def create_trajectory_data():
"""Create TrajectoryData object with two arrays."""
traj = TrajectoryData()
# I create sample data
stepids = np.array([60, 70])
times = stepids * 0.01
cells = np.array([[[
2.,
0.,
0.,
], [
0.,
2.,
0.,
], [
0.,
0.,
2.,
]], [[
3.,
0.,
0.,
], [
0.,
3.,
0.,
], [
0.,
0.,
3.,
]]])
symbols = ['H', 'O', 'C']
positions = np.array([[[0., 0., 0.], [0.5, 0.5, 0.5], [1.5, 1.5, 1.5]],
[[0., 0., 0.], [0.5, 0.5, 0.5], [1.5, 1.5, 1.5]]])
velocities = np.array([[[0., 0., 0.], [0., 0., 0.], [0., 0., 0.]],
[[0.5, 0.5, 0.5], [0.5, 0.5, 0.5], [-0.5, -0.5, -0.5]]])
# I set the node
traj.set_trajectory(
stepids=stepids, cells=cells, symbols=symbols, positions=positions, times=times, velocities=velocities
)
traj.store()
# Create 2 groups and add the data to one of them
g_ne = Group(label='non_empty_group')
g_ne.store()
g_ne.add_nodes(traj)
g_e = Group(label='empty_group')
g_e.store()
return {
DummyVerdiDataListable.NODE_ID_STR: traj.id,
DummyVerdiDataListable.NON_EMPTY_GROUP_ID_STR: g_ne.id,
DummyVerdiDataListable.EMPTY_GROUP_ID_STR: g_e.id
}
def parse(self, **kwargs):
"""Parse the retrieved files of a completed `NebCalculation` into output 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 a filepath under the key `retrieved_temporary_files`
which should contain the temporary retrieved files.
"""
from aiida.orm import TrajectoryData, ArrayData
import os
import numpy
PREFIX = self.node.process_class._PREFIX
# Check that the retrieved folder is there
try:
out_folder = self.retrieved
except NotExistent:
return self.exit(self.exit_codes.ERROR_NO_RETRIEVED_FOLDER)
list_of_files = out_folder.list_object_names(
) # Note: this includes folders, but not the files they contain.
# The stdout is required for parsing
filename_stdout = self.node.get_attribute('output_filename')
if filename_stdout not in list_of_files:
return self.exit(self.exit_codes.ERROR_OUTPUT_STDOUT_READ)
# Look for optional settings input node and potential 'parser_options' dictionary within it
# Note that we look for both NEB and PW parser options under "inputs.settings.parser_options";
# we don't even have a namespace "inputs.pw.settings".
try:
settings = self.node.inputs.settings.get_dict()
parser_options = settings[self.get_parser_settings_key()]
except (AttributeError, KeyError, NotExistent):
settings = {}
parser_options = {}
# load the pw input parameters dictionary
pw_input_dict = self.node.inputs.pw__parameters.get_dict()
# load the neb input parameters dictionary
neb_input_dict = self.node.inputs.parameters.get_dict()
# First parse the Neb output
try:
stdout = out_folder.get_object_content(filename_stdout)
neb_out_dict, iteration_data, raw_successful = parse_raw_output_neb(
stdout, neb_input_dict)
# TODO: why do we ignore raw_successful ?
except (OSError, QEOutputParsingError):
return self.exit(self.exit_codes.ERROR_OUTPUT_STDOUT_READ)
for warn_type in ['warnings', 'parser_warnings']:
for message in neb_out_dict[warn_type]:
self.logger.warning('parsing NEB output: {}'.format(message))
if 'QE neb run did not reach the end of the execution.' in neb_out_dict[
'parser_warnings']:
return self.exit(self.exit_codes.ERROR_OUTPUT_STDOUT_INCOMPLETE)
# Retrieve the number of images
try:
num_images = neb_input_dict['num_of_images']
except KeyError:
try:
num_images = neb_out_dict['num_of_images']
except KeyError:
return self.exit(self.exit_codes.ERROR_OUTPUT_STDOUT_PARSE)
if num_images < 2:
return self.exit(self.exit_codes.ERROR_OUTPUT_STDOUT_PARSE)
# Now parse the information from the individual pw calculations for the different images
image_data = {}
positions = []
cells = []
