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 create_dummy_substance(number_of_components, elements=None):
"""Creates a substance with a given number of components,
each containing the specified elements.
Parameters
----------
number_of_components : int
The number of components to add to the substance.
elements : list of str
The elements that each component should containt.
Returns
-------
Substance
The created substance.
"""
if elements is None:
elements = ["C"]
substance = Substance()
mole_fraction = 1.0 / number_of_components
for index in range(number_of_components):
smiles_pattern = "".join(elements * (index + 1))
substance.add_component(Component(smiles_pattern),
MoleFraction(mole_fraction))
return substance
def test_build_docked_coordinates_protocol():
"""Tests docking a methanol molecule into alpha-Cyclodextrin."""
if not has_openeye():
pytest.skip("The `BuildDockedCoordinates` protocol requires OpenEye.")
ligand_substance = Substance()
ligand_substance.add_component(
Component("CO", role=Component.Role.Ligand),
ExactAmount(1),
)
# TODO: This test could likely be made substantially faster
# by storing the binary prepared receptor. Would this
# be in breach of any oe license terms?
with tempfile.TemporaryDirectory() as temporary_directory:
build_docked_coordinates = BuildDockedCoordinates("build_methanol")
build_docked_coordinates.ligand_substance = ligand_substance
build_docked_coordinates.number_of_ligand_conformers = 5
build_docked_coordinates.receptor_coordinate_file = get_data_filename(
"test/molecules/acd.mol2")
build_docked_coordinates.execute(temporary_directory,
ComputeResources())
docked_pdb = PDBFile(
build_docked_coordinates.docked_complex_coordinate_path)
assert docked_pdb.topology.getNumResidues() == 2
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 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_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 data_frame() -> pandas.DataFrame:
temperatures = [298.15, 318.15]
pressures = [101.325, 101.0]
properties = [Density, EnthalpyOfMixing]
mole_fractions = [(1.0, ), (1.0, ), (0.25, 0.75), (0.75, 0.25)]
smiles = {1: [("C(F)(Cl)(Br)", ), ("C", )], 2: [("CO", "C"), ("C", "CO")]}
loop_variables = [(
temperature,
pressure,
property_type,
mole_fraction,
) for temperature in temperatures for pressure in pressures
for property_type in properties
for mole_fraction in mole_fractions]
data_entries = []
for temperature, pressure, property_type, mole_fraction in loop_variables:
n_components = len(mole_fraction)
for smiles_tuple in smiles[n_components]:
substance = Substance()
for smiles_pattern, x in zip(smiles_tuple, mole_fraction):
substance.add_component(Component(smiles_pattern),
MoleFraction(x))
data_entries.append(
property_type(
thermodynamic_state=ThermodynamicState(
temperature=temperature * unit.kelvin,
pressure=pressure * unit.kilopascal,
),
phase=PropertyPhase.Liquid,
value=1.0 * property_type.default_unit(),
uncertainty=1.0 * property_type.default_unit(),
source=MeasurementSource(doi=" "),
substance=substance,
))
data_set = PhysicalPropertyDataSet()
data_set.add_properties(*data_entries)
return data_set.to_pandas()
def test_solvate_existing_structure_protocol():
"""Tests solvating a single methanol molecule in water."""
import mdtraj
methanol_component = Component("CO")
methanol_substance = Substance()
methanol_substance.add_component(methanol_component, ExactAmount(1))
water_substance = Substance()
water_substance.add_component(Component("O"), MoleFraction(1.0))
with tempfile.TemporaryDirectory() as temporary_directory:
build_methanol_coordinates = BuildCoordinatesPackmol("build_methanol")
build_methanol_coordinates.max_molecules = 1
build_methanol_coordinates.substance = methanol_substance
build_methanol_coordinates.execute(temporary_directory,
ComputeResources())
methanol_residue_name = build_methanol_coordinates.assigned_residue_names[
methanol_component.identifier]
solvate_coordinates = SolvateExistingStructure("solvate_methanol")
solvate_coordinates.max_molecules = 9
solvate_coordinates.substance = water_substance
solvate_coordinates.solute_coordinate_file = (
build_methanol_coordinates.coordinate_file_path)
solvate_coordinates.execute(temporary_directory, ComputeResources())
solvated_system = mdtraj.load_pdb(
solvate_coordinates.coordinate_file_path)
assert solvated_system.n_residues == 10
assert solvated_system.top.residue(0).name == methanol_residue_name
def _setup_dummy_system(directory):
"""Generate a temporary parameterized system object."""
