def test_single_Vasp_dbinsertion(self):
# add the workflow
structure = self.struct_si
# instructs to use db_file set by FWorker, see env_chk
my_wf = get_wf(structure,
"optimize_only.yaml",
vis=MPRelaxSet(structure, force_gamma=True),
common_params={
"vasp_cmd": VASP_CMD,
"db_file": ">>db_file<<"
})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
# add an msonable object to additional fields
my_wf.fws[0].tasks[-1]['additional_fields'].update(
{"test_additional_field": self.struct_si})
self.lp.add_wf(my_wf)
# run the workflow
rapidfire(self.lp, fworker=_fworker)
d = self.get_task_collection().find_one()
self._check_run(d, mode="structure optimization")
self._check_run(d, mode="additional field")
wf = self.lp.get_wf_by_fw_id(1)
self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()]))
def test_single_Vasp_dbinsertion(self):
# add the workflow
structure = self.struct_si
# instructs to use db_file set by FWorker, see env_chk
my_wf = get_wf(structure, "optimize_only.yaml", vis=MPRelaxSet(structure, force_gamma=True),
common_params={"vasp_cmd": VASP_CMD,
"db_file": ">>db_file<<"})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
# add an msonable object to additional fields
my_wf.fws[0].tasks[-1]['additional_fields'].update(
{"test_additional_field": self.struct_si})
self.lp.add_wf(my_wf)
# run the workflow
# set the db_file variable
rapidfire(self.lp, fworker=FWorker(env={"db_file": os.path.join(db_dir, "db.json")}))
d = self.get_task_collection().find_one()
self._check_run(d, mode="structure optimization")
self._check_run(d, mode="additional field")
wf = self.lp.get_wf_by_fw_id(1)
self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()]))
def wf_scan_opt(structure, c=None):
c = c or {}
vasp_cmd = c.get("VASP_CMD", VASP_CMD)
db_file = c.get("DB_FILE", DB_FILE)
user_incar_settings = c.get("USER_INCAR_SETTINGS", {})
half_kpts = c.get("HALF_KPOINTS_FIRST_RELAX", HALF_KPOINTS_FIRST_RELAX)
ediffg = user_incar_settings.get("EDIFFG", -0.05)
wf = get_wf(structure,
"optimize_only.yaml",
vis=MVLScanRelaxSet(structure,
user_incar_settings=user_incar_settings),
common_params={
"vasp_cmd": vasp_cmd,
"db_file": db_file
})
wf = use_custodian(wf,
custodian_params={
"ediffg": ediffg,
"max_force_threshold": 0,
"half_kpts_first_relax": half_kpts,
"job_type": "metagga_opt_run",
"vasp_cmd": vasp_cmd
})
wf = add_common_powerups(wf, c)
if c.get("ADD_WF_METADATA", ADD_WF_METADATA):
wf = add_wf_metadata(wf, structure)
if c.get("REMOVE_WAVECAR", REMOVE_WAVECAR):
wf = clean_up_files(wf)
return wf
def test_bandgap_check_Vasp(self):
# add the workflow
structure = self.struct_si
# instructs to use db_file set by FWorker, see env_chk
my_wf = get_wf(structure,
"bandstructure.yaml",
vis=MPRelaxSet(structure, force_gamma=True),
common_params={
"vasp_cmd": VASP_CMD,
"db_file": ">>db_file<<"
})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
my_wf = add_namefile(my_wf) # add a slug of fw-name to output files
my_wf = add_bandgap_check(my_wf,
check_bandgap_params={"max_gap": 0.1},
fw_name_constraint="structure optimization")
self.lp.add_wf(my_wf)
# run the workflow
# set the db_file variable
rapidfire(self.lp, fworker=_fworker)
# structure optimization should be completed
self.assertEqual(
self.lp.fireworks.find_one({"name": "Si-structure optimization"},
{"state": 1})["state"], "COMPLETED")
self.assertEqual(
self.lp.fireworks.find_one({"name": "Si-static"},
{"state": 1})["state"], "DEFUSED")
def test_bandgap_check_Vasp(self):
# add the workflow
structure = self.struct_si
