def test_program_not_installed():
"""
Make sure an error is raised when we try and use a program that is not available.
"""
g_opt = GeometryOptimiser()
with pytest.raises(SpecificationError):
g_opt.program = "test"
def test_optimiser_keywords(optimiser):
"""
For the given optimiser make sure the keywords are updated correctly.
"""
g = GeometryOptimiser(optimiser=optimiser, maxiter=1, convergence="GAU")
keywords = g._build_optimiser_keywords(program="psi4")
assert 1 in keywords.values()
assert "GAU" in keywords.values()
def _run_qm_opt(
self,
molecule: "Ligand",
conformers: List[np.array],
qc_spec: QCOptions,
local_options: LocalResource,
) -> "Ligand":
"""
Run the main QM optimisation on each of the input conformers in order and stop when we get a fully optimised structure.
Args:
molecule: The qubekit molecule to run the optimisation on.
conformers: The list of pre-optimised conformers.
qc_spec: The QCSpec used to run the QM optimisation.
local_options: The local resource that is available for the optimisation.
"""
opt_mol = deepcopy(molecule)
g_opt = GeometryOptimiser(convergence=self.convergence_criteria,
maxiter=50)
for i, conformer in enumerate(
tqdm(conformers,
desc="Optimising conformer",
total=len(conformers),
ncols=80)):
with folder_setup(folder_name=f"conformer_{i}"):
# set the coords
opt_mol.coordinates = conformer
# errors are auto raised from the class so catch the result, and write to file
qm_result, result = g_opt.optimise(
molecule=opt_mol,
allow_fail=True,
return_result=True,
qc_spec=qc_spec,
local_options=local_options,
)
if result.success:
break
else:
# grab last coords and bump
coords = qm_result.coordinates + np.random.choice(
a=[0, 0.01], size=(qm_result.n_atoms, 3))
opt_mol.coordinates = coords
bump_mol, bump_result = g_opt.optimise(
molecule=opt_mol,
allow_fail=True,
return_result=True,
local_options=local_options,
qc_spec=qc_spec,
)
if bump_result.success:
qm_result = bump_mol
break
else:
raise GeometryOptimisationError(
"No molecule conformer could be optimised to GAU TIGHT")
return qm_result
def test_optimiser_keywords(optimiser):
"""
For the given optimiser make sure the keywords are updated correctly.
"""
if "psi4" not in qcengine.list_available_programs():
pytest.skip("Psi4 missing skipping.")
g = GeometryOptimiser(
optimiser=optimiser, maxiter=1, convergence="GAU", program="psi4"
)
keywords = g.build_optimiser_keywords()
assert 1 in keywords.values()
assert "GAU" in keywords.values()
def test_optmiser_fail_no_output(tmpdir):
"""
Make sure we raise an error correctly when there is no output from a failed optimisation.
"""
if "psi4" not in qcengine.list_available_programs():
pytest.skip("Psi4 missing skipping test.")
with tmpdir.as_cwd():
mol = Ligand.from_file(file_name=get_data("water.pdb"))
g = GeometryOptimiser(
program="psi4", method="wb97x-dbj", basis="dzvp", maxiter=10
)
with pytest.raises(RuntimeError):
g.optimise(molecule=mol, allow_fail=False)
def test_optking_fail():
"""
Optking currently only works with psi4 make sure we raise an error if we use
a different program.
"""
with pytest.raises(SpecificationError):
mol = Ligand.from_file(file_name=get_data("water.pdb"))
g = GeometryOptimiser(optimiser="optking")
g.optimise(
molecule=mol,
qc_spec=QCOptions(program="rdkit", basis=None, method="uff"),
local_options=LocalResource(cores=1, memory=1),
)
def test_optimise_fail_output(tmpdir):
"""
Make sure the optimised geometries and result is still wrote out if we fail the molecule and an error is rasied.
"""
with tmpdir.as_cwd():
mol = Ligand.from_file(file_name=get_data("water.pdb"))
g = GeometryOptimiser(
program="torchani", method="ani1ccx", basis=None, maxiter=5
)
with pytest.raises(RuntimeError):
g.optimise(molecule=mol, allow_fail=False)
files = os.listdir()
assert "opt.xyz" in files
assert "opt_trajectory.xyz" in files
assert "result.json" in files
def test_spec_validation_pass(program, basis, method):
"""
Make sure we can correctly validate a specification.
