def validate_kpoint_mesh(callback_kwargs, ctx, param, value):
"""
Command line option validator for a kpoints mesh tuple. The value should be a tuple
of three positive integers out of which a KpointsData object will be created with
a mesh equal to the tuple.
:param callback_kwargs: an optional dictionary with arguments for internal use in the validator
:param ctx: internal context of the click.command
:param param: the click Parameter, i.e. either the Option or Argument to which the validator is hooked up
:param value: a tuple of three positive integers
:returns: a KpointsData instance
"""
from aiida.orm.data.array.kpoints import KpointsData
if any([type(i) != int
for i in value]) or any([int(i) <= 0 for i in value]):
raise click.BadParameter(
'all values of the tuple should be positive greater than zero integers'
)
try:
kpoints = KpointsData()
kpoints.set_kpoints_mesh(value)
except ValueError as exception:
raise click.BadParameter(
"failed to create a KpointsData mesh out of {}\n{}".format(
value, exception))
return kpoints
def setup_kpoints(self):
"""
Define the k-point mesh for the Siesta calculation.
"""
self.report('Running setup_kpoints')
kpoints_mesh = KpointsData()
kpmesh=self.ctx.protocol['kpoints_mesh']
kpoints_mesh.set_kpoints_mesh([kpmesh,kpmesh,kpmesh])
self.ctx.kpoints_mesh = kpoints_mesh
def sub_create_bands_data(cls, user=None):
from aiida.orm.data.array.kpoints import KpointsData
from aiida.orm import JobCalculation
from aiida.orm.data.structure import StructureData
from aiida.common.links import LinkType
from aiida.orm.data.array.bands import BandsData
import numpy
s = StructureData(cell=((2., 0., 0.), (0., 2., 0.), (0., 0., 2.)))
s.append_atom(position=(0., 0., 0.),
symbols=['Ba', 'Ti'],
weights=(1., 0.),
name='mytype')
if user is not None:
s.dbnode.user = user._dbuser
s.store()
c = JobCalculation(computer=cls.computer,
resources={
'num_machines': 1,
'num_mpiprocs_per_machine': 1
})
if user is not None:
c.dbnode.user = user._dbuser
c.store()
c.add_link_from(s, "S1", LinkType.INPUT)
c._set_state(calc_states.RETRIEVING)
# define a cell
alat = 4.
cell = numpy.array([
[alat, 0., 0.],
[0., alat, 0.],
[0., 0., alat],
])
k = KpointsData()
k.set_cell(cell)
k.set_kpoints_path()
if user is not None:
k.dbnode.user = user._dbuser
k.store()
b = BandsData()
b.set_kpointsdata(k)
input_bands = numpy.array(
[numpy.ones(4) * i for i in range(k.get_kpoints().shape[0])])
b.set_bands(input_bands, units='eV')
if user is not None:
b.dbnode.user = user._dbuser
b.store()
b.add_link_from(c, link_type=LinkType.CREATE)
return b
def execute(args):
"""
The main execution of the script, which will run some preliminary checks on the command
line arguments before passing them to the workchain and running it
"""
try:
code = Code.get_from_string(args.codename)
except NotExistent as exception:
print "Execution failed: could not retrieve the code '{}'".format(args.codename)
print "Exception report: {}".format(exception)
return
try:
parent_calc = load_node(args.parent_calc)
except NotExistent as exception:
print "Execution failed: failed to load the node for the given parent calculation '{}'".format(args.parent_calc)
print "Exception report: {}".format(exception)
return
if not isinstance(parent_calc, PwCalculation):
print "The provided parent calculation {} is not of type PwCalculation, aborting...".format(args.parent_calc)
return
qpoints = KpointsData()
qpoints.set_kpoints_mesh(args.qpoints)
parameters = {
'INPUTPH': {
'tr2_ph': 1e-10,
}
}
settings = {}
options = {
'resources': {
'num_machines': 1
},
'max_wallclock_seconds': args.max_wallclock_seconds,
}
run(
PhBaseWorkChain,
code=code,
parent_calc=parent_calc,
qpoints=qpoints,
parameters=ParameterData(dict=parameters),
settings=ParameterData(dict=settings),
options=ParameterData(dict=options),
max_iterations=Int(args.max_iterations)
)
def submit_jobs(self):
print("structure PK: %i" % self.inputs.structure.pk)
grp, created = Group.get_or_create(name=self.inputs.group)
grp.add_nodes([self.calc])
print("stress tensor PK: %i" % self.calc.pk)
# get calculation class
C = CalculationFactory(self.inputs.code.get_input_plugin_name())
Proc = C.process()
num_points = 5
# volume scales from 0.94 to 1.06, alat scales as pow(1/3)
scales = numpy.linspace(0.94**(1 / 3.0), 1.06**(1 / 3.0),
num_points).tolist()
calcs = {}
for scale in scales:
print("scale = %f" % scale)
# scaled structure
new_structure = scaled_structure(self.inputs.structure,
Float(scale))
# basic parameters of the calculation
params = calculation_helpers.create_calculation_parameters(
self.inputs.code, str(self.inputs.partition),
int(self.inputs.ranks_per_node), int(self.inputs.ranks_kp),
int(self.inputs.ranks_diag))
inputs = Proc.get_inputs_template()
inputs.code = self.inputs.code
inputs._options.resources = params['calculation_resources']
inputs._options.max_wallclock_seconds = 20 * 60
inputs._options.custom_scheduler_commands = params[
'custom_scheduler_commands']
inputs._options.environment_variables = params[
'environment_variables']
inputs._options.mpirun_extra_params = params['mpirun_extra_params']
inputs.structure = new_structure
inputs.kpoints = KpointsData()
inputs.kpoints.set_kpoints_mesh(self.inputs.kmesh,
offset=(0.0, 0.0, 0.0))
inputs.parameters = params['calculation_parameters']
inputs.settings = params['calculation_settings']
if self.inputs.code.get_input_plugin_name(
) == 'quantumespresso.pw':
inputs.pseudo = get_pseudos(new_structure,
self.inputs.atomic_files)
if self.inputs.code.get_input_plugin_name() == 'exciting.exciting':
inputs.lapwbasis = get_lapwbasis(new_structure,
self.inputs.atomic_files)
future = submit(Proc, **inputs)
def execute(args):
"""
The main execution of the script, which will run some preliminary checks on the command
line arguments before passing them to the workchain and running it
"""
try:
code = Code.get_from_string(args.codename)
except NotExistent as exception:
print "Execution failed: could not retrieve the code '{}'".format(args.codename)
print "Exception report: {}".format(exception)
return
try:
structure = load_node(args.structure)
except NotExistent as exception:
print "Execution failed: failed to load the node for the given structure pk '{}'".format(args.structure)
print "Exception report: {}".format(exception)
return
if not isinstance(structure, StructureData):
print "The provided pk {} for the structure does not correspond to StructureData, aborting...".format(args.parent_calc)
return
kpoints = KpointsData()
kpoints.set_kpoints_mesh(args.kpoints)
parameters = load_property_json('parameters.json')
basis = load_property_json('basis.json')
settings = load_property_json('settings.json')
options = load_property_json('options.json')
options['max_wallclock_seconds'] = args.max_wallclock_seconds
run(
SiestaWorkChain,
code=code,
structure=structure,
pseudo_family=Str(args.pseudo_family),
kpoints=kpoints,
parameters=ParameterData(dict=parameters),
settings=ParameterData(dict=settings),
options=ParameterData(dict=options),
basis=ParameterData(dict=basis),
max_iterations=Int(args.max_iterations),
)
def setup_kpoints(self):
"""
Define the k-point mesh for the relax and scf calculations. Also get the k-point path for
the bands calculation for the initial input structure from SeeKpath
"""
kpoints_mesh = KpointsData()
kpoints_mesh.set_cell_from_structure(self.inputs.structure)
kpoints_mesh.set_kpoints_mesh_from_density(
distance=self.ctx.protocol['kpoints_mesh_density'],
offset=self.ctx.protocol['kpoints_mesh_offset'])
self.ctx.kpoints_mesh = kpoints_mesh
def _get_kpoints(self, nx, use_symmetry=True):
nx = max(1, nx)
kpoints = KpointsData()
if use_symmetry:
kpoints.set_kpoints_mesh([nx, 1, 1], offset=[0.0, 0.0, 0.0])
else:
# list kpoints explicitly
points = [[r, 0.0, 0.0] for r in np.linspace(0, 0.5, nx)]
kpoints.set_kpoints(points)
return kpoints
def setup_kpoints(self):
"""
Define the k-point mesh for the relax and scf calculations.
"""
kpoints_mesh = KpointsData()
kpoints_mesh.set_cell_from_structure(self.ctx.structure_initial_primitive)
kpoints_mesh.set_kpoints_mesh_from_density(
distance=self.ctx.protocol['kpoints_mesh_density'],
offset=self.ctx.protocol['kpoints_mesh_offset']
)
self.ctx.kpoints_mesh = kpoints_mesh
def connect_structure_bands(structure):
alat = 4.
cell = np.array([
[alat, 0., 0.],
[0., alat, 0.],
[0., 0., alat],
])
k = KpointsData()
k.set_cell(cell)
k.set_kpoints_path([('G', 'M', 2)])
b = BandsData()
b.set_kpointsdata(k)
b.set_bands([[1.0, 2.0], [3.0, 4.0]])
k.store()
b.store()
return b
def _legacy_get_explicit_kpoints_path(structure, **kwargs):
"""
Call the get_explicit_kpoints_path of the legacy implementation
:param structure: a StructureData node
:param float kpoint_distance: parameter controlling the distance between kpoints. Distance is
given in crystal coordinates, i.e. the distance is computed in the space of b1, b2, b3.
