def setup_pseudo_potentials(self):
"""
Based on the given input structure and the protocol, use the SSSP library to determine the
optimal pseudo potentials for the different elements in the structure
"""
structure = self.ctx.structure_initial_primitive
pseudo_familyname = self.ctx.protocol['pseudo_familyname']
self.ctx.inputs['pseudos'] = get_pseudos_from_structure(structure, pseudo_familyname)
def setup_pseudo_potentials(self):
"""
Based on the given input structure, get the
pseudo potentials for the different elements in the structure
"""
self.report('Running setup_pseudo_potentials')
structure = self.ctx.structure_initial_primitive
pseudo_familyname = self.ctx.protocol['pseudo_familyname']
self.ctx.rsi_inputs['pseudos'] = get_pseudos_from_structure(structure, pseudo_familyname)
def use_pseudos_from_family(self, family_name):
"""
Set the pseudo to use for all atomic kinds, picking pseudos from the
family with name family_name.
:note: The structure must already be set.
:param family_name: the name of the group containing the pseudos
"""
from collections import defaultdict
try:
## structure = inputdict.pop(self.get_linkname('structure'))
structure = self.get_inputs_dict()[self.get_linkname('structure')]
except AttributeError:
raise ValueError(
"Structure is not set yet! Therefore, the method "
"use_pseudos_from_family cannot automatically set "
"the pseudos")
# A dict {kind_name: pseudo_object}
kind_pseudo_dict = get_pseudos_from_structure(structure, family_name)
# We have to group the species by pseudo, I use the pseudo PK
# pseudo_dict will just map PK->pseudo_object
pseudo_dict = {}
# Will contain a list of all species of the pseudo with given PK
pseudo_species = defaultdict(list)
for kindname, pseudo in kind_pseudo_dict.iteritems():
pseudo_dict[pseudo.pk] = pseudo
pseudo_species[pseudo.pk].append(kindname)
for pseudo_pk in pseudo_dict:
pseudo = pseudo_dict[pseudo_pk]
kinds = pseudo_species[pseudo_pk]
# I set the pseudo for all species, sorting alphabetically
self.use_pseudo(pseudo, sorted(kinds))
def validate_pseudo_potentials(self):
"""
Validate the inputs related to pseudopotentials to check that we have the minimum required
amount of information to be able to run a SiestaCalculation
"""
if all(
[key not in self.inputs for key in ['pseudos', 'pseudo_family']]):
self.abort_nowait(
'neither explicit pseudos nor a pseudo_family was specified in the inputs'
)
return
elif all([key in self.inputs for key in ['pseudos', 'pseudo_family']]):
self.report(
'both explicit pseudos as well as a pseudo_family were specified: using explicit pseudos'
)
self.ctx.inputs['pseudo'] = self.inputs.pseudos
elif 'pseudos' in self.inputs:
self.report(
'only explicit pseudos were specified: using explicit pseudos')
self.ctx.inputs['pseudo'] = self.inputs.pseudos
elif 'pseudo_family' in self.inputs:
self.report(
'only a pseudo_family was specified: using pseudos from pseudo_family'
)
structure = self.inputs.structure
self.ctx.inputs['pseudo'] = get_pseudos_from_structure(
structure, self.inputs.pseudo_family.value)
for kind in self.inputs.structure.get_kind_names():
if kind not in self.ctx.inputs['pseudo']:
self.abort_nowait(
'no pseudo available for element {}'.format(kind))
elif not isinstance(self.ctx.inputs['pseudo'][kind], PsfData):
self.abort_nowait(
'pseudo for element {} is not of type PsfData'.format(
kind))
'md-numcgsteps': 7,
'md-maxcgdispl': '0.200 bohr',
'md-maxforcetol': '0.020 eV/Ang',
'geometry-must-converge': True
}
parameters = Dict(dict=params_dict)
#------------------------------------------------------------------------
#
# No basis set spec in this calculation (default)
#
#--------------------- Pseudopotentials ---------------------------------
#
# FIXME: The family name is hardwired
#
pseudos_dict = get_pseudos_from_structure(s, 'sample_psf_family')
#-----------------------------------------------------------------------
#
#--All the inputs of a Siesta calculations are listed in a dictionary--
#
inputs = {
'structure': s,
'parameters': parameters,
'code': code,
'pseudos': pseudos_dict,
'metadata': {
'options': options,
'label': "Water molecule -- geom fail"
}
}
'pao-energy-shift': '100 meV',
'%block pao-basis-sizes': """
Si DZP
%endblock pao-basis-sizes""",
})
#The kpoints mesh
kpoints = KpointsData()
kpoints.set_kpoints_mesh([11, 11, 11])
##-------------------K-points for bands --------------------
bandskpoints = KpointsData()
bandskpoints = result['explicit_kpoints']
#The pseudopotentials
pseudos_dict = get_pseudos_from_structure(structure, 'nc-sr-04_pbe_standard-psf')
#Resources
options = {
"max_wallclock_seconds": 600,
# "withmpi" : True,
"resources": {
"num_machines": 1,
"num_mpiprocs_per_machine": 1,
}
}
inputs = {
'structure': structure,
'parameters': parameters,
'code': code,