def generate_state(index):
coords = index * np.ones((N_ATOMS, 3))
vels = index * np.ones((N_ATOMS, 3))
alpha = float(index) / 10.
energy = float(index)
return SystemState(coords, vels, alpha, energy)
def generate_state(index):
coords = index * np.ones((N_ATOMS, 3))
vels = index * np.ones((N_ATOMS, 3))
alpha = float(index) / 10.
energy = float(index)
box_vectors = np.zeros(3)
return SystemState(coords, vels, alpha, energy, box_vectors)
def _run_param_mc(self, state):
if not self._parameter_manager.has_parameters():
return state
if self._options.param_mcmc_steps is None:
raise RuntimeError(
"There are sampled parameters, but param_mcmc_steps is not set."
)
energy = self.get_energy(state)
for _ in range(self._options.param_mcmc_steps):
trial_params = self._parameter_manager.sample(state.parameters)
if not self._parameter_manager.is_valid(trial_params):
accept = False
else:
trial_state = SystemState(
state.positions,
state.velocities,
state.alpha,
state.energy,
state.box_vector,
trial_params,
state.mappings,
)
trial_energy = self.get_energy(trial_state)
delta = trial_energy - energy
if delta < 0:
accept = True
else:
if random.random() < math.exp(-delta):
accept = True
else:
accept = False
if accept:
state = trial_state
energy = trial_energy
# Update transfomers in case we rejected the
# last MCMC move
if not accept:
self._transformers_update(state)
return state
def test_should_reject_impossible_move(self):
# setup
start = np.array([
[0.0, 0.0, -1.0],
[0.0, 2.0, -1.0],
[0.0, 0.0, -2.0],
[1.0, 0.0, -1.0],
[0.0, 0.0, 0.0],
[-1.0, 0.0, -1.0],
])
end = np.array([
[0.0, 0.0, -1.0],
[0.0, 2.0, -1.0],
[0.0, 0.0, -2.0],
[1.0, 0.0, -1.0],
[0.0, 0.0, 0.0],
[-1.0, 0.0, -1.0],
])
state = SystemState(start, np.zeros_like(start), 0.0, 0.0, np.zeros(3))
mock_runner = mock.Mock()
mock_runner.get_energy.return_value = 1000.0
mover = mc.RandomTorsionMover(
AtomIndex(0), AtomIndex(1),
[AtomIndex(4), AtomIndex(5)])
# exercise
with mock.patch("meld.system.montecarlo._generate_uniform_angle"
) as mock_gen_angle:
mock_gen_angle.return_value = 90.0
new_state, accepted = mover.trial(state, mock_runner)
# assert
self.assertEqual(new_state.energy, 0.0)
self.assertEqual(accepted, False)
np.testing.assert_array_almost_equal(new_state.positions, end)