def main(rowNum):
conc = get_conc(rowNum)
print(conc)
if conc is None:
return
settings = settings_from_json(settings_file)
atoms = bulk('Al', a=4.05, crystalstructure='fcc', cubic=True) * (N, N, N)
atoms = attach_calculator(settings, atoms, get_eci())
cu = ['Cu'] * int(conc['Cu'] * len(atoms))
si = ['Si'] * int(conc['Si'] * len(atoms))
mg = ['Mg'] * int(conc['Mg'] * len(atoms))
al = ['Al'] * (len(atoms) - len(cu) - len(mg) - len(si))
symbols = al + mg + si + cu
shuffle(symbols)
atoms.symbols = symbols
# Trigger a calculation
atoms.get_potential_energy()
temperatures = list(range(1000, 1, -50))
obs = LowestEnergyStructure(atoms)
for T in temperatures:
print(f"Temperature {T}")
mc = Montecarlo(atoms, T)
mc.attach(obs)
mc.run(steps=20 * len(atoms))
db = connect(db_name)
calc = SinglePointCalculator(obs.emin_atoms, energy=obs.lowest_energy)
obs.emin_atoms.set_calculator(calc)
db.write(obs.emin_atoms)
def test_mgsi100():
eci = {}
with open("data/almgsix_normal_ce.json", 'r') as infile:
data = json.load(infile)
eci = data['eci']
settings = settings_from_json("data/settings_almgsiX_voldev.json")
settings.basis_func_type = "binary_linear"
atoms = bulk('Al', a=4.05, cubic=True) * (4, 4, 4)
atoms = attach_calculator(settings, atoms, eci)
for i in range(int(len(atoms) / 2)):
atoms[i].symbol = 'Mg'
atoms[i + int(len(atoms) / 2)].symbol = 'Si'
mc = Montecarlo(atoms, 1000)
temps = [1000, 800, 600, 500, 400, 300, 200, 100]
for T in temps:
mc.T = T
mc.run(steps=100 * len(atoms))
fname = "data/" + atoms.get_chemical_formula() + "_mc_test.xyz"
write(fname, atoms)
def main():
settings = settings_from_json("data/almgsicu_settings.json")
cf = CorrFunction(settings)
traj = TrajectoryReader("../../AlMgSiMC/data/surfacePure.traj")
corrs = []
energies = []
sizes = []
for i in range(0, len(traj), 2):
init = traj[i]
final = traj[i + 1]
corrs.append(cf.get_cf(wrap_and_sort_by_position(init)))
sizes.append(len(init))
energies.append(final.get_potential_energy())
keys = sorted(corrs[0].keys())
with open(outfile, 'w') as out:
header = ",".join(keys)
header += ",E_DFT,size"
out.write(header + "\n")
for c, e, s in zip(corrs, energies, sizes):
data = ",".join(str(c[k]) for k in keys)
data += f",{e},{s}\n"
out.write(data)
print(f"Data written to {outfile}")
from clease.settings import settings_from_json
from clease import NewStructures
from ase.db import connect
settings = settings_from_json("data/cupd_settings.json")
dft_db = "data/cupd.db"
def main():
initial_structs = []
final_structs = []
with connect(dft_db) as db:
groups = set()
for row in db.select():
groups.add(row.get('group', -1))
for g in groups:
try:
init = db.get([('group', '=', g),
('struct_type', '=', 'initial')])
final = db.get([('group', '=', g),
('struct_type', '=', 'relaxed')])
initial_structs.append(init.toatoms())
final_structs.append(final.toatoms())
except KeyError:
pass
# Sanity checks
for i, f in zip(initial_structs, final_structs):
i_formula = i.get_chemical_formula()
f_formula = f.get_chemical_formula()
from clease.settings import settings_from_json
from clease import NewStructures
from ase.db import connect
settings = settings_from_json("data/almgsicu_settings.json")
dft_db = "data/almgsicu.db"
def main():
initial_structs = []
final_structs = []
with connect(dft_db) as db:
groups = set()
for row in db.select():
groups.add(row.get('group', -1))
for g in groups:
try:
init = db.get([('group', '=', g),
('struct_type', '=', 'initial')])
final = db.get([('group', '=', g),
('struct_type', '=', 'relaxed')])
initial_structs.append(init.toatoms())
final_structs.append(final.toatoms())
except KeyError:
pass
# Sanity checks
for i, f in zip(initial_structs, final_structs):
i_formula = i.get_chemical_formula()
f_formula = f.get_chemical_formula()