class OswaldInterpolationErrorOperator(OperatorBase):
linear = True
def __init__(self, subdomain, solution_space, grid, block_space):
self.subdomain, self.grid, self.block_space = subdomain, grid, block_space
self.neighborhood = grid.neighborhood_of(subdomain)
self.source = solution_space.subspaces[subdomain]
self.range = BlockVectorSpace(
[solution_space.subspaces[ii] for ii in self.neighborhood],
'OI_{}'.format(subdomain))
def apply(self, U, mu=None):
assert U in self.source
results = self.range.empty(reserve=len(U))
for u_i in range(len(U)):
result = self.range.zeros()
result._blocks[self.neighborhood.index(self.subdomain)].axpy(
1, U[u_i])
for i_ii, ii in enumerate(self.neighborhood):
ii_neighborhood = self.grid.neighborhood_of(ii)
ii_neighborhood_space = self.block_space.restricted_to_neighborhood(
ii_neighborhood)
subdomain_uh_with_neighborhood_support = make_discrete_function(
ii_neighborhood_space,
ii_neighborhood_space.project_onto_neighborhood([
U._list[u_i].impl if nn == self.subdomain else Vector(
self.block_space.local_space(nn).size(), 0.)
for nn in ii_neighborhood
], ii_neighborhood))
interpolated_u_vector = ii_neighborhood_space.project_onto_neighborhood(
[
Vector(self.block_space.local_space(nn).size(), 0.)
for nn in ii_neighborhood
], ii_neighborhood)
interpolated_u = make_discrete_function(
ii_neighborhood_space, interpolated_u_vector)
apply_oswald_interpolation_operator(
self.grid, ii,
make_subdomain_boundary_info(
self.grid,
{'type': 'xt.grid.boundaryinfo.alldirichlet'}),
subdomain_uh_with_neighborhood_support, interpolated_u)
local_sizes = np.array([
ii_neighborhood_space.local_space(nn).size()
for nn in ii_neighborhood
])
offsets = np.hstack(([0], np.cumsum(local_sizes)))
ind = ii_neighborhood.index(ii)
result._blocks[i_ii]._list[0].data[:] -= \
np.frombuffer(interpolated_u_vector)[offsets[ind]:offsets[ind+1]]
results.append(result)
return results
class OswaldInterpolationErrorOperator(EstimatorOperatorBase):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
assert self.subdomain == self.kk == self.jj
self.range = BlockVectorSpace([self.global_space.subspaces[ii] for ii in self.neighborhood],
'OI_{}'.format(self.subdomain))
def _apply(self, U, mu=None):
from dune.gdt import apply_oswald_interpolation_operator
assert len(U) == 1
assert U in self.source
result = self.range.zeros()
result._blocks[self.neighborhood.index(self.subdomain)].axpy(1, U)
for i_ii, ii in enumerate(self.neighborhood):
ii_neighborhood = self.grid.neighborhood_of(ii)
ii_neighborhood_space = self.block_space.restricted_to_neighborhood(ii_neighborhood)
subdomain_uh_with_neighborhood_support = make_discrete_function(
ii_neighborhood_space,
ii_neighborhood_space.project_onto_neighborhood(
[U._list[0].impl if nn == self.subdomain else Vector(self.block_space.local_space(nn).size(), 0.)
for nn in ii_neighborhood],
ii_neighborhood
)
)
interpolated_u_vector = ii_neighborhood_space.project_onto_neighborhood(
[Vector(self.block_space.local_space(nn).size(), 0.) for nn in ii_neighborhood], ii_neighborhood)
interpolated_u = make_discrete_function(ii_neighborhood_space, interpolated_u_vector)
apply_oswald_interpolation_operator(
self.grid, ii,
make_subdomain_boundary_info(self.grid, {'type': 'xt.grid.boundaryinfo.alldirichlet'}),
subdomain_uh_with_neighborhood_support,
interpolated_u
)
local_sizes = np.array([ii_neighborhood_space.local_space(nn).size() for nn in ii_neighborhood])
offsets = np.hstack(([0], np.cumsum(local_sizes)))
ind = ii_neighborhood.index(ii)
result._blocks[i_ii]._list[0].data[:] -= np.frombuffer(interpolated_u_vector)[offsets[ind]:offsets[ind+1]]
return result
