def __init__(self, d):
self._impl = d
lhs_op = BlockOperator([[wrapper[d.get_local_operator(ss)] if ss == nn
else wrapper[d.get_coupling_operator(ss, nn)] if nn in list(d.neighbouring_subdomains(ss))
else None
for nn in np.arange(d.num_subdomains())] for ss in np.arange(d.num_subdomains())])
rhs_op = BlockOperator.hstack([wrapper[d.get_local_functional(ss)] for ss in np.arange(d.num_subdomains())])
operators = {'operator': lhs_op}
functionals = {'rhs': rhs_op}
vector_operators = {}
self.operators = FrozenDict(operators)
self.functionals = FrozenDict(functionals)
self.vector_operators = FrozenDict(vector_operators)
self.operator = operators['operator']
self.solution_space = self.operator.source
self.rhs = functionals['rhs']
self.products = {k: BlockDiagonalOperator([wrapper[d.get_local_product(ss, k)]
for ss in np.arange(d.num_subdomains())])
for k in list(d.available_products())}
if self.products:
for k, v in self.products.iteritems():
setattr(self, '{}_product'.format(k), v)
setattr(self, '{}_norm'.format(k), induced_norm(v))
self.linear = all(op.linear for op in operators.itervalues())
self.num_subdomains = self._impl.num_subdomains()
self.neighboring_subdomains = [self._impl.neighbouring_subdomains(ss)
for ss in np.arange(self.num_subdomains)]
self.build_parameter_type(inherits=operators.values())
assert self.parameter_type == self._wrapper[d.parameter_type()]
def test_hstack():
np.random.seed(0)
A = np.random.randn(2, 3)
B = np.random.randn(2, 4)
Aop = NumpyMatrixOperator(A)
Bop = NumpyMatrixOperator(B)
Cop = BlockOperator.hstack((Aop, Bop))
assert Cop.source.dim == 7
assert Cop.range.dim == 2
def test_hstack():
np.random.seed(0)
A = np.random.randn(2, 3)
B = np.random.randn(2, 4)
Aop = NumpyMatrixOperator(A)
Bop = NumpyMatrixOperator(B)
Cop = BlockOperator.hstack((Aop, Bop))
assert Cop.source.dim == 7
assert Cop.range.dim == 2
