def test_to_from_dict(self):
# no complicated objects in the 'data' or 'nodes' field
a = StructureNL(self.s, self.hulk, ['test_project'], self.pmg,
['remark1'], {"_my_data": "string"},
[self.valid_node, self.valid_node2])
b = StructureNL.from_dict(a.as_dict())
self.assertEqual(a, b)
# complicated objects in the 'data' and 'nodes' field
complicated_node = {
"name": "complicated node",
"url": "www.complicatednodegoeshere.com",
"description": {
"structure": self.s2
}
}
a = StructureNL(self.s, self.hulk, ['test_project'], self.pmg,
['remark1'], {"_my_data": {
"structure": self.s2
}}, [complicated_node, self.valid_node])
b = StructureNL.from_dict(a.as_dict())
self.assertEqual(
a, b, 'to/from dict is broken when object embedding is '
'used! Apparently MontyEncoding is broken...')
#Test molecule
molnl = StructureNL(self.mol, self.hulk, references=self.pmg)
b = StructureNL.from_dict(molnl.as_dict())
self.assertEqual(molnl, b)
def test_to_from_dict(self):
# no complicated objects in the 'data' or 'nodes' field
a = StructureNL(self.s, self.hulk, ['test_project'], self.pmg,
['remark1'], {"_my_data": "string"},
[self.valid_node, self.valid_node2])
b = StructureNL.from_dict(a.as_dict())
self.assertEqual(a, b)
# complicated objects in the 'data' and 'nodes' field
complicated_node = {
"name": "complicated node",
"url": "www.complicatednodegoeshere.com",
"description": {
"structure": self.s2
}
}
a = StructureNL(self.s, self.hulk, ['test_project'], self.pmg,
['remark1'], {"_my_data": {
"structure": self.s2
}}, [complicated_node, self.valid_node])
b = StructureNL.from_dict(a.as_dict())
self.assertEqual(
a, b, 'to/from dict is broken when object embedding is '
'used! Apparently MontyEncoding is broken...')
#Test molecule
molnl = StructureNL(self.mol, self.hulk, references=self.pmg)
b = StructureNL.from_dict(molnl.as_dict())
self.assertEqual(molnl, b)
def run_task(self, fw_spec):
# Read structure from previous relaxation
relaxed_struct = fw_spec['output']['crystal']
# Generate deformed structures
d_struct_set = DeformedStructureSet(relaxed_struct, ns=0.06)
wf=[]
for i, d_struct in enumerate(d_struct_set.def_structs):
fws=[]
connections={}
f = Composition(d_struct.formula).alphabetical_formula
snl = StructureNL(d_struct, 'Joseph Montoya <*****@*****.**>',
projects=["Elasticity"])
tasks = [AddSNLTask()]
snl_priority = fw_spec.get('priority', 1)
spec = {'task_type': 'Add Deformed Struct to SNL database',
'snl': snl.as_dict(),
'_queueadapter': QA_DB,
'_priority': snl_priority}
if 'snlgroup_id' in fw_spec and isinstance(snl, MPStructureNL):
spec['force_mpsnl'] = snl.as_dict()
spec['force_snlgroup_id'] = fw_spec['snlgroup_id']
del spec['snl']
fws.append(Firework(tasks, spec,
name=get_slug(f + '--' + spec['task_type']),
fw_id=-1000+i*10))
connections[-1000+i*10] = [-999+i*10]
spec = snl_to_wf._snl_to_spec(snl,
parameters={'exact_structure':True})
spec = update_spec_force_convergence(spec)
spec['deformation_matrix'] = d_struct_set.deformations[i].tolist()
