def test_validate_data_set():
valid_property = Density(
ThermodynamicState(298 * unit.kelvin, 1 * unit.atmosphere),
PropertyPhase.Liquid,
Substance.from_components("O"),
0.0 * unit.gram / unit.milliliter,
0.0 * unit.gram / unit.milliliter,
)
data_set = PhysicalPropertyDataSet()
data_set.add_properties(valid_property)
data_set.validate()
invalid_property = Density(
ThermodynamicState(-1 * unit.kelvin, 1 * unit.atmosphere),
PropertyPhase.Liquid,
Substance.from_components("O"),
0.0 * unit.gram / unit.milliliter,
0.0 * unit.gram / unit.milliliter,
)
with pytest.raises(AssertionError):
data_set.add_properties(invalid_property)
data_set.add_properties(invalid_property, validate=False)
with pytest.raises(AssertionError):
data_set.validate()
def test_generate_request_options(self):
training_set = create_data_set("data-set-1", 1)
target = create_evaluator_target("evaluator-target-1",
[training_set.id])
target.allow_direct_simulation = True
target.allow_reweighting = True
target.n_molecules = 512
target.n_effective_samples = 10
request_options = OptimizationInputFactory._generate_request_options(
target, training_set.to_evaluator())
assert request_options.calculation_layers == [
"ReweightingLayer",
"SimulationLayer",
]
assert request_options.calculation_schemas != UNDEFINED
expected_simulation_schema = Density.default_simulation_schema(
n_molecules=512)
expected_reweighting_schema = Density.default_reweighting_schema(
n_effective_samples=10)
assert (
request_options.calculation_schemas["Density"]
["SimulationLayer"].json() == expected_simulation_schema.json())
assert (
request_options.calculation_schemas["Density"]
["ReweightingLayer"].json() == expected_reweighting_schema.json())
def _build_entry(*smiles: str) -> Density:
"""Builds a density data entry measured at ambient conditions
and for a system containing the specified smiles patterns in
equal amounts.
Parameters
----------
smiles
The smiles to build components for.
Returns
-------
The built components.
"""
assert len(smiles) > 0
return Density(
thermodynamic_state=ThermodynamicState(
temperature=298.15 * unit.kelvin,
pressure=101.325 * unit.kilopascal,
),
phase=PropertyPhase.Liquid,
value=1.0 * Density.default_unit(),
uncertainty=1.0 * Density.default_unit(),
source=MeasurementSource(doi=" "),
substance=Substance.from_components(*smiles),
)
def estimated_reference_sets():
estimated_density = Density(
thermodynamic_state=ThermodynamicState(298.15 * unit.kelvin,
pressure=1.0 * unit.atmosphere),
phase=PropertyPhase.Liquid,
substance=Substance.from_components("O", "CC=O"),
value=1.0 * unit.kilogram / unit.meter**3,
uncertainty=0.1 * unit.kilogram / unit.meter**3,
)
estimated_density.id = "1"
estimated_enthalpy = EnthalpyOfMixing(
thermodynamic_state=ThermodynamicState(298.15 * unit.kelvin,
pressure=1.0 * unit.atmosphere),
phase=PropertyPhase.Liquid,
substance=Substance.from_components("O", "CC=O"),
value=1.0 * unit.kilocalorie / unit.mole,
uncertainty=0.1 * unit.kilojoule / unit.mole,
)
estimated_enthalpy.id = "2"
estimated_data_set = PhysicalPropertyDataSet()
estimated_data_set.add_properties(estimated_density, estimated_enthalpy)
reference_density = DataSetEntry(
id=1,
property_type="Density",
temperature=298.15,
pressure=101.325,
value=0.001,
std_error=0.0001,
doi=" ",
components=[
Component(smiles="O", mole_fraction=0.5),
Component(smiles="CC=O", mole_fraction=0.5),
],
)
reference_enthalpy = DataSetEntry(
id=2,
property_type="EnthalpyOfMixing",
temperature=298.15,
pressure=101.325,
value=4.184,
std_error=0.1,
doi=" ",
components=[
Component(smiles="O", mole_fraction=0.5),
Component(smiles="CC=O", mole_fraction=0.5),
],
)
reference_data_set = DataSet(
id="ref",
description=" ",
authors=[Author(name=" ", email="*****@*****.**", institute=" ")],
entries=[reference_density, reference_enthalpy],
)
return estimated_data_set, reference_data_set
def test_physical_property_state_methods():
dummy_property = create_dummy_property(Density)
property_state = dummy_property.__getstate__()
recreated_property = Density()
recreated_property.__setstate__(property_state)
recreated_state = recreated_property.__getstate__()
original_json = json.dumps(property_state, cls=TypedJSONEncoder)
recreated_json = json.dumps(recreated_state, cls=TypedJSONEncoder)
assert original_json == recreated_json
def create_filterable_data_set():
"""Creates a dummy data with a diverse set of properties to
be filtered, namely:
- a liquid density measured at 298 K and 0.5 atm with 1 component containing only carbon.
