def test_iterate_regional_gamma_pressure():
problem = make_lv_mechanics_problem("regional")
target_gamma = problem.material.activation.vector().get_local()
for i in range(len(target_gamma)):
target_gamma[i] = 0.01 - i * 0.001
gamma = problem.material.activation
target_pressure = 0.1
plv = [p.traction for p in problem.bcs.neumann if p.name == "lv"]
pressure = plv[0]
iterate(problem, (pressure, gamma), (target_pressure, target_gamma))
def test_iterate_regional_gamma_pressure():
problem = make_lv_mechanics_problem('regional')
target_gamma = problem.material.activation.vector().get_local()
for i in range(len(target_gamma)):
target_gamma[i] = 0.1 - i * 0.001
gamma = problem.material.activation
target_pressure = 1.0
plv = [p.traction for p in problem.bcs.neumann if p.name == 'lv']
pressure = plv[0]
with pytest.raises(ValueError):
iterate(problem, (pressure, gamma), (target_pressure, target_gamma))
def increase_pressure(self):
p_lv_next = next(self.lv_pressure_gen)
if self.has_rv:
p_rv_next = next(self.rv_pressure_gen)
target = (p_lv_next, p_rv_next)
control = (self.p_lv, self.p_rv)
else:
target = p_lv_next
control = self.p_lv
iterate(problem=self.solver,
target=target,
control=control,
continuation=True)
def next_active(self,
gamma_current,
gamma,
assign_prev_state=True,
steps=None):
old_states, old_gammas = self.load_states()
states, gammas = iterate(problem=self.solver,
control=gamma,
target=gamma_current,
continuation=True,
old_states=old_states,
old_controls=old_gammas)
# Store these gammas and states which can be used
# as initial guess for the newton solver in a later
# iteration
self.store_states(states, gammas)
if assign_prev_state:
# Assign the previous state
self.solver.reinit(states[-1])
self.solver.material.activation.assign(gammas[-1])
return self.get_state(False)
def test_iterate_gamma(problem):
target_gamma = 0.1
gamma = problem.material.activation
if has_dolfin_adjoint:
dolfin.parameters["adjoint"]["stop_annotating"] = False
dolfin_adjoint.adj_reset()
iterate(problem, gamma, target_gamma)
assert all(gamma.vector().get_local() == target_gamma)
assert dolfin.norm(problem.state.vector()) > 0
if has_dolfin_adjoint:
assert dolfin_adjoint.replay_dolfin(tol=1e-12)
def iteration(self, control):
"""
FIXME
TODO: Make this more elegant
"""
logger.info(f"Try control value {constant2float(control)}")
for count in range(self.data_points):
# Stop the recording
annotate = annotation.annotate
bcs = [bc.bc.traction for bc in self.bcs]
targets = [bc.data[count] for bc in self.bcs]
# Iterate bc
iterate(self.problem, bcs, targets)
annotation.annotate = False
# Iterate control
prev_states, prev_controls = iterate(self.problem, self.control,
control)
self.problem.state.assign(prev_states[-1])
self.control.assign(prev_controls[-1])
# Continue recording
annotation.annotate = annotate
for b in self.bcs:
b._count = count
b.assign_bc()
self.problem.solve()
self.control.assign(control, annotate=annotate)
self.problem.solve()
u, p = dolfin.split(self.problem.state)
for t in self.targets:
t._count = count
t.assign(u, annotate=annotate)
yield count
def test_iterate_pressure(problem):
target_pressure = 1.0
plv = [p.traction for p in problem.bcs.neumann if p.name == 'lv']
pressure = plv[0]
if has_dolfin_adjoint:
dolfin.parameters["adjoint"]["stop_annotating"] = False
dolfin_adjoint.adj_reset()
iterate(problem, pressure, target_pressure)
if has_dolfin_adjoint:
# Check the recording
assert dolfin_adjoint.replay_dolfin(tol=1e-12)
# Check that the pressure is correct
assert float(plv[0]) == target_pressure
# Check that the state is nonzero
assert dolfin.norm(problem.state.vector()) > 0
def test_iterate_gamma_pressure(problem):
target_pressure = 1.0
plv = [p.traction for p in problem.bcs.neumann if p.name == 'lv']
pressure = plv[0]
target_gamma = 0.1
gamma = problem.material.activation
if has_dolfin_adjoint:
dolfin.parameters["adjoint"]["stop_annotating"] = False
dolfin_adjoint.adj_reset()
iterate(problem, (pressure, gamma), (target_pressure, target_gamma))
assert all(gamma.vector().get_local() == target_gamma)
assert float(plv[0]) == target_pressure
assert dolfin.norm(problem.state.vector()) > 0
if has_dolfin_adjoint:
assert dolfin_adjoint.replay_dolfin(tol=1e-12)
def test_iterate_gamma_cg1(continuation):
problem = make_lv_mechanics_problem('CG_1')
V = problem.material.activation.function_space()
target_gamma \
= dolfin.interpolate(dolfin.Expression('0.1 * x[0]',
degree=1), V)
gamma = problem.material.activation
if has_dolfin_adjoint:
dolfin.parameters["adjoint"]["stop_annotating"] = False
dolfin_adjoint.adj_reset()
iterate(problem, gamma, target_gamma, continuation=continuation)
assert np.all(
gamma.vector().get_local() - target_gamma.vector().get_local() < 1e-12)
assert dolfin.norm(problem.state.vector()) > 0
if has_dolfin_adjoint:
assert dolfin_adjoint.replay_dolfin(tol=1e-12)
def test_iterate_gamma_regional():
problem = make_lv_mechanics_problem('regional')
target_gamma = problem.material.activation.vector().get_local()
for i in range(len(target_gamma)):
target_gamma[i] = 0.1 - i * 0.001
print(target_gamma)
gamma = problem.material.activation
if has_dolfin_adjoint:
dolfin.parameters["adjoint"]["stop_annotating"] = False
dolfin_adjoint.adj_reset()
iterate(problem, gamma, target_gamma)
print(gamma.vector().get_local())
assert np.all(gamma.vector().get_local() - target_gamma < 1e-12)
assert dolfin.norm(problem.state.vector()) > 0
if has_dolfin_adjoint:
assert dolfin_adjoint.replay_dolfin(tol=1e-12)