"""
if program not in qcengine.list_available_programs():
pytest.skip(f"{program} missing skipping test")
_ = GeometryOptimiser(program=program, basis=basis, method=method)
def test_optking_fail():
"""
Optking currently only works with psi4 make sure we raise an error if we use
a different program.
"""
with pytest.raises(SpecificationError):
GeometryOptimiser(optimiser="optking", program="rdkit")
def test_spec_validation_fail(program, basis, method):
"""
Make sure than an invalid specification raises an error.
"""
if program not in qcengine.list_available_programs():
pytest.skip(f"{program} missing skipping test")
with pytest.raises(SpecificationError):
_ = GeometryOptimiser(program=program, basis=basis, method=method)
def test_local_options():
"""
Make sure the task config is correctly made and keywords are converted.
"""
g_opt = GeometryOptimiser(cores=10, memory=2)
local_options = g_opt.local_options
assert g_opt.cores == local_options["ncores"]
assert g_opt.memory == local_options["memory"]
def test_optimise(program, basis, method, tmpdir):
"""
Test running different optimisers with different programs.
"""
if program not in qcengine.list_available_programs():
pytest.skip(f"{program} missing skipping test.")
with tmpdir.as_cwd():
mol = Ligand.from_file(get_data("water.pdb"))
g = GeometryOptimiser(
program=program,
basis=basis,
method=method,
optimiser="geometric",
convergence="GAU",
)
result_mol, _ = g.optimise(molecule=mol, return_result=False)
assert result_mol.coordinates.tolist() != mol.coordinates.tolist()
def _pre_opt(self, molecule: "Ligand", qc_spec: QCOptions,
local_options: LocalResource) -> List[np.array]:
"""Run the pre optimisation stage and return the optimised conformers ready for QM optimisation.
Args:
molecule: The qubekit molecule to run the optimisation on.
Returns:
A list of final coordinates from the optimisations.
"""
from multiprocessing import Pool
g_opt = GeometryOptimiser(convergence="GAU", maxiter=self.maxiter)
# generate the input conformations, number will include the input conform if provided
geometries = molecule.generate_conformers(
n_conformers=self.seed_conformers)
molecule.to_multiconformer_file(file_name="starting_coords.xyz",
positions=geometries)
opt_list = []
with Pool(processes=local_options.cores) as pool:
for confomer in geometries:
opt_mol = deepcopy(molecule)
opt_mol.coordinates = confomer
opt_list.append(
pool.apply_async(
g_opt.optimise,
(opt_mol, qc_spec, local_options, True, True)))
results = []
for result in tqdm(
opt_list,
desc=
f"Optimising conformers with {self.pre_optimisation_method}",
total=len(opt_list),
ncols=80,
):
# errors are auto raised from the class so catch the result, and write to file
result_mol, opt_result = result.get()
if opt_result.success:
# save the final energy and molecule
results.append((result_mol, opt_result.energies[-1]))
else:
# save the molecule and final energy from the last step if it fails
results.append(
(result_mol, opt_result.input_data["energies"][-1]))
# sort the results
results.sort(key=lambda x: x[1])
final_geometries = [re[0].coordinates for re in results]
# write all conformers out
molecule.to_multiconformer_file(file_name="final_pre_opt_coords.xyz",
positions=final_geometries)
return final_geometries
def test_optimise(qc_spec: QCOptions, tmpdir):
"""
Test running different optimisers with different programs.
"""
if qc_spec.program.lower() not in qcengine.list_available_programs():
pytest.skip(f"{qc_spec.program} missing skipping test.")
with tmpdir.as_cwd():
mol = Ligand.from_file(get_data("water.pdb"))
g = GeometryOptimiser(
optimiser="geometric",
convergence="GAU",
)
result_mol, _ = g.optimise(
molecule=mol,
return_result=False,
qc_spec=qc_spec,
local_options=LocalResource(cores=1, memory=1),
)
assert result_mol.coordinates.tolist() != mol.coordinates.tolist()
def test_missing_optimiser():
"""
Make sure an error is raised when we try and set a missing optimiser.
"""
with pytest.raises(SpecificationError):
_ = GeometryOptimiser(optimiser="bad_optimiser")
def test_rdkit_available():
"""
Make sure the geometry optimiser allows rdkit as this comes with QUBEKit.
"""
g_opt = GeometryOptimiser()
g_opt.program = "rdkit"