force_field_path = path.join(directory, "ff.json")
with open(force_field_path, "w") as file:
file.write(build_tip3p_smirnoff_force_field().json())
substance = Substance.from_components("O")
build_coordinates = BuildCoordinatesPackmol("build_coordinates")
build_coordinates.max_molecules = 10
build_coordinates.mass_density = 0.05 * unit.grams / unit.milliliters
build_coordinates.substance = substance
build_coordinates.execute(directory)
assign_parameters = BuildSmirnoffSystem("assign_parameters")
assign_parameters.force_field_path = force_field_path
assign_parameters.coordinate_file_path = build_coordinates.coordinate_file_path
assign_parameters.substance = substance
assign_parameters.execute(directory)
return (
build_coordinates.coordinate_file_path,
assign_parameters.parameterized_system,
)
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 test_compute_dipole_moments(tmpdir):
coordinate_path = get_data_filename("test/trajectories/water.pdb")
trajectory_path = get_data_filename("test/trajectories/water.dcd")
# Build a system object for water
force_field_path = os.path.join(tmpdir, "ff.json")
with open(force_field_path, "w") as file:
file.write(build_tip3p_smirnoff_force_field().json())
assign_parameters = BuildSmirnoffSystem("")
assign_parameters.force_field_path = force_field_path
assign_parameters.coordinate_file_path = coordinate_path
assign_parameters.substance = Substance.from_components("O")
assign_parameters.execute(str(tmpdir))
# TODO - test gradients when TIP3P library charges added.
protocol = ComputeDipoleMoments("")
protocol.parameterized_system = assign_parameters.parameterized_system
protocol.trajectory_path = trajectory_path
protocol.execute(str(tmpdir))
assert len(protocol.dipole_moments) == 10
assert protocol.dipole_moments.value.shape[1] == 3
assert not np.allclose(protocol.dipole_moments.value,
0.0 * unit.elementary_charge * unit.nanometers)
def test_base_simulation_data_storage():
substance = Substance.from_components("C")
with tempfile.TemporaryDirectory() as base_directory:
data_directory = os.path.join(base_directory, "data_directory")
data_object = create_dummy_simulation_data(data_directory, substance)
backend_directory = os.path.join(base_directory, "storage_dir")
storage = LocalFileStorage(backend_directory)
storage_key = storage.store_object(data_object, data_directory)
# Regenerate the data directory.
os.makedirs(data_directory, exist_ok=True)
assert storage.has_object(data_object)
assert storage_key == storage.store_object(data_object, data_directory)
retrieved_object, retrieved_directory = storage.retrieve_object(
storage_key, StoredSimulationData)
assert backend_directory in retrieved_directory
assert data_object.json() == retrieved_object.json()
def test_compute_state_energy_gradients(tmpdir):
build_tip3p_smirnoff_force_field().json(os.path.join(tmpdir, "ff.json"))
_, parameterized_system = _setup_dummy_system(
tmpdir, Substance.from_components("O"), 10,
os.path.join(tmpdir, "ff.json"))
protocol = SolvationYankProtocol("")
protocol.thermodynamic_state = ThermodynamicState(298.15 * unit.kelvin,
1.0 * unit.atmosphere)
protocol.gradient_parameters = [
ParameterGradientKey("vdW", "[#1]-[#8X2H2+0:1]-[#1]", "epsilon")
]
gradients = protocol._compute_state_energy_gradients(
mdtraj.load_dcd(
get_data_filename("test/trajectories/water.dcd"),
get_data_filename("test/trajectories/water.pdb"),
),
parameterized_system.topology,
parameterized_system.force_field.to_force_field(),
True,
ComputeResources(),
)
assert len(gradients) == 1
assert not np.isclose(gradients[0].value, 0.0 * unit.dimensionless)
def data_frame() -> pandas.DataFrame:
temperatures = [303.15, 298.15]
property_types = [Density, EnthalpyOfVaporization]
data_set_entries = []
def _temperature_noise():
return (numpy.random.rand() / 2.0 + 0.51) / 10.0
for temperature in temperatures:
for index, property_type in enumerate(property_types):
noise = _temperature_noise()
noise *= 1 if index == 0 else -1
data_set_entries.append(
property_type(
thermodynamic_state=ThermodynamicState(
temperature=temperature * unit.kelvin,
pressure=101.325 * unit.kilopascal,
),
phase=PropertyPhase.Liquid,
value=1.0 * property_type.default_unit(),
uncertainty=1.0 * property_type.default_unit(),
source=MeasurementSource(doi=" "),
substance=Substance.from_components("C"),
), )
data_set_entries.append(
property_type(
thermodynamic_state=ThermodynamicState(
temperature=(temperature + noise) * unit.kelvin,