The distance set will be the closest possible to this value, compatible with the requirement
of putting equispaced points between two special points (since extrema are included).
:param bool cartesian: if set to true, reads the coordinates eventually passed in value as cartesian coordinates
:param float epsilon_length: threshold on lengths comparison, used to get the bravais lattice info
:param float epsilon_angle: threshold on angles comparison, used to get the bravais lattice info
"""
args_recognized = [
'value', 'kpoint_distance', 'cartesian', 'epsilon_length',
'epsilon_angle'
]
args_unknown = set(kwargs).difference(args_recognized)
if args_unknown:
raise ValueError("unknown arguments {}".format(args_unknown))
point_coords, path, bravais_info, explicit_kpoints, labels = legacy.get_explicit_kpoints_path(
cell=structure.cell, pbc=structure.pbc, **kwargs)
kpoints = KpointsData()
kpoints.set_cell(structure.cell)
kpoints.set_kpoints(explicit_kpoints)
kpoints.labels = labels
parameters = {
'bravais_info': bravais_info,
'point_coords': point_coords,
'path': path,
}
return {
'parameters': ParameterData(dict=parameters),
'explicit_kpoints': kpoints
}
def create_kpoints_from_distance(structure, distance, force_parity):
"""
Generate a uniformly spaced kpoint mesh for a given structure where the spacing between kpoints in reciprocal
space is guaranteed to be at least the defined distance.
:param structure: the StructureData to which the mesh should apply
:param distance: a Float with the desired distance between kpoints in reciprocal space
:param force_parity: a Bool to specify whether the generated mesh should maintain parity
:returns: a KpointsData with the generated mesh
"""
from aiida.orm.data.array.kpoints import KpointsData
kpoints = KpointsData()
kpoints.set_cell_from_structure(structure)
kpoints.set_kpoints_mesh_from_density(distance.value,
force_parity=force_parity.value)
return kpoints
def run_seekpath(self):
"""
Run the relaxed structure through SeeKPath to get the new primitive structure, just in case
the symmetry of the cell changed in the cell relaxation step
"""
if 'workchain_relax' not in self.ctx:
structure = self.inputs.structure
else:
try:
structure = self.ctx.workchain_relax.out.output_structure
except:
self.abort_nowait(
'the relax workchain did not output an output_structure node'
)
return
seekpath_parameters = ParameterData(
dict={
'reference_distance': self.inputs.kpoints_distance_bands.value
})
result = seekpath_structure_analysis(structure, seekpath_parameters)
self.ctx.structure = result['primitive_structure']
# Construct a new kpoint mesh for the scf calculation on the current primitive structure
kpoints_mesh = KpointsData()
kpoints_mesh.set_cell_from_structure(self.ctx.structure)
kpoints_mesh.set_kpoints_mesh_from_density(
self.inputs.kpoints_distance.value)
# Save the kpoints objects for the scf and bands calculation in the context
self.ctx.kpoints_mesh = kpoints_mesh
self.ctx.kpoints_path = result['explicit_kpoints']
self.out('primitive_structure', result['primitive_structure'])
self.out('seekpath_parameters', result['parameters'])
def execute(args):
"""
The main execution of the script, which will run some preliminary checks on the command
line arguments before passing them to the workchain and running it
"""
try:
code = Code.get_from_string(args.codename)
except NotExistent as exception:
print "Execution failed: could not retrieve the code '{}'".format(args.codename)
print "Exception report: {}".format(exception)
return
try:
structure = load_node(args.structure)
except:
#
# Slightly distorted structure
#
alat = 5.430 # angstrom
cell = [[0.5*alat, 0.5*alat, 0.,],
[0., 0.5*alat, 0.5*alat,],
[0.5*alat, 0., 0.5*alat,],
]
# Si
# This was originally given in the "ScaledCartesian" format
#
structure = StructureData(cell=cell)
structure.append_atom(position=(0.000*alat,0.000*alat,0.000*alat),symbols=['Si'])
structure.append_atom(position=(0.250*alat,0.245*alat,0.250*alat),symbols=['Si'])
#print "Execution failed: failed to load the node for the given structure pk '{}'".format(args.structure)
#print "Exception report: {}".format(exception)
#return
if not isinstance(structure, StructureData):
print "The provided pk {} for the structure does not correspond to StructureData, aborting...".format(args.parent_calc)
return
kpoints = KpointsData()
kpoints.set_kpoints_mesh(args.kpoints)
bandskpoints = KpointsData()
bandskpoints.set_cell(structure.cell, structure.pbc)
bandskpoints.set_kpoints_path(kpoint_distance = 0.05)
parameters = {
'xc-functional': 'LDA',
'xc-authors': 'CA',
'spinpolarized': False,
'meshcutoff': '150.0 Ry',
'max-scfiterations': 50,
'dm-numberpulay': 4,
'dm-mixingweight': 0.3,
'dm-tolerance': 1.e-4,
'Solution-method': 'diagon',
'electronic-temperature': '25 meV',
'md-typeofrun': 'cg',
'md-numcgsteps': 10,
'md-maxcgdispl': '0.1 Ang',
'md-maxforcetol': '0.04 eV/Ang'
}
# default basis
basis = {
'pao-energy-shift': '100 meV',
'%block pao-basis-sizes': """
Si DZP """,
}
settings = {}
options = {
'resources': {
'num_machines': 1
},
'max_wallclock_seconds': args.max_wallclock_seconds,
}
run(
SiestaBaseWorkChain,
code=code,
structure=structure,
pseudo_family=Str(args.pseudo_family),
kpoints=kpoints,
bandskpoints=bandskpoints,
parameters=ParameterData(dict=parameters),
settings=ParameterData(dict=settings),
options=ParameterData(dict=options),
basis=ParameterData(dict=basis),
max_iterations=Int(args.max_iterations),
)
alat=5.4
alat2=alat/2
alat3=alat2/2
from aiida.orm.data.array.kpoints import KpointsData
kpoints = KpointsData()
kpoints_mesh = 2
kpoints.set_kpoints_mesh([kpoints_mesh,kpoints_mesh,kpoints_mesh])
StructureData = DataFactory("structure")
the_cell = [[alat/2,alat/2,0.],[alat/2,0.,alat/2],[0.,alat/2,alat/2]]
structure = StructureData(cell=the_cell)
structure.cell
structure.append_atom(position=(alat/4.,alat/4.,alat/4.),symbols="Si")
structure.sites
from ase.lattice.spacegroup import crystal
ase_structure = crystal('Si', [(0,0,0)], spacegroup=227,
cellpar=[alat, alat, alat, 90, 90, 90],primitive_cell=True)
structure=StructureData(ase=ase_structure)
structure.store()
nameCode='pw@local-seb'
code=Code.get_from_string(nameCode)
calc=code.new_calc()
calc.label="PW test"
calc.description="First calculus on BaTiO3"
calc.set_resources({"num_machines": 1})
calc.set_max_wallclock_seconds(30*60)
def get_explicit_kpoints_path(structure, parameters):
"""
Return the kpoint path for band structure (in scaled and absolute
coordinates), given a crystal structure,
using the paths proposed in the various publications (see description
of the 'recipe' input parameter). The parameters are the same
as get get_explicit_k_path in __init__, but here all structures are
input and returned as AiiDA structures rather than tuples, and similarly
k-points-related information as a AiiDA KpointsData class.
:param structure: The AiiDA StructureData for which we want to obtain
the suggested path.
:param parameters: A dictionary whose key-value pairs are passed as
additional kwargs to the ``seekpath.get_explicit_k_path`` function.
:return: A dictionary with four nodes:
- ``explicit_kpoints``: a KpointsData with the (explicit) kpoints
(with labels set).
