n_train_force = int(1e5)
save_interval = 100
timestep = 5.0
train_traj = "training.traj"
train_force_traj = "training_force.traj"
max_steps = int(4e3)
convergence = {
"energy_rmse": 1e-16,
"force_rmse": None,
"max_steps": max_steps
}
force_coefficient = None
overfit = 1e-7
hidden_layers = [10, 10]
cutoff = Polynomial(5.0, gamma=5.0)
num_radial_etas = 7
num_angular_etas = 11
num_zetas = 1
angular_type = "G4"
trn = Trainer(
convergence=convergence,
force_coefficient=force_coefficient,
overfit=overfit,
cutoff=cutoff,
hidden_layers=hidden_layers,
)
trn.create_Gs(elements, num_radial_etas, num_angular_etas, num_zetas,
angular_type)
trjbd = TrajectoryBuilder()
calc = EMT()
train_atoms = trjbd.build_atoms(system, size, temp, calc)
calc = EMT()
test_atoms = trjbd.build_atoms(system, size, temp, calc)
steps, train_traj = trjbd.integrate_atoms(train_atoms, train_traj, n_train,
save_interval)
steps, test_traj = trjbd.integrate_atoms(test_atoms, test_traj, n_test,
save_interval)
rcs = [2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0]
gamma = 5.0
cutoffs = []
for rc in rcs:
cutoffs.append(Cosine(rc))
cutoffs.append(Polynomial(rc, gamma=gamma))
calcs = {}
for cutoff in cutoffs:
trn.cutoff = cutoff
trn.create_Gs(elements, num_radial_etas, num_angular_etas, num_zetas,
angular_type)
label = "{}-{}".format(cutoff.__class__.__name__, cutoff.Rc)
dblabel = label + "-train"
calc = trn.create_calc(label=label, dblabel=dblabel)
ann = Annealer(
calc=calc,
images=train_traj,
Tmax=20,
Tmin=1,