def mpirun(options_obj):
print(COMM.rank)
if COMM.rank == 0:
from optavc.optimize import Optimization
optimization_obj = Optimization(options_obj)
optimization_obj.run()
else:
worker(compute)
'program': "molpro",
'prep_cmd': "module load molpro",
'command':
"molpro -n 8 --nouse-logfile --no-xml-output -o {}/output.dat {}/input.dat",
'time_limit': "08:00:00",
'memory': "4GB",
# 'num_cores' : 1,
'energy_regex': r" ENERGY\(1\)\s+=\s+(-\d+\.\d+)",
'dask': "/global/cscratch1/sd/md38294/scheduler.json",
'success_regex': r" Variable memory released",
'input_name': "input.dat",
'output_name': "output.dat",
'submitter': submitoptavc,
'maxiter': 20,
'findif': {
'points': 3
},
'job_array': True,
'optking': {
'max_force_g_convergence': 1e-7,
'rms_force_g_convergence': 1e-7,
}
}
from optavc.options import Options
options_obj = Options(**options_kwargs)
from optavc.optimize import Optimization
optimization_obj = Optimization(options_obj)
optimization_obj.run()
sync=True,
job_array=optns.job_array_range)
# 2. build an options object
from optavc.options import Options
options_kwargs = {
'template_file_path': "template.dat",
'energy_regex': r"@DF-RHF Final Energy:\s+(-\d+\.\d+)",
'success_regex': r"\*\*\* P[Ss][Ii]4 exiting successfully.",
'queue': "gen4.q",
'program': "psi4@master",
'input_name': "input.dat",
'output_name': "output.dat",
'submitter': submit,
'maxiter': 20,
'job_array': True,
'g_convergence': "gau_verytight",
'findif': {
'points': 3
}
}
options_obj = Options(**options_kwargs)
# 3. call optimizer
from optavc.optimize import Optimization
optimization_obj = Optimization(options_obj)
optimization_obj.run(restart_iteration=4)