# for each image...
for i in range(num_images):
# check if any of the known XML output file names are present, and parse the first that we find
relative_output_folder = os.path.join(
'{}_{}'.format(PREFIX, i + 1), '{}.save'.format(PREFIX))
retrieved_files = self.retrieved.list_object_names(
relative_output_folder)
for xml_filename in PwCalculation.xml_filenames:
if xml_filename in retrieved_files:
xml_file_path = os.path.join(relative_output_folder,
xml_filename)
try:
with out_folder.open(xml_file_path) as xml_file:
parsed_data_xml, logs_xml = parse_pw_xml(
xml_file, None)
except IOError:
return self.exit(self.exit_codes.ERROR_OUTPUT_XML_READ)
except XMLParseError:
return self.exit(
self.exit_codes.ERROR_OUTPUT_XML_PARSE)
except XMLUnsupportedFormatError:
return self.exit(
self.exit_codes.ERROR_OUTPUT_XML_FORMAT)
except Exception:
import traceback
traceback.print_exc()
return self.exit(
self.exit_codes.ERROR_UNEXPECTED_PARSER_EXCEPTION)
# this image is dealt with, so break the inner loop and go to the next image
break
# otherwise, if none of the filenames we tried exists, exit with an error
else:
return self.exit(self.exit_codes.ERROR_MISSING_XML_FILE)
# look for pw output and parse it
pw_out_file = os.path.join('{}_{}'.format(PREFIX, i + 1), 'PW.out')
try:
with out_folder.open(pw_out_file, 'r') as f:
pw_out_text = f.read() # Note: read() and not readlines()
except IOError:
return self.exit(self.exit_codes.ERROR_OUTPUT_STDOUT_READ)
try:
parsed_data_stdout, logs_stdout = parse_pw_stdout(
pw_out_text, pw_input_dict, parser_options,
parsed_data_xml)
except Exception:
return self.exit(
self.exit_codes.ERROR_UNEXPECTED_PARSER_EXCEPTION)
parsed_structure = parsed_data_stdout.pop('structure', {})
parsed_trajectory = parsed_data_stdout.pop('trajectory', {})
parsed_parameters = PwParser.build_output_parameters(
parsed_data_xml, parsed_data_stdout)
# Explicit information about k-points does not need to be queryable so we remove it from the parameters
parsed_parameters.pop('k_points', None)
parsed_parameters.pop('k_points_units', None)
parsed_parameters.pop('k_points_weights', None)
# Delete bands # TODO: this is just to make pytest happy; do we want to keep them instead?
parsed_parameters.pop('bands', None)
# Append the last frame of some of the smaller trajectory arrays to the parameters for easy querying
PwParser.final_trajectory_frame_to_parameters(
parsed_parameters, parsed_trajectory)
# If the parser option 'all_symmetries' is False, we reduce the raw parsed symmetries to save space
all_symmetries = False if parser_options is None else parser_options.get(
'all_symmetries', False)
if not all_symmetries and 'cell' in parsed_structure:
reduce_symmetries(parsed_parameters, parsed_structure,
self.logger)
structure_data = convert_qe2aiida_structure(parsed_structure)
key = 'pw_output_image_{}'.format(i + 1)
image_data[key] = parsed_parameters
positions.append([site.position for site in structure_data.sites])
cells.append(structure_data.cell)
