def main(args):
eval_name = args.modelpath.split("/")[-1]
eval_file = "evaluation_" + eval_name + ".txt"
if os.path.exists(eval_file):
if args.overwrite:
os.remove(eval_file)
else:
raise Exception(
"The evaluation file already exists. Delete it or add the overwrite flag."
)
device = "cuda" if args.cuda else "cpu"
calculator = mlcalcdriver.calculators.SchnetPackCalculator(args.modelpath,
device=device)
with connect(args.dbpath) as db:
answers, results = (
[[] for _ in range(len(args.properties))],
[[] for _ in range(len(args.properties))],
)
posinp = []
for row in db.select():
for i, prop in enumerate(args.properties):
answers[i].append(row.data[prop])
posinp.append(Posinp.from_ase(row.toatoms()))
if len(posinp) == args.batch_size:
job = Job(posinp=posinp, calculator=calculator)
for i, prop in enumerate(args.properties):
job.run(prop, batch_size=args.batch_size)
results[i].append(job.results[prop].tolist())
posinp = []
if len(posinp) > 0:
job = Job(posinp=posinp, calculator=calculator)
for i, prop in enumerate(args.properties):
job.run(prop, batch_size=args.batch_size)
results[i].append(job.results[prop])
posinp = []
header, error = [], []
for prop in args.properties:
header += ["MAE_" + prop, "%Error_" + prop, "RMSE_" + prop]
for l1, l2 in zip(answers, results):
an, re = np.array(l1).flatten(), np.concatenate(l2).flatten()
error.append(np.abs(an - re).mean())
error.append(np.abs((an - re) / an).mean() * 100)
error.append(np.sqrt(np.mean((an - re)**2)))
with open(eval_file, "w") as file:
wr = csv.writer(file)
wr.writerow(header)
wr.writerow(error)
def test_periodic(self):
pos1 = Posinp.from_file(os.path.join(pos_folder, "periodic.xyz"))
atoms = posinp_to_ase_atoms(pos1)
pos2 = Posinp.from_ase(atoms)
assert pos1 == pos2
def test_surface(self):
pos1 = Posinp.from_file(os.path.join(pos_folder, "surface2.xyz"))
atoms = posinp_to_ase_atoms(pos1)
pos2 = Posinp.from_ase(atoms)
assert pos1 == pos2