pressure=101.325 * unit.kilopascal,
),
phase=PropertyPhase.Liquid,
value=1.0 * property_type.default_unit(),
uncertainty=1.0 * property_type.default_unit(),
source=MeasurementSource(doi=" "),
substance=Substance.from_components("C"),
), )
data_set = PhysicalPropertyDataSet()
data_set.add_properties(*data_set_entries)
data_frame = data_set.to_pandas()
return data_frame
def test_weight_by_mole_fraction_protocol(component_smiles, value):
full_substance = Substance.from_components("C", "CC", "CCC")
component = Substance.from_components(component_smiles)
mole_fraction = next(
iter(full_substance.get_amounts(component.components[0].identifier))
).value
with tempfile.TemporaryDirectory() as temporary_directory:
weight_protocol = WeightByMoleFraction("weight")
weight_protocol.value = value
weight_protocol.full_substance = full_substance
weight_protocol.component = component
weight_protocol.execute(temporary_directory, ComputeResources())
assert weight_protocol.weighted_value == value * mole_fraction
def test_add_mole_fractions():
substance = Substance()
substance.add_component(Component("C"), MoleFraction(0.5))
substance.add_component(Component("C"), MoleFraction(0.5))
assert substance.number_of_components == 1
amounts = substance.get_amounts(substance.components[0])
assert len(amounts) == 1
amount = next(iter(amounts))
assert isinstance(amount, MoleFraction)
assert np.isclose(amount.value, 1.0)
def _execute(self, directory, available_resources):
filtered_components = []
total_mole_fraction = 0.0
for component in self.input_substance.components:
if component.role not in self.component_roles:
continue
filtered_components.append(component)
amounts = self.input_substance.get_amounts(component)
for amount in amounts:
if not isinstance(amount, MoleFraction):
continue
total_mole_fraction += amount.value
if self.expected_components != UNDEFINED and self.expected_components != len(
filtered_components
):
raise ValueError(
f"The filtered substance does not contain the expected number of "
f"components ({self.expected_components}) - {filtered_components}",
)
inverse_mole_fraction = (
1.0 if np.isclose(total_mole_fraction, 0.0) else 1.0 / total_mole_fraction
)
self.filtered_substance = Substance()
for component in filtered_components:
amounts = self.input_substance.get_amounts(component)
for amount in amounts:
if isinstance(amount, MoleFraction):
amount = MoleFraction(amount.value * inverse_mole_fraction)
self.filtered_substance.add_component(component, amount)
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 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 test_base_simulation_data_query():
substance_a = Substance.from_components("C")
substance_b = Substance.from_components("CO")
substance_full = Substance.from_components("C", "CO")
substances = [substance_a, substance_b, substance_full]
with tempfile.TemporaryDirectory() as base_directory:
backend_directory = os.path.join(base_directory, "storage_dir")
storage = LocalFileStorage(backend_directory)
for substance in substances:
data_directory = os.path.join(base_directory,
f"{substance.identifier}")
data_object = create_dummy_simulation_data(data_directory,
substance)
storage.store_object(data_object, data_directory)
for substance in substances:
substance_query = SimulationDataQuery()
substance_query.substance = substance
results = storage.query(substance_query)
assert results is not None and len(results) == 1
assert len(next(iter(results.values()))[0]) == 3
component_query = SimulationDataQuery()
component_query.substance = substance_full
component_query.substance_query = SubstanceQuery()
component_query.substance_query.components_only = True
results = storage.query(component_query)
assert results is not None and len(results) == 2
def create_substance():
test_substance = Substance()
test_substance.add_component(
Component("C", role=Component.Role.Solute),
ExactAmount(1),
)
test_substance.add_component(
Component("CC", role=Component.Role.Ligand),
ExactAmount(1),
)
test_substance.add_component(
Component("CCC", role=Component.Role.Receptor),
ExactAmount(1),
)
test_substance.add_component(
Component("O", role=Component.Role.Solvent),
MoleFraction(1.0),
)
return test_substance
def dummy_complex() -> Substance:
substance = Substance()
substance.add_component(
Component(smiles="C", role=Component.Role.Ligand), ExactAmount(1)
)
substance.add_component(
Component(smiles="CO", role=Component.Role.Receptor), ExactAmount(1)
