def test_convert_mdata (self):
mdata = json.load(open(machine_file))
mdata = convert_mdata(mdata, ["fp"])
self.assertEqual(mdata["fp_command"], "vasp_std")
self.assertEqual(mdata["fp_group_size"], 8)
self.assertEqual(mdata["fp_machine"]["batch_type"], "PBS")
self.assertEqual(mdata["fp_user_forward_files"], ["vdw_kernel.bindat"])
def run_equi(confs, inter_param, mdata):
# find all POSCARs and their name like mp-xxx
# ...
conf_dirs = []
for conf in confs:
conf_dirs.extend(glob.glob(conf))
conf_dirs.sort()
# generate a list of task names like mp-xxx/relaxation/relax_task
# ...
work_path_list = []
for ii in conf_dirs:
work_path_list.append(os.path.abspath(os.path.join(ii, 'relaxation')))
all_task = []
for ii in work_path_list:
all_task.append(os.path.join(ii, 'relax_task'))
inter_type = inter_param['type']
# vasp
if inter_type == "vasp":
mdata = convert_mdata(mdata, ["fp"])
elif inter_type in lammps_task_type:
mdata = convert_mdata(mdata, ["model_devi"])
else:
raise RuntimeError("unknown task %s, something wrong" % inter_type)
# dispatch the tasks
# POSCAR here is useless
virtual_calculator = make_calculator(inter_param, "POSCAR")
forward_files = virtual_calculator.forward_files()
forward_common_files = virtual_calculator.forward_common_files()
backward_files = virtual_calculator.backward_files()
# backward_files += logs
# ...
run_tasks = util.collect_task(all_task, inter_type)
if len(run_tasks) == 0:
return
else:
# if LooseVersion()
run_tasks = [os.path.basename(ii) for ii in all_task]
machine, resources, command, group_size = util.get_machine_info(
mdata, inter_type)
print('%d tasks will be submited ' % len(run_tasks))
for ii in range(len(work_path_list)):
work_path = work_path_list[ii]
disp = make_dispatcher(machine, resources, work_path,
[run_tasks[ii]], group_size)
print("%s --> Runing... " % (work_path))
api_version = mdata.get('api_version', '0.9')
if LooseVersion(api_version) < LooseVersion('1.0'):
warnings.warn(
f"the dpdispatcher will be updated to new version."
f"And the interface may be changed. Please check the documents for more details"
)
disp.run_jobs(resources,
command,
work_path, [run_tasks[ii]],
group_size,
forward_common_files,
forward_files,
backward_files,
outlog='outlog',
errlog='errlog')
elif LooseVersion(api_version) >= LooseVersion('1.0'):
submission = make_submission(
mdata_machine=machine,
mdata_resource=resources,
commands=[command],
work_path=work_path,
run_tasks=run_tasks,
group_size=group_size,
forward_common_files=forward_common_files,
forward_files=forward_files,
backward_files=backward_files,
outlog='outlog',
errlog='errlog')
submission.run_submission()
def run_property(confs, inter_param, property_list, mdata):
# find all POSCARs and their name like mp-xxx
# ...
# conf_dirs = glob.glob(confs)
# conf_dirs.sort()
processes = len(property_list)
pool = Pool(processes=processes)
print("Submit job via %d processes" % processes)
conf_dirs = []
for conf in confs:
conf_dirs.extend(glob.glob(conf))
conf_dirs.sort()
task_list = []
work_path_list = []
multiple_ret = []
for ii in conf_dirs:
sepline(ch=ii, screen=True)
for jj in property_list:
# determine the suffix: from scratch or refine
# ...
if jj.get("skip", False):
continue
if 'init_from_suffix' and 'output_suffix' in jj:
suffix = jj['output_suffix']
elif 'reproduce' in jj and jj['reproduce']:
suffix = 'reprod'
else:
suffix = '00'
property_type = jj['type']
path_to_work = os.path.abspath(
os.path.join(ii, property_type + '_' + suffix))
work_path_list.append(path_to_work)
tmp_task_list = glob.glob(
os.path.join(path_to_work, 'task.[0-9]*[0-9]'))
tmp_task_list.sort()
task_list.append(tmp_task_list)
inter_param_prop = inter_param
if 'cal_setting' in jj and 'overwrite_interaction' in jj[
'cal_setting']:
inter_param_prop = jj['cal_setting']['overwrite_interaction']
# dispatch the tasks
# POSCAR here is useless
virtual_calculator = make_calculator(inter_param_prop, "POSCAR")
forward_files = virtual_calculator.forward_files(property_type)
forward_common_files = virtual_calculator.forward_common_files(
property_type)
backward_files = virtual_calculator.backward_files(property_type)
# backward_files += logs
# ...
inter_type = inter_param_prop['type']
# vasp
if inter_type == "vasp":
mdata = convert_mdata(mdata, ["fp"])
elif inter_type in lammps_task_type:
mdata = convert_mdata(mdata, ["model_devi"])
else:
raise RuntimeError("unknown task %s, something wrong" %
inter_type)
work_path = path_to_work
all_task = tmp_task_list
run_tasks = util.collect_task(all_task, inter_type)
if len(run_tasks) == 0:
continue
else:
ret = pool.apply_async(worker, (
work_path,
all_task,
forward_common_files,
forward_files,
backward_files,
mdata,
inter_type,
))
multiple_ret.append(ret)
pool.close()
pool.join()
for ii in range(len(multiple_ret)):
if not multiple_ret[ii].successful():
raise RuntimeError("Job %d is not successful!" % ii)
print('%d jobs are finished' % len(multiple_ret))
def run_equi(confs, inter_param, mdata):