# Add also PW warnings and errors to the neb output data, avoiding repetitions.
for log_type in ['warning', 'error']:
for message in logs_stdout[log_type]:
formatted_message = '{}: {}'.format(log_type, message)
if formatted_message not in neb_out_dict['warnings']:
neb_out_dict['warnings'].append(formatted_message)
# Symbols can be obtained simply from the last image
symbols = [str(site.kind_name) for site in structure_data.sites]
output_params = Dict(
dict=dict(list(neb_out_dict.items()) + list(image_data.items())))
self.out('output_parameters', output_params)
trajectory = TrajectoryData()
trajectory.set_trajectory(
stepids=numpy.arange(1, num_images + 1),
cells=numpy.array(cells),
symbols=symbols,
positions=numpy.array(positions),
)
self.out('output_trajectory', trajectory)
if parser_options is not None and parser_options.get(
'all_iterations', False):
if iteration_data:
arraydata = ArrayData()
for k, v in iteration_data.items():
arraydata.set_array(k, numpy.array(v))
self.out('iteration_array', arraydata)
# Load the original and interpolated energy profile along the minimum-energy path (mep)
try:
filename = PREFIX + '.dat'
with out_folder.open(filename, 'r') as handle:
mep = numpy.loadtxt(handle)
except Exception:
self.logger.warning(
'could not open expected output file `{}`.'.format(filename))
mep = numpy.array([[]])
try:
filename = PREFIX + '.int'
with out_folder.open(filename, 'r') as handle:
interp_mep = numpy.loadtxt(handle)
except Exception:
self.logger.warning(
'could not open expected output file `{}`.'.format(filename))
interp_mep = numpy.array([[]])
# Create an ArrayData with the energy profiles
mep_arraydata = ArrayData()
mep_arraydata.set_array('mep', mep)
mep_arraydata.set_array('interpolated_mep', interp_mep)
self.out('output_mep', mep_arraydata)
return
def parse(self, **kwargs):
"""Receives in input a dictionary of retrieved nodes.
Does all the logic here.
"""
retrieved = self.retrieved
# check what is inside the folder
list_of_files = retrieved._repository.list_object_names()
# options.metadata become attributes like this:
stdout_filename = self.node.get_attribute('output_filename')
# at least the stdout should exist
if stdout_filename not in list_of_files:
return self.exit(self.exit_codes.ERROR_OUTPUT_STDOUT_READ)
# This should match 1 file
xml_files = [
xml_file for xml_file in self.node.process_class.xml_filenames
if xml_file in list_of_files
]
if not xml_files:
return self.exit(self.exit_codes.ERROR_MISSING_XML_FILE)
elif len(xml_files) > 1:
return self.exit(self.exit_codes.ERROR_OUTPUT_XML_MULTIPLE)
# cp.x can produce, depending on the particular version of the code, a file called `print_counter.xml` or
# `print_counter`, which is a plain text file with the number of the last timestep written in the trajectory
# output. Note that if no trajectory is produced (for example because a single conjugate gradient step was
# performed to calculate the ground state and the wavefunctions velocities) no printer_counter* file is written.
print_counter_xml = True
no_trajectory_output = False
filename_counter_txt = self.node.process_class._FILE_PRINT_COUNTER_BASENAME
filename_counter_xml = self.node.process_class._FILE_XML_PRINT_COUNTER_BASENAME
# The following can happen and is not an error!
if filename_counter_xml not in list_of_files and filename_counter_txt not in list_of_files:
self.logger.error(
f'We could not find the print counter file (`{filename_counter_txt}` or `{filename_counter_xml}`), '
'assuming no trajectory output was produced')
no_trajectory_output = True
if not no_trajectory_output:
if filename_counter_txt in list_of_files:
self.logger.info('print counter not in xml format')
print_counter_xml = False
filename_counter = filename_counter_txt
else: # xml format
print_counter_xml = True
self.logger.info('print counter in xml format')
filename_counter = filename_counter_xml
output_stdout = retrieved.get_object_content(stdout_filename)
output_xml = retrieved.get_object_content(xml_files[0])
output_xml_counter = None if no_trajectory_output else retrieved.get_object_content(
filename_counter)
out_dict, _raw_successful = parse_cp_raw_output(
output_stdout, output_xml, output_xml_counter, print_counter_xml)
if not no_trajectory_output:
