def test_bandsexport_single_kp(self):
"""
Plot band for single k-point (issue #2462).
"""
kpnts = KpointsData()
kpnts.set_kpoints([[0., 0., 0.]])
bands = BandsData()
bands.set_kpointsdata(kpnts)
bands.set_bands([[1.0, 2.0]])
bands.store()
# matplotlib
options = [str(bands.id), '--format', 'mpl_singlefile']
res = self.cli_runner.invoke(cmd_bands.bands_export,
options,
catch_exceptions=False)
self.assertIn(
b'p.scatter', res.stdout_bytes,
'The string p.scatter was not found in the bands mpl export')
# gnuplot
with self.cli_runner.isolated_filesystem():
options = [str(bands.id), '--format', 'gnuplot', '-o', 'bands.gnu']
self.cli_runner.invoke(cmd_bands.bands_export,
options,
catch_exceptions=False)
with open('bands.gnu', 'r') as gnu_file:
res = gnu_file.read()
self.assertIn(
'vectors nohead', res,
'The string "vectors nohead" was not found in the gnuplot script'
)
def create_aiida_bands_data(fleurinp, retrieved):
"""
Creates :py:class:`aiida.orm.BandsData` object containing the kpoints and eigenvalues
from the `banddos.hdf` file of the calculation
:param fleurinp: :py:class:`~aiida_fleur.data.fleurinp.FleurinpData` for the calculation
:param retrieved: :py:class:`aiida.orm.FolderData` for the bandstructure calculation
:returns: :py:class:`aiida.orm.BandsData` for the bandstructure calculation
:raises: ExitCode 300, banddos.hdf file is missing
:raises: ExitCode 310, banddos.hdf reading failed
:raises: ExitCode 320, reading kpointsdata from Fleurinp failed
"""
from masci_tools.io.parsers.hdf5 import HDF5Reader, HDF5TransformationError
from masci_tools.io.parsers.hdf5.recipes import FleurSimpleBands #no projections only eigenvalues for now
from aiida.engine import ExitCode
try:
kpoints = fleurinp.get_kpointsdata_ncf(only_used=True)
except ValueError as exc:
return ExitCode(
320,
message=f'Retrieving kpoints data from fleurinp failed with: {exc}'
)
if 'banddos.hdf' in retrieved.list_object_names():
try:
with retrieved.open('banddos.hdf', 'rb') as f:
with HDF5Reader(f) as reader:
data, attributes = reader.read(recipe=FleurSimpleBands)
except (HDF5TransformationError, ValueError) as exc:
return ExitCode(310,
message=f'banddos.hdf reading failed with: {exc}')
else:
return ExitCode(300,
message='banddos.hdf file not in the retrieved files')
bands = BandsData()
bands.set_kpointsdata(kpoints)
nkpts, nbands = attributes['nkpts'], attributes['nbands']
eigenvalues = data['eigenvalues_up'].reshape((nkpts, nbands))
if 'eigenvalues_down' in data:
eigenvalues_dn = data['eigenvalues_down'].reshape((nkpts, nbands))
eigenvalues = [eigenvalues, eigenvalues_dn]
bands.set_bands(eigenvalues, units='eV')
bands.label = 'output_banddos_wc_bands'
bands.description = (
'Contains BandsData for the bandstructure calculation')
return bands
def connect_structure_bands(strct): # pylint: disable=unused-argument
alat = 4.
cell = np.array([
[alat, 0., 0.],
[0., alat, 0.],
[0., 0., alat],
])
kpnts = KpointsData()
kpnts.set_cell(cell)
kpnts.set_kpoints([[0., 0., 0.], [0.1, 0.1, 0.1]])
bands = BandsData()
bands.set_kpointsdata(kpnts)
bands.set_bands([[1.0, 2.0], [3.0, 4.0]])
return bands
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([[0., 0., 0.], [0.1, 0.1, 0.1]])
b = BandsData()
b.set_kpointsdata(k)
b.set_bands([[1.0, 2.0], [3.0, 4.0]])
return b
def spin_dependent_subparser(out_info_dict):
"""This find the projection and bands arrays from the out_file and out_info_dict. Used to handle the different
possible spin-cases in a convenient manner.