spec['original_task_id'] = fw_spec["task_id"]
spec['_priority'] = fw_spec['_priority']*2
#Turn off dupefinder for deformed structure
del spec['_dupefinder']
spec['task_type'] = "Optimize deformed structure"
fws.append(Firework([VaspWriterTask(), SetupElastConstTask(),
get_custodian_task(spec)],
spec,
name=get_slug(f + '--' + spec['task_type']),
fw_id=-999+i*10))
priority = fw_spec['_priority']*3
spec = {'task_type': 'VASP db insertion',
'_priority': priority,
'_allow_fizzled_parents': True,
'_queueadapter': QA_DB,
'elastic_constant':"deformed_structure",
'clean_task_doc':True,
'deformation_matrix':d_struct_set.deformations[i].tolist(),
'original_task_id':fw_spec["task_id"]}
fws.append(Firework([VaspToDBTask()],
spec,
name=get_slug(f + '--' + spec['task_type']),
fw_id=-998+i*10))
connections[-999+i*10] = [-998+i*10]
wf.append(Workflow(fws, connections))
return FWAction(additions=wf)
def run_task(self, fw_spec):
# Read structure from previous relaxation
relaxed_struct = fw_spec['output']['crystal']
# Generate deformed structures
d_struct_set = DeformedStructureSet(relaxed_struct, ns=0.06)
wf=[]
for i, d_struct in enumerate(d_struct_set.def_structs):
fws=[]
connections={}
f = Composition(d_struct.formula).alphabetical_formula
snl = StructureNL(d_struct, 'Joseph Montoya <*****@*****.**>',
projects=["Elasticity"])
tasks = [AddSNLTask()]
snl_priority = fw_spec.get('priority', 1)
spec = {'task_type': 'Add Deformed Struct to SNL database',
'snl': snl.as_dict(),
'_queueadapter': QA_DB,
'_priority': snl_priority}
if 'snlgroup_id' in fw_spec and isinstance(snl, MPStructureNL):
spec['force_mpsnl'] = snl.as_dict()
spec['force_snlgroup_id'] = fw_spec['snlgroup_id']
del spec['snl']
fws.append(Firework(tasks, spec,
name=get_slug(f + '--' + spec['task_type']),
fw_id=-1000+i*10))
connections[-1000+i*10] = [-999+i*10]
spec = snl_to_wf._snl_to_spec(snl,
parameters={'exact_structure':True})
spec = update_spec_force_convergence(spec)
spec['deformation_matrix'] = d_struct_set.deformations[i].tolist()
spec['original_task_id'] = fw_spec["task_id"]
spec['_priority'] = fw_spec['_priority']*2
#Turn off dupefinder for deformed structure
del spec['_dupefinder']
spec['task_type'] = "Optimize deformed structure"
fws.append(Firework([VaspWriterTask(), SetupElastConstTask(),
get_custodian_task(spec)],
spec,
name=get_slug(f + '--' + spec['task_type']),
fw_id=-999+i*10))
priority = fw_spec['_priority']*3
spec = {'task_type': 'VASP db insertion',
'_priority': priority,
'_allow_fizzled_parents': True,
'_queueadapter': QA_DB,
'elastic_constant':"deformed_structure",
'clean_task_doc':True,
'deformation_matrix':d_struct_set.deformations[i].tolist(),
'original_task_id':fw_spec["task_id"]}
fws.append(Firework([VaspToDBTask(), AddElasticDataToDBTask()], spec,
name=get_slug(f + '--' + spec['task_type']),
fw_id=-998+i*10))
connections[-999+i*10] = [-998+i*10]
wf.append(Workflow(fws, connections))
return FWAction(additions=wf)
def structure_to_mock_job(structure):