# parse the trajectory. Units in Angstrom, picoseconds and eV.
# append everthing in the temporary dictionary raw_trajectory
raw_trajectory = {}
evp_keys = [
'electronic_kinetic_energy', 'cell_temperature',
'ionic_temperature', 'scf_total_energy', 'enthalpy',
'enthalpy_plus_kinetic', 'energy_constant_motion', 'volume',
'pressure'
]
# order of atom in the output trajectory changed somewhere after 6.5
if LooseVersion(out_dict['creator_version']) > LooseVersion('6.5'):
new_cp_ordering = True
else:
new_cp_ordering = False
# Now prepare the reordering, as files in the xml are ordered
if new_cp_ordering:
reordering = None
else:
try:
# this works for old xml only
reordering = self._generate_sites_ordering(
out_dict['species'], out_dict['atoms'])
except KeyError:
# this works for newer versions
reordering = self._generate_sites_ordering(
out_dict['structure']['species'],
out_dict['structure']['atoms'])
pos_filename = f'{self.node.process_class._PREFIX}.pos'
if pos_filename not in list_of_files:
out_dict['warnings'].append(
'Unable to open the POS file... skipping.')
return self.exit_codes.ERROR_READING_POS_FILE
number_of_atoms = out_dict.get(
'number_of_atoms', out_dict['structure']['number_of_atoms']
if 'structure' in out_dict else None)
trajectories = [
('positions', 'pos', CONSTANTS.bohr_to_ang, number_of_atoms),
('cells', 'cel', CONSTANTS.bohr_to_ang, 3),
('velocities', 'vel',
CONSTANTS.bohr_to_ang / (CONSTANTS.timeau_to_sec * 10**12),
number_of_atoms),
('forces', 'for',
CONSTANTS.hartree_to_ev / CONSTANTS.bohr_to_ang,
number_of_atoms),
]
for name, extension, scale, elements in trajectories:
try:
with retrieved.open(
f'{self.node.process_class._PREFIX}.{extension}'
) as datafile:
data = [l.split() for l in datafile]
# POSITIONS stored in angstrom
traj_data = parse_cp_traj_stanzas(
num_elements=elements,
splitlines=data,
prepend_name=f'{name}_traj',
rescale=scale)
# here initialize the dictionary. If the parsing of positions fails, though, I don't have anything
# out of the CP dynamics. Therefore, the calculation status is set to FAILED.
if extension != 'cel':
raw_trajectory[
f'{name}_ordered'] = self._get_reordered_array(
traj_data[f'{name}_traj_data'], reordering)
else:
# NOTE: the trajectory output has the cell matrix transposed!!
raw_trajectory['cells'] = numpy.array(
traj_data['cells_traj_data']).transpose((0, 2, 1))
if extension == 'pos':
raw_trajectory['traj_times'] = numpy.array(
traj_data[f'{name}_traj_times'])
except IOError:
out_dict['warnings'].append(
f'Unable to open the {extension.upper()} file... skipping.'
)
# =============== EVP trajectory ============================
try:
with retrieved.open(
f'{self._node.process_class._PREFIX}.evp') as handle:
matrix = numpy.genfromtxt(handle)
# there might be a different format if the matrix has one row only
try:
matrix.shape[1]
except IndexError:
matrix = numpy.array(numpy.matrix(matrix))
if LooseVersion(
out_dict['creator_version']) > LooseVersion('5.1'):