- a gaseous dielectric measured at 288 K and 1 atm with 2 components containing only nitrogen.
- a solid EoM measured at 308 K and 1.5 atm with 3 components containing only oxygen.
Returns
-------
PhysicalPropertyDataSet
The created data set.
"""
source = CalculationSource("Dummy", {})
carbon_substance = create_dummy_substance(number_of_components=1,
elements=["C"])
density_property = Density(
thermodynamic_state=ThermodynamicState(temperature=298 * unit.kelvin,
pressure=0.5 * unit.atmosphere),
phase=PropertyPhase.Liquid,
substance=carbon_substance,
value=1 * unit.gram / unit.milliliter,
uncertainty=0.11 * unit.gram / unit.milliliter,
source=source,
)
nitrogen_substance = create_dummy_substance(number_of_components=2,
elements=["N"])
dielectric_property = DielectricConstant(
thermodynamic_state=ThermodynamicState(temperature=288 * unit.kelvin,
pressure=1 * unit.atmosphere),
phase=PropertyPhase.Gas,
substance=nitrogen_substance,
value=1 * unit.dimensionless,
uncertainty=0.11 * unit.dimensionless,
source=source,
)
oxygen_substance = create_dummy_substance(number_of_components=3,
elements=["O"])
enthalpy_property = EnthalpyOfMixing(
thermodynamic_state=ThermodynamicState(temperature=308 * unit.kelvin,
pressure=1.5 * unit.atmosphere),
phase=PropertyPhase.Solid,
substance=oxygen_substance,
value=1 * unit.kilojoules / unit.mole,
uncertainty=0.11 * unit.kilojoules / unit.mole,
source=source,
)
data_set = PhysicalPropertyDataSet()
data_set.add_properties(density_property, dielectric_property,
enthalpy_property)
return data_set
def test_same_component_batching():
thermodynamic_state = ThermodynamicState(temperature=1.0 * unit.kelvin,
pressure=1.0 * unit.atmosphere)
data_set = PhysicalPropertyDataSet()
data_set.add_properties(
Density(
thermodynamic_state=thermodynamic_state,
substance=Substance.from_components("O", "C"),
value=0.0 * unit.kilogram / unit.meter**3,
),
EnthalpyOfVaporization(
thermodynamic_state=thermodynamic_state,
substance=Substance.from_components("O", "C"),
value=0.0 * unit.kilojoule / unit.mole,
),
Density(
thermodynamic_state=thermodynamic_state,
substance=Substance.from_components("O", "CO"),
value=0.0 * unit.kilogram / unit.meter**3,
),
EnthalpyOfVaporization(
thermodynamic_state=thermodynamic_state,
substance=Substance.from_components("O", "CO"),
value=0.0 * unit.kilojoule / unit.mole,
),
)
options = RequestOptions()
submission = EvaluatorClient._Submission()
submission.dataset = data_set
submission.options = options
with DaskLocalCluster() as calculation_backend:
server = EvaluatorServer(calculation_backend)
batches = server._batch_by_same_component(submission, "")
assert len(batches) == 2
assert len(batches[0].queued_properties) == 2
assert len(batches[1].queued_properties) == 2
def test_from_pandas():
"""A test to ensure that data sets may be created from pandas objects."""
