def project_firedrake(v, V, **kwargs):
annotate = kwargs.pop("annotate", None)
to_annotate = utils.to_annotate(annotate)
if isinstance(v, backend.Expression) and (annotate is not True):
to_annotate = False
if isinstance(v, backend.Constant) and (annotate is not True):
to_annotate = False
if isinstance(V, backend.functionspaceimpl.WithGeometry):
result = utils.function_to_da_function(backend.Function(V, name=None))
elif isinstance(V, backend.function.Function):
result = utils.function_to_da_function(V)
else:
raise ValueError("Can't project into a '%r'" % V)
name = kwargs.pop("name", None)
if name is not None:
result.adj_name = name
result.rename(name, "a Function from dolfin-adjoint")
with misc.annotations(to_annotate):
result = backend.project(v, result, **kwargs)
return result
def copy(self, *args, **kwargs):
name = kwargs.pop("name", None)
annotate = kwargs.pop("annotate", None)
to_annotate = utils.to_annotate(annotate)
with misc.annotations(False):
copy = backend.Function.copy(self, *args, **kwargs)
copy = utils.function_to_da_function(copy)
if name is not None:
copy.adj_name = name
copy.rename(name, "a Function from dolfin-adjoint")
adjglobals.function_names.add(name)
if to_annotate:
assignment.register_assign(copy, self)
return copy
def replay_dolfin(forget=False, tol=0.0, stop=False):
with misc.annotations(False):
if not backend.parameters["adjoint"]["record_all"]:
info_red("Warning: your replay test will be much more effective with dolfin.parameters['adjoint']['record_all'] = True.")
success = True
for i in range(adjglobals.adjointer.equation_count):
(fwd_var, output) = adjglobals.adjointer.get_forward_solution(i)
storage = libadjoint.MemoryStorage(output)
storage.set_compare(tol=tol)
storage.set_overwrite(True)
out = adjglobals.adjointer.record_variable(fwd_var, storage)
success = success and out
if forget:
adjglobals.adjointer.forget_forward_equation(i)
if not out and stop:
break
return success
def hessian(J, m, warn=True):
'''Choose which Hessian the user wants.'''
with misc.annotations(False):
H = BasicHessian(J, m, warn=warn)
return H
