def test_parse_output(driver):
"""
Test reading gaussian outfiles and extracting the correct information based on the
driver type.
"""
outfiles = {}
with open(get_data("gaussian.log")) as log:
outfiles["gaussian.log"] = log.read()
with open(get_data("gaussian.fchk")) as fchk:
outfiles["lig.fchk"] = fchk.read()
# build the input
mol = Ligand.from_file(file_name=get_data("acetone.pdb"))
# build the atomic model
qc_spec = qcel.models.common_models.Model(method="pbe", basis="6-31G")
# build a job for a specific driver
qc_task = qcel.models.AtomicInput(molecule=mol.to_qcschema(),
driver=driver,
model=qc_spec)
g = GaussianHarness()
result = g.parse_output(outfiles=outfiles, input_model=qc_task)
if driver == "energy":
assert result.return_result == -1.931393770857046e02
elif driver == "gradient":
assert result.return_result.shape == (10, 3)
elif driver == "hessian":
assert result.return_result.shape == (30, 30)
def test_full_run(driver, tmpdir):
"""
For the given driver try a full execution if the user has gaussian installed.
"""
if not GaussianHarness.found():
pytest.skip("Gaussian 09/16 not available test skipped.")
with tmpdir.as_cwd():
# build the input
mol = Ligand.from_file(file_name=get_data("acetone.pdb"))
# build the atomic model
qc_spec = qcel.models.common_models.Model(method="wB97XD",
basis="6-311++G(d,p)")
# build a job for a specific driver
qc_task = qcel.models.AtomicInput(molecule=mol.to_qcschema(),
driver=driver,
model=qc_spec)
g = GaussianHarness()
# run locally with 2 cores and 2 GB memory
result = g.compute(
input_data=qc_task,
config=qcng.config.TaskConfig(**{
"memory": 2,
"ncores": 2,
"nnodes": 1,
"retries": 1
}),
)
outfiles = {}
with open(get_data("gaussian.log")) as log:
outfiles["gaussian.log"] = log.read()
with open(get_data("gaussian.fchk")) as fchk:
outfiles["lig.fchk"] = fchk.read()
ref_result = g.parse_output(outfiles=outfiles, input_model=qc_task)
assert np.allclose(ref_result.return_result, result.return_result)