def test_create_dataset_atom_map(): """Test creating a dataset with molecules with atom maps.""" factory = OptimizationDatasetFactory() mol = Molecule.from_smiles("CCCC([O-])=O") mol.properties['atom_map'] = {1: 1, 2: 2, 3: 3, 4: 4} _ = factory.create_dataset(dataset_name="test name", molecules=mol, description="Force field test", tagline="A test dataset")
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="Test optimizations info with pcm water", molecules=molecules, description="Test optimization dataset", tagline="Testing optimization 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_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"] == 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 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_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", ) # 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_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"] == 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 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_adding_specifications(fractal_compute_server): """ Test adding specifications to datasets. Here we are testing multiple scenarios: 1) Adding an identical specification to a dataset 2) Adding a spec with the same name as another but with different options 3) overwrite a spec which was added but never used. """ client = FractalClient(fractal_compute_server) mol = Molecule.from_smiles("CO") # make a dataset factory = OptimizationDatasetFactory() opt_dataset = factory.create_dataset( dataset_name="Specification error check", molecules=mol, description="test adding new compute specs to datasets", tagline="test adding new compute specs") opt_dataset.clear_qcspecs() # add a new mm spec opt_dataset.add_qc_spec(method="openff-1.0.0", basis="smirnoff", program="openmm", spec_description="default openff spec", spec_name="openff-1.0.0") # submit the optimizations and let the compute run opt_dataset.submit(client=client) fractal_compute_server.await_results() fractal_compute_server.await_services() # grab the collection ds = client.get_collection(opt_dataset.type, opt_dataset.dataset_name) # now try and add the specification again this should return True assert opt_dataset._add_dataset_specification( spec=opt_dataset.qc_specifications["openff-1.0.0"], procedure_spec=opt_dataset.optimization_procedure.get_optimzation_spec( ), dataset=ds) is True # now change part of the spec but keep the name the same opt_dataset.clear_qcspecs() opt_dataset.add_qc_spec(method="openff-1.2.1", basis="smirnoff", spec_name="openff-1.0.0", program="openmm", spec_description="openff-1.2.1 with wrong name.") # now try and add this specification with the same name but different settings with pytest.raises(QCSpecificationError): opt_dataset._add_dataset_specification( spec=opt_dataset.qc_specifications["openff-1.0.0"], procedure_spec=opt_dataset.optimization_procedure. get_optimzation_spec(), dataset=ds) # now add a new specification but no compute and make sure it is overwritten opt_dataset.clear_qcspecs() opt_dataset.add_qc_spec(method="ani1x", basis=None, program="torchani", spec_name="ani", spec_description="a ani spec") assert opt_dataset._add_dataset_specification( spec=opt_dataset.qc_specifications["ani"], procedure_spec=opt_dataset.optimization_procedure.get_optimzation_spec( ), dataset=ds) is True # now change the spec slightly and add again opt_dataset.clear_qcspecs() opt_dataset.add_qc_spec(method="ani1ccx", basis=None, program="torchani", spec_name="ani", spec_description="a ani spec") assert opt_dataset._add_dataset_specification( spec=opt_dataset.qc_specifications["ani"], procedure_spec=opt_dataset.optimization_procedure.get_optimzation_spec( ), dataset=ds) is True