- ``parameters``: a ParameterData, whose content is
the same dictionary as returned by the ``seekpath.get_explicit_k_path`` function
(see `seekpath documentation <https://seekpath.readthedocs.io/>`_),
except that:
- ``conv_lattice``, ``conv_positions``, ``conv_types``
are removed and replaced by the ``conv_structure`` output node
- ``primitive_lattice``, ``primitive_positions``, ``primitive_types``
are removed and replaced by the `primitive_structure` output node
- ``reciprocal_primitive_lattice``, ``explicit_kpoints_abs``,
``explicit_kpoints_rel`` and ``explicit_kpoints_labels`` are removed
and replaced by the ``explicit_kpoints`` output node
- ``primitive_structure``: A StructureData with the primitive structure
- ``conv_structure``: A StructureData with the primitive structure
"""
check_seekpath_is_installed()
import seekpath
structure_tuple, kind_info, kinds = structure_to_spglib_tuple(structure)
result = {}
rawdict = seekpath.get_explicit_k_path(structure=structure_tuple,
**parameters)
# Replace primitive structure with AiiDA StructureData
primitive_lattice = rawdict.pop('primitive_lattice')
primitive_positions = rawdict.pop('primitive_positions')
primitive_types = rawdict.pop('primitive_types')
primitive_tuple = (primitive_lattice, primitive_positions, primitive_types)
primitive_structure = spglib_tuple_to_structure(primitive_tuple, kind_info,
kinds)
# Replace conv structure with AiiDA StructureData
conv_lattice = rawdict.pop('conv_lattice')
conv_positions = rawdict.pop('conv_positions')
conv_types = rawdict.pop('conv_types')
conv_tuple = (conv_lattice, conv_positions, conv_types)
conv_structure = spglib_tuple_to_structure(conv_tuple, kind_info, kinds)
# Remove reciprocal_primitive_lattice, recalculated by kpoints class
rawdict.pop('reciprocal_primitive_lattice')
kpoints_abs = rawdict.pop('explicit_kpoints_abs')
kpoints_rel = rawdict.pop('explicit_kpoints_rel')
kpoints_labels = rawdict.pop('explicit_kpoints_labels')
# set_kpoints expects labels like [[0,'X'],[34,'L'],...], so generate it here skipping empty labels
labels = [[idx, label] for idx, label in enumerate(kpoints_labels)
if label]
kpoints = KpointsData()
kpoints.set_cell_from_structure(primitive_structure)
kpoints.set_kpoints(kpoints_abs, cartesian=True, labels=labels)
result['parameters'] = ParameterData(dict=rawdict)
result['explicit_kpoints'] = kpoints
result['primitive_structure'] = primitive_structure
result['conv_structure'] = conv_structure
return result
def parse_with_retrieved(self, retrieved):
"""
Parse the output nodes for a PwCalculations from a dictionary of retrieved nodes.
Two nodes that are expected are the default 'retrieved' FolderData node which will
store the retrieved files permanently in the repository. The second required node
is the unstored FolderData node with the temporary retrieved files, which should
be passed under the key 'retrieved_temporary_folder_key' of the Parser class.
:param retrieved: a dictionary of retrieved nodes
"""
import os
successful = True
# Load the input dictionary
parameters = self._calc.inp.parameters.get_dict()
# Look for optional settings input node and potential 'parser_options' dictionary within it
try:
settings = self._calc.inp.settings.get_dict()
parser_opts = settings[self.get_parser_settings_key()]
except (AttributeError, KeyError):
settings = {}
parser_opts = {}
# Check that the retrieved folder is there
try:
out_folder = retrieved[self._calc._get_linkname_retrieved()]
except KeyError:
self.logger.error("No retrieved folder found")
return False, ()
# Verify that the retrieved_temporary_folder is within the arguments if temporary files were specified
if self._calc._get_retrieve_temporary_list():
try:
temporary_folder = retrieved[
self.retrieved_temporary_folder_key]
dir_with_bands = temporary_folder.get_abs_path('.')
except KeyError:
self.logger.error(
'the {} was not passed as an argument'.format(
self.retrieved_temporary_folder_key))
return False, ()
else:
dir_with_bands = None
list_of_files = out_folder.get_folder_list()
# The stdout is required for parsing
if self._calc._OUTPUT_FILE_NAME not in list_of_files:
self.logger.error(
"The standard output file '{}' was not found but is required".
format(self._calc._OUTPUT_FILE_NAME))
return False, ()
# The xml file is required for parsing
if self._calc._DATAFILE_XML_BASENAME not in list_of_files:
self.logger.error(
"The xml output file '{}' was not found but is required".
format(self._calc._DATAFILE_XML_BASENAME))
successful = False
xml_file = None
else:
xml_file = os.path.join(out_folder.get_abs_path('.'),
self._calc._DATAFILE_XML_BASENAME)
out_file = os.path.join(out_folder.get_abs_path('.'),
self._calc._OUTPUT_FILE_NAME)
# Call the raw parsing function
parsing_args = [
out_file, parameters, parser_opts, xml_file, dir_with_bands
]
out_dict, trajectory_data, structure_data, bands_data, raw_successful = parse_raw_output(
*parsing_args)
# If calculation was not considered failed already, use the new value
successful = raw_successful if successful else successful
# If the parser option 'all_symmetries' is not set to True, we reduce the raw parsed symmetries to safe space
all_symmetries = parser_opts.get('all_symmetries', False)
if not all_symmetries:
# In the standard output, each symmetry operation print two rotation matrices:
#
# * S_cryst^T: matrix in crystal coordinates, transposed
# * S_cart: matrix in cartesian coordinates,
#
# The XML files only print one matrix:
#
# * S_cryst: matrix in crystal coordinates
#
# The raw parsed symmetry information from the XML is large and will load the database heavily if stored as
# is for each calculation. Instead, we will map these dictionaries onto a static dictionary of rotation
# matrices generated by the _get_qe_symmetry_list static method. This dictionary will return the rotation
# matrices in cartesian coordinates, i.e. S_cart. In order to compare the raw matrices from the XML to these
# static matrices we have to convert S_cryst into S_cart. We derive here how that is done:
#
# S_cryst * v_cryst = v_cryst'
#
# where v_cryst' is the rotated vector v_cryst under S_cryst
# We define `cell` where cell vectors are rows. Converting a vector from crystal to cartesian
# coordinates is defined as:
#
# cell^T * v_cryst = v_cart
#
# The inverse of this operation is defined as
#
# v_cryst = cell^Tinv * v_cart
#
# Replacing the last equation into the first we find:
#
# S_cryst * cell^Tinv * v_cart = cell^Tinv * v_cart'
#
# Multiply on the left with cell^T gives:
#
# cell^T * S_cryst * cell^Tinv * v_cart = v_cart'
#
# which can be rewritten as:
#
# S_cart * v_cart = v_cart'
#
# where:
#
# S_cart = cell^T * S_cryst * cell^Tinv
#
# We compute here the transpose and its inverse of the structure cell basis, which is needed to transform
# the parsed rotation matrices, which are in crystal coordinates, to cartesian coordinates, which are the
# matrices that are returned by the _get_qe_symmetry_list staticmethod
cell = structure_data['cell']['lattice_vectors']
cell_T = numpy.transpose(cell)
cell_Tinv = numpy.linalg.inv(cell_T)
try:
if 'symmetries' in out_dict.keys():
old_symmetries = out_dict['symmetries']
new_symmetries = []
for this_sym in old_symmetries:
name = this_sym['name'].strip()
for i, this in enumerate(self._possible_symmetries):
# Since we do an exact comparison we strip the string name from whitespace
# and as soon as it is matched, we break to prevent it from matching another
if name == this['name'].strip():
index = i
break
else:
index = None
self.logger.error(
'Symmetry {} not found'.format(name))
new_dict = {}
if index is not None:
# The raw parsed rotation matrix is in crystal coordinates, whereas the mapped rotation
# in self._possible_symmetries is in cartesian coordinates. To allow them to be compared
# to make sure we matched the correct rotation symmetry, we first convert the parsed matrix
# to cartesian coordinates. For explanation of the method, see comment above.
rotation_cryst = this_sym['rotation']
rotation_cart_new = self._possible_symmetries[
index]['matrix']
rotation_cart_old = numpy.dot(
cell_T, numpy.dot(rotation_cryst, cell_Tinv))
inversion = self._possible_symmetries[index][
'inversion']
if not are_matrices_equal(
rotation_cart_old,
rotation_cart_new,
swap_sign_matrix_b=inversion):
self.logger.error(
'Mapped rotation matrix {} does not match the original rotation {}'
.format(rotation_cart_new,
rotation_cart_old))
new_dict['all_symmetries'] = this_sym
else:
# Note: here I lose the information about equivalent ions and fractional_translation.
new_dict['t_rev'] = this_sym['t_rev']
new_dict['symmetry_number'] = index
else:
new_dict['all_symmetries'] = this_sym
new_symmetries.append(new_dict)
out_dict[
'symmetries'] = new_symmetries # and overwrite the old one
except KeyError: # no symmetries were parsed (failed case, likely)
self.logger.error("No symmetries were found in output")
new_nodes_list = []
# I eventually save the new structure. structure_data is unnecessary after this
in_struc = self._calc.get_inputs_dict()['structure']
type_calc = parameters['CONTROL']['calculation']
struc = in_struc
if type_calc in ['relax', 'vc-relax', 'md', 'vc-md']:
if 'cell' in structure_data.keys():
struc = convert_qe2aiida_structure(structure_data,
input_structure=in_struc)
new_nodes_list.append(
(self.get_linkname_outstructure(), struc))
k_points_list = trajectory_data.pop('k_points', None)
k_points_weights_list = trajectory_data.pop('k_points_weights', None)
if k_points_list is not None:
# Build the kpoints object
if out_dict['k_points_units'] not in ['2 pi / Angstrom']:
raise QEOutputParsingError(
'Error in kpoints units (should be cartesian)')
kpoints_from_output = KpointsData()
kpoints_from_output.set_cell_from_structure(struc)
kpoints_from_output.set_kpoints(k_points_list,
cartesian=True,
weights=k_points_weights_list)
kpoints_from_input = self._calc.inp.kpoints
if not bands_data:
try:
kpoints_from_input.get_kpoints()
except AttributeError:
new_nodes_list += [(self.get_linkname_out_kpoints(),
kpoints_from_output)]
# Converting bands into a BandsData object (including the kpoints)
if bands_data:
kpoints_for_bands = kpoints_from_output
try:
kpoints_from_input.get_kpoints()
kpoints_for_bands.labels = kpoints_from_input.labels
except (AttributeError, ValueError, TypeError):
# AttributeError: no list of kpoints in input
# ValueError: labels from input do not match the output
# list of kpoints (some kpoints are missing)
# TypeError: labels are not set, so kpoints_from_input.labels=None
pass
# Get the bands occupations and correct the occupations of QE:
# If it computes only one component, it occupies it with half number of electrons
try:
bands_data['occupations'][1]
the_occupations = bands_data['occupations']
except IndexError:
the_occupations = 2. * numpy.array(
bands_data['occupations'][0])
try:
bands_data['bands'][1]
bands_energies = bands_data['bands']
except IndexError:
bands_energies = bands_data['bands'][0]
the_bands_data = BandsData()
the_bands_data.set_kpointsdata(kpoints_for_bands)
the_bands_data.set_bands(bands_energies,
units=bands_data['bands_units'],
occupations=the_occupations)
new_nodes_list += [('output_band', the_bands_data)]
out_dict['linknames_band'] = ['output_band']
# Separate the atomic_occupations dictionary in its own node if it is present
atomic_occupations = out_dict.get('atomic_occupations', {})
if atomic_occupations:
out_dict.pop('atomic_occupations')
atomic_occupations_node = ParameterData(dict=atomic_occupations)
new_nodes_list.append(
('output_atomic_occupations', atomic_occupations_node))
output_params = ParameterData(dict=out_dict)
new_nodes_list.append((self.get_linkname_outparams(), output_params))
if trajectory_data:
from aiida.orm.data.array.trajectory import TrajectoryData
from aiida.orm.data.array import ArrayData
try:
positions = numpy.array(
trajectory_data.pop('atomic_positions_relax'))
try:
cells = numpy.array(
trajectory_data.pop('lattice_vectors_relax'))
# if KeyError, the MD was at fixed cell
except KeyError:
cells = numpy.array([in_struc.cell] * len(positions))
symbols = numpy.array(
[str(i.kind_name) for i in in_struc.sites])
stepids = numpy.arange(
len(positions)) # a growing integer per step
# I will insert time parsing when they fix their issues about time
# printing (logic is broken if restart is on)
traj = TrajectoryData()
traj.set_trajectory(
stepids=stepids,
cells=cells,
symbols=symbols,
positions=positions,
)
for x in trajectory_data.iteritems():
traj.set_array(x[0], numpy.array(x[1]))
new_nodes_list.append(
(self.get_linkname_outtrajectory(), traj))
except KeyError:
# forces, atomic charges and atomic mag. moments, in scf calculation (when outputed)
arraydata = ArrayData()
for x in trajectory_data.iteritems():
arraydata.set_array(x[0], numpy.array(x[1]))
new_nodes_list.append(
(self.get_linkname_outarray(), arraydata))
return successful, new_nodes_list
def parse_with_retrieved(self, retrieved):
"""
Receives in input a dictionary of retrieved nodes.
Does all the logic here.
"""
from aiida.common.exceptions import InvalidOperation
import os
import glob
successful = True
# check if I'm not to overwrite anything
#state = self._calc.get_state()
#if state != calc_states.PARSING:
# raise InvalidOperation("Calculation not in {} state"
# .format(calc_states.PARSING) )
# retrieve the input parameter
calc_input = self._calc.inp.parameters
# look for eventual flags of the parser
try:
parser_opts = self._calc.inp.settings.get_dict()[
self.get_parser_settings_key()]
except (AttributeError, KeyError):
parser_opts = {}
# load the input dictionary
# TODO: pass this input_dict to the parser. It might need it.
input_dict = self._calc.inp.parameters.get_dict()
# Check that the retrieved folder is there
try:
out_folder = retrieved[self._calc._get_linkname_retrieved()]
except KeyError:
self.logger.error("No retrieved folder found")
return False, ()
# check what is inside the folder
list_of_files = out_folder.get_folder_list()
# at least the stdout should exist
if not self._calc._OUTPUT_FILE_NAME in list_of_files:
self.logger.error("Standard output not found")
successful = False
return successful, ()
# if there is something more, I note it down, so to call the raw parser
# with the right options
# look for xml
has_xml = False
if self._calc._DATAFILE_XML_BASENAME in list_of_files:
has_xml = True
# look for bands
has_bands = False
if glob.glob(os.path.join(out_folder.get_abs_path('.'), 'K*[0-9]')):
# Note: assuming format of kpoints subfolder is K*[0-9]
has_bands = True
# TODO: maybe it can be more general than bands only?
out_file = os.path.join(out_folder.get_abs_path('.'),
self._calc._OUTPUT_FILE_NAME)
xml_file = os.path.join(out_folder.get_abs_path('.'),
self._calc._DATAFILE_XML_BASENAME)
dir_with_bands = out_folder.get_abs_path('.')
# call the raw parsing function
parsing_args = [out_file, input_dict, parser_opts]
if has_xml:
parsing_args.append(xml_file)
if has_bands:
if not has_xml:
self.logger.warning("Cannot parse bands if xml file not "
"found")
else:
parsing_args.append(dir_with_bands)
out_dict, trajectory_data, structure_data, raw_successful = parse_raw_output(
*parsing_args)
# if calculation was not considered failed already, use the new value
successful = raw_successful if successful else successful
new_nodes_list = []
# I eventually save the new structure. structure_data is unnecessary after this
in_struc = self._calc.get_inputs_dict()['structure']
type_calc = input_dict['CONTROL']['calculation']
struc = in_struc
if type_calc in ['relax', 'vc-relax', 'md', 'vc-md']:
if 'cell' in structure_data.keys():
struc = convert_qe2aiida_structure(structure_data,
input_structure=in_struc)
new_nodes_list.append(
(self.get_linkname_outstructure(), struc))
k_points_list = trajectory_data.pop('k_points', None)
k_points_weights_list = trajectory_data.pop('k_points_weights', None)
if k_points_list is not None:
# build the kpoints object
if out_dict['k_points_units'] not in ['2 pi / Angstrom']:
raise QEOutputParsingError(
'Error in kpoints units (should be cartesian)')
# converting bands into a BandsData object (including the kpoints)
kpoints_from_output = KpointsData()
kpoints_from_output.set_cell_from_structure(struc)
kpoints_from_output.set_kpoints(k_points_list,
cartesian=True,
weights=k_points_weights_list)
kpoints_from_input = self._calc.inp.kpoints
try:
kpoints_from_input.get_kpoints()
except AttributeError:
new_nodes_list += [(self.get_linkname_out_kpoints(),
kpoints_from_output)]
# convert the dictionary into an AiiDA object
output_params = ParameterData(dict=out_dict)
# return it to the execmanager
new_nodes_list.append((self.get_linkname_outparams(), output_params))
if trajectory_data:
import numpy
from aiida.orm.data.array.trajectory import TrajectoryData
from aiida.orm.data.array import ArrayData
try:
positions = numpy.array(
trajectory_data.pop('atomic_positions_relax'))
try:
cells = numpy.array(
trajectory_data.pop('lattice_vectors_relax'))
# if KeyError, the MD was at fixed cell
except KeyError:
cells = numpy.array([in_struc.cell] * len(positions))
symbols = numpy.array(
[str(i.kind_name) for i in in_struc.sites])
stepids = numpy.arange(
len(positions)) # a growing integer per step
# I will insert time parsing when they fix their issues about time
# printing (logic is broken if restart is on)
traj = TrajectoryData()
traj.set_trajectory(
stepids=stepids,
cells=cells,
symbols=symbols,
positions=positions,
)
for x in trajectory_data.iteritems():
traj.set_array(x[0], numpy.array(x[1]))
# return it to the execmanager
new_nodes_list.append(
(self.get_linkname_outtrajectory(), traj))
except KeyError: # forces in scf calculation (when outputed)
arraydata = ArrayData()
for x in trajectory_data.iteritems():
arraydata.set_array(x[0], numpy.array(x[1]))
# return it to the execmanager
new_nodes_list.append(
(self.get_linkname_outarray(), arraydata))
return successful, new_nodes_list
def parse_with_retrieved(self, retrieved):
"""
Parse the output nodes for a PwCalculations from a dictionary of retrieved nodes.
Two nodes that are expected are the default 'retrieved' FolderData node which will
store the retrieved files permanently in the repository. The second required node
is the unstored FolderData node with the temporary retrieved files, which should
be passed under the key 'retrieved_temporary_folder_key' of the Parser class.