# instructs to use db_file set by FWorker, see env_chk
my_wf = get_wf(structure, "bandstructure.yaml",
vis=MPRelaxSet(structure, force_gamma=True),
common_params={"vasp_cmd": VASP_CMD,
"db_file": ">>db_file<<"})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
my_wf = add_namefile(my_wf) # add a slug of fw-name to output files
my_wf = add_bandgap_check(my_wf, check_bandgap_params={"max_gap": 0.1}, fw_name_constraint="structure optimization")
self.lp.add_wf(my_wf)
# run the workflow
# set the db_file variable
rapidfire(self.lp, fworker=FWorker(env={"db_file": os.path.join(db_dir, "db.json")}))
# structure optimization should be completed
self.assertEqual(self.lp.fireworks.find_one(
{"name": "Si-structure optimization"}, {"state": 1})["state"],
"COMPLETED")
self.assertEqual(self.lp.fireworks.find_one(
{"name": "Si-static"}, {"state": 1})["state"],
"DEFUSED")
def _single_vasp_lobster(self,
delete_wavecars=False,
user_supplied_basis=None,
fake=True):
# add the workflow
structure = self.struct_si
my_wf = get_wf_lobster(structure=structure,
c={
"vasp_cmd": VASP_CMD,
"DB_FILE": None
},
user_kpoints_settings={"grid_density": 100},
delete_all_wavecars=delete_wavecars,
user_supplied_basis=user_supplied_basis)
if fake:
my_wf = use_fake_vasp(my_wf, refs_dirs_si_vasp)
my_wf = use_fake_lobster(my_wf, refs_dirs_si_lobster)
else:
my_wf = use_custodian(my_wf)
self.lp.add_wf(my_wf)
# run the workflow
rapidfire(self.lp)
fw = self.lp.get_fw_by_id(fw_id=1)
with open(os.path.join(fw.launches[-1].launch_dir,
"task_lobster.json")) as f:
d = json.load(f)
self._check_run(d, mode="lobsternormal", database=False)
wf = self.lp.get_wf_by_fw_id(1)
self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()]))
def test_trackers(self):
# add the workflow
structure = self.struct_si
my_wf = get_wf(structure,
"optimize_only.yaml",
vis=MPRelaxSet(structure, force_gamma=True),
common_params={"vasp_cmd": VASP_CMD})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
my_wf = add_trackers(my_wf)
self.lp.add_wf(my_wf)
# run the workflow
rapidfire(self.lp, fworker=_fworker)
for x in self.lp.get_tracker_data(1):
for t in x["trackers"]:
self.assertGreater(len(t.content.split("\n")), 20)
wf = self.lp.get_wf_by_fw_id(1)
self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()]))
def _single_lobster_db_insertion(self, fake=True):
structure = self.struct_mp
my_wf = get_wf_lobster_test_basis(
structure=structure,
c={
"vasp_cmd": VASP_CMD,
"DB_FILE": DB_FILE
},
user_kpoints_settings={"grid_density": 100},
delete_all_wavecars=False)
if fake:
my_wf = use_fake_vasp(my_wf, ref_dirs=refs_dirs_complex_vasp)
my_wf = use_fake_lobster(my_wf, ref_dirs=refs_dirs_complex_lobster)
else:
my_wf = use_custodian(my_wf)
self.lp.add_wf(my_wf)
# run the workflow
rapidfire(self.lp)
d = self.get_task_collection(coll_name="lobster").find_one(
filter={"basis_id": 1})
self._check_run(d, mode="lobsternormal")
wf = self.lp.get_wf_by_fw_id(1)
self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()]))
def _single_lobster_db_insertion(self,
delete_wavecars=False,
user_supplied_basis=None,
fake=True):
structure = self.struct_si
my_wf = get_wf_lobster(structure=structure,
c={
"vasp_cmd": VASP_CMD,
"DB_FILE": DB_FILE
},
user_kpoints_settings={"grid_density": 100},
delete_all_wavecars=delete_wavecars,
user_supplied_basis=user_supplied_basis,
additional_outputs=["ICOOPLIST.lobster"])
if fake:
my_wf = use_fake_vasp(my_wf, refs_dirs_si_vasp)
my_wf = use_fake_lobster(my_wf, refs_dirs_si_lobster)
else:
my_wf = use_custodian(my_wf)
self.lp.add_wf(my_wf)