# Between version 5.1 and 5.1.1, someone decided to change
# the .evp output format, without any way to know that this
# happened... SVN commit 11158.
# I here use the version number to parse, plus some
# heuristics to check that I'm doing the right thing
#print "New version"
raw_trajectory['steps'] = numpy.array(matrix[:, 0],
dtype=int)
raw_trajectory['times'] = matrix[:, 1] # TPS, ps
raw_trajectory[
'electronic_kinetic_energy'] = matrix[:,
2] * CONSTANTS.hartree_to_ev # EKINC, eV
raw_trajectory['cell_temperature'] = matrix[:,
3] # TEMPH, K
raw_trajectory['ionic_temperature'] = matrix[:,
4] # TEMPP, K
raw_trajectory[
'scf_total_energy'] = matrix[:,
5] * CONSTANTS.hartree_to_ev # ETOT, eV
raw_trajectory[
'enthalpy'] = matrix[:,
6] * CONSTANTS.hartree_to_ev # ENTHAL, eV
raw_trajectory[
'enthalpy_plus_kinetic'] = matrix[:,
7] * CONSTANTS.hartree_to_ev # ECONS, eV
raw_trajectory[
'energy_constant_motion'] = matrix[:,
8] * CONSTANTS.hartree_to_ev # ECONT, eV
raw_trajectory['volume'] = matrix[:, 9] * (
CONSTANTS.bohr_to_ang**3) # volume, angstrom^3
raw_trajectory['pressure'] = matrix[:,
10] # out_press, GPa
else:
#print "Old version"
raw_trajectory['steps'] = numpy.array(matrix[:, 0],
dtype=int)
raw_trajectory[
'electronic_kinetic_energy'] = matrix[:,
1] * CONSTANTS.hartree_to_ev # EKINC, eV
raw_trajectory['cell_temperature'] = matrix[:,
2] # TEMPH, K
raw_trajectory['ionic_temperature'] = matrix[:,
3] # TEMPP, K
raw_trajectory[
'scf_total_energy'] = matrix[:,
4] * CONSTANTS.hartree_to_ev # ETOT, eV
raw_trajectory[
'enthalpy'] = matrix[:,
5] * CONSTANTS.hartree_to_ev # ENTHAL, eV
raw_trajectory[
'enthalpy_plus_kinetic'] = matrix[:,
6] * CONSTANTS.hartree_to_ev # ECONS, eV
raw_trajectory[
'energy_constant_motion'] = matrix[:,
7] * CONSTANTS.hartree_to_ev # ECONT, eV
raw_trajectory['volume'] = matrix[:, 8] * (
CONSTANTS.bohr_to_ang**3) # volume, angstrom^3
raw_trajectory['pressure'] = matrix[:, 9] # out_press, GPa
raw_trajectory['times'] = matrix[:, 10] # TPS, ps
# Huristics to understand if it's correct.
# A better heuristics could also try to fix possible issues
# (in new versions of QE, it's possible to recompile it with
# the __OLD_FORMAT flag to get back the old version format...)
# but I won't do it, as there may be also other columns swapped.
# Better to stop and ask the user to check what's going on.
#work around for 100ps format bug
mask = numpy.array(raw_trajectory['traj_times']) >= 0
len_bugged = len(
numpy.array(raw_trajectory['times'])[mask == False])
len_ok = len(numpy.array(raw_trajectory['times'])[mask])
if len_ok > 0:
max_time_difference = abs(
numpy.array(raw_trajectory['times'])[mask] -
numpy.array(raw_trajectory['traj_times'])[mask]).max()
else:
max_time_difference = 0.0
if max_time_difference > 1.e-4 or (
len_bugged > 0 and numpy.array(raw_trajectory['times'])
[mask == False].min() < 100.0
): # It is typically ~1.e-7 due to roundoff errors
# If there is a large discrepancy
# it means there is something very weird going on...
return self.exit_codes.ERROR_READING_TRAJECTORY_DATA
# keep both times array (that usually are duplicated)
# so that the user can check them by himselves
if len_bugged > 0:
out_dict['warnings'].append(
'100ps format bug detected: ignoring trajectory\'s printed time from 100ps on'
)
except IOError:
out_dict['warnings'].append(
'Unable to open the EVP file... skipping.')
