def load_paw(cls, **kwargs):
'''
py:method:: load_paw([family=None][, element=None][, symbol=None])
Load PawData nodes from the databank. Use kwargs to filter.
:return: a list of PawData instances
:rtype: list
:key str family: Filter by family
:key str element: Filter by chemical symbol
:key str symbol: Filter by PAW symbol (example: As vs. As_d)
:raises ValueError: if no PAWs are found
'''
usage_msg = 'use import_family or from_folder to import PAWs'
error_msg = 'no PAWs found for the given kwargs!\n'+usage_msg
group = kwargs.pop('group', None)
family = kwargs.pop('family', None)
silent = kwargs.pop('silent', None)
if not (group or family):
q = QueryTool()
q.set_class(cls)
for k, v in kwargs.iteritems():
q.add_attr_filter(k, '=', v)
res = list(q.run_query())
else:
if family:
group, created = cls.get_or_create_famgroup(family)
elif group:
created = not group._is_stored
try:
paw_filter = cls._node_filter(**kwargs)
res = filter(paw_filter, group.nodes)
except ValueError as e:
if silent:
res = []
elif created:
raise NotExistent('No family with that name exists')
else:
raise e
if not res and not silent:
raise ValueError(error_msg)
return res
calc.use_structure(struct)
calc.use_parameters(parameters)
from aiida.orm.querytool import QueryTool
for e in elements:
fname = None
for name in sssp_names:
if name.lower().startswith("{}.".format(e.lower())):
fname = name
if name.lower().startswith("{}_".format(e.lower())):
fname = name
q = QueryTool()
q.set_class(UpfData)
q.add_attr_filter('filename', 'exact', fname)
upf = q.run_query().next()
calc.use_pseudo(upf, kind=e)
calc.use_kpoints(kpoints)
if settings is not None:
calc.use_settings(settings)
from aiida.common.exceptions import InputValidationError
try:
if submit_test:
subfolder, script_filename = calc.submit_test()
print "Test_submit for calculation (uuid='{}')".format(
calc.uuid)
def get_cifs_with_name(filename):
q = QueryTool()
q.set_class(DataFactory('cif'))
q.add_attr_filter('filename', '=', filename)
return q.run_query()
def load_paw(cls, **kwargs):
q = QueryTool()
q.set_class(cls)
for k, v in kwargs.iteritems():
q.add_attr_filter(k, '=', v)
return list(q.run_query())