# run the workflow
rapidfire(self.lp)
d = self.get_task_collection(coll_name="lobster").find_one()
if delete_wavecars:
self._check_run(d, mode="lobsternormal_delete_wavecars")
else:
self._check_run(d, mode="lobsternormal")
wf = self.lp.get_wf_by_fw_id(1)
self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()]))
def test_chgcar_db_read(self):
# add the workflow
structure = self.struct_si
# instructs to use db_file set by FWorker, see env_chk
my_wf = get_wf(structure, "static_only.yaml", vis=MPStaticSet(structure, force_gamma=True),
common_params={"vasp_cmd": VASP_CMD,
"db_file": ">>db_file<<"})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
# set the flags for storing charge densties
my_wf.fws[0].tasks[-1]["parse_chgcar"] = True
my_wf.fws[0].tasks[-1]["parse_aeccar"] = True
self.lp.add_wf(my_wf)
# run the workflow
# set the db_file variable
rapidfire(self.lp, fworker=FWorker(env={"db_file": os.path.join(db_dir, "db.json")}))
d = self.get_task_collection().find_one()
self._check_run(d, mode="static")
wf = self.lp.get_wf_by_fw_id(1)
self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()]))
chgcar_fs_id = d["calcs_reversed"][0]["chgcar_fs_id"]
accar0_fs_id = d["calcs_reversed"][0]["aeccar0_fs_id"]
accar2_fs_id = d["calcs_reversed"][0]["aeccar2_fs_id"]
self.assertTrue(bool(chgcar_fs_id))
self.assertTrue(bool(accar0_fs_id))
self.assertTrue(bool(accar2_fs_id))
def test_single_Vasp_dbinsertion(self):
# add the workflow
structure = self.struct_si
# instructs to use db_file set by FWorker, see env_chk
my_wf = get_wf(structure,
"optimize_only.yaml",
vis=MPRelaxSet(structure, force_gamma=True),
common_params={
"vasp_cmd": VASP_CMD,
"db_file": ">>db_file<<"
})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
self.lp.add_wf(my_wf)
# run the workflow
# set the db_file variable
rapidfire(
self.lp,
fworker=FWorker(env={"db_file": os.path.join(db_dir, "db.json")}))
d = self.get_task_collection().find_one()
self._check_run(d, mode="structure optimization")
wf = self.lp.get_wf_by_fw_id(1)
self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()]))
def test_use_scratch_dir(self):
my_wf = self._copy_wf(self.bs_wf)
my_wf = use_custodian(my_wf)
my_wf = use_scratch_dir(my_wf, ">>scratch_dir<<")
found = 0
for fw in my_wf.fws:
for t in fw.tasks:
if 'RunVaspCustodian' in str(t):
self.assertEqual(t["scratch_dir"], ">>scratch_dir<<")
found += 1
self.assertEqual(found, 4)
def test_use_scratch_dir(self):
my_wf = self._copy_wf(self.bs_wf)
my_wf = use_custodian(my_wf)
my_wf = use_scratch_dir(my_wf, ">>scratch_dir<<")
found = 0
for fw in my_wf.fws:
for t in fw.tasks:
if 'RunVaspCustodian' in str(t):
self.assertEqual(t["scratch_dir"], ">>scratch_dir<<")
found += 1
self.assertEqual(found, 4)
def test_bandstructure_Vasp(self):
# add the workflow
structure = self.struct_si
# instructs to use db_file set by FWorker, see env_chk
my_wf = get_wf(structure,
"bandstructure.yaml",
vis=MPRelaxSet(structure, force_gamma=True),
common_params={
"vasp_cmd": VASP_CMD,
"db_file": ">>db_file<<"
})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
my_wf = add_namefile(my_wf) # add a slug of fw-name to output files
self.lp.add_wf(my_wf)
# run the workflow
# set the db_file variable
rapidfire(
self.lp,
fworker=FWorker(env={"db_file": os.path.join(db_dir, "db.json")}))
# make sure the structure relaxation ran OK
d = self.get_task_collection().find_one(
{"task_label": "structure optimization"},
sort=[("_id", DESCENDING)])
self._check_run(d, mode="structure optimization")