)
return substance
def test_calculate_reduced_potential_openmm():
substance = Substance.from_components("O")
thermodynamic_state = ThermodynamicState(298 * unit.kelvin,
1.0 * unit.atmosphere)
with tempfile.TemporaryDirectory() as directory:
force_field_path = path.join(directory, "ff.json")
with open(force_field_path, "w") as file:
file.write(build_tip3p_smirnoff_force_field().json())
build_coordinates = BuildCoordinatesPackmol("build_coordinates")
build_coordinates.max_molecules = 10
build_coordinates.mass_density = 0.05 * unit.grams / unit.milliliters
build_coordinates.substance = substance
build_coordinates.execute(directory, None)
assign_parameters = BuildSmirnoffSystem("assign_parameters")
assign_parameters.force_field_path = force_field_path
assign_parameters.coordinate_file_path = build_coordinates.coordinate_file_path
assign_parameters.substance = substance
assign_parameters.execute(directory, None)
reduced_potentials = OpenMMReducedPotentials("reduced_potentials")
reduced_potentials.substance = substance
reduced_potentials.thermodynamic_state = thermodynamic_state
reduced_potentials.reference_force_field_paths = [force_field_path]
reduced_potentials.system_path = assign_parameters.system_path
reduced_potentials.trajectory_file_path = get_data_filename(
"test/trajectories/water.dcd")
reduced_potentials.coordinate_file_path = get_data_filename(
"test/trajectories/water.pdb")
reduced_potentials.kinetic_energies_path = get_data_filename(
"test/statistics/stats_pandas.csv")
reduced_potentials.high_precision = False
reduced_potentials.execute(directory, ComputeResources())
assert path.isfile(reduced_potentials.statistics_file_path)
final_array = StatisticsArray.from_pandas_csv(
reduced_potentials.statistics_file_path)
assert ObservableType.ReducedPotential in final_array
def test_evaluate_energies_openmm():
substance = Substance.from_components("O")
thermodynamic_state = ThermodynamicState(298 * unit.kelvin,
1.0 * unit.atmosphere)
with tempfile.TemporaryDirectory() as directory:
coordinate_path, parameterized_system = _setup_dummy_system(directory)
reduced_potentials = OpenMMEvaluateEnergies("")
reduced_potentials.substance = substance
reduced_potentials.thermodynamic_state = thermodynamic_state
reduced_potentials.parameterized_system = parameterized_system
reduced_potentials.trajectory_file_path = get_data_filename(
"test/trajectories/water.dcd")
reduced_potentials.execute(directory, ComputeResources())
assert ObservableType.ReducedPotential in reduced_potentials.output_observables
assert ObservableType.PotentialEnergy in reduced_potentials.output_observables
def test_build_tleap_system():
with tempfile.TemporaryDirectory() as directory:
force_field_path = path.join(directory, "ff.json")
with open(force_field_path, "w") as file:
file.write(TLeapForceFieldSource().json())
substance = Substance.from_components("CCCCCCCC", "O", "C(=O)N")
build_coordinates = BuildCoordinatesPackmol("build_coordinates")
build_coordinates.max_molecules = 9
build_coordinates.substance = substance
build_coordinates.execute(directory, None)
assign_parameters = BuildTLeapSystem("assign_parameters")
assign_parameters.force_field_path = force_field_path
assign_parameters.coordinate_file_path = build_coordinates.coordinate_file_path
assign_parameters.substance = substance
assign_parameters.execute(directory, None)
assert path.isfile(assign_parameters.system_path)
def test_build_smirnoff_system():
with tempfile.TemporaryDirectory() as directory:
force_field_path = path.join(directory, "ff.json")
with open(force_field_path, "w") as file:
file.write(build_tip3p_smirnoff_force_field().json())
substance = Substance.from_components("C", "O", "CO", "C(=O)N")
build_coordinates = BuildCoordinatesPackmol("build_coordinates")
build_coordinates.max_molecules = 8
build_coordinates.substance = substance
build_coordinates.execute(directory)
assign_parameters = BuildSmirnoffSystem("assign_parameters")
assign_parameters.force_field_path = force_field_path
assign_parameters.coordinate_file_path = build_coordinates.coordinate_file_path
assign_parameters.substance = substance
assign_parameters.execute(directory)
assert path.isfile(assign_parameters.parameterized_system.system_path)
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 test_build_coordinates_packmol_exact(count_exact_amount):
"""Tests that the build coordinate protocol behaves correctly for substances
with exact amounts."""