:param retrieved: a dictionary of retrieved nodes
"""
import os
import numpy
successful = True
# Load the input dictionary
parameters = self._calc.inp.parameters.get_dict()
# Look for optional settings input node and potential 'parser_options' dictionary within it
try:
settings = self._calc.inp.settings.get_dict()
parser_opts = settings[self.get_parser_settings_key()]
except (AttributeError, KeyError):
settings = {}
parser_opts = {}
# Check that the retrieved folder is there
try:
out_folder = retrieved[self._calc._get_linkname_retrieved()]
except KeyError:
self.logger.error("No retrieved folder found")
return False, ()
# Verify that the retrieved_temporary_folder is within the arguments if temporary files were specified
if self._calc._get_retrieve_temporary_list():
try:
temporary_folder = retrieved[self.retrieved_temporary_folder_key]
dir_with_bands = temporary_folder.get_abs_path('.')
except KeyError:
self.logger.error('the {} was not passed as an argument'.format(self.retrieved_temporary_folder_key))
return False, ()
else:
dir_with_bands = None
list_of_files = out_folder.get_folder_list()
# The stdout is required for parsing
if not self._calc._OUTPUT_FILE_NAME in list_of_files:
self.logger.error("The standard output file '{}' was not found but is required".format(self._calc._OUTPUT_FILE_NAME))
return False, ()
# The xml file is required for parsing
if not self._calc._DATAFILE_XML_BASENAME in list_of_files:
self.logger.error("The xml output file '{}' was not found but is required".format(self._calc._DATAFILE_XML_BASENAME))
successful = False
xml_file = None
else:
xml_file = os.path.join(out_folder.get_abs_path('.'), self._calc._DATAFILE_XML_BASENAME)
out_file = os.path.join(out_folder.get_abs_path('.'), self._calc._OUTPUT_FILE_NAME)
# Call the raw parsing function
parsing_args = [out_file, parameters, parser_opts, xml_file, dir_with_bands]
out_dict, trajectory_data, structure_data, bands_data, raw_successful = parse_raw_output(*parsing_args)
# If calculation was not considered failed already, use the new value
successful = raw_successful if successful else successful
# The symmetry info has large arrays, that occupy most of the database.
# turns out most of this is due to 64 matrices that are repeated over and over again.
# therefore I map part of the results in a list of dictionaries wrote here once and for all
# if the parser_opts has a key all_symmetries set to True, I don't reduce it
all_symmetries = parser_opts.get('all_symmetries', False)
if not all_symmetries:
try:
if 'symmetries' in out_dict.keys():
old_symmetries = out_dict['symmetries']
new_symmetries = []
for this_sym in old_symmetries:
name = this_sym['name']
index = None
for i,this in enumerate(self._possible_symmetries):
if name in this['name']:
index = i
if index is None:
self.logger.error("Symmetry {} not found".format(name))
new_dict = {}
# note: here I lose the information about equivalent
# ions and fractional_translation.
# They will be present with all_symmetries=True
new_dict['t_rev'] = this_sym['t_rev']
new_dict['symmetry_number'] = index
new_symmetries.append(new_dict)
out_dict['symmetries'] = new_symmetries # and overwrite the old one
except KeyError: # no symmetries were parsed (failed case, likely)
self.logger.error("No symmetries were found in output")
new_nodes_list = []
# I eventually save the new structure. structure_data is unnecessary after this
in_struc = self._calc.get_inputs_dict()['structure']
type_calc = parameters['CONTROL']['calculation']
struc = in_struc
if type_calc in ['relax', 'vc-relax', 'md', 'vc-md']:
if 'cell' in structure_data.keys():
struc = convert_qe2aiida_structure(structure_data, input_structure=in_struc)
new_nodes_list.append((self.get_linkname_outstructure(), struc))
k_points_list = trajectory_data.pop('k_points', None)
k_points_weights_list = trajectory_data.pop('k_points_weights', None)
if k_points_list is not None:
# Build the kpoints object
if out_dict['k_points_units'] not in ['2 pi / Angstrom']:
raise QEOutputParsingError('Error in kpoints units (should be cartesian)')
kpoints_from_output = KpointsData()
kpoints_from_output.set_cell_from_structure(struc)
kpoints_from_output.set_kpoints(k_points_list, cartesian=True, weights=k_points_weights_list)
kpoints_from_input = self._calc.inp.kpoints
if not bands_data:
try:
kpoints_from_input.get_kpoints()
except AttributeError:
new_nodes_list += [(self.get_linkname_out_kpoints(), kpoints_from_output)]
# Converting bands into a BandsData object (including the kpoints)
if bands_data:
kpoints_for_bands = kpoints_from_output
try:
kpoints_from_input.get_kpoints()
kpoints_for_bands.labels = kpoints_from_input.labels
except (AttributeError, ValueError, TypeError):
# AttributeError: no list of kpoints in input
# ValueError: labels from input do not match the output
# list of kpoints (some kpoints are missing)
# TypeError: labels are not set, so kpoints_from_input.labels=None
pass
# Get the bands occupations and correct the occupations of QE:
# If it computes only one component, it occupies it with half number of electrons
try:
bands_data['occupations'][1]
the_occupations = bands_data['occupations']
except IndexError:
the_occupations = 2.*numpy.array(bands_data['occupations'][0])
try:
bands_data['bands'][1]
bands_energies = bands_data['bands']
except IndexError:
bands_energies = bands_data['bands'][0]
the_bands_data = BandsData()
the_bands_data.set_kpointsdata(kpoints_for_bands)
the_bands_data.set_bands(bands_energies,
units = bands_data['bands_units'],
occupations = the_occupations)
new_nodes_list += [('output_band', the_bands_data)]
out_dict['linknames_band'] = ['output_band']
# Separate the atomic_occupations dictionary in its own node if it is present
atomic_occupations = out_dict.get('atomic_occupations', {})
if atomic_occupations:
out_dict.pop('atomic_occupations')
atomic_occupations_node = ParameterData(dict=atomic_occupations)
new_nodes_list.append(('output_atomic_occupations', atomic_occupations_node))
output_params = ParameterData(dict=out_dict)
new_nodes_list.append((self.get_linkname_outparams(), output_params))
if trajectory_data:
from aiida.orm.data.array.trajectory import TrajectoryData
from aiida.orm.data.array import ArrayData
try:
positions = numpy.array( trajectory_data.pop('atomic_positions_relax'))
try:
cells = numpy.array( trajectory_data.pop('lattice_vectors_relax'))
# if KeyError, the MD was at fixed cell
except KeyError:
cells = numpy.array([in_struc.cell] * len(positions))
symbols = numpy.array([str(i.kind_name) for i in in_struc.sites])
stepids = numpy.arange(len(positions)) # a growing integer per step
# I will insert time parsing when they fix their issues about time
# printing (logic is broken if restart is on)
traj = TrajectoryData()
traj.set_trajectory(
stepids = stepids,
cells = cells,
symbols = symbols,
positions = positions,
)
for x in trajectory_data.iteritems():
traj.set_array(x[0],numpy.array(x[1]))
new_nodes_list.append((self.get_linkname_outtrajectory(),traj))
except KeyError:
# forces, atomic charges and atomic mag. moments, in scf calculation (when outputed)
arraydata = ArrayData()
for x in trajectory_data.iteritems():
arraydata.set_array(x[0],numpy.array(x[1]))
new_nodes_list.append((self.get_linkname_outarray(),arraydata))
return successful, new_nodes_list
def submit_stress_tensor(**kwargs):
# get code
#code = Code.get(label='pw.sirius.x', computername='piz_daint', useremail='*****@*****.**')
code = test_and_get_code('pw.sirius.x', expected_code_type='quantumespresso.pw')
#code.set_prepend_text(prep_text)
# calculation should always belong to some group, otherwise things get messy after some time
stress_tensor_grp, created = Group.get_or_create(name=kwargs['group'])
# create parameters
params = create_calculation_parameters(code,
kwargs.get('partition', 'cpu'),
kwargs.get('num_ranks_per_node', 36),
kwargs.get('num_ranks_kp', 1),
kwargs.get('num_ranks_diag', 1))
# load structure
structure = load_node(kwargs['structure_pk'])
# generate k-points
params['kpoints'] = KpointsData()
params['kpoints'].set_kpoints_mesh(kwargs.get('kmesh', [24, 24, 24]), offset=(0.0, 0.0, 0.0))
params['atomic_files'] = kwargs['atomic_files']
params['calculation_wallclock_seconds'] = kwargs.get('time_limit', 3600)
params['structure'] = structure
params['num_points'] = 5
params['group'] = kwargs['group']
params['kpoints'].store()
params['calculation_parameters'].store()
params['calculation_settings'].store()
stress_tensor_dict = {}
stress_tensor_dict['label'] = 'stress_tensor_' + structure.get_formula() + '_' + code.label
stress_tensor_dict['description'] = "Stress tensor for structure with PK=%i"%structure.pk
stress_tensor_dict['calc_pk'] = []
stress_tensor_dict['num_points'] = params['num_points']
stress_tensor_dict['structure_pk'] = structure.pk
stress_tensor_dict['code_pk'] = code.pk
stress_tensor_dict['job_tag'] = params['job_tag']
# volume scales from 0.94 to 1.06, alat scales as pow(1/3)
scales = np.linspace(0.992, 1.008, num=params['num_points']).tolist()
eps = np.linspace(-0.008, 0.008, num=params['num_points']).tolist()
#scales = np.linspace(0.99, 1.05, num=params['num_points']).tolist()
use_symmetry = .False.