thermodynamic_state = ThermodynamicState(temperature=298.15 * unit.kelvin,
pressure=1.0 * unit.atmosphere)
original_data_set = PhysicalPropertyDataSet()
original_data_set.add_properties(
Density(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
substance=Substance.from_components("CO", "O"),
value=1.0 * unit.kilogram / unit.meter**3,
uncertainty=1.0 * unit.kilogram / unit.meter**3,
source=MeasurementSource(doi="10.5281/zenodo.596537"),
),
EnthalpyOfVaporization(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.from_string("Liquid + Gas"),
substance=Substance.from_components("C"),
value=2.0 * unit.kilojoule / unit.mole,
source=MeasurementSource(reference="2"),
),
DielectricConstant(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
substance=Substance.from_components("C"),
value=3.0 * unit.dimensionless,
source=MeasurementSource(reference="3"),
),
)
data_frame = original_data_set.to_pandas()
recreated_data_set = PhysicalPropertyDataSet.from_pandas(data_frame)
assert len(original_data_set) == len(recreated_data_set)
for original_property in original_data_set:
recreated_property = next(x for x in recreated_data_set
if x.id == original_property.id)
assert (original_property.thermodynamic_state ==
recreated_property.thermodynamic_state)
assert original_property.phase == recreated_property.phase
assert original_property.substance == recreated_property.substance
assert numpy.isclose(original_property.value, recreated_property.value)
if original_property.uncertainty == UNDEFINED:
assert original_property.uncertainty == recreated_property.uncertainty
else:
assert numpy.isclose(original_property.uncertainty,
recreated_property.uncertainty)
assert original_property.source.doi == recreated_property.source.doi
assert original_property.source.reference == recreated_property.source.reference
def test_filter_ionic_liquid():
thermodynamic_state = ThermodynamicState(
temperature=298.15 * unit.kelvin,
pressure=101.325 * unit.kilopascal,
)
# Ensure ionic liquids are filtered.
data_set = PhysicalPropertyDataSet()
data_set.add_properties(
Density(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
value=1.0 * Density.default_unit(),
uncertainty=1.0 * Density.default_unit(),
source=MeasurementSource(doi=" "),
substance=Substance.from_components("[Na+].[Cl-]"),
),
Density(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
value=1.0 * Density.default_unit(),
uncertainty=1.0 * Density.default_unit(),
source=MeasurementSource(doi=" "),
substance=Substance.from_components("C"),
),
)
data_frame = data_set.to_pandas()
filtered_frame = FilterByIonicLiquid.apply(
data_frame,
FilterByIonicLiquidSchema(),
)
assert len(filtered_frame) == 1
def simple_evaluator_data_set():
"""Create a simple evaluator `PhysicalPropertyDataSet` which contains
a simple binary density measurement.
Returns
-------
PhysicalPropertyDataSet
"""
evaluator_density = Density(
thermodynamic_state=ThermodynamicState(298.15 * unit.kelvin,
pressure=1.0 * unit.atmosphere),
phase=PropertyPhase.Liquid,
substance=Substance.from_components("O", "CC=O"),
value=1.0 * unit.kilogram / unit.meter**3,
uncertainty=0.1 * unit.kilogram / unit.meter**3,
source=MeasurementSource(doi="10.1000/xyz123"),
)
evaluator_density.id = "1"
evaluator_data_set = PhysicalPropertyDataSet()
evaluator_data_set.add_properties(evaluator_density)
return evaluator_data_set
def data_frame() -> pandas.DataFrame:
data_set = PhysicalPropertyDataSet()
data_set.add_properties(
Density(
thermodynamic_state=ThermodynamicState(
temperature=298.15 * unit.kelvin,
pressure=101.325 * unit.kilopascal,
),
phase=PropertyPhase.Liquid,
value=1.0 * Density.default_unit(),
uncertainty=1.0 * Density.default_unit(),
source=MeasurementSource(doi=" "),
substance=Substance.from_components("C"),
),
Density(
thermodynamic_state=ThermodynamicState(
temperature=305.15 * unit.kelvin,
pressure=101.325 * unit.kilopascal,
),
phase=PropertyPhase.Liquid,
value=1.0 * Density.default_unit(),
uncertainty=1.0 * Density.default_unit(),
source=MeasurementSource(doi=" "),
substance=Substance.from_components("C"),
),
Density(
thermodynamic_state=ThermodynamicState(
temperature=298.15 * unit.kelvin,
pressure=105.325 * unit.kilopascal,
),
phase=PropertyPhase.Liquid,
value=1.0 * Density.default_unit(),
uncertainty=1.0 * Density.default_unit(),
source=MeasurementSource(doi=" "),
substance=Substance.from_components("C"),
),
)
return data_set.to_pandas()
def define_data_set(reweighting: bool) -> PhysicalPropertyDataSet:
# Define a common state to compute estimates at
states = [
ThermodynamicState(temperature=296.15 * unit.kelvin,
pressure=1.0 * unit.atmosphere),
ThermodynamicState(temperature=298.15 * unit.kelvin,
pressure=1.0 * unit.atmosphere),
ThermodynamicState(temperature=300.15 * unit.kelvin,
pressure=1.0 * unit.atmosphere),
]
data_set = PhysicalPropertyDataSet()