# make sure the static run ran OK
d = self.get_task_collection().find_one({"task_label": "static"},
sort=[("_id", DESCENDING)])
self._check_run(d, mode="static")
# make sure the uniform run ran OK
d = self.get_task_collection().find_one({"task_label": "nscf uniform"},
sort=[("_id", DESCENDING)])
self._check_run(d, mode="nscf uniform")
# make sure the uniform run ran OK
d = self.get_task_collection().find_one({"task_label": "nscf line"},
sort=[("_id", DESCENDING)])
self._check_run(d, mode="nscf line")
wf = self.lp.get_wf_by_fw_id(1)
self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()]))
def _run_scan_relax(self, wf, dir_name):
if not VASP_CMD:
wf = use_fake_vasp(wf, {
"SCAN structure optimization":
os.path.join(reference_dir, dir_name)
},
check_kpoints=False,
check_potcar=False,
clear_inputs=False,
check_incar=False)
else:
wf = use_custodian(wf)
wf = use_potcar_spec(wf)
self.lp.add_wf(wf)
# run the workflow
rapidfire(self.lp, fworker=_fworker)
def test_single_Vasp_dbinsertion(self):
# add the workflow
structure = self.struct_si
# instructs to use db_file set by FWorker, see env_chk
my_wf = get_wf(structure, "optimize_only.yaml", vis=MPRelaxSet(structure, force_gamma=True),
common_params={"vasp_cmd": VASP_CMD,
"db_file": ">>db_file<<"})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
self.lp.add_wf(my_wf)
# run the workflow
# set the db_file variable
rapidfire(self.lp, fworker=FWorker(env={"db_file": os.path.join(db_dir, "db.json")}))
d = self._get_task_collection().find_one()
self._check_run(d, mode="structure optimization")
def test_single_Vasp(self):
# add the workflow
structure = self.struct_si
my_wf = get_wf(structure, "optimize_only.yaml", vis=MPRelaxSet(structure, force_gamma=True),
common_params={"vasp_cmd": VASP_CMD})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
self.lp.add_wf(my_wf)
# run the workflow
rapidfire(self.lp, fworker=_fworker)
d = self.get_task_collection().find_one({"task_label": "structure optimization"})
self._check_run(d, mode="structure optimization")
wf = self.lp.get_wf_by_fw_id(1)
self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()]))
def test_single_Vasp(self):
# add the workflow
structure = self.struct_si
my_wf = get_wf(structure, "optimize_only.yaml", vis=MPRelaxSet(structure, force_gamma=True),
common_params={"vasp_cmd": VASP_CMD})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
self.lp.add_wf(my_wf)
# run the workflow
rapidfire(self.lp)
fw = self.lp.get_fw_by_id(1)
with open(os.path.join(fw.launches[-1].launch_dir, "task.json")) as f:
d = json.load(f)
self._check_run(d, mode="structure optimization")
def test_trackers(self):
# add the workflow
structure = self.struct_si
my_wf = get_wf(structure, "optimize_only.yaml",
vis=MPRelaxSet(structure, force_gamma=True),
common_params={"vasp_cmd": VASP_CMD})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
my_wf = add_trackers(my_wf)
self.lp.add_wf(my_wf)
# run the workflow
rapidfire(self.lp)
for x in self.lp.get_tracker_data(1):
for t in x["trackers"]:
self.assertGreater(len(t.content.split("\n")), 20)
def test_bandstructure_Vasp(self):
# add the workflow
structure = self.struct_si
# instructs to use db_file set by FWorker, see env_chk
my_wf = get_wf(structure, "bandstructure.yaml",
vis=MPRelaxSet(structure, force_gamma=True),
common_params={"vasp_cmd": VASP_CMD,
"db_file": ">>db_file<<"})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
my_wf = add_namefile(my_wf) # add a slug of fw-name to output files
self.lp.add_wf(my_wf)