if use_symmetry:
SGN = get_space_group_number(structure_id=structure_id)
else:
SGN = 1
LC = self.get_Laue_dict(space_group_number=SGN)
def_list = get_Lagrange_distorted_index(structure_id=structure_id, LC=LC)
SCs = len(def_list)
alat_steps = params['num_points']
distorted_structure_index = []
eps_index = 0
for i in def_list:
for a in eps:
eps_index = eps_index + 1
distorted_structure_index.append(eps_index)
for ii in distorted_structure_index:
a = eps[ii % alat_steps - 1]
i = def_list[int((ii - 1) / alat_steps)]
M_Lagrange_eps = get_Lagrange_strain_matrix(eps=a, def_mtx_index=i)
structure_new = get_Lagrange_distorted_structure(structure_id=structure_id, M_Lagrange_eps=M_Lagrange_eps)
structure_new.store()
calc_label = 'gs_' + structure.get_formula() + '_' + code.label
calc_desc = params['job_tag']
# create calculation
calc = create_calculation(structure_new, params, calc_label, calc_desc)
calc.store()
print "created calculation with uuid='{}' and PK={}".format(calc.uuid, calc.pk)
stress_tensor_grp.add_nodes([calc])
calc.submit()
stress_tensor_dict['calc_pk'].append(calc.pk)
stress_tensor_node = ParameterData(dict=stress_tensor_dict)
stress_tensor_node.store()
stress_tensor_grp.add_nodes([stress_tensor_node])
print "created stress tensor node with uuid='{}' and PK={}".format(stress_tensor_node.uuid, stress_tensor_node.pk)
from aiida.orm.data.base import Str, Int
from aiida.orm.data.array.kpoints import KpointsData
from aiida.orm.data.parameter import ParameterData
from aiida.workflows.user.base import VASPBaseWorkChain
VaspCalculation = CalculationFactory('vasp.vasp')
options = {
'resources': {
'num_machines': 1,
'tot_num_mpiprocs': 1,
},
'max_wallclock_seconds': 1800,
}
kpoints = KpointsData()
kpoints.set_kpoints_mesh([1, 1, 1])
inputs = {
'code': Code.get_from_string('VASP.5.4.4@Raichu'),
'structure': load_node(888),
'kpoints': kpoints,
'parameters': ParameterData(dict={}),
'settings': ParameterData(dict={}),
'pseudo_family': Str('vasp-pbe'),
'options' : ParameterData( dict = {
'max_wallclock_seconds' : 3600,
'max_memory_kb': 10000000,
'resources' : { 'num_machines': 1
},
}),
'tot_num_mpiprocs': 28,
},
'max_wallclock_seconds': 60 * 60 * 10,
})
wannier90_parameters = ParameterData(
dict={
'bands_plot': False,
'num_iter': 12,
'guiding_centres': True,
'num_wann': 4,
#'exclude_bands': exclude_bands,
# 'wannier_plot':True,
# 'wannier_plot_list':[1]
})
structure = load_node(152)
scf_kpoints = KpointsData()
scf_kpoints.set_kpoints_mesh([4, 4, 4])
nscf_kpoints = KpointsData()
nscf_kpoints.set_kpoints_mesh([4, 4, 4])
projections = List()
projections.extend(['As:s', 'As:p'])
wc = submit(
SimpleWannier90WorkChain,
pw_code=Code.get_from_string('pw_6.1@fidis'),
pw2wannier90_code=Code.get_from_string('pw2wannier90_6.1@fidis'),
wannier90_code=Code.get_from_string('wannier90_2.1@fidis'),
#orbital_projections=projections,
structure=structure,
pseudo_family=Str('SSSP_efficiency_v0.95'),
#wannier90_parameters=wannier90_parameters,
scf={
def execute(args):
"""
The main execution of the script, which will run some preliminary checks on the command
line arguments before passing them to the workchain and running it
"""
try:
siesta_code = Code.get_from_string(args.siesta_codename)
except NotExistent as exception:
print "Execution failed: could not retrieve the code '{}'".format(
args.siesta_codename)
print "Exception report: {}".format(exception)
return
try:
gollum_code = Code.get_from_string(args.gollum_codename)
except NotExistent as exception:
print "Execution failed: could not retrieve the code '{}'".format(
args.gollum_codename)
print "Exception report: {}".format(exception)
return
protocol = Str(args.protocol)
###### Siesta structures ##############################
alat = 1.00 # Angstrom. Not passed to the fdf file
# Leads
cellle = [[
20.,
0.,
0.,
], [
0.,
20.,
0.,
], [
0.,
0.,
5.,
]]
sle = StructureData(cell=cellle)
for i in range(0, 2):
sle.append_atom(position=(0., 0., i * 2.5), symbols=['Au'])
if args.structure_em > 0:
structure_le = load_node(args.structure_le)
else:
structure_le = sle
# Extended molecule
cellem = [[
20.,
0.,
0.,
], [
0.,
20.,
0.,
], [
0.,
0.,
45.,
]]
sem = StructureData(cell=cellem)
for i in range(0, 18):
sem.append_atom(position=(0., 0., i * 2.5), symbols=['Au'])
if args.structure_em > 0:
structure_em = load_node(args.structure_em)
else:
structure_em = sem
###### Siesta k-ppoints ###############################
kpoints_le = KpointsData()
kpoints_le.set_kpoints_mesh([1, 1, 90])
kpoints_em = KpointsData()
kpoints_em.set_kpoints_mesh([1, 1, 10])
###### Gollum parameters ##############################
# The "atom" block is definied independently
pms = {
'NBlock leadp': """
2 2 -1
2 2 1 """,
'atom': """
1 2 2
0 0 10
2 2 2 """
}
parameters = ParameterData(dict=pms)
######
run(GollumSiestaWorkChain,
siesta_code=siesta_code,
gollum_code=gollum_code,
structure_le=structure_le,
structure_em=structure_em,
protocol=protocol,
kpoints_le=kpoints_le,
kpoints_em=kpoints_em,
parameters=parameters)
def get_kpointsdata(self):
"""
Return a KpointsData object based on the data in the input file.
This uses all of the data in the input file to do the necessary unit
conversion, ect. and then creates an AiiDa KpointsData object.
**Note:** If the calculation uses only the gamma k-point (`if
self.k_points['type'] == 'gamma'`), it is necessary to also attach a
settings node to the calculation with `gamma_only = True`.
:return: KpointsData object of the kpoints in the input file
:rtype: aiida.orm.data.array.kpoints.KpointsData
:raises NotImplementedError: if the kpoints are
in a format not yet supported.
"""
from aiida.orm.data.array.kpoints import KpointsData
# Initialize the KpointsData node
kpointsdata = KpointsData()
# Get the structure using this class's method.
structuredata = self.get_structuredata()
# Set the structure information of the kpoints node.
kpointsdata.set_cell_from_structure(structuredata)
# Set the kpoints and weights, doing any necessary units conversion.
if self.k_points['type'] == 'crystal': # relative to recip latt vecs
kpointsdata.set_kpoints(self.k_points['points'],
weights=self.k_points['weights'])
elif self.k_points['type'] == 'tpiba': # cartesian; units of 2*pi/alat
alat = np.linalg.norm(structuredata.cell[0]) # alat in Angstrom
kpointsdata.set_kpoints(np.array(self.k_points['points']) *
(2. * np.pi / alat),
weights=self.k_points['weights'],
cartesian=True)
elif self.k_points['type'] == 'automatic':
kpointsdata.set_kpoints_mesh(self.k_points['points'],
offset=self.k_points['offset'])
elif self.k_points['type'] == 'gamma':
kpointsdata.set_kpoints_mesh([1, 1, 1])
else:
raise NotImplementedError(
'Support for creating KpointsData from input units of {} is'
'not yet implemented'.format(self.k_points['type']))
return kpointsdata
def band_parser(band_dat_path, band_kpt_path, special_points, structure):
"""
Parsers the bands output data, along with the special points retrieved
from the input kpoints to construct a BandsData object which is then
returned. Cannot handle discontinuities in the kpath, if two points are
assigned to same spot only one will be passed.
