front(), b_rows.size(), &b_rows.front());
b.apply("add");
}
