def test_context_manager_replace():
with fsr.handler_context({'syn-mod': SynHandlerMod}):
assert_true(fsr._h_registry['syn-mod'] is SynHandlerMod)
with fsr.handler_context({'syn-mod': SynHandlerEcho}):
assert_true(fsr._h_registry['syn-mod'] is SynHandlerEcho)
assert_true(fsr._h_registry['syn-mod'] is SynHandlerMod)
assert_false('syn-mod' in fsr._h_registry)
def test_maps_spectrum_round_trip(self):
sn = np.sin(self.th)
with fsr.handler_context({'hdf5_maps': HDFM}):
for eid, sc in zip(self.eids_spectrum, self.scale):
print(eid)
data = retrieve(eid)
assert_array_equal(data, sc * sn)
def test_register_fail():
with fsr.handler_context({'syn-mod': SynHandlerMod}):
# shouldn't raise, it is a no-op as it is regiristering
# the same class with the same name
fsr.register_handler('syn-mod', SynHandlerMod)
# should raise as it is trying to change the registered class
assert_raises(RuntimeError, fsr.register_handler,
'syn-mod', SynHandlerEcho)
def test_custom():
test_path = os.path.join(BASE_PATH, str(uuid.uuid4()) + '.npy')
dd = np.random.rand(500, 500)
with fs_write.NpyWriter(test_path, resource_kwargs={'mmap_mode': 'r'}) as f:
eid = f.add_data(dd)
with fsr.handler_context({'npy': fs_read.NpyHandler}):
ret = fsc.retrieve(eid)
assert_array_equal(dd, ret)
def test_overwrite_global():
mock_base = dict(spec='syn-mod',
resource_path='',
resource_kwargs={'shape': (5, 7)})
res = fsc.insert_resource(**mock_base)
cache_key = (str(res.id), SynHandlerMod.__name__)
with fsr.handler_context({'syn-mod': SynHandlerMod}):
fsr.get_spec_handler(res.id)
assert_in(cache_key, fsr._HANDLER_CACHE)
fsr.register_handler('syn-mod', SynHandlerEcho, overwrite=True)
assert_not_in(cache_key, fsr._HANDLER_CACHE)
def test_get_handler_global():
mock_base = dict(spec='syn-mod',
resource_path='',
resource_kwargs={'shape': (5, 7)})
res = fsc.insert_resource(**mock_base)
cache_key = (str(res.id), SynHandlerMod.__name__)
with fsr.handler_context({'syn-mod': SynHandlerMod}):
handle = fsr.get_spec_handler(res.id)
assert_true(isinstance(handle, SynHandlerMod))
assert_in(cache_key, fsr._HANDLER_CACHE)
assert_not_in(cache_key, fsr._HANDLER_CACHE)
def run_simulation(sim):
# Load info from simulation request
sim_params, = find_simulation_parameter_document(_id=sim.params.id)
# TODO: Throw in some statments about timeouts, acceptable U(q), etc.
iterations = sim_params.iterations
target_acceptance = sim_params.target_acceptance
ensemble_temp = sim_params.temperature
# Load Starting Atoms
starting_atoms_entry, = find_atomic_config_document(
_id=sim.starting_atoms.id)
starting_atoms = starting_atoms_entry.file_payload
try:
traj_entry, = find_atomic_config_document(_id=sim.starting_atoms.id)
traj = traj_entry.file_payload
except:
traj_entry = None
traj = None
# We want to continue this simulation
if isinstance(traj, list):
# Give back the final configuration
atoms = traj[-1]
# Search filestore and get the file_location
with handler_context({'ase': FileLocation}):
atoms_file_location = fsc.retrieve(starting_atoms_entry.file_uid)
wtraj = PickleTrajectory(atoms_file_location, 'a')
# This is a new sim with a new trajectory
elif traj is None:
# Give back the initial config
atoms = starting_atoms
# Generate new file location and save it to filestore
new_atoms_entry = insert_atom_document(
starting_atoms_entry.name + '_' + sim.name, atoms)
with handler_context({'ase': FileLocation}):
new_file_location = fsc.retrieve(new_atoms_entry.file_uid)
wtraj = PickleTrajectory(new_file_location, 'w')
sim.simulation_atoms = new_atoms_entry
sim.save()
# Create Calculators
pes, = find_pes_document(_id=sim.pes.id)
master_calc = pes.payload
# Attach MulitCalc to atoms
atoms.set_calculator(master_calc)
sim.start_total_energy.append(atoms.get_total_energy())
sim.start_potential_energy.append(atoms.get_potential_energy())