# Solvation free energies.
if not reweighting:
ethanol_substance = Substance.from_components("CCO")
ethanol_substance.add_component(
Component("CC=O", Component.Role.Solute), ExactAmount(1))
ethanal_substance = Substance.from_components("CC=O")
ethanal_substance.add_component(
Component("CCO", Component.Role.Solute), ExactAmount(1))
data_set.add_properties(
SolvationFreeEnergy(
thermodynamic_state=states[1],
phase=PropertyPhase.Liquid,
substance=ethanol_substance,
value=0.0 * SolvationFreeEnergy.default_unit(),
),
SolvationFreeEnergy(
thermodynamic_state=states[1],
phase=PropertyPhase.Liquid,
substance=ethanal_substance,
value=0.0 * SolvationFreeEnergy.default_unit(),
),
*CurationWorkflow.apply(
PhysicalPropertyDataSet(),
CurationWorkflowSchema(component_schemas=[
ImportFreeSolvSchema(),
FilterBySubstancesSchema(substances_to_include=[("O",
"CO")]),
]),
),
)
for state in states:
# Excess properties.
data_set.add_properties(
ExcessMolarVolume(
thermodynamic_state=state,
phase=PropertyPhase.Liquid,
substance=Substance.from_components("CC=O", "CCO"),
value=0.0 * ExcessMolarVolume.default_unit(),
),
EnthalpyOfMixing(
thermodynamic_state=state,
phase=PropertyPhase.Liquid,
substance=Substance.from_components("CC=O", "CCO"),
value=0.0 * EnthalpyOfMixing.default_unit(),
),
)
# Pure properties
data_set.add_properties(
Density(
thermodynamic_state=state,
phase=PropertyPhase.Liquid,
substance=Substance.from_components("CCO"),
value=0.0 * Density.default_unit(),
),
EnthalpyOfVaporization(
thermodynamic_state=state,
phase=PropertyPhase(PropertyPhase.Liquid | PropertyPhase.Gas),
substance=Substance.from_components("CCO"),
value=0.0 * EnthalpyOfVaporization.default_unit(),
),
DielectricConstant(
thermodynamic_state=state,
phase=PropertyPhase.Liquid,
substance=Substance.from_components("CCO"),
value=0.0 * DielectricConstant.default_unit(),
),
)
return data_set
def test_analysed_result_from_evaluator():
"""Tests the `AnalysedResult.from_evaluator` function."""
expected_mean = 0.0
expected_std = numpy.random.rand() + 1.0
values = numpy.random.normal(expected_mean, expected_std, 1000)
estimated_properties = []
reference_entries = []
for index, value in enumerate(values):
property_id = index + 1
estimated_density = Density(
thermodynamic_state=ThermodynamicState(298.15 * unit.kelvin,
pressure=1.0 *
unit.atmosphere),
phase=PropertyPhase.Liquid,
substance=Substance.from_components("O"),
value=value * Density.default_unit(),
uncertainty=0.0 * Density.default_unit(),
)
estimated_density.id = str(property_id)
estimated_properties.append(estimated_density)
reference_density = DataSetEntry(
id=property_id,
property_type="Density",
temperature=298.15,
pressure=101.325,
value=expected_mean,
std_error=None,
doi=" ",
components=[Component(smiles="O", mole_fraction=1.0)],
)
reference_entries.append(reference_density)
estimated_data_set = PhysicalPropertyDataSet()
estimated_data_set.add_properties(*estimated_properties)
reference_data_set = DataSet(
id="ref",
description=" ",
authors=[Author(name=" ", email="*****@*****.**", institute=" ")],
entries=reference_entries,
)
analysis_environments = [ChemicalEnvironment.Aqueous]
analysed_results = DataSetResult.from_evaluator(
reference_data_set=reference_data_set,
estimated_data_set=estimated_data_set,
analysis_environments=analysis_environments,
statistic_types=[StatisticType.RMSE],
bootstrap_iterations=1000,
)
assert len(analysed_results.result_entries) == len(estimated_properties)
full_statistics = next(
iter(x for x in analysed_results.statistic_entries
if x.category is None))
assert full_statistics.property_type == "Density"
assert full_statistics.n_components == 1
assert full_statistics.statistic_type == StatisticType.RMSE
assert numpy.isclose(full_statistics.value, expected_std, rtol=0.10)
def test_storage_retrieval():
# Create some dummy properties
methane = Substance.from_components("C")
methanol = Substance.from_components("CO")
mixture = Substance.from_components("C", "CO")
