def test_torsiondrive_submissions(fractal_compute_server, specification):
"""
Test submitting a torsiondrive dataset and computing it.
"""
client = FractalClient(fractal_compute_server)
qc_spec, driver = specification
program = qc_spec["program"]
if not has_program(program):
pytest.skip(f"Program '{program}' not found.")
molecules = Molecule.from_smiles("CO")
factory = TorsiondriveDatasetFactory(driver=driver)
factory.add_qc_spec(**qc_spec,
spec_name="default",
spec_description="test",
overwrite=True)
dataset = factory.create_dataset(
dataset_name=f"Test torsiondrives info {program}, {driver}",
molecules=molecules,
description="Test torsiondrive dataset",
tagline="Testing torsiondrive datasets",
)
with pytest.raises(DatasetInputError):
dataset.submit(client=client, await_result=False)
# now add a mock url so we can submit the data
dataset.metadata.long_description_url = "https://test.org"
# now submit again
dataset.submit(client=client, await_result=False)
fractal_compute_server.await_services(max_iter=50)
# make sure of the results are complete
ds = client.get_collection("TorsionDriveDataset", dataset.dataset_name)
# check the metadata
meta = Metadata(**ds.data.metadata)
assert meta == dataset.metadata
# check the provenance
assert dataset.provenance == ds.data.provenance
# check the qc spec
for qc_spec in dataset.qc_specifications.values():
spec = ds.data.specs[qc_spec.spec_name]
assert spec.description == qc_spec.spec_description
assert spec.qc_spec.driver == dataset.driver
assert spec.qc_spec.method == qc_spec.method
assert spec.qc_spec.basis == qc_spec.basis
assert spec.qc_spec.program == qc_spec.program
# check the keywords
keywords = client.query_keywords(spec.qc_spec.keywords)[0]
assert keywords.values["maxiter"] == dataset.maxiter
assert keywords.values["scf_properties"] == dataset.scf_properties
# query the dataset
ds.query(qc_spec.spec_name)
for index in ds.df.index:
record = ds.df.loc[index].default
# this will take some time so make sure it is running with no error
assert record.status.value == "COMPLETE", print(record.dict())
assert record.error is None
assert len(record.final_energy_dict) == 24
def test_optimization_submissions(fractal_compute_server, specification):
"""Test submitting an Optimization dataset to a snowflake server."""
client = FractalClient(fractal_compute_server)
qc_spec, driver = specification
program = qc_spec["program"]
if not has_program(program):
pytest.skip(f"Program '{program}' not found.")
molecules = Molecule.from_file(get_data("butane_conformers.pdb"), "pdb")
factory = OptimizationDatasetFactory(driver=driver)
factory.add_qc_spec(**qc_spec,
spec_name="default",
spec_description="test",
overwrite=True)
dataset = factory.create_dataset(
dataset_name=f"Test optimizations info {program}, {driver}",
molecules=molecules[:2],
description="Test optimization dataset",
tagline="Testing optimization datasets",
)
with pytest.raises(DatasetInputError):
dataset.submit(client=client, await_result=False)
# now add a mock url so we can submit the data
dataset.metadata.long_description_url = "https://test.org"
# now submit again
dataset.submit(client=client, await_result=False)
fractal_compute_server.await_results()
# make sure of the results are complete
ds = client.get_collection("OptimizationDataset", dataset.dataset_name)
# check the metadata
meta = Metadata(**ds.data.metadata)
assert meta == dataset.metadata
# check the provenance
assert dataset.provenance == ds.data.provenance
# check the qc spec
for qc_spec in dataset.qc_specifications.values():
spec = ds.data.specs[qc_spec.spec_name]
assert spec.description == qc_spec.spec_description
assert spec.qc_spec.driver == dataset.driver
assert spec.qc_spec.method == qc_spec.method
assert spec.qc_spec.basis == qc_spec.basis
assert spec.qc_spec.program == qc_spec.program
# check the keywords
keywords = client.query_keywords(spec.qc_spec.keywords)[0]
assert keywords.values["maxiter"] == dataset.maxiter
assert keywords.values["scf_properties"] == dataset.scf_properties
# query the dataset
ds.query(qc_spec.spec_name)
for index in ds.df.index:
record = ds.df.loc[index].default
assert record.status.value == "COMPLETE"
assert record.error is None
assert len(record.trajectory) > 1
# if we used psi4 make sure the properties were captured
if program == "psi4":
result = record.get_trajectory()[0]
assert "CURRENT DIPOLE X" in result.extras["qcvars"].keys()
assert "SCF QUADRUPOLE XX" in result.extras["qcvars"].keys()
def test_optimization_submissions_with_pcm(fractal_compute_server):
"""Test submitting an Optimization dataset to a snowflake server with PCM."""
client = FractalClient(fractal_compute_server)
program = "psi4"
if not has_program(program):
pytest.skip(f"Program '{program}' not found.")