# run the workflow
# set the db_file variable
rapidfire(self.lp, fworker=FWorker(env={"db_file": os.path.join(db_dir, "db.json")}))
# make sure the structure relaxation ran OK
d = self.get_task_collection().find_one({"task_label": "structure optimization"},
sort=[("_id", DESCENDING)])
self._check_run(d, mode="structure optimization")
# make sure the static run ran OK
d = self.get_task_collection().find_one({"task_label": "static"}, sort=[("_id", DESCENDING)])
self._check_run(d, mode="static")
# make sure the uniform run ran OK
d = self.get_task_collection().find_one({"task_label": "nscf uniform"}, sort=[("_id", DESCENDING)])
self._check_run(d, mode="nscf uniform")
# make sure the uniform run ran OK
d = self.get_task_collection().find_one({"task_label": "nscf line"}, sort=[("_id", DESCENDING)])
self._check_run(d, mode="nscf line")
wf = self.lp.get_wf_by_fw_id(1)
self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()]))
def test_single_Vasp(self):
# add the workflow
structure = self.struct_si
my_wf = get_wf(structure, "optimize_only.yaml", vis=MPRelaxSet(structure, force_gamma=True),
common_params={"vasp_cmd": VASP_CMD})
if not VASP_CMD:
my_wf = use_fake_vasp(my_wf, ref_dirs_si)
else:
my_wf = use_custodian(my_wf)
self.lp.add_wf(my_wf)
# run the workflow
rapidfire(self.lp)
fw = self.lp.get_fw_by_id(1)
with open(os.path.join(fw.launches[-1].launch_dir, "task.json")) as f:
d = json.load(f)
self._check_run(d, mode="structure optimization")
wf = self.lp.get_wf_by_fw_id(1)
self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()]))
def wf_scan_opt(structure, c=None):
c = c or {}
vasp_cmd = c.get("VASP_CMD", VASP_CMD)
db_file = c.get("DB_FILE", DB_FILE)
user_incar_settings = c.get("USER_INCAR_SETTINGS", {})
half_kpts = c.get("HALF_KPOINTS_FIRST_RELAX", HALF_KPOINTS_FIRST_RELAX)
ediffg = user_incar_settings.get("EDIFFG", -0.05)
wf = get_wf(
structure,
"optimize_only.yaml",
vis=MVLScanRelaxSet(
structure, user_incar_settings=user_incar_settings),
common_params={
"vasp_cmd": vasp_cmd,
"db_file": db_file
})
wf = use_custodian(
wf,
custodian_params={
"ediffg": ediffg,
"max_force_threshold": 0,
"half_kpts_first_relax": half_kpts,
"job_type": "metagga_opt_run",
"db_file": db_file,
"vasp_cmd": vasp_cmd
})
wf = add_common_powerups(wf, c)
if c.get("ADD_WF_METADATA", ADD_WF_METADATA):
wf = add_wf_metadata(wf, structure)
if c.get("REMOVE_WAVECAR", REMOVE_WAVECAR):
wf = clean_up_files(wf)
return wf
def test_custodian_powerups(self):
my_wf = copy_wf(self.bs_wf)
my_wf = remove_custodian(my_wf)
for fw in my_wf.fws:
task_idx = 1 if "structure optimization" in fw.name else 2
self.assertTrue("RunVaspDirect" in fw.tasks[task_idx]._fw_name)
self.assertEqual(fw.tasks[task_idx]["vasp_cmd"], "test_VASP")
my_wf_double_relax = remove_custodian(copy_wf(self.bs_wf))
my_wf_double_relax = use_custodian(
my_wf_double_relax,
fw_name_constraint="structure optimization",
custodian_params={"job_type": "double_relaxation_run"},
)
for fw in my_wf_double_relax.fws:
if "structure optimization" in fw.name:
self.assertTrue("RunVaspCustodian" in fw.tasks[1]._fw_name)
self.assertEqual(fw.tasks[1]["job_type"], "double_relaxation_run")
else:
self.assertTrue("RunVaspDirect" in fw.tasks[2]._fw_name)
self.assertFalse("job_type" in fw.tasks[2])
def test_custodian_powerups(self):
my_wf = self._copy_wf(self.bs_wf)
my_wf = remove_custodian(my_wf)
for fw in my_wf.fws:
task_idx = 1 if "structure optimization" in fw.name else 2
self.assertTrue(
"RunVaspDirect" in fw.to_dict()["spec"]["_tasks"][task_idx]["_fw_name"])
self.assertEqual(
fw.to_dict()["spec"]["_tasks"][task_idx]["vasp_cmd"], "test_VASP")