# Needs at least one author. This is for a mock job, so can put whatever.
snl = StructureNL(structure, [{"name": "Saurabh Bajaj", "email": "*****@*****.**"},
{"name": "Anubhav Jain", "email": "*****@*****.**"}])
job = snl.as_dict()
if 'is_valid' not in job:
job.update(get_meta_from_structure(snl.structure))
sorted_structure = snl.structure.get_sorted_structure()
job.update(sorted_structure.as_dict())
return job
def main():
import argparse
parser = argparse.ArgumentParser(
description="Run A QChem Job for a QChem Input File")
parser.add_argument(
"-d",
"--directory",
dest="directory",
type=str,
required=True,
help=
"the directory contains all the QChem jobs to be pretended to run again"
)
parser.add_argument("-p",
"--priority",
dest="priority",
type=int,
default=100,
help="the FireWorks priority")
parser.add_argument("-b",
"--batch_size",
dest="batch_size",
type=int,
default=100,
help="the number of FireWorks in a Workflow")
options = parser.parse_args()
fw_priority = options.priority
batch_size = options.batch_size
lp = LaunchPad.auto_load()
src_dir = os.path.abspath(options.directory)
src_dir_sub_dirs = glob.glob(os.path.join(src_dir, "*"))
num_dirs = len(src_dir_sub_dirs)
current_fwid = 1
links_dict = dict()
fws_all = []
num_fw_in_current_batch = 0
batch_num = 1
for i, sd in enumerate(src_dir_sub_dirs):
if not os.path.isdir(sd):
continue
fw_json_filename = os.path.join(sd, "FW.json")
if not (os.path.exists(fw_json_filename)
or os.path.exists(fw_json_filename + ".gz")):
continue
with zopen(zpath(fw_json_filename), 'rt') as f:
fw_dict = json.load(f)
print("{percent:4.2%} completed, processing directory {d:s}, "
"molecule name {molname:s}," \
" mission {mission:s}".format(percent=i / float(num_dirs), d=sd,
molname=
fw_dict['spec']['user_tags'][
'molname'],
mission=
fw_dict['spec']['user_tags'][
'mission']))
molname = fw_dict['spec']['user_tags']['molname']
egsnl_tasks = [AddEGSNLTask()]
if 'mol' in fw_dict:
mol = Molecule.from_dict(fw_dict['spec']['mol'])
else:
mol = Molecule.from_dict(
fw_dict['spec']['qcinp']['jobs'][0]['molecule'])
snl = StructureNL(mol, "Xiaohui Qu <*****@*****.**>",
"Electrolyte Genome")
egsnl_task_spec = {
'task_type': 'Add to SNL database',
'snl': snl.as_dict(),
'_category': 'Parse Previous QChem Job',
'_priority': fw_priority
}
snl_fw_id = current_fwid
current_fwid += 1
fws_all.append(
Firework(
egsnl_tasks,
egsnl_task_spec,
name=get_slug(molname +
' -- Add to SNL database For fake QChem Task'),
fw_id=snl_fw_id))
fake_qchem_tasks = [FakeRunQChemTask()]
src_qchem_dir = sd
fake_qchem_spec = {
'_priority': fw_priority * 2,
'src_qchem_dir': src_qchem_dir,
'_category': 'Parse Previous QChem Job',
'run_tags': fw_dict['spec']['run_tags'],
'implicit_solvent': fw_dict['spec']['implicit_solvent'],
'task_type': fw_dict['spec']['task_type'],
'charge': fw_dict['spec']['charge'],
'spin_multiplicity': fw_dict['spec']['spin_multiplicity'],
'num_atoms': fw_dict['spec']['num_atoms'],
'user_tags': fw_dict['spec']['user_tags'],
'mol': mol.as_dict(),
'inchi': fw_dict['spec']['inchi'],
'_dupefinder': fw_dict['spec']['_dupefinder'],
'qcinp': fw_dict['spec']['qcinp'],
'qm_method': fw_dict['spec']['qm_method'],
'inchi_root': fw_dict['spec']['inchi_root']
}
for k in ['mixed_basis', 'mixed_aux_basis']:
if k in fw_dict['spec']:
fake_qchem_spec[k] = fw_dict['spec'][k]
fake_qchem_fw_id = current_fwid
current_fwid += 1
fws_all.append(
Firework(fake_qchem_tasks,
fake_qchem_spec,
name='Fake' + fw_dict['name'],
fw_id=fake_qchem_fw_id))
links_dict[snl_fw_id] = fake_qchem_fw_id
num_fw_in_current_batch += 1
if num_fw_in_current_batch >= 100:
wf = Workflow(fws_all, links_dict,
"Read Previous QChem Jobs Id-{}".format(batch_num))
lp.add_wf(wf)
batch_num += 1
links_dict = dict()
fws_all = []
num_fw_in_current_batch = 0
if num_fw_in_current_batch > 0:
wf = Workflow(fws_all, links_dict, "Read Previous QChem Jobs")
lp.add_wf(wf)