:param out_info_dict: contains various technical internals useful in parsing
:return: ProjectionData, BandsData parsed from out_file
"""
out_file = out_info_dict['out_file']
spin_down = out_info_dict['spin_down']
od = out_info_dict #using a shorter name for convenience
# regular expressions needed for later parsing
WaveFraction1_re = re.compile(r'\=(.*?)\*') # state composition 1
WaveFractionremain_re = re.compile(r'\+(.*?)\*') # state comp 2
FunctionId_re = re.compile(r'\#(.*?)\]') # state identity
# primes arrays for the later parsing
num_wfc = len(od['wfc_lines'])
bands = np.zeros([od['k_states'], od['num_bands']])
projection_arrays = np.zeros([od['k_states'], od['num_bands'], num_wfc])
try:
for i in range(od['k_states']):
if spin_down:
i += od['k_states']
# grabs band energy
for j in range(i * od['num_bands'], (i + 1) * od['num_bands'], 1):
out_ind = od['e_lines'][j]
try:
# post ~6.3 output format "e ="
val = out_file[out_ind].split()[2]
float(val)
except ValueError:
# pre ~6.3 output format? "==== e("
val = out_file[out_ind].split()[4]
bands[i % od['k_states']][j % od['num_bands']] = val
#subloop grabs pdos
wave_fraction = []
wave_id = []
for k in range(od['e_lines'][j] + 1, od['psi_lines'][j], 1):
out_line = out_file[k]
wave_fraction += WaveFraction1_re.findall(out_line)
wave_fraction += WaveFractionremain_re.findall(out_line)
wave_id += FunctionId_re.findall(out_line)
if len(wave_id) != len(wave_fraction):
raise IndexError
for l in range(len(wave_id)):
wave_id[l] = int(wave_id[l])
wave_fraction[l] = float(wave_fraction[l])
#sets relevant values in pdos_array
projection_arrays[i % od['k_states']][j % od['num_bands']][
wave_id[l] - 1] = wave_fraction[l]
except IndexError:
raise QEOutputParsingError(
'the standard out file does not comply with the official documentation.'
)
bands_data = BandsData()
# Attempts to retrieve the kpoints from the parent calc
parent_calc = out_info_dict['parent_calc']
try:
parent_kpoints = parent_calc.get_incoming(
link_label_filter='kpoints').one().node
except ValueError:
raise QEOutputParsingError(
'The parent had no input kpoints! Cannot parse from this!')
try:
if len(od['k_vect']) != len(parent_kpoints.get_kpoints()):
raise AttributeError
bands_data.set_kpointsdata(parent_kpoints)
except AttributeError:
bands_data.set_kpoints(od['k_vect'].astype(float))
bands_data.set_bands(bands, units='eV')
orbitals = out_info_dict['orbitals']
if len(orbitals) != np.shape(projection_arrays[0, 0, :])[0]:
raise QEOutputParsingError('There was an internal parsing error, '
' the projection array shape does not agree'
' with the number of orbitals')
projection_data = ProjectionData()
projection_data.set_reference_bandsdata(bands_data)
projections = [projection_arrays[:, :, i] for i in range(len(orbitals))]
# Do the bands_check manually here
for projection in projections:
if np.shape(projection) != np.shape(bands):
raise AttributeError('Projections not the same shape as the bands')
#insert here some logic to assign pdos to the orbitals
pdos_arrays = spin_dependent_pdos_subparser(out_info_dict)
energy_arrays = [out_info_dict['energy']] * len(orbitals)
projection_data.set_projectiondata(orbitals,
list_of_projections=projections,
list_of_energy=energy_arrays,
list_of_pdos=pdos_arrays,
bands_check=False)
# pdos=pdos_arrays
return bands_data, projection_data
def parse(self, **kwargs): # noqa: MC0001 - is mccabe too complex funct -
"""
Receives in input a dictionary of retrieved nodes. Does all the logic here.
"""
from aiida.engine import ExitCode
parser_info = {}
parser_info['parser_info'] = 'AiiDA Siesta Parser V. {}'.format(
self._version)
try:
output_folder = self.retrieved
except exceptions.NotExistent:
raise OutputParsingError("Folder not retrieved")
output_path, messages_path, xml_path, json_path, bands_path, basis_enthalpy_path = \
self._fetch_output_files(output_folder)
if xml_path is None:
raise OutputParsingError("Xml file not retrieved")
xmldoc = get_parsed_xml_doc(xml_path)
result_dict = get_dict_from_xml_doc(xmldoc)
if output_path is None:
raise OutputParsingError("output file not retrieved")
output_dict = dict(
list(result_dict.items()) + list(parser_info.items()))
warnings_list = []
if json_path is not None:
from .json_time import get_timing_info
global_time, timing_decomp = get_timing_info(json_path)
if global_time is None:
warnings_list.append(["Cannot fully parse the time.json file"])
else:
output_dict["global_time"] = global_time
output_dict["timing_decomposition"] = timing_decomp
if basis_enthalpy_path is not None:
the_file = open(basis_enthalpy_path)
bas_enthalpy = float(the_file.read().split()[0])
the_file.close()
output_dict["basis_enthalpy"] = bas_enthalpy
output_dict["basis_enthalpy_units"] = "eV"
else:
warnings_list.append(["BASIS_ENTHALPY file not retrieved"])
have_errors_to_analyse = False
if messages_path is None:
# Perhaps using an old version of Siesta
warnings_list.append([
'WARNING: No MESSAGES file, could not check if calculation terminated correctly'
])
else:
have_errors_to_analyse = True
#succesful when "INFO: Job completed" is present in message files
succesful, from_message = self._get_warnings_from_file(
messages_path)
warnings_list.append(from_message)
output_dict["warnings"] = warnings_list
# An output_parametrs port is always return, even if only parser's info are present
output_data = Dict(dict=output_dict)
self.out('output_parameters', output_data)
