def run_and_assert_serialization_succeeds(self, obj):
obj.run(self.job_manager, wait=True)
attrs_to_ignore = SIM_GROUP_IGNORE + ["simulations"]
assert_roundtrip_identical(obj, ignore=attrs_to_ignore)
assert_round_trip_to_file_identical(self.filepath,
obj,
ignore=attrs_to_ignore)
def test_lazy_loading_simulation(self):
# Copy cadet file, so the lazy copy can find it and be run too:
copyfile(self.result_filepath, self.sim.cadet_filepath)
try:
object_to_save = LazyLoadingSimulation.from_simulation(self.sim)
self.assertIsNotNone(object_to_save.output)
assert_roundtrip_identical(object_to_save)
finally:
os.remove(self.sim.cadet_filepath)
def test_create_save_load_sim_grid_unit_scalar(self):
cp = make_sample_simulation2()
diff = (SingleParamSimulationDiff("method.method_steps[0].flow_rate",
UnitScalar(5, units=cm_per_hr)), )
obj = SimulationGroup(center_point_simulation=cp,
name="foo",
simulation_diffs=[diff])
assert_roundtrip_identical(obj, ignore=SIM_GROUP_IGNORE)
assert_round_trip_to_file_identical(self.filepath,
obj,
ignore=SIM_GROUP_IGNORE)
def test_task(self):
project = KromatographyProject(study=self.study)
object_to_save = KromatographyTask(project=project)
# Ignore datasource since managed by the containing Application object
# Ignore sim group cp because not serialized.
assert_roundtrip_identical(object_to_save, ignore=self.ignore)
serial_data, array_collection = serialize(object_to_save)
new_object, _ = deserialize(serial_data, array_collection)
# Until it is embedded into the KromApplication, the datasource is not
# set:
self.assertIsNone(new_object.project.datasource)
self.assertIsNone(new_object.project.study.datasource)
def test_float(self):
val = 2.
assert_roundtrip_identical(val)
val = 1.e-3
assert_roundtrip_identical(val)
def test_create_save_load_monte_carlo_sim_group(self):
obj = make_sample_mc_simulation_group()
assert_roundtrip_identical(obj, ignore=SIM_GROUP_IGNORE)
assert_round_trip_to_file_identical(self.filepath,
obj,
ignore=SIM_GROUP_IGNORE)
def test_product(self):
object_to_save = self.study.product
assert_roundtrip_identical(object_to_save)
def test_unitarray(self):
arr = np.array([1, 2, 3, 4])
a = UnitArray(arr, units="m")
assert_roundtrip_identical(a)
def test_ParameterScanDescription(self):
scan_data = {"name": "binding_model.sma_nu[2]", "low": 4, "high": 6,
"num_values": 5, "spacing": "Linear"}
p = ParameterScanDescription(**scan_data)
assert_roundtrip_identical(p)
def test_unitscalar(self):
a = UnitScalar(1., units="m")
assert_roundtrip_identical(a)
def test_unitscalar_custom_units(self):
a = UnitScalar(1., units=extinction_coefficient_unit)
assert_roundtrip_identical(a)
a = UnitScalar(1., units=absorption_unit)
assert_roundtrip_identical(a)
def test_uuid(self):
val = uuid4()
assert_roundtrip_identical(val)
def test_array(self):
arr = np.array([1, 2, 3, 4])
assert_roundtrip_identical(arr)
def test_int(self):
val = 23746523
assert_roundtrip_identical(val)
def test_study(self):
object_to_save = self.study
assert_roundtrip_identical(object_to_save, ignore=self.ignore)
def test_str(self):
val = "this is a random string to store"
assert_roundtrip_identical(val)
def test_binding_parameters(self):
object_to_save = self.sim.binding_model.sma_nu
assert_roundtrip_identical(object_to_save)
def test_binding_model_langmuir_ph(self):
object_to_save = make_sample_langmuir_binding_model(ph_dependence=True)
assert_roundtrip_identical(object_to_save)
def test_binding_model_langmuir(self):
object_to_save = make_sample_langmuir_binding_model()
assert_roundtrip_identical(object_to_save)
def test_simulation(self):
assert_roundtrip_identical(self.sim)
