def mutate_and_relax(candidate, name, iteration, cnt_max, **kwargs):
print_output("__%s__" % name)
found = False
cnt = 0
while found is False and cnt < cnt_max:
candidate_backup = Structure(candidate)
candidate.mutate(**kwargs)
print_output("%s after mutation: " % name + str(candidate))
run_util.str_info(candidate)
if not candidate.is_geometry_valid():
print_output(" The geometry of %s is invalid." % name)
cnt += 1
# Rebuild the structure
candidate = candidate_backup
continue
if candidate not in blacklist:
name = "generation_%d_%s" % (iteration, name)
run_util.optimize(candidate, energy_function, params, name)
run_util.check_for_kill()
candidate.send_to_blacklist(blacklist)
print_output(str(candidate)+":, energy: "+str(float(
candidate))+", is temporary added to the population")
run_util.relax_info(candidate)
found = True
population.append(candidate)
else:
print_output("Geomerty of "+str(candidate)+" is fine, but already "
"known.")
cnt += 1
candidate = candidate_backup
if cnt == cnt_max:
raise Exception("The allowed number of trials for generating"
" a unique child has been exceeded.")
def mutate_and_relax(candidate, name, iteration, cnt_max, **kwargs):
print_output("__%s__" % name)
found = False
cnt = 0
while found is False and cnt < cnt_max:
candidate_backup = Structure(candidate)
candidate.mutate(**kwargs)
print_output("%s after mutation: " % name + str(candidate))
run_util.str_info(candidate)
if not candidate.is_geometry_valid():
print_output(" The geometry of %s is invalid." % name)
cnt += 1
# Rebuild the structure
candidate = candidate_backup
continue
if candidate not in blacklist:
name = "generation_%d_%s" % (iteration, name)
run_util.optimize(candidate, energy_function, params, name)
run_util.check_for_kill()
candidate.send_to_blacklist(blacklist)
print_output(
str(candidate) + ":, energy: " + str(float(candidate)) +
", is temporary added to the population")
run_util.relax_info(candidate)
found = True
population.append(candidate)
else:
print_output("Geomerty of " + str(candidate) +
" is fine, but already "
"known.")
cnt += 1
candidate = candidate_backup
if cnt == cnt_max:
raise Exception("The allowed number of trials for generating"
" a unique child has been exceeded.")
str3d.generate_structure()
if not str3d.is_geometry_valid():
print_output("The geometry of " + str(str3d) + " is invalid.")
cnt += 1
continue
if str3d not in blacklist:
name = "initial_%d" % (len(population))
# Perform the local optimization
run_util.optimize(str3d, energy_function, params, name)
run_util.check_for_kill()
str3d.send_to_blacklist(blacklist)
population.append(str3d)
print_output(
str(str3d) + ", energy: " + str(float(str3d)) +
", was added to the population")
run_util.relax_info(str3d)
cnt += 1
else:
print_output("Geomerty of " + str(str3d) + " is fine, but already "
"known.")
cnt += 1
if cnt == cnt_max:
print_output("The allowed number of trials for building the "
"population has been exceeded. The code terminates.")
sys.exit(0)
print_output("___Initialization completed___")
population.sort()
print_output("Initial population after sorting: ")
for i in range(len(population)):
print_output(str(population[i]) + " " + str(float(population[i])))
min_energy.append(population[0].energy)
str3d = Structure(mol)
str3d.generate_structure()
if not str3d.is_geometry_valid():
print_output("The geometry of "+str(str3d)+" is invalid.")
cnt += 1
continue
if str3d not in blacklist:
name = "initial_%d" % (len(population))
# Perform the local optimization
run_util.optimize(str3d, energy_function, params, name)
run_util.check_for_kill()
str3d.send_to_blacklist(blacklist)
population.append(str3d)
print_output(str(str3d)+", energy: "+str(float(str3d)) +
", was added to the population")
run_util.relax_info(str3d)
cnt += 1
else:
print_output("Geomerty of "+str(str3d)+" is fine, but already "
"known.")
cnt += 1
if cnt == cnt_max:
print_output("The allowed number of trials for building the "
"population has been exceeded. The code terminates.")
sys.exit(0)
print_output("___Initialization completed___")
population.sort()
print_output("Initial population after sorting: ")
for i in range(len(population)):
print_output(str(population[i])+" "+str(float(population[i])))
min_energy.append(population[0].energy)