import mdtraj
substance = Substance()
substance.add_component(Component("O"), MoleFraction(1.0))
substance.add_component(Component("C"), ExactAmount(1))
max_molecule = 11 if count_exact_amount else 10
build_coordinates = BuildCoordinatesPackmol("build_coordinates")
build_coordinates.max_molecules = max_molecule
build_coordinates.count_exact_amount = count_exact_amount
build_coordinates.substance = substance
with tempfile.TemporaryDirectory() as directory:
build_coordinates.execute(directory)
built_system = mdtraj.load_pdb(build_coordinates.coordinate_file_path)
assert built_system.n_residues == 11
def _build_input_output_substances():
"""Builds sets if input and expected substances for the
`test_build_coordinate_composition` test.
Returns
-------
list of tuple of Substance and Substance
A list of input and expected substances.
"""
# Start with some easy cases
substances = [
(Substance.from_components("O"), Substance.from_components("O")),
(Substance.from_components("O",
"C"), Substance.from_components("O", "C")),
(
Substance.from_components("O", "C", "CO"),
Substance.from_components("O", "C", "CO"),
),
]
# Handle some cases where rounding will need to occur.
input_substance = Substance()
input_substance.add_component(Component("O"), MoleFraction(0.41))
input_substance.add_component(Component("C"), MoleFraction(0.59))
expected_substance = Substance()
expected_substance.add_component(Component("O"), MoleFraction(0.4))
expected_substance.add_component(Component("C"), MoleFraction(0.6))
substances.append((input_substance, expected_substance))
input_substance = Substance()
input_substance.add_component(Component("O"), MoleFraction(0.59))
input_substance.add_component(Component("C"), MoleFraction(0.41))
expected_substance = Substance()
expected_substance.add_component(Component("O"), MoleFraction(0.6))
expected_substance.add_component(Component("C"), MoleFraction(0.4))
substances.append((input_substance, expected_substance))
return substances
def default_simulation_schema(absolute_tolerance=UNDEFINED,
relative_tolerance=UNDEFINED,
n_molecules=2000):
"""Returns the default calculation schema to use when estimating
this class of property from direct simulations.
Parameters
----------
absolute_tolerance: pint.Quantity, optional
The absolute tolerance to estimate the property to within.
relative_tolerance: float
The tolerance (as a fraction of the properties reported
uncertainty) to estimate the property to within.
n_molecules: int
The number of molecules to use in the simulation.
Returns
-------
SimulationSchema
The schema to follow when estimating this property.
"""
assert absolute_tolerance == UNDEFINED or relative_tolerance == UNDEFINED
calculation_schema = SimulationSchema()
calculation_schema.absolute_tolerance = absolute_tolerance
calculation_schema.relative_tolerance = relative_tolerance
use_target_uncertainty = (absolute_tolerance != UNDEFINED
or relative_tolerance != UNDEFINED)
# Setup the fully solvated systems.
build_full_coordinates = coordinates.BuildCoordinatesPackmol(
"build_solvated_coordinates")
build_full_coordinates.substance = ProtocolPath("substance", "global")
build_full_coordinates.max_molecules = n_molecules
assign_full_parameters = forcefield.BaseBuildSystem(
"assign_solvated_parameters")
assign_full_parameters.force_field_path = ProtocolPath(
"force_field_path", "global")
assign_full_parameters.substance = ProtocolPath("substance", "global")
assign_full_parameters.coordinate_file_path = ProtocolPath(
"coordinate_file_path", build_full_coordinates.id)