sim.start_kinetic_energy.append(atoms.get_kinetic_energy())
sim.start_time.append(ttime.time())
sim.ran = True
sim.save()
# Simulate
# TODO: eventually support different simulation engines
out_traj, samples, l_p_i, seed = nuts(atoms, target_acceptance, iterations,
ensemble_temp, wtraj)
sim.end_time.append(ttime.time())
sim.total_iterations.append(sim.params.iterations)
sim.total_samples.append(samples)
sim.leapfrog_per_iter.append(l_p_i)
sim.finished = True
sim.seed.append(seed)
sim.save()
# Write info to DB
sim.final_potential_energy.append(out_traj[-1].get_potential_energy())
sim.final_kinetic_energy.append(out_traj[-1].get_kinetic_energy())
sim.final_kinetic_energy.append(out_traj[-1].get_total_energy())
sim.save()
def test_retrival(self):
with fsr.handler_context({'npy_FRAMEWISE': NpyFrameWise}):
for i, datum_id in enumerate(self.datum_ids):
data = retrieve(datum_id)
known_data = i * np.ones((9, 8))
assert_array_equal(data, known_data)
def test_maps_plane_round_trip(self):
base = self.scale.reshape(self.N, self.M)
with fsr.handler_context({'hdf5_planes': HDFE}):
for eid, v in zip(self.eids_planes, np.sin(self.th)):
data = retrieve(eid)
assert_array_equal(data, base * v)
def _npsave_helper(dd, base_path):
eid = fs_write.save_ndarray(dd, base_path)
with fsr.handler_context({'npy': fs_read.NpyHandler}):
ret = fsc.retrieve(eid)
assert_array_equal(dd, ret)
def run_simulation(sim):
# Load info from simulation request
sim_params, = find_simulation_parameter_document(_id=sim.params.id)
# TODO: Throw in some statments about timeouts, acceptable U(q), etc.
iterations = sim_params.iterations
target_acceptance = sim_params.target_acceptance
ensemble_temp = sim_params.temperature
# Load Starting Atoms
starting_atoms_entry, = find_atomic_config_document(_id=sim.starting_atoms.id)
starting_atoms = starting_atoms_entry.file_payload
try:
traj_entry, = find_atomic_config_document(_id=sim.starting_atoms.id)
traj = traj_entry.file_payload
except:
traj_entry = None
traj = None
# We want to continue this simulation
if isinstance(traj, list):
# Give back the final configuration
atoms = traj[-1]
# Search filestore and get the file_location
with handler_context({'ase': FileLocation}):
atoms_file_location = fsc.retrieve(starting_atoms_entry.file_uid)
wtraj = PickleTrajectory(atoms_file_location, 'a')
# This is a new sim with a new trajectory
elif traj is None:
# Give back the initial config
atoms = starting_atoms
# Generate new file location and save it to filestore
new_atoms_entry = insert_atom_document(
starting_atoms_entry.name + '_' + sim.name, atoms)
with handler_context({'ase': FileLocation}):
new_file_location = fsc.retrieve(new_atoms_entry.file_uid)
wtraj = PickleTrajectory(new_file_location, 'w')
sim.simulation_atoms = new_atoms_entry
sim.save()
# Create Calculators
pes, = find_pes_document(_id=sim.pes.id)
master_calc = pes.payload
# Attach MulitCalc to atoms
atoms.set_calculator(master_calc)
sim.start_total_energy.append(atoms.get_total_energy())
sim.start_potential_energy.append(atoms.get_potential_energy())
sim.start_kinetic_energy.append(atoms.get_kinetic_energy())
sim.start_time.append(ttime.time())
sim.ran = True
sim.save()
# Simulate
# TODO: eventually support different simulation engines
out_traj, samples, l_p_i, seed = nuts(atoms, target_acceptance, iterations,
ensemble_temp, wtraj)
sim.end_time.append(ttime.time())
sim.total_iterations.append(sim.params.iterations)
sim.total_samples.append(samples)
sim.leapfrog_per_iter.append(l_p_i)
sim.finished = True
sim.seed.append(seed)
sim.save()
# Write info to DB
sim.final_potential_energy.append(out_traj[-1].get_potential_energy())
sim.final_kinetic_energy.append(out_traj[-1].get_kinetic_energy())
sim.final_kinetic_energy.append(out_traj[-1].get_total_energy())
sim.save()