my_wf_double_relax = remove_custodian(self._copy_wf(self.bs_wf))
my_wf_double_relax = use_custodian(my_wf_double_relax,
fw_name_constraint="structure optimization",
custodian_params={"job_type": "double_relaxation_run"})
for fw in my_wf_double_relax.fws:
if "structure optimization" in fw.name:
self.assertTrue("RunVaspCustodian" in fw.to_dict()["spec"]["_tasks"][1]["_fw_name"])
self.assertEqual(fw.to_dict()["spec"]["_tasks"][1]["job_type"],
"double_relaxation_run")
else:
self.assertTrue("RunVaspDirect" in fw.to_dict()["spec"]["_tasks"][2]["_fw_name"])
self.assertFalse("job_type" in fw.to_dict()["spec"]["_tasks"][2])
def _run_scan_relax(self, wf, formula):
if not VASP_CMD:
wf = use_fake_vasp(wf, {
"PBEsol structure optimization":
os.path.join(reference_dir,
"PBESol_pre_opt_for_SCAN_{}".format(formula)),
"R2SCAN structure optimization":
os.path.join(reference_dir,
"SCAN_structure_optimization_{}".format(formula))
},
check_kpoints=False,
check_potcar=False,
clear_inputs=False,
check_incar=False)
else:
wf = use_custodian(wf)
wf = use_potcar_spec(wf)
fw_ids = self.lp.add_wf(wf)
# run the workflow
rapidfire(self.lp, fworker=_fworker)
return fw_ids
def get_aneb_wf(
structure,
working_ion,
insert_coords,
insert_coords_combinations,
n_images,
vasp_input_set=None,
override_default_vasp_params=None,
handler_group=None,
selective_dynamics_scheme="fix_two_atom",
launch_mode="all",
vasp_cmd=VASP_CMD,
db_file=DB_FILE,
wall_time=None,
additional_fields=None,
tags=None,
powerup_dicts=None,
name="ApproxNEB",
):
"""
Workflow for running the "ApproxNEB" algorithm to estimate
energetic barriers for a working ion in a structure (host)
between end point positions specified by insert_coords and
insert_coords_combinations. Note this workflow is only
intended for the dilute lattice limit (where one working
ion is in a large supercell structure of the host and
little volume change upon insertion is expected).
By default workflow sets appropriate VASP input parameters
and Custodian handler groups.
This workflow uses an "approx_neb" collection to organize
outputs and generate inputs for new VASP calculations for
easier data management and analysis. An "approx_neb"
additional field is automatically added to all task docs
generated to assist record keeping.
To make modifications to docs generated by this
workflow, use of the additional_fields and tags arguments
is recommended to ensure all fireworks, tasks collection
docs, and approx_neb collection docs are modified.
Args:
structure (Structure): structure of empty host
working_ion: specie of site to insert in structure
(e.g. "Li").
insert_coords (1x3 array or list of 1x3 arrays):
fractional coordinates of site(s) to insert in
structure (e.g. [[0,0,0], [0,0.25,0], [0.5,0,0]]).
insert_coords_combinations (list of strings): list of
strings corresponding to the list index of
insert_coords to specify which combination
of end_points to use for path interpolation.
(e.g. ["0+1", "0+2"])
n_images: n_images (int): number of images
interpolated between end point structures for
each path set by insert_coords_combinations
vasp_input_set (VaspInputSet class): can use to
define VASP input parameters.
See pymatgen.io.vasp.sets module for more
information. MPRelaxSet() and
override_default_vasp_params are used if
vasp_input_set = None.
override_default_vasp_params (dict): if provided,
vasp_input_set is disregarded and the Vasp Input
Set is created by passing override_default_vasp_params
to MPRelaxSet(). Allows for easy modification of
MPRelaxSet().
