def set_optimization_tag(self, fractal_uri, tag, dataset_name):
from qcportal.models.task_models import PriorityEnum
client = FractalClient(fractal_uri, verify=False)
optds = client.get_collection("OptimizationDataset", dataset_name)
optds.status()
opts = optds.df.values.flatten()
optids = [opt.id for opt in opts if opt.status != 'COMPLETE']
for id in optids:
client.modify_tasks(operation='modify',
base_result=id,
new_tag=tag)
def set_optimization_priority(self, fractal_uri, priority, dataset_name):
from qcportal.models.task_models import PriorityEnum
client = FractalClient(fractal_uri, verify=False)
optds = client.get_collection("OptimizationDataset", dataset_name)
optds.status()
opts = optds.df.values.flatten()
priority_map = {
"high": PriorityEnum.HIGH,
"normal": PriorityEnum.NORMAL,
"low": PriorityEnum.LOW
}
optids = [opt.id for opt in opts if opt.status != 'COMPLETE']
for id in optids:
client.modify_tasks(operation='modify',
base_result=id,
new_priority=priority_map[priority])
def errorcycle_optimizations(self,
fractal_uri,
dataset_name,
client=None,
compute_specs=None,
molids=None):
"""Restart optimizations that have failed.
Parameters
----------
compute_specs : iterable
Iterable of compute spec names to error cycle only.
molids : iterable
Iterable of molecule ids to error cycle only.
"""
if client is None:
client = FractalClient(fractal_uri, verify=False)
optds = client.get_collection("OptimizationDataset", dataset_name)
optds.status()
df = optds.df
if (molids is not None) and (len(molids) != 0):
df = df.loc[list(molids)]
if compute_specs is not None:
df = df[compute_specs]
for opt in df.values.flatten():
if opt.status == 'ERROR':
client.modify_tasks(operation='restart', base_result=opt.id)
print(f"Restarted ERRORed optimization `{opt.id}`")
if opt.status == 'INCOMPLETE' and (opt.final_molecule is not None):
client.modify_tasks(operation='regenerate', base_result=opt.id)
print(f"Regnerated INCOMPLETE optimization `{opt.id}`")