#
# When using floating sites, Siesta associates 'atomic positions' to them, and
# the structure and forces in the XML file include these fake atoms.
# In order to return physical structures and forces, we need to remove them.
# Recall that the input structure is the physical one, and the floating sites
# are specified in the 'basis' input
#
physical_structure = self.node.inputs.structure
number_of_real_atoms = len(physical_structure.sites)
# If the structure has changed, save it
#
if output_dict['variable_geometry']:
in_struc = self.node.inputs.structure
# The next function never fails. If problems arise, the initial structure is
# returned. The input structure is also necessary because the CML file
# traditionally contains only the atomic symbols and not the site names.
# The returned structure does not have any floating atoms, they are removed
# in the `get_last_structure` call.
success, out_struc = get_last_structure(xmldoc, in_struc)
if not success:
self.logger.warning(
"Problem in parsing final structure, returning inp structure in output_structure"
)
self.out('output_structure', out_struc)
# Attempt to parse forces and stresses. In case of failure "None" is returned.
# Therefore the function never crashes
forces, stress = get_final_forces_and_stress(xmldoc)
if forces is not None and stress is not None:
from aiida.orm import ArrayData
arraydata = ArrayData()
arraydata.set_array('forces',
np.array(forces[0:number_of_real_atoms]))
arraydata.set_array('stress', np.array(stress))
self.out('forces_and_stress', arraydata)
#Attempt to parse the ion files. Files ".ion.xml" are not produced by siesta if ions file are used
#in input (`user-basis = T`). This explains the first "if" statement. The SiestaCal input is called
#`ions__El` (El is the element label) therefore we look for the str "ions" in any of the inputs name.
if not any(["ions" in inp for inp in self.node.inputs]): #pylint: disable=too-many-nested-blocks
from aiida_siesta.data.ion import IonData
ions = {}
#Ions from the structure
in_struc = self.node.inputs.structure
for kind in in_struc.get_kind_names():
ion_file_name = kind + ".ion.xml"
if ion_file_name in output_folder._repository.list_object_names(
):
ion_file_path = os.path.join(
output_folder._repository._get_base_folder().abspath,
ion_file_name)
ions[kind] = IonData(ion_file_path)
else:
self.logger.warning(f"no ion file retrieved for {kind}")
#Ions from floating_sites
if "basis" in self.node.inputs:
basis_dict = self.node.inputs.basis.get_dict()
if "floating_sites" in basis_dict:
floating_kinds = []
for orb in basis_dict["floating_sites"]:
if orb["name"] not in floating_kinds:
floating_kinds.append(orb["name"])
ion_file_name = orb["name"] + ".ion.xml"
if ion_file_name in output_folder._repository.list_object_names(
):
ion_file_path = os.path.join(
output_folder._repository._get_base_folder(
).abspath, ion_file_name)
ions[orb["name"]] = IonData(ion_file_path)
else:
self.logger.warning(
f"no ion file retrieved for {orb['name']}")
#Return the outputs
if ions:
self.out('ion_files', ions)
# Error analysis
if have_errors_to_analyse:
# No metter if "INFO: Job completed" is present (succesfull) or not, we check for known
# errors. They might apprear as WARNING (therefore with succesful True) or FATAL
# (succesful False)
for line in from_message:
if u'split options' in line:
min_split = get_min_split(output_path)
if min_split:
self.logger.error(
"Error in split_norm option. Minimum value is {}".
format(min_split))
return self.exit_codes.SPLIT_NORM
if u'sys::die' in line:
#This is the situation when siesta dies with no specified error
#to be reported in "MESSAGES", unfortunately some interesting cases
#are treated in this way, we explore the .out file for more insights.