# Add extra unused data to make sure the wrong data isn't
# Being retrieved.
unused_pure = Substance.from_components("CCO")
unused_mixture = Substance.from_components("CCO", "CO")
data_to_store = [
(methane, PropertyPhase.Liquid, 1000),
(methanol, PropertyPhase.Liquid, 1000),
(methanol, PropertyPhase.Gas, 1),
(mixture, PropertyPhase.Liquid, 1000),
(unused_pure, PropertyPhase.Liquid, 1000),
(unused_mixture, PropertyPhase.Liquid, 1000),
]
storage_keys = {}
state = ThermodynamicState(temperature=1.0 * unit.kelvin)
properties = [
# Properties with a full system query.
Density(
value=1.0 * unit.gram / unit.litre,
substance=methanol,
thermodynamic_state=state,
),
DielectricConstant(
value=1.0 * unit.dimensionless, substance=methane, thermodynamic_state=state
),
# Properties with a multi-component query.
EnthalpyOfVaporization(
value=1.0 * unit.joule / unit.mole,
substance=methanol,
thermodynamic_state=state,
),
# Property with a multi-phase query.
EnthalpyOfMixing(
value=1.0 * unit.joule / unit.mole,
substance=mixture,
thermodynamic_state=state,
),
ExcessMolarVolume(
value=1.0 * unit.meter ** 3, substance=mixture, thermodynamic_state=state
),
]
expected_data_per_property = {
Density: {"full_system_data": [(methanol, PropertyPhase.Liquid, 1000)]},
DielectricConstant: {
"full_system_data": [(methane, PropertyPhase.Liquid, 1000)]
},
EnthalpyOfVaporization: {
"liquid_data": [(methanol, PropertyPhase.Liquid, 1000)],
"gas_data": [(methanol, PropertyPhase.Gas, 1)],
},
EnthalpyOfMixing: {
"full_system_data": [(mixture, PropertyPhase.Liquid, 1000)],
"component_data": [
[(methane, PropertyPhase.Liquid, 1000)],
[(methanol, PropertyPhase.Liquid, 1000)],
],
},
ExcessMolarVolume: {
"full_system_data": [(mixture, PropertyPhase.Liquid, 1000)],
"component_data": [
[(methane, PropertyPhase.Liquid, 1000)],
[(methanol, PropertyPhase.Liquid, 1000)],
],
},
}
force_field = SmirnoffForceFieldSource.from_path("smirnoff99Frosst-1.1.0.offxml")
with tempfile.TemporaryDirectory() as base_directory:
# Create a storage backend with some dummy data.
backend_directory = os.path.join(base_directory, "storage_dir")
storage_backend = LocalFileStorage(backend_directory)
force_field_id = storage_backend.store_force_field(force_field)
for substance, phase, n_mol in data_to_store:
data_directory = os.path.join(base_directory, substance.identifier)
data = create_dummy_simulation_data(
data_directory,
substance=substance,
force_field_id=force_field_id,
phase=phase,
number_of_molecules=n_mol,
)
storage_key = storage_backend.store_object(data, data_directory)
storage_keys[(substance, phase, n_mol)] = storage_key
for physical_property in properties:
schema = registered_calculation_schemas["ReweightingLayer"][
physical_property.__class__.__name__
]
if callable(schema):
schema = schema()
# noinspection PyProtectedMember
metadata = ReweightingLayer._get_workflow_metadata(
base_directory,
physical_property,
"",
[],
storage_backend,
schema,
)
assert metadata is not None
expected_data_list = expected_data_per_property[physical_property.__class__]
for data_key in expected_data_list:
assert data_key in metadata
stored_metadata = metadata[data_key]
expected_metadata = expected_data_list[data_key]
assert len(stored_metadata) == len(expected_metadata)
if isinstance(stored_metadata[0], list):