:param band_dat_path: file path to the aiida_band.dat file
:param band_kpt_path: file path to the aiida_band.kpt file
:param special_points: special points to add labels to the bands a dictionary in
the form expected in the input as described in the wannier90 documentation
:return: BandsData object constructed from the input params
"""
import numpy as np
from aiida.orm.data.array.bands import BandsData
from aiida.orm.data.array.kpoints import KpointsData
# imports the data
out_kpt = np.genfromtxt(band_kpt_path, skip_header=1, usecols=(0, 1, 2))
out_dat = np.genfromtxt(band_dat_path, usecols=1)
# reshaps the output bands
out_dat = out_dat.reshape(len(out_kpt), (len(out_dat) / len(out_kpt)),
order="F")
# finds expected points of discontinuity
kpath = special_points['path']
cont_break = [(i, (kpath[i - 1][1], kpath[i][0]))
for i in range(1, len(kpath))
if kpath[i - 1][1] != kpath[i][0]]
# finds the special points
special_points_dict = special_points['point_coords']
labels = [(i, k) for k in special_points_dict for i in range(len(out_kpt))
if all(np.isclose(special_points_dict[k], out_kpt[i]))]
labels.sort()
# Checks and appends labels if discontinuity
appends = []
for x in cont_break:
# two cases the break is before or the break is after
# if the break is before
if labels[x[0]][1] != x[1][0]:
# checks to see if the discontinuity was already there
if labels[x[0] - 1] == x[1][0]:
continue
else:
insert_point = x[0]
new_label = x[1][0]
kpoint = labels[x[0]][0] - 1
appends += [[insert_point, new_label, kpoint]]
# if the break is after
if labels[x[0]][1] != x[1][1]:
# checks to see if the discontinuity was already there
if labels[x[0] + 1] == x[1][1]:
continue
else:
insert_point = x[0] + 1
new_label = x[1][1]
kpoint = labels[x[0]][0] + 1
appends += [[insert_point, new_label, kpoint]]
appends.sort()
for i in range(len(appends)):
append = appends[i]
labels.insert(append[0] + i, (append[2], unicode(append[1])))
bands = BandsData()
k = KpointsData()
k.set_cell_from_structure(structure)
k.set_kpoints(out_kpt, cartesian=False)
bands.set_kpointsdata(k)
bands.set_bands(out_dat, units='eV')
bands.labels = labels
return bands
def execute(args):
"""
The main execution of the script, which will run some preliminary checks on the command
line arguments before passing them to the workchain and running it
"""
try:
code = Code.get_from_string(args.codename)
except NotExistent as exception:
print "Execution failed: could not retrieve the code '{}'".format(args.codename)
print "Exception report: {}".format(exception)
return
try:
structure = load_node(args.structure)
except NotExistent as exception:
print "Execution failed: failed to load the node for the given structure pk '{}'".format(args.structure)
print "Exception report: {}".format(exception)
return
if not isinstance(structure, StructureData):
print "The provided pk {} for the structure does not correspond to StructureData, aborting...".format(args.parent_calc)
return
kpoints = KpointsData()
kpoints.set_kpoints_mesh(args.kpoints)
parameters = {
'xc:functional': 'LDA',
'xc:authors': 'CA',
'spinpolarized': True,
'meshcutoff': '40.000 Ry',
'dm:numberpulay': 4,
'dm:mixingweight': 0.3,
'dm:tolerance': 1.e-3,
'max-scfiterations': 3,
'scf-must-converge': True,
'Solution-method': 'diagon',
'electronic-temperature': '25 meV',
'md-typeofrun': 'CG',
'md-numcgsteps': 0,
'md-maxcgdispl': '0.1 Ang',
'md-maxforcetol': '0.04 eV/Ang',
'writeforces': True,
'writecoorstep': True
}
basis = {
'pao-energy-shift': '300 meV',
'%block pao-basis-sizes': """
Si DZP """,
}
settings = {}
options = {
'resources': {
'num_machines': 1
},
'max_wallclock_seconds': args.max_wallclock_seconds,
}
run(
SiestaBaseWorkChain,
code=code,
structure=structure,
pseudo_family=Str(args.pseudo_family),
kpoints=kpoints,
parameters=ParameterData(dict=parameters),
settings=ParameterData(dict=settings),
options=ParameterData(dict=options),
basis=ParameterData(dict=basis),
max_iterations=Int(args.max_iterations),
)
def execute(args):
"""
The main execution of the script, which will run some preliminary checks on the command
line arguments before passing them to the workchain and running it
"""
try:
code = Code.get_from_string(args.codename)
except NotExistent as exception:
print "Execution failed: could not retrieve the code '{}'".format(
args.codename)
print "Exception report: {}".format(exception)
return
try:
structure = load_node(args.structure)
except NotExistent as exception:
print "Execution failed: failed to load the node for the given structure pk '{}'".format(
args.structure)
print "Exception report: {}".format(exception)
return
if not isinstance(structure, StructureData):
print "The provided pk {} for the structure does not correspond to StructureData, aborting...".format(
args.parent_calc)
return
kpoints = KpointsData()
kpoints.set_kpoints_mesh(args.kpoints)
parameters = {
'xc-functional': 'LDA',
'xc-authors': 'CA',
'mesh-cutoff': '100.000 Ry',
'max-scfiterations': 30,
'dm-numberpulay': 4,
'dm-mixingweight': 0.1,
'dm-tolerance': 1.e-4,
'md-typeofrun': 'cg',
'md-numcgsteps': 8,
'md-maxcgdispl': '0.200 bohr',
'md-maxforcetol': '0.020 eV/Ang',
'geometry-must-converge': True,
'xml-write': True
}
# default basis
basis = {}
settings = {}
options = {
'resources': {
'num_machines': 1
},
'max_wallclock_seconds': args.max_wallclock_seconds,
}
run(
SiestaBaseWorkChain,
code=code,
structure=structure,
pseudo_family=Str(args.pseudo_family),
kpoints=kpoints,
parameters=ParameterData(dict=parameters),
settings=ParameterData(dict=settings),
options=ParameterData(dict=options),
basis=ParameterData(dict=basis),
max_iterations=Int(args.max_iterations),
)
def test_pw_translation(self):
from aiida.tools.dbexporters.tcod \
import translate_calculation_specific_values
# from aiida.tools.dbexporters.tcod_plugins.pw \
# import PwTcodtranslator as PWT
# from aiida.tools.dbexporters.tcod_plugins.cp \
# import CpTcodtranslator as CPT
from aiida.orm.code import Code
from aiida.orm.data.array import ArrayData
from aiida.orm.data.array.kpoints import KpointsData
from aiida.orm.data.parameter import ParameterData
import numpy
from aiida.common.pluginloader import get_plugin
PWT = get_plugin('tools.dbexporters.tcod_plugins',
'quantumespresso.pw')
CPT = get_plugin('tools.dbexporters.tcod_plugins',
'quantumespresso.cp')
code = Code()
code._set_attr('remote_exec_path', '/test')
kpoints = KpointsData()
kpoints.set_kpoints_mesh([2, 3, 4], offset=[0.25, 0.5, 0.75])
def empty_list():
return []
calc = FakeObject({
"inp": {
"parameters": ParameterData(dict={}),
"kpoints": kpoints,
"code": code
},
"out": {
"output_parameters": ParameterData(dict={})
},
"get_inputs": empty_list
})
res = translate_calculation_specific_values(calc, PWT)
self.assertEquals(
res, {
'_dft_BZ_integration_grid_X': 2,
'_dft_BZ_integration_grid_Y': 3,
'_dft_BZ_integration_grid_Z': 4,
'_dft_BZ_integration_grid_shift_X': 0.25,
'_dft_BZ_integration_grid_shift_Y': 0.5,
'_dft_BZ_integration_grid_shift_Z': 0.75,
'_dft_pseudopotential_atom_type': [],
'_dft_pseudopotential_type': [],
'_dft_pseudopotential_type_other_name': [],
'_tcod_software_package': 'Quantum ESPRESSO',
'_tcod_software_executable_path': '/test',
})
calc = FakeObject({
"inp": {
"parameters":
ParameterData(dict={
'SYSTEM': {
'ecutwfc': 40,
'occupations': 'smearing'
}
})
},
"out": {
"output_parameters":
ParameterData(dict={
'number_of_electrons': 10,
})
},
"get_inputs": empty_list
})
res = translate_calculation_specific_values(calc, PWT)
self.assertEquals(
res, {
'_dft_cell_valence_electrons': 10,
'_tcod_software_package': 'Quantum ESPRESSO',
'_dft_BZ_integration_smearing_method': 'Gaussian',
'_dft_pseudopotential_atom_type': [],
'_dft_pseudopotential_type': [],
'_dft_pseudopotential_type_other_name': [],
'_dft_kinetic_energy_cutoff_EEX': 2176.910676048,
'_dft_kinetic_energy_cutoff_charge_density': 2176.910676048,
'_dft_kinetic_energy_cutoff_wavefunctions': 544.227669012,
})
calc = FakeObject({
"inp": {
"parameters": ParameterData(dict={})
},
"out": {
"output_parameters": ParameterData(dict={
'energy_xc': 5,
})
},
"get_inputs": empty_list
})
with self.assertRaises(ValueError):
translate_calculation_specific_values(calc, PWT)
calc = FakeObject({
"inp": {
"parameters": ParameterData(dict={})
},
"out": {
"output_parameters":
ParameterData(dict={
'energy_xc': 5,
'energy_xc_units': 'meV'
})
},
"get_inputs": empty_list
})
with self.assertRaises(ValueError):
translate_calculation_specific_values(calc, PWT)
energies = {
'energy': -3701.7004199449257,
'energy_one_electron': -984.0078459766,
'energy_xc': -706.6986753641559,
'energy_ewald': -2822.6335103043157,
'energy_hartree': 811.6396117001462,
'fermi_energy': 10.25208617898623,
}
dct = energies
for key in energies.keys():
dct["{}_units".format(key)] = 'eV'
calc = FakeObject({
"inp": {
"parameters":
ParameterData(dict={'SYSTEM': {
'smearing': 'mp'
}})
},
"out": {
"output_parameters": ParameterData(dict=dct)
},
"get_inputs": empty_list
})
res = translate_calculation_specific_values(calc, PWT)
self.assertEquals(
res, {
'_tcod_total_energy': energies['energy'],
'_dft_1e_energy': energies['energy_one_electron'],
'_dft_correlation_energy': energies['energy_xc'],
'_dft_ewald_energy': energies['energy_ewald'],
'_dft_hartree_energy': energies['energy_hartree'],
'_dft_fermi_energy': energies['fermi_energy'],
'_tcod_software_package': 'Quantum ESPRESSO',
'_dft_BZ_integration_smearing_method': 'Methfessel-Paxton',
'_dft_BZ_integration_MP_order': 1,
'_dft_pseudopotential_atom_type': [],
'_dft_pseudopotential_type': [],
'_dft_pseudopotential_type_other_name': [],
})
dct = energies
dct['number_of_electrons'] = 10
for key in energies.keys():
dct["{}_units".format(key)] = 'eV'
calc = FakeObject({
"inp": {
"parameters":
ParameterData(dict={'SYSTEM': {
'smearing': 'unknown-method'
}})
},
"out": {
"output_parameters": ParameterData(dict=dct)
},
"get_inputs": empty_list
})
res = translate_calculation_specific_values(calc, CPT)
self.assertEquals(
res, {
'_dft_cell_valence_electrons': 10,
'_tcod_software_package': 'Quantum ESPRESSO'
})
ad = ArrayData()
ad.set_array("forces", numpy.array([[[1, 2, 3], [4, 5, 6]]]))
calc = FakeObject({
"inp": {
"parameters":
ParameterData(dict={'SYSTEM': {
'smearing': 'unknown-method'
}})
},
"out": {
"output_parameters": ParameterData(dict={}),
"output_array": ad
},
"get_inputs": empty_list
})
res = translate_calculation_specific_values(calc, PWT)