# Perform a quick minimisation of the full system to give
# YANK a better starting point for its minimisation.
energy_minimisation = openmm.OpenMMEnergyMinimisation(
"energy_minimisation")
energy_minimisation.system_path = ProtocolPath(
"system_path", assign_full_parameters.id)
energy_minimisation.input_coordinate_file = ProtocolPath(
"coordinate_file_path", build_full_coordinates.id)
equilibration_simulation = openmm.OpenMMSimulation(
"equilibration_simulation")
equilibration_simulation.ensemble = Ensemble.NPT
equilibration_simulation.steps_per_iteration = 100000
equilibration_simulation.output_frequency = 10000
equilibration_simulation.timestep = 2.0 * unit.femtosecond
equilibration_simulation.thermodynamic_state = ProtocolPath(
"thermodynamic_state", "global")
equilibration_simulation.system_path = ProtocolPath(
"system_path", assign_full_parameters.id)
equilibration_simulation.input_coordinate_file = ProtocolPath(
"output_coordinate_file", energy_minimisation.id)
# Create a substance which only contains the solute (e.g. for the
# vacuum phase simulations).
filter_solvent = miscellaneous.FilterSubstanceByRole("filter_solvent")
filter_solvent.input_substance = ProtocolPath("substance", "global")
filter_solvent.component_roles = [Component.Role.Solvent]
filter_solute = miscellaneous.FilterSubstanceByRole("filter_solute")
filter_solute.input_substance = ProtocolPath("substance", "global")
filter_solute.component_roles = [Component.Role.Solute]
# Setup the solute in vacuum system.
build_vacuum_coordinates = coordinates.BuildCoordinatesPackmol(
"build_vacuum_coordinates")
build_vacuum_coordinates.substance = ProtocolPath(
"filtered_substance", filter_solute.id)
build_vacuum_coordinates.max_molecules = 1
assign_vacuum_parameters = forcefield.BaseBuildSystem(
"assign_parameters")
assign_vacuum_parameters.force_field_path = ProtocolPath(
"force_field_path", "global")
assign_vacuum_parameters.substance = ProtocolPath(
"filtered_substance", filter_solute.id)
assign_vacuum_parameters.coordinate_file_path = ProtocolPath(
"coordinate_file_path", build_vacuum_coordinates.id)
# Set up the protocol to run yank.
run_yank = yank.SolvationYankProtocol("run_solvation_yank")
run_yank.solute = ProtocolPath("filtered_substance", filter_solute.id)
run_yank.solvent_1 = ProtocolPath("filtered_substance",
filter_solvent.id)
run_yank.solvent_2 = Substance()
run_yank.thermodynamic_state = ProtocolPath("thermodynamic_state",
"global")
run_yank.steps_per_iteration = 500
run_yank.checkpoint_interval = 50
run_yank.solvent_1_coordinates = ProtocolPath(
"output_coordinate_file", equilibration_simulation.id)
run_yank.solvent_1_system = ProtocolPath("system_path",
assign_full_parameters.id)
run_yank.solvent_2_coordinates = ProtocolPath(
"coordinate_file_path", build_vacuum_coordinates.id)
run_yank.solvent_2_system = ProtocolPath("system_path",
assign_vacuum_parameters.id)
# Set up the group which will run yank until the free energy has been determined to within
# a given uncertainty
conditional_group = groups.ConditionalGroup("conditional_group")
conditional_group.max_iterations = 20
if use_target_uncertainty:
condition = groups.ConditionalGroup.Condition()
condition.type = groups.ConditionalGroup.Condition.Type.LessThan
condition.right_hand_value = ProtocolPath("target_uncertainty",
"global")
condition.left_hand_value = ProtocolPath(
"estimated_free_energy.error", conditional_group.id,
run_yank.id)
conditional_group.add_condition(condition)
# Define the total number of iterations that yank should run for.
total_iterations = miscellaneous.MultiplyValue("total_iterations")
total_iterations.value = 2000
total_iterations.multiplier = ProtocolPath("current_iteration",
conditional_group.id)
# Make sure the simulations gets extended after each iteration.
run_yank.number_of_iterations = ProtocolPath("result",
total_iterations.id)
conditional_group.add_protocols(total_iterations, run_yank)
# Define the full workflow schema.
schema = WorkflowSchema()
schema.protocol_schemas = [
build_full_coordinates.schema,
assign_full_parameters.schema,
energy_minimisation.schema,
equilibration_simulation.schema,
filter_solvent.schema,
filter_solute.schema,
build_vacuum_coordinates.schema,
assign_vacuum_parameters.schema,
conditional_group.schema,
]
schema.final_value_source = ProtocolPath("estimated_free_energy",
conditional_group.id,
run_yank.id)
calculation_schema.workflow_schema = schema
return calculation_schema