# Flatten any lists of lists.
stored_metadata = [
item for sublist in stored_metadata for item in sublist
]
expected_metadata = [
item for sublist in expected_metadata for item in sublist
]
metadata_storage_keys = [
os.path.basename(x) for x, _, _ in stored_metadata
]
expected_storage_keys = [storage_keys[x] for x in expected_metadata]
assert sorted(metadata_storage_keys) == sorted(expected_storage_keys)
def complete_evaluator_data_set():
"""Create a more comprehensive `PhysicalPropertyDataSet` which contains one
measurement for each of:
* pure density
* binary density
* pure enthalpy of vaporization
* binary enthalpy of mixing
* binary excess molar volume
* hydration free energy
Returns
-------
PhysicalPropertyDataSet
"""
thermodynamic_state = ThermodynamicState(298.15 * unit.kelvin,
pressure=1.0 * unit.atmosphere)
source = MeasurementSource(doi="10.1000/xyz123")
solvation_substance = Substance()
solvation_substance.add_component(Component("O"), MoleFraction(1.0))
solvation_substance.add_component(Component("CCCO"), ExactAmount(1))
evaluator_properties = [
Density(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
substance=Substance.from_components("O"),
value=1.0 * unit.kilogram / unit.meter**3,
uncertainty=0.1 * unit.kilogram / unit.meter**3,
source=source,
),
Density(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
substance=Substance.from_components("O", "CC=O"),
value=1.0 * unit.kilogram / unit.meter**3,
uncertainty=0.1 * unit.kilogram / unit.meter**3,
source=source,
),
EnthalpyOfVaporization(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase(PropertyPhase.Liquid | PropertyPhase.Gas),
substance=Substance.from_components("CCO"),
value=1.0 * EnthalpyOfVaporization.default_unit(),
uncertainty=0.1 * EnthalpyOfVaporization.default_unit(),
source=source,
),
EnthalpyOfMixing(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
substance=Substance.from_components("CCCCO", "CC(C=O)C"),
value=1.0 * EnthalpyOfMixing.default_unit(),
uncertainty=0.1 * EnthalpyOfMixing.default_unit(),
source=source,
),
ExcessMolarVolume(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
substance=Substance.from_components("C(=O)CCCO", "CCCCCC"),
value=1.0 * ExcessMolarVolume.default_unit(),
uncertainty=0.1 * ExcessMolarVolume.default_unit(),
source=source,
),
SolvationFreeEnergy(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
substance=solvation_substance,
value=1.0 * SolvationFreeEnergy.default_unit(),
uncertainty=0.1 * SolvationFreeEnergy.default_unit(),
source=source,
),
]
for index, evaluator_property in enumerate(evaluator_properties):
evaluator_property.id = str(index + 1)
evaluator_data_set = PhysicalPropertyDataSet()
evaluator_data_set.add_properties(*evaluator_properties)
return evaluator_data_set
def test_reindex_data_set():
"""Tests that the ``reindex_data_set`` function behaves as expected."""
