def _permutation_load(tensor, directory, filename, form, form_name,
mpi_comm):
if form_name not in _permutation_storage:
if not PickleIO.exists_file(directory, "." + form_name):
raise OSError
else:
V_0 = wrapping.form_argument_space(form, 0)
V_0__dof_map_reader_mapping = wrapping.build_dof_map_reader_mapping(
V_0)
V_0__dof_map_writer_mapping = PickleIO.load_file(
directory, "." + form_name)
vector_permutation = dict(
) # from index at time of saving to current index
writer_vec = _vector_load(directory, filename, mpi_comm)
writer_row_start, writer_row_end = writer_vec.getOwnershipRange(
)
for writer_row in range(writer_row_start, writer_row_end):
(global_cell_index,
cell_dof) = V_0__dof_map_writer_mapping[writer_row]
vector_permutation[
writer_row] = V_0__dof_map_reader_mapping[
global_cell_index][cell_dof]
_permutation_storage[form_name] = vector_permutation
return _permutation_storage[form_name]
def _permutation_save(tensor, directory, form, form_name, mpi_comm):
if not PickleIO.exists_file(directory, "." + form_name):
V_0 = wrapping.form_argument_space(form, 0)
V_1 = wrapping.form_argument_space(form, 1)
V_0__dof_map_writer_mapping = wrapping.build_dof_map_writer_mapping(
V_0)
V_1__dof_map_writer_mapping = wrapping.build_dof_map_writer_mapping(
V_1)
matrix_row_mapping = dict(
) # from processor dependent row indices to processor independent tuple
matrix_col_mapping = dict(
) # from processor dependent col indices to processor independent tuple
mat = wrapping.to_petsc4py(tensor)
row_start, row_end = mat.getOwnershipRange()
for row in range(row_start, row_end):
matrix_row_mapping[row] = V_0__dof_map_writer_mapping[row]
cols, _ = mat.getRow(row)
for col in cols:
if col not in matrix_col_mapping:
matrix_col_mapping[col] = V_1__dof_map_writer_mapping[
col]
gathered_matrix_row_mapping = mpi_comm.reduce(matrix_row_mapping,
root=0,
op=_dict_update_op)
gathered_matrix_col_mapping = mpi_comm.reduce(matrix_col_mapping,
root=0,
op=_dict_update_op)
gathered_matrix_mapping = (gathered_matrix_row_mapping,
gathered_matrix_col_mapping)
PickleIO.save_file(gathered_matrix_mapping, directory,
"." + form_name)
def _permutation_load(tensor, directory, filename, form, form_name, mpi_comm):
if form_name not in _permutation_storage:
if not PickleIO.exists_file(directory, "." + form_name):
raise OSError
else:
V_0 = wrapping.form_argument_space(form, 0)
V_1 = wrapping.form_argument_space(form, 1)
V_0__dof_map_reader_mapping = wrapping.build_dof_map_reader_mapping(V_0)
V_1__dof_map_reader_mapping = wrapping.build_dof_map_reader_mapping(V_1)
(V_0__dof_map_writer_mapping, V_1__dof_map_writer_mapping) = PickleIO.load_file(
directory, "." + form_name)
matrix_row_permutation = dict() # from row index at time of saving to current row index
matrix_col_permutation = dict() # from col index at time of saving to current col index
writer_mat = _matrix_load(directory, filename, mpi_comm)
writer_row_start, writer_row_end = writer_mat.getOwnershipRange()
for writer_row in range(writer_row_start, writer_row_end):
(global_cell_index, cell_dof) = V_0__dof_map_writer_mapping[writer_row]
matrix_row_permutation[writer_row] = V_0__dof_map_reader_mapping[global_cell_index][cell_dof]
writer_cols, _ = writer_mat.getRow(writer_row)
for writer_col in writer_cols:
if writer_col not in matrix_col_permutation:
(global_cell_index, cell_dof) = V_1__dof_map_writer_mapping[writer_col]
matrix_col_permutation[writer_col] = V_1__dof_map_reader_mapping[
global_cell_index][cell_dof]
_permutation_storage[form_name] = (matrix_row_permutation, matrix_col_permutation)
return _permutation_storage[form_name]
def _permutation_save(tensor, directory, form, form_name, mpi_comm):
if not PickleIO.exists_file(directory, "." + form_name):
V_0 = wrapping.form_argument_space(form, 0)
V_0__dof_map_writer_mapping = wrapping.build_dof_map_writer_mapping(
V_0)
vector_mapping = dict(
) # from processor dependent indices to processor independent tuple
vec = wrapping.to_petsc4py(tensor)
row_start, row_end = vec.getOwnershipRange()
for row in range(row_start, row_end):
vector_mapping[row] = V_0__dof_map_writer_mapping[row]
gathered_vector_mapping = mpi_comm.reduce(vector_mapping,
root=0,
op=_dict_update_op)
PickleIO.save_file(gathered_vector_mapping, directory,
"." + form_name)