self.assertEquals(
res,
{
'_tcod_software_package': 'Quantum ESPRESSO',
'_dft_BZ_integration_smearing_method': 'other',
'_dft_BZ_integration_smearing_method_other': 'unknown-method',
'_dft_pseudopotential_atom_type': [],
'_dft_pseudopotential_type': [],
'_dft_pseudopotential_type_other_name': [],
## Residual forces are no longer produced, as they should
## be in the same CIF loop with coordinates -- to be
## implemented later, since it's not yet clear how.
# '_tcod_atom_site_resid_force_Cartn_x': [1,4],
# '_tcod_atom_site_resid_force_Cartn_y': [2,5],
# '_tcod_atom_site_resid_force_Cartn_z': [3,6],
})
def parse_with_retrieved(self, retrieved):
"""
Parses the datafolder, stores results.
This parser for this simple code does simply store in the DB a node
representing the file of phonon frequencies
"""
from aiida.common.exceptions import InvalidOperation
# suppose at the start that the job is successful
successful = True
new_nodes_list = []
# Check that the retrieved folder is there
try:
out_folder = retrieved[self._calc._get_linkname_retrieved()]
except KeyError:
self.logger.error("No retrieved folder found")
return False, ()
# check what is inside the folder
list_of_files = out_folder.get_folder_list()
# at least the stdout should exist
if not self._calc._OUTPUT_FILE_NAME in list_of_files:
successful = False
self.logger.error("Standard output not found")
return successful, ()
# check that the file has finished (i.e. JOB DONE is inside the file)
filpath = out_folder.get_abs_path(self._calc._OUTPUT_FILE_NAME)
with open(filpath, 'r') as fil:
lines = fil.read()
if "JOB DONE" not in lines:
successful = False
self.logger.error("Computation did not finish properly")
# check that the phonon frequencies file is present
try:
# define phonon frequencies file name
phonon_file = out_folder.get_abs_path(
self._calc._PHONON_FREQUENCIES_NAME)
except OSError:
successful = False
self.logger.error("File with phonon frequencies not found")
return successful, new_nodes_list
# extract the kpoints from the input data and create the kpointsdata for bands
kpointsdata = self._calc.inp.kpoints
try:
kpoints = kpointsdata.get_kpoints()
kpointsdata_for_bands = kpointsdata.copy()
except AttributeError:
kpoints = kpointsdata.get_kpoints_mesh(print_list=True)
kpointsdata_for_bands = KpointsData()
kpointsdata_for_bands.set_kpoints(kpoints)
# find the number of kpoints
num_kpoints = kpoints.shape[0]
# call the raw parsing function
parsed_data = parse_raw_matdyn_phonon_file(phonon_file)
# extract number of kpoints read from the file (and take out from output
# dictionary)
try:
this_num_kpoints = parsed_data.pop('num_kpoints')
except KeyError:
successful = False
self.logger.error("Wrong number of kpoints")
# warning message already in parsed_data
return successful, new_nodes_list
# check that the number of kpoints from the file is the same as the one
# in the input kpoints
if num_kpoints != this_num_kpoints:
successful = False
self.logger.error("Number of kpoints different in input and in "
"phonon frequencies file")
# extract phonon bands (and take out from output dictionary)
phonon_bands = parsed_data.pop('phonon_bands')
# save phonon branches into BandsData
output_bands = BandsData()
output_bands.set_kpointsdata(kpointsdata_for_bands)
output_bands.set_bands(phonon_bands, units='THz')
# convert the dictionary into an AiiDA object (here only warnings remain)
output_params = ParameterData(dict=parsed_data)
for message in parsed_data['warnings']:
self.logger.error(message)
# prepare the list of output nodes to be returned
new_nodes_list = [(self.get_linkname_outparams(), output_params),
(self.get_linkname_outbands(), output_bands)]
return successful, new_nodes_list
def execute(args):
"""
The main execution of the script, which will run some preliminary checks on the command
line arguments before passing them to the workchain and running it
"""
try:
code = Code.get_from_string(args.codename)
except NotExistent as exception:
print "Execution failed: could not retrieve the code '{}'".format(args.codename)
print "Exception report: {}".format(exception)
return
alat = 10.0 # angstrom
cell = [[alat, 0., 0.,],
[0., alat, 0.,],
[0., 0., alat,],
]
# Water molecule
# One of the H atoms is sligthy moved
s = StructureData(cell=cell)
s.append_atom(position=(0.000,0.000,0.00),symbols=['O'])
s.append_atom(position=(0.757,0.586,0.00),symbols=['H'])
s.append_atom(position=(-0.780,0.600,0.00),symbols=['H'])
structure = s
kpoints = KpointsData()
kpoints.set_kpoints_mesh(args.kpoints)
parameters = {
'meshcutoff': '80.000 Ry',
'dm:numberpulay': 4,
'dm:mixingweight': 0.2,
'dm:tolerance': 1.e-3,
'max-scfiterations': 30,
'scf-must-converge': True,
'geometry-must-converge': True,
'electronic-temperature': '25 meV',
'md-typeofrun': 'CG',
'md-numcgsteps': 6,
'md-maxcgdispl': '0.1 Ang',
'md-maxforcetol': '0.03 eV/Ang',
'xml:write': True
}
basis = {
'pao-energy-shift': '300 meV',
'pao-basis-size': 'DZP'
}
settings = {}
options = {
'resources': {
'num_machines': 1
},
'max_wallclock_seconds': args.max_wallclock_seconds,
}
run(
SiestaBaseWorkChain,
code=code,
structure=structure,
pseudo_family=Str(args.pseudo_family),
kpoints=kpoints,
parameters=ParameterData(dict=parameters),
settings=ParameterData(dict=settings),
options=ParameterData(dict=options),
basis=ParameterData(dict=basis),
max_iterations=Int(args.max_iterations),
)
def run_bands(self):
"""
Run the SiestaBaseWorkChain in scf+bands mode on the primitive cell of the relaxed input structure
"""
self.report('Running bands calculation')
try:
structure = self.ctx.workchain_relax.out.output_structure
except:
self.abort_nowait('failed to get the output structure from the relaxation run')
return
self.ctx.structure_relaxed_primitive = structure
inputs = dict(self.ctx.inputs)
kpoints_mesh = KpointsData()
kpoints_mesh.set_cell_from_structure(self.ctx.structure_relaxed_primitive)
kpoints_mesh.set_kpoints_mesh_from_density(
distance=self.ctx.protocol['kpoints_mesh_density'],
offset=self.ctx.protocol['kpoints_mesh_offset'])
bandskpoints = KpointsData()
bandskpoints.set_cell(structure.cell, structure.pbc)
bandskpoints.set_kpoints_path(kpoint_distance = 0.05)
self.ctx.kpoints_path = bandskpoints
# Final input preparation, wrapping dictionaries in ParameterData nodes
inputs['bandskpoints'] = self.ctx.kpoints_path
inputs['kpoints'] = kpoints_mesh
inputs['structure'] = self.ctx.structure_relaxed_primitive
inputs['parameters'] = ParameterData(dict=inputs['parameters'])
inputs['basis'] = ParameterData(dict=inputs['basis'])
inputs['settings'] = ParameterData(dict=inputs['settings'])
running = submit(SiestaBaseWorkChain, **inputs)
self.report('launching SiestaBaseWorkChain<{}> in scf+bands mode'.format(running.pid))
return ToContext(workchain_bands=running)