if is_polarization_problem(output_path):
return self.exit_codes.BASIS_POLARIZ
if u'SCF_NOT_CONV' in line:
return self.exit_codes.SCF_NOT_CONV
if u'GEOM_NOT_CONV' in line:
return self.exit_codes.GEOM_NOT_CONV
#Because no known error has been found, attempt to parse bands if requested
if bands_path is None:
if "bandskpoints" in self.node.inputs:
return self.exit_codes.BANDS_FILE_NOT_PRODUCED
else:
#bands, coords = self._get_bands(bands_path)
try:
bands = self._get_bands(bands_path)
except (ValueError, IndexError):
return self.exit_codes.BANDS_PARSE_FAIL
from aiida.orm import BandsData
arraybands = BandsData()
#Reset the cell for KpointsData of bands, necessary
#for bandskpoints without cell and if structure changed
bkp = self.node.inputs.bandskpoints.clone()
if output_dict['variable_geometry']:
bkp.set_cell_from_structure(out_struc)
else:
bkp.set_cell_from_structure(self.node.inputs.structure)
arraybands.set_kpointsdata(bkp)
arraybands.set_bands(bands, units="eV")
self.out('bands', arraybands)
#bandsparameters = Dict(dict={"kp_coordinates": coords})
#self.out('bands_parameters', bandsparameters)
#At the very end, return a particular exit code if "INFO: Job completed"
#was not present in the MESSAGES file, but no known error is detected.
if have_errors_to_analyse:
if not succesful:
self.logger.error(
'The calculation finished without "INFO: Job completed", but no '
'error could be processed. Might be that the calculation was killed externally'
)
return self.exit_codes.UNEXPECTED_TERMINATION
return ExitCode(0)
def band_parser_legacy(band_dat, band_kpt, special_points, structure): # pylint: disable=too-many-locals
"""
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. Used for wannier90 < 3.0
:param band_dat: list of str with each str stores one line of aiida_band.dat file
:param band_kpt: list of str with each str stores one line of 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,
and a list contains warnings.
"""
import numpy as np
from aiida.orm import BandsData
from aiida.orm import KpointsData
warnings = []
warnings.append((
"Note: no file named SEEDNAME_band.labelinfo.dat found. "
"You are probably using a version of Wannier90 before 3.0. "
"There, the labels associated with each k-points were not printed in output "
"and there were also cases in which points were not calculated "
"(see issue #195 on the Wannier90 GitHub page). "
"I will anyway try to do my best to assign labels, "
"but the assignment might be wrong "
"(especially if there are path discontinuities)."))
# imports the data
out_kpt = np.genfromtxt(band_kpt, skip_header=1, usecols=(0, 1, 2))
out_dat = np.genfromtxt(band_dat, 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']
# We set atol to 1e-5 because in the kpt file the coords are printed with fixed precision
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], rtol=0, atol=1.e-5))
]
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
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
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, append in enumerate(appends):
labels.insert(append[0] + i, (append[2], six.text_type(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, warnings
def band_parser(band_dat, band_kpt, band_labelinfo, structure): # pylint: disable=too-many-locals
"""
Parsers the bands output data to construct a BandsData object which is then
returned. Used for wannier90 >= 3.0
:param band_dat: list of str with each str stores one line of aiida_band.dat file
:param band_kpt: list of str with each str stores one line of aiida_band.kpt file
:param band_labelinfo: list of str with each str stores one line in aiida_band.labelinfo.dat file
:return: BandsData object constructed from the input params
"""
import numpy as np
from aiida.orm import BandsData
from aiida.orm import KpointsData
warnings = []
# imports the data
out_kpt = np.genfromtxt(band_kpt, skip_header=1, usecols=(0, 1, 2))
out_dat = np.genfromtxt(band_dat, usecols=1)
# reshaps the output bands
out_dat = out_dat.reshape(len(out_kpt), (len(out_dat) // len(out_kpt)),
order="F")
labels_dict = {}
for line_idx, line in enumerate(band_labelinfo, start=1):
if not line.strip():
continue
try:
# label, idx, xval, kx, ky, kz = line.split()
label, idx, _, _, _, _ = line.split()
except ValueError:
warnings.append(
('Wrong number of items in line {} of the labelinfo file - '
'I will not assign that label')).format(line_idx)
continue
try:
idx = int(idx)
except ValueError:
warnings.append((
"Invalid value for the index in line {} of the labelinfo file, "
"it's not an integer - I will not assign that label"
)).format(line_idx)
continue
# I use a dictionary because there are cases in which there are
# two lines for the same point (e.g. when I do a zero-length path,
# from a point to the same point, just to have that value)
# Note the -1 because in fortran indices are 1-based, in Python are
# 0-based
labels_dict[idx - 1] = label
labels = [(key, labels_dict[key]) for key in sorted(labels_dict)]
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, warnings