For example, to set ISIF=2 in the INCAR use:
{"user_incar_settings":{"ISIF":2}}
handler_group (str or [ErrorHandler]): group of handlers to
use for RunVaspCustodian firetask. See handler_groups
dict in the code for the groups and complete list of
handlers in each group. Alternatively, you can specify a
list of ErrorHandler objects.
selective_dynamics_scheme (str): "fix_two_atom"
launch_mode (str): "all" or "screening"
vasp_cmd (str): the name of the full executable for running
VASP.
db_file (str): path to file containing the database
credentials.
wall_time (int): Total walltime in seconds. If this is None and
the job is running on a PBS system, the handler will attempt to
determine the walltime from the PBS_WALLTIME environment
variable. If the wall time cannot be determined or is not
set, this handler will have no effect.
additional_fields (dict): specifies more information
to be stored in the approx_neb collection to
assist user record keeping.
tags (list): list of strings to be stored in the
approx_neb collection under the "tags" field to
assist user record keeping.
powerup_dicts (list): additional powerups given to all the dynamically
created image fireworks
name (str): name for the workflow returned
Returns: Workflow
"""
approx_neb_params = override_default_vasp_params or {
"user_incar_settings": {
"EDIFF": 0.0005,
"EDIFFG": -0.05,
"IBRION": 1,
"ISIF": 3,
"ISMEAR": 0,
"LDAU": False,
"NSW": 400,
"ADDGRID": True,
"ISYM": 1,
"NELMIN": 4,
}
}
handler_group = handler_group or [
VaspErrorHandler(),
MeshSymmetryErrorHandler(),
NonConvergingErrorHandler(),
PotimErrorHandler(),
PositiveEnergyErrorHandler(),
FrozenJobErrorHandler(),
StdErrHandler(),
WalltimeHandler(wall_time=wall_time),
]
wf_uuid = str(uuid4())
additional_fields = deepcopy(additional_fields)
host_fw = HostFW(
structure=structure,
approx_neb_wf_uuid=wf_uuid,
db_file=db_file,
vasp_input_set=vasp_input_set,
vasp_cmd=vasp_cmd,
override_default_vasp_params=deepcopy(approx_neb_params),
additional_fields=additional_fields,
tags=tags,
)
# modifies incar settings needed for end point and image structure relaxations
if "user_incar_settings" not in approx_neb_params.keys():
approx_neb_params = {"user_incar_settings": {}}
approx_neb_params["user_incar_settings"]["ISIF"] = 2
approx_neb_params["user_incar_settings"]["ISYM"] = 0
approx_neb_params["user_incar_settings"]["LDAU"] = False
end_point_fws = []
for n, coord in enumerate(insert_coords):
end_point_fws.append(
EndPointFW(
approx_neb_wf_uuid=wf_uuid,
insert_specie=working_ion,
insert_coords=coord,
end_points_index=n,
db_file=db_file,
override_default_vasp_params=approx_neb_params,
parents=host_fw,
))
evaluate_path_fws = []
for end_points_combo in insert_coords_combinations:
if isinstance(end_points_combo, (str)):
combo = end_points_combo.split("+")
if len(combo) == 2:
c = [int(combo[0]), int(combo[-1])]
else:
raise ValueError(
"string format in insert_coords_combinations is incorrect")
evaluate_path_fws.append(
EvaluatePathFW(
approx_neb_wf_uuid=wf_uuid,
end_points_combo=end_points_combo,
mobile_specie=working_ion,
n_images=n_images,
selective_dynamics_scheme=selective_dynamics_scheme,
launch_mode=launch_mode,
vasp_cmd=vasp_cmd,
db_file=db_file,
override_default_vasp_params=approx_neb_params,
handler_group=handler_group,
parents=[end_point_fws[c[0]], end_point_fws[c[1]]],
add_additional_fields=additional_fields,
add_tags=tags,
))
wf = Workflow([host_fw] + end_point_fws + evaluate_path_fws)
wf = use_custodian(wf, custodian_params={"handler_group": handler_group})
if isinstance(tags, (list)):
wf = add_tags(wf, tags)
if isinstance(additional_fields, (dict)):
wf = add_additional_fields_to_taskdocs(wf,
update_dict=additional_fields)
if powerup_dicts is not None:
wf = powerup_by_kwargs(wf, powerup_dicts)
for fw in wf.fws:
fw.spec["vasp_powerups"] = powerup_dicts
wf.metadata.update({"approx_neb_wf_uuid": wf_uuid})
wf.name = name
return wf