# use a single small molecule due to the extra time PCM takes
molecules = Molecule.from_smiles("C")
factory = OptimizationDatasetFactory(driver="gradient")
factory.add_qc_spec(method="hf",
basis="sto-3g",
program=program,
spec_name="default",
spec_description="test",
implicit_solvent=PCMSettings(units="au",
medium_Solvent="water"),
overwrite=True)
dataset = factory.create_dataset(
dataset_name=f"Test optimizations info with pcm water",
molecules=molecules,
description="Test optimization dataset",
tagline="Testing optimization datasets",
)
with pytest.raises(DatasetInputError):
dataset.submit(client=client, await_result=False)
# now add a mock url so we can submit the data
dataset.metadata.long_description_url = "https://test.org"
# now submit again
dataset.submit(client=client, await_result=False)
fractal_compute_server.await_results()
# make sure of the results are complete
ds = client.get_collection("OptimizationDataset", dataset.dataset_name)
# check the metadata
meta = Metadata(**ds.data.metadata)
assert meta == dataset.metadata
# check the provenance
assert dataset.provenance == ds.data.provenance
# check the qc spec
for qc_spec in dataset.qc_specifications.values():
spec = ds.data.specs[qc_spec.spec_name]
assert spec.description == qc_spec.spec_description
assert spec.qc_spec.driver == dataset.driver
assert spec.qc_spec.method == qc_spec.method
assert spec.qc_spec.basis == qc_spec.basis
assert spec.qc_spec.program == qc_spec.program
# check the keywords
keywords = client.query_keywords(spec.qc_spec.keywords)[0]
assert keywords.values["maxiter"] == dataset.maxiter
assert keywords.values["scf_properties"] == dataset.scf_properties
# query the dataset
ds.query(qc_spec.spec_name)
for index in ds.df.index:
record = ds.df.loc[index].default
assert record.status.value == "COMPLETE"
assert record.error is None
assert len(record.trajectory) > 1
result = record.get_trajectory()[0]
assert "CURRENT DIPOLE X" in result.extras["qcvars"].keys()
assert "SCF QUADRUPOLE XX" in result.extras["qcvars"].keys()
# make sure the PCM result was captured
assert result.extras["qcvars"]["PCM POLARIZATION ENERGY"] < 0
def test_adding_compute(fractal_compute_server, dataset_data):
"""
Test adding new compute to each of the dataset types using none psi4 programs.
"""
client = FractalClient(fractal_compute_server)
mol = Molecule.from_smiles("CO")
factory_type, dataset_type = dataset_data
# make and clear out the qc specs
factory = factory_type()
factory.clear_qcspecs()
factory.add_qc_spec(method="openff-1.0.0",
basis="smirnoff",
program="openmm",
spec_name="default",
spec_description="default spec for openff")
dataset = factory.create_dataset(
dataset_name=f"Test adding compute to {factory_type}",
molecules=mol,
description=f"Testing adding compute to a {dataset_type} dataset",
tagline="tests for adding compute.")
# now add a mock url so we can submit the data
dataset.metadata.long_description_url = "https://test.org"
# now submit again
dataset.submit(client=client, await_result=False)
# make sure that the compute has finished
fractal_compute_server.await_results()
fractal_compute_server.await_services(max_iter=50)
# now lets make a dataset with new compute and submit it
# transfer the metadata to compare the elements
compute_dataset = dataset_type(dataset_name=dataset.dataset_name,
metadata=dataset.metadata)
compute_dataset.clear_qcspecs()
# now add the new compute spec
compute_dataset.add_qc_spec(method="uff",
basis=None,
program="rdkit",
spec_name="rdkit",
spec_description="rdkit basic spec")
# make sure the dataset has no molecules and submit it
assert compute_dataset.dataset == {}
compute_dataset.submit(client=client)
# make sure that the compute has finished
fractal_compute_server.await_results()
fractal_compute_server.await_services(max_iter=50)
# make sure of the results are complete
ds = client.get_collection(dataset.dataset_type, dataset.dataset_name)
# check the metadata
meta = Metadata(**ds.data.metadata)
assert meta == dataset.metadata
assert ds.data.description == dataset.description
assert ds.data.tagline == dataset.dataset_tagline
assert ds.data.tags == dataset.dataset_tags
# check the provenance
assert dataset.provenance == ds.data.provenance
# update all specs into one dataset
dataset.add_qc_spec(**compute_dataset.qc_specifications["rdkit"].dict())
# get the last ran spec
if dataset.dataset_type == "DataSet":
for specification in ds.data.history:
driver, program, method, basis, spec_name = specification
spec = dataset.qc_specifications[spec_name]
assert driver == dataset.driver
assert program == spec.program
assert method == spec.method
assert basis == spec.basis
for spec in dataset.qc_specifications.values():
query = ds.get_records(
method=spec.method,
basis=spec.basis,
program=spec.program,
)
for index in query.index:
result = query.loc[index].record
assert result.status.value.upper() == "COMPLETE"
assert result.error is None
assert result.return_result is not None
else:
# check the qc spec
for qc_spec in dataset.qc_specifications.values():
spec = ds.data.specs[qc_spec.spec_name]
assert spec.description == qc_spec.spec_description
assert spec.qc_spec.driver == dataset.driver
assert spec.qc_spec.method == qc_spec.method
assert spec.qc_spec.basis == qc_spec.basis
assert spec.qc_spec.program == qc_spec.program
# check the keywords
keywords = client.query_keywords(spec.qc_spec.keywords)[0]
assert keywords.values["maxiter"] == dataset.maxiter
assert keywords.values["scf_properties"] == dataset.scf_properties
# query the dataset
ds.query(qc_spec.spec_name)
for index in ds.df.index:
record = ds.df.loc[index].default
# this will take some time so make sure it is running with no error
assert record.status.value == "COMPLETE", print(record.dict())
assert record.error is None
