def _drop_double_transpose_transpose(expr, self):
"""When the expression and its child are transposes the grandchild is returned,
because A=A.T.T."""
child, = expr.children
if isinstance(child, Transpose):
grandchild, = child.children
return self(grandchild)
elif child.terminal and child.rank > 1:
return Tensor(adjoint(child.form))
else:
return type(expr)(*map(self, expr.children))
def __init__(self, a, row_bcs=[], col_bcs=[], fc_params=None, appctx=None):
self.a = a
self.aT = a.T if isinstance(self.a, slate.TensorBase) else adjoint(a)
self.fc_params = fc_params
self.appctx = appctx
self.row_bcs = row_bcs
self.col_bcs = col_bcs
# create functions from test and trial space to help
# with 1-form assembly
test_space, trial_space = [
a.arguments()[i].function_space() for i in (0, 1)
]
from firedrake import function
self._y = function.Function(test_space)
self._x = function.Function(trial_space)
# These are temporary storage for holding the BC
# values during matvec application. _xbc is for
# the action and ._ybc is for transpose.
if len(self.row_bcs) > 0:
self._xbc = function.Function(trial_space)
if len(self.col_bcs) > 0:
self._ybc = function.Function(test_space)
# Get size information from template vecs on test and trial spaces
trial_vec = trial_space.dof_dset.layout_vec
test_vec = test_space.dof_dset.layout_vec
self.col_sizes = trial_vec.getSizes()
self.row_sizes = test_vec.getSizes()
self.block_size = (test_vec.getBlockSize(), trial_vec.getBlockSize())
if isinstance(self.a, slate.TensorBase):
self.action = self.a * slate.AssembledVector(self._x)
self.actionT = self.aT * slate.AssembledVector(self._y)
else:
self.action = action(self.a, self._x)
self.actionT = action(self.aT, self._y)
from firedrake.assemble import create_assembly_callable
self._assemble_action = create_assembly_callable(
self.action,
tensor=self._y,
form_compiler_parameters=self.fc_params)
self._assemble_actionT = create_assembly_callable(
self.actionT,
tensor=self._x,
form_compiler_parameters=self.fc_params)
def __init__(self, a, row_bcs=[], col_bcs=[],
fc_params=None, appctx=None):
self.a = a
self.aT = adjoint(a)
self.fc_params = fc_params
self.appctx = appctx
self.row_bcs = row_bcs
self.col_bcs = col_bcs
# create functions from test and trial space to help
# with 1-form assembly
test_space, trial_space = [
a.arguments()[i].function_space() for i in (0, 1)
]
from firedrake import function
self._y = function.Function(test_space)
self._x = function.Function(trial_space)
# These are temporary storage for holding the BC
# values during matvec application. _xbc is for
# the action and ._ybc is for transpose.
if len(self.row_bcs) > 0:
self._xbc = function.Function(trial_space)
if len(self.col_bcs) > 0:
self._ybc = function.Function(test_space)
# Get size information from template vecs on test and trial spaces
trial_vec = trial_space.dof_dset.layout_vec
test_vec = test_space.dof_dset.layout_vec
self.col_sizes = trial_vec.getSizes()
self.row_sizes = test_vec.getSizes()
self.block_size = (test_vec.getBlockSize(), trial_vec.getBlockSize())
self.action = action(self.a, self._x)
self.actionT = action(self.aT, self._y)
from firedrake.assemble import create_assembly_callable
self._assemble_action = create_assembly_callable(self.action, tensor=self._y,
form_compiler_parameters=self.fc_params)
self._assemble_actionT = create_assembly_callable(self.actionT, tensor=self._x,
form_compiler_parameters=self.fc_params)
def __init__(self, a, row_bcs=[], col_bcs=[], fc_params=None, appctx=None):
self.a = a
self.aT = adjoint(a)
self.fc_params = fc_params
self.appctx = appctx
# Collect all DirichletBC instances including
# DirichletBCs applied to an EquationBC.
# all bcs (DirichletBC, EquationBCSplit)
self.bcs = row_bcs
self.bcs_col = col_bcs
self.row_bcs = tuple(bc for bc in itertools.chain(*row_bcs)
if isinstance(bc, DirichletBC))
self.col_bcs = tuple(bc for bc in itertools.chain(*col_bcs)
if isinstance(bc, DirichletBC))
# create functions from test and trial space to help
# with 1-form assembly
test_space, trial_space = [
a.arguments()[i].function_space() for i in (0, 1)
]
from firedrake import function
self._y = function.Function(test_space)
self._x = function.Function(trial_space)
# These are temporary storage for holding the BC
# values during matvec application. _xbc is for
# the action and ._ybc is for transpose.
if len(self.bcs) > 0:
self._xbc = function.Function(trial_space)
if len(self.col_bcs) > 0:
self._ybc = function.Function(test_space)
# Get size information from template vecs on test and trial spaces
trial_vec = trial_space.dof_dset.layout_vec
test_vec = test_space.dof_dset.layout_vec
self.col_sizes = trial_vec.getSizes()
self.row_sizes = test_vec.getSizes()
self.block_size = (test_vec.getBlockSize(), trial_vec.getBlockSize())
self.action = action(self.a, self._x)
self.actionT = action(self.aT, self._y)
from firedrake.assemble import create_assembly_callable
# For assembling action(f, self._x)
self.bcs_action = []
for bc in self.bcs:
if isinstance(bc, DirichletBC):
self.bcs_action.append(bc)
elif isinstance(bc, EquationBCSplit):
self.bcs_action.append(bc.reconstruct(action_x=self._x))
self._assemble_action = create_assembly_callable(
self.action,
tensor=self._y,
bcs=self.bcs_action,
form_compiler_parameters=self.fc_params)
# For assembling action(adjoint(f), self._y)
# Sorted list of equation bcs
self.objs_actionT = []
for bc in self.bcs:
self.objs_actionT += bc.sorted_equation_bcs()
self.objs_actionT.append(self)
# Each par_loop is to run with appropriate masks on self._y
self._assemble_actionT = []
# Deepest EquationBCs first
for bc in self.bcs:
for ebc in bc.sorted_equation_bcs():
self._assemble_actionT.append(
create_assembly_callable(
action(adjoint(ebc.f), self._y),
tensor=self._xbc,
bcs=None,
form_compiler_parameters=self.fc_params))
# Domain last
self._assemble_actionT.append(
create_assembly_callable(
self.actionT,
tensor=self._x if len(self.bcs) == 0 else self._xbc,
bcs=None,
form_compiler_parameters=self.fc_params))