# find all POSCARs and their name like mp-xxx
# ...
conf_dirs = []
for conf in confs:
conf_dirs.extend(glob.glob(conf))
conf_dirs.sort()
processes = len(conf_dirs)
pool = Pool(processes=processes)
print("Submit job via %d processes" % processes)
# generate a list of task names like mp-xxx/relaxation/relax_task
# ...
work_path_list = []
for ii in conf_dirs:
work_path_list.append(os.path.abspath(os.path.join(ii, 'relaxation')))
all_task = []
for ii in work_path_list:
all_task.append(os.path.join(ii, 'relax_task'))
inter_type = inter_param['type']
# vasp
if inter_type == "vasp":
mdata = convert_mdata(mdata, ["fp"])
elif inter_type in lammps_task_type:
mdata = convert_mdata(mdata, ["model_devi"])
else:
raise RuntimeError("unknown task %s, something wrong" % inter_type)
# dispatch the tasks
# POSCAR here is useless
virtual_calculator = make_calculator(inter_param, "POSCAR")
forward_files = virtual_calculator.forward_files()
forward_common_files = virtual_calculator.forward_common_files()
backward_files = virtual_calculator.backward_files()
# backward_files += logs
# ...
run_tasks = util.collect_task(all_task, inter_type)
if len(run_tasks) == 0:
return
else:
run_tasks = [os.path.basename(ii) for ii in all_task]
machine, resources, command, group_size = util.get_machine_info(
mdata, inter_type)
print('%d tasks will be submited ' % len(run_tasks))
multiple_ret = []
for ii in range(len(work_path_list)):
work_path = work_path_list[ii]
ret = pool.apply_async(worker, (
work_path,
run_tasks[ii],
forward_common_files,
forward_files,
backward_files,
mdata,
inter_type,
))
multiple_ret.append(ret)
pool.close()
pool.join()
for ii in range(len(multiple_ret)):
if not multiple_ret[ii].successful():
raise RuntimeError(
"Task %d is not successful! work_path: %s " %
(ii, work_path_list[ii]))
print('finished')
def gen_init_bulk(args) :
try:
import ruamel
from monty.serialization import loadfn,dumpfn
warnings.simplefilter('ignore', ruamel.yaml.error.MantissaNoDotYAML1_1Warning)
jdata=loadfn(args.PARAM)
if args.MACHINE is not None:
mdata=loadfn(args.MACHINE)
except:
with open (args.PARAM, 'r') as fp :
jdata = json.load (fp)
if args.MACHINE is not None:
with open (args.MACHINE, "r") as fp:
mdata = json.load(fp)
if args.MACHINE is not None:
# Selecting a proper machine
mdata = convert_mdata(mdata, ["fp"])
#disp = make_dispatcher(mdata["fp_machine"])
# Decide work path
out_dir = out_dir_name(jdata)
jdata['out_dir'] = out_dir
dlog.info ("# working dir %s" % out_dir)
# Decide whether to use a given poscar
from_poscar = False
if 'from_poscar' in jdata :
from_poscar = jdata['from_poscar']
# Verify md_nstep
md_nstep_jdata = jdata["md_nstep"]
try:
md_incar = jdata['md_incar']
if os.path.isfile(md_incar):
standard_incar = incar_upper(Incar.from_file(md_incar))
nsw_flag = False
if "NSW" in standard_incar:
nsw_flag = True
nsw_steps = standard_incar['NSW']
#dlog.info("nsw_steps is", nsw_steps)
#dlog.info("md_nstep_jdata is", md_nstep_jdata)
if nsw_flag:
if (nsw_steps != md_nstep_jdata):
dlog.info("WARNING: your set-up for MD steps in PARAM and md_incar are not consistent!")
dlog.info("MD steps in PARAM is %d"%(md_nstep_jdata))
dlog.info("MD steps in md_incar is %d"%(nsw_steps))
dlog.info("DP-GEN will use settings in md_incar!")
jdata['md_nstep'] = nsw_steps
except KeyError:
pass
## correct element name
temp_elements = []
for ele in jdata['elements']:
temp_elements.append(ele[0].upper() + ele[1:])
jdata['elements'] = temp_elements
dlog.info("Elements are %s"% ' '.join(jdata['elements']))
## Iteration
stage_list = [int(i) for i in jdata['stages']]
for stage in stage_list:
if stage == 1 :
dlog.info("Current stage is 1, relax")
create_path(out_dir)
shutil.copy2(args.PARAM, os.path.join(out_dir, 'param.json'))
if from_poscar :
make_super_cell_poscar(jdata)
else :
make_unit_cell(jdata)
make_super_cell(jdata)
place_element(jdata)
if args.MACHINE is not None:
make_vasp_relax(jdata, mdata)
run_vasp_relax(jdata, mdata)
else:
make_vasp_relax(jdata, {"fp_resources":{}})
elif stage == 2 :
dlog.info("Current stage is 2, perturb and scale")
make_scale(jdata)
pert_scaled(jdata)
elif stage == 3 :
dlog.info("Current stage is 3, run a short md")
if args.MACHINE is not None:
make_vasp_md(jdata, mdata)
run_vasp_md(jdata, mdata)
else:
make_vasp_md(jdata, {"fp_resources":{}})
elif stage == 4 :
dlog.info("Current stage is 4, collect data")
coll_vasp_md(jdata)
else :
raise RuntimeError("unknown stage %d" % stage)