# get the symbols from the input
# TODO: I should have kinds in TrajectoryData
input_structure = self.node.inputs.structure
raw_trajectory['symbols'] = [
str(i.kind_name) for i in input_structure.sites
]
traj = TrajectoryData()
traj.set_trajectory(
stepids=raw_trajectory['steps'],
cells=raw_trajectory['cells'],
symbols=raw_trajectory['symbols'],
positions=raw_trajectory['positions_ordered'],
times=raw_trajectory['times'],
velocities=raw_trajectory['velocities_ordered'],
)
# eventually set the forces
try:
traj.set_array('forces', raw_trajectory['forces_ordered'])
except KeyError:
out_dict['warnings'].append('failed to set forces')
for this_name in evp_keys:
try:
traj.set_array(this_name, raw_trajectory[this_name])
except KeyError:
# Some columns may have not been parsed, skip
pass
self.out('output_trajectory', traj)
# Remove big dictionaries that would be redundant
# For atoms and cell, there is a small possibility that nothing is parsed but then probably nothing moved.
for key in [
'atoms', 'cell', 'ions_positions_stau', 'ions_positions_svel',
'ions_positions_taui', 'atoms_index_list', 'atoms_if_pos_list',
'ions_positions_force', 'bands', 'structure'
]:
out_dict.pop(key, None)
# convert the dictionary into an AiiDA object
output_params = Dict(dict=out_dict)
self.out('output_parameters', output_params)
def parse(self, **kwargs):
"""Receives in input a dictionary of retrieved nodes.
Does all the logic here.
"""
try:
out_folder = self.retrieved
except NotExistent:
return self.exit(self.exit_codes.ERROR_NO_RETRIEVED_FOLDER)
# check what is inside the folder
list_of_files = out_folder._repository.list_object_names()
# options.metadata become attributes like this:
stdout_filename = self.node.get_attribute('output_filename')
# at least the stdout should exist
if stdout_filename not in list_of_files:
return self.exit(self.exit_codes.ERROR_OUTPUT_STDOUT_READ)
# This should match 1 file
xml_files = [
xml_file for xml_file in self.node.process_class.xml_filenames
if xml_file in list_of_files
]
if not xml_files:
return self.exit(self.exit_codes.ERROR_MISSING_XML_FILE)
elif len(xml_files) > 1:
return self.exit(self.exit_codes.ERROR_OUTPUT_XML_MULTIPLE)
if self.node.process_class._FILE_XML_PRINT_COUNTER_BASENAME not in list_of_files:
self.logger.error(
'We could not find the print counter file in the output')
# TODO: Add an error for this counter
return self.exit(self.exit_codes.ERROR_MISSING_XML_FILE)
output_stdout = out_folder.get_object_content(stdout_filename)
output_xml = out_folder.get_object_content(xml_files[0])
output_xml_counter = out_folder.get_object_content(
self.node.process_class._FILE_XML_PRINT_COUNTER_BASENAME)
out_dict, _raw_successful = parse_cp_raw_output(
output_stdout, output_xml, output_xml_counter)
# parse the trajectory. Units in Angstrom, picoseconds and eV.
# append everthing in the temporary dictionary raw_trajectory
raw_trajectory = {}
evp_keys = [
'electronic_kinetic_energy', 'cell_temperature',
'ionic_temperature', 'scf_total_energy', 'enthalpy',
'enthalpy_plus_kinetic', 'energy_constant_motion', 'volume',
'pressure'
]
# Now prepare the reordering, as filex in the xml are ordered
reordering = self._generate_sites_ordering(out_dict['species'],
out_dict['atoms'])
pos_filename = '{}.{}'.format(self.node.process_class._PREFIX, 'pos')
if pos_filename not in list_of_files:
return self.exit(self.exit_codes.ERROR_READING_POS_FILE)
trajectories = [
('positions', 'pos', CONSTANTS.bohr_to_ang,
out_dict['number_of_atoms']),
('cells', 'cel', CONSTANTS.bohr_to_ang, 3),
('velocities', 'vel',
CONSTANTS.bohr_to_ang / CONSTANTS.timeau_to_sec * 10**12,
out_dict['number_of_atoms']),
]
for name, extension, scale, elements in trajectories:
try:
with out_folder.open('{}.{}'.format(
self.node.process_class._PREFIX,
extension)) as datafile:
data = [l.split() for l in datafile]
# POSITIONS stored in angstrom
traj_data = parse_cp_traj_stanzas(
num_elements=elements,
splitlines=data,
prepend_name='{}_traj'.format(name),
rescale=scale)
