def test_torsiondrive_scan_keywords(fractal_compute_server): """ Test running torsiondrives with unique keyword settings which overwrite the global grid spacing and scan range. """ client = FractalClient(fractal_compute_server) molecules = Molecule.from_smiles("CO") factory = TorsiondriveDatasetFactory() scan_enum = workflow_components.ScanEnumerator() scan_enum.add_torsion_scan(smarts="[*:1]~[#6:2]-[#8:3]~[*:4]") factory.add_workflow_components(scan_enum) factory.clear_qcspecs() factory.add_qc_spec(method="openff_unconstrained-1.1.0", basis="smirnoff", program="openmm", spec_description="scan range test", spec_name="openff-1.1.0") dataset = factory.create_dataset( dataset_name="Torsiondrive scan keywords", molecules=molecules, description="Testing scan keywords which overwrite the global settings", tagline="Testing scan keywords which overwrite the global settings") # now set the keywords keys = list(dataset.dataset.keys()) entry = dataset.dataset[keys[0]] entry.keywords = {"grid_spacing": [5], "dihedral_ranges": [(-10, 10)]} # now submit dataset.submit(client=client) fractal_compute_server.await_services(max_iter=50) # make sure of the results are complete ds = client.get_collection("TorsionDriveDataset", dataset.dataset_name) # get the entry record = ds.get_record(ds.df.index[0], "openff-1.1.0") assert record.keywords.grid_spacing == [5] assert record.keywords.grid_spacing != dataset.grid_spacing assert record.keywords.dihedral_ranges == [(-10, 10)] assert record.keywords.dihedral_ranges != dataset.dihedral_ranges
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", ) # force a metadata validation error dataset.metadata.long_description = None with pytest.raises(DatasetInputError): dataset.submit(client=client) # re-add the description so we can submit the data dataset.metadata.long_description = "Test basics dataset" # now submit again dataset.submit(client=client) 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"] == qc_spec.maxiter assert keywords.values["scf_properties"] == qc_spec.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