def action_apply_basis(self, op):
range_basis, source_basis = self.range_basis, self.source_basis
if source_basis is None:
try:
V = op.apply_adjoint(range_basis)
except NotImplementedError:
raise RuleNotMatchingError('apply_adjoint not implemented')
if isinstance(op.source, NumpyVectorSpace):
from pymor.operators.numpy import NumpyMatrixOperator
return NumpyMatrixOperator(V.to_numpy(),
source_id=op.source.id,
name=op.name)
else:
from pymor.operators.constructions import VectorArrayOperator
return VectorArrayOperator(V, adjoint=True, name=op.name)
else:
if range_basis is None:
V = op.apply(source_basis)
if isinstance(op.range, NumpyVectorSpace):
from pymor.operators.numpy import NumpyMatrixOperator
return NumpyMatrixOperator(V.to_numpy().T,
range_id=op.range.id,
name=op.name)
else:
from pymor.operators.constructions import VectorArrayOperator
return VectorArrayOperator(V, adjoint=False, name=op.name)
else:
from pymor.operators.numpy import NumpyMatrixOperator
return NumpyMatrixOperator(op.apply2(range_basis,
source_basis),
name=op.name)
def action_EmpiricalInterpolatedOperator(self,
op,
range_basis,
source_basis,
product=None):
if len(op.interpolation_dofs) == 0:
return self.apply(ZeroOperator(op.source, op.range, op.name),
range_basis, source_basis, product)
elif not hasattr(op, 'restricted_operator') or source_basis is None:
raise RuleNotMatchingError(
'Has no restricted operator or source_basis is None')
else:
if range_basis is not None:
if product is None:
projected_collateral_basis = NumpyVectorSpace.make_array(
op.collateral_basis.dot(range_basis), op.range.id)
else:
projected_collateral_basis = NumpyVectorSpace.make_array(
product.apply2(op.collateral_basis, range_basis),
op.range.id)
else:
projected_collateral_basis = op.collateral_basis
return ProjectedEmpiciralInterpolatedOperator(
op.restricted_operator, op.interpolation_matrix,
NumpyVectorSpace.make_array(
source_basis.components(op.source_dofs)),
projected_collateral_basis, op.triangular, op.source.id, None,
op.name)
def action_IdentityOperator(self, op):
dim_range, dim_source = self.dim_range, self.dim_source
if dim_range != dim_source:
raise RuleNotMatchingError(
'dim_range and dim_source must be equal.')
space = op.source if dim_source is None else NumpyVectorSpace(
dim_source)
return IdentityOperator(space, name=op.name)
def action_apply_basis(self, op):
range_basis, source_basis, product = self.range_basis, self.source_basis, self.product
if source_basis is None:
if range_basis is None:
return op
else:
try:
V = op.apply_transpose(
product.apply(range_basis) if product else range_basis)
except NotImplementedError:
raise RuleNotMatchingError(
'apply_transpose not implemented')
if isinstance(op.source, NumpyVectorSpace):
from pymor.operators.numpy import NumpyMatrixOperator
return NumpyMatrixOperator(V.data,
source_id=op.source.id,
range_id=op.range.id,
name=op.name)
else:
from pymor.operators.constructions import VectorArrayOperator
return VectorArrayOperator(V,
transposed=True,
space_id=op.range.id,
name=op.name)
else:
if range_basis is None:
V = op.apply(source_basis)
if isinstance(op.range, NumpyVectorSpace):
from pymor.operators.numpy import NumpyMatrixOperator
return NumpyMatrixOperator(V.data.T,
source_id=op.source.id,
range_id=op.range.id,
name=op.name)
else:
from pymor.operators.constructions import VectorArrayOperator
return VectorArrayOperator(V,
transposed=False,
space_id=op.source.id,
name=op.name)
elif product is None:
from pymor.operators.numpy import NumpyMatrixOperator
return NumpyMatrixOperator(op.apply2(range_basis,
source_basis),
source_id=op.source.id,
range_id=op.range.id,
name=op.name)
else:
from pymor.operators.numpy import NumpyMatrixOperator
V = op.apply(source_basis)
return NumpyMatrixOperator(product.apply2(range_basis, V),
source_id=op.source.id,
range_id=op.range.id,
name=op.name)