# here initialize the dictionary. If the parsing of positions fails, though, I don't have anything
# out of the CP dynamics. Therefore, the calculation status is set to FAILED.
if extension != 'cel':
raw_trajectory['{}_ordered'.format(
name)] = self._get_reordered_array(
traj_data['{}_traj_data'.format(name)], reordering)
else:
raw_trajectory['cells'] = numpy.array(
traj_data['cells_traj_data'])
if extension == 'pos':
raw_trajectory['times'] = numpy.array(
traj_data['{}_traj_times'.format(name)])
except IOError:
out_dict['warnings'].append(
'Unable to open the {} file... skipping.'.format(
extension.upper()))
# =============== EVP trajectory ============================
try:
with out_folder.open('{}.evp'.format(
self._node.process_class._PREFIX)) as handle:
matrix = numpy.genfromtxt(handle)
# there might be a different format if the matrix has one row only
try:
matrix.shape[1]
except IndexError:
matrix = numpy.array(numpy.matrix(matrix))
if LooseVersion(out_dict['creator_version']) > LooseVersion('5.1'):
# Between version 5.1 and 5.1.1, someone decided to change
# the .evp output format, without any way to know that this
# happened... SVN commit 11158.
# I here use the version number to parse, plus some
# heuristics to check that I'm doing the right thing
#print "New version"
raw_trajectory['steps'] = numpy.array(matrix[:, 0], dtype=int)
raw_trajectory['evp_times'] = matrix[:, 1] # TPS, ps
raw_trajectory[
'electronic_kinetic_energy'] = matrix[:,
2] * CONSTANTS.hartree_to_ev # EKINC, eV
raw_trajectory['cell_temperature'] = matrix[:, 3] # TEMPH, K
raw_trajectory['ionic_temperature'] = matrix[:, 4] # TEMPP, K
raw_trajectory[
'scf_total_energy'] = matrix[:,
5] * CONSTANTS.hartree_to_ev # ETOT, eV
raw_trajectory[
'enthalpy'] = matrix[:,
6] * CONSTANTS.hartree_to_ev # ENTHAL, eV
raw_trajectory[
'enthalpy_plus_kinetic'] = matrix[:,
7] * CONSTANTS.hartree_to_ev # ECONS, eV
raw_trajectory[
'energy_constant_motion'] = matrix[:,
8] * CONSTANTS.hartree_to_ev # ECONT, eV
raw_trajectory['volume'] = matrix[:, 9] * (
CONSTANTS.bohr_to_ang**3) # volume, angstrom^3
raw_trajectory['pressure'] = matrix[:, 10] # out_press, GPa
else:
#print "Old version"
raw_trajectory['steps'] = numpy.array(matrix[:, 0], dtype=int)
raw_trajectory[
'electronic_kinetic_energy'] = matrix[:,
1] * CONSTANTS.hartree_to_ev # EKINC, eV
raw_trajectory['cell_temperature'] = matrix[:, 2] # TEMPH, K
raw_trajectory['ionic_temperature'] = matrix[:, 3] # TEMPP, K
raw_trajectory[
'scf_total_energy'] = matrix[:,
4] * CONSTANTS.hartree_to_ev # ETOT, eV
raw_trajectory[
'enthalpy'] = matrix[:,
5] * CONSTANTS.hartree_to_ev # ENTHAL, eV
raw_trajectory[
'enthalpy_plus_kinetic'] = matrix[:,
6] * CONSTANTS.hartree_to_ev # ECONS, eV
raw_trajectory[
'energy_constant_motion'] = matrix[:,
7] * CONSTANTS.hartree_to_ev # ECONT, eV
raw_trajectory['volume'] = matrix[:, 8] * (
CONSTANTS.bohr_to_ang**3) # volume, angstrom^3
raw_trajectory['pressure'] = matrix[:, 9] # out_press, GPa
raw_trajectory['evp_times'] = matrix[:, 10] