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 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 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 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_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)
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 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 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 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 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