setup_timestamp_logging(logging.INFO)
evaluator_data_set = PhysicalPropertyDataSet()
evaluator_data_set.add_properties(
Density(
thermodynamic_state=ThermodynamicState(
temperature=298.15 * unit.kelvin,
pressure=1.0 * unit.atmosphere),
phase=PropertyPhase.Liquid,
substance=substances.Substance.from_components("O"),
value=1.0 * Density.default_unit(),
uncertainty=1.0 * Density.default_unit(),
),
Density(
thermodynamic_state=ThermodynamicState(
temperature=298.15 * unit.kelvin,
pressure=1.0 * unit.atmosphere),
phase=PropertyPhase.Liquid,
substance=substances.Substance.from_components("C", "O"),
value=1.0 * Density.default_unit(),
uncertainty=1.0 * Density.default_unit(),
),
Density(
thermodynamic_state=ThermodynamicState(
temperature=300.0 * unit.kelvin,
pressure=1.0 * unit.atmosphere),
phase=PropertyPhase.Liquid,
substance=substances.Substance.from_components("C", "O"),
value=1.0 * Density.default_unit(),
uncertainty=1.0 * Density.default_unit(),
),
)
data_set = DataSet(
id="data-set",
description=" ",
authors=[Author(name=" ", email="*****@*****.**", institute=" ")],
entries=[
DataSetEntry(
id=1,
property_type="Density",
temperature=298.15,
pressure=101.325,
value=1.0,
std_error=1.0,
doi=" ",
components=[
Component(smiles="O", mole_fraction=0.5),
Component(smiles="C", mole_fraction=0.5),
],
),
DataSetEntry(
id=2,
property_type="Density",
temperature=298.15,
pressure=101.325,
value=1.0,
std_error=1.0,
doi=" ",
components=[Component(smiles="O", mole_fraction=1.0)],
),
],
)
un_indexed_id = evaluator_data_set.properties[2].id
reindex_data_set(evaluator_data_set, data_set)
assert evaluator_data_set.properties[0].id == "2"
assert evaluator_data_set.properties[1].id == "1"
assert evaluator_data_set.properties[2].id == un_indexed_id
data_set_collection = DataSetCollection(data_sets=[
DataSet(
id="0",
description=" ",
authors=[Author(name=" ", email="*****@*****.**", institute=" ")],
entries=[
DataSetEntry(
id=3,
property_type="Density",
temperature=298.15,
pressure=101.325,
value=1.0,
std_error=1.0,
doi=" ",
components=[
Component(smiles="O", mole_fraction=0.5),
Component(smiles="C", mole_fraction=0.5),
],
)
],
),
DataSet(
id="1",
description=" ",
authors=[Author(name=" ", email="*****@*****.**", institute=" ")],
entries=[
DataSetEntry(
id=4,
property_type="Density",
temperature=298.15,
pressure=101.325,
value=1.0,
std_error=1.0,
doi=" ",
components=[Component(smiles="O", mole_fraction=1.0)],
)
],
),
])
reindex_data_set(evaluator_data_set, data_set_collection)
assert evaluator_data_set.properties[0].id == "4"
assert evaluator_data_set.properties[1].id == "3"
assert evaluator_data_set.properties[2].id == un_indexed_id
def test_to_pandas():
"""A test to ensure that data sets are convertable to pandas objects."""
source = CalculationSource("Dummy", {})
pure_substance = Substance.from_components("C")
binary_substance = Substance.from_components("C", "O")
data_set = PhysicalPropertyDataSet()
for temperature in [
298 * unit.kelvin, 300 * unit.kelvin, 302 * unit.kelvin
]:
thermodynamic_state = ThermodynamicState(temperature=temperature,
pressure=1.0 *
unit.atmosphere)
density_property = Density(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
substance=pure_substance,
value=1 * unit.gram / unit.milliliter,
uncertainty=0.11 * unit.gram / unit.milliliter,
source=source,
)
dielectric_property = DielectricConstant(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
substance=pure_substance,
value=1 * unit.dimensionless,
uncertainty=0.11 * unit.dimensionless,
source=source,
)
data_set.add_properties(density_property)
data_set.add_properties(dielectric_property)
for temperature in [
298 * unit.kelvin, 300 * unit.kelvin, 302 * unit.kelvin
]:
thermodynamic_state = ThermodynamicState(temperature=temperature,
pressure=1.0 *
unit.atmosphere)
enthalpy_property = EnthalpyOfMixing(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
substance=binary_substance,
value=1 * unit.kilojoules / unit.mole,
uncertainty=0.11 * unit.kilojoules / unit.mole,
source=source,
)
excess_property = ExcessMolarVolume(
thermodynamic_state=thermodynamic_state,
phase=PropertyPhase.Liquid,
substance=binary_substance,
value=1 * unit.meter**3 / unit.mole,
uncertainty=0.11 * unit.meter**3 / unit.mole,
source=source,
)
data_set.add_properties(enthalpy_property)
data_set.add_properties(excess_property)
data_set_pandas = data_set.to_pandas()
required_columns = [
"Id",
"Temperature (K)",
"Pressure (kPa)",
"Phase",
"N Components",
"Source",
"Component 1",
"Role 1",
"Mole Fraction 1",
"Exact Amount 1",
"Component 2",
"Role 2",
"Mole Fraction 2",
"Exact Amount 2",
]
assert all(x in data_set_pandas for x in required_columns)
assert data_set_pandas is not None
assert data_set_pandas.shape == (12, 22)
data_set_without_na = data_set_pandas.dropna(axis=1, how="all")
assert data_set_without_na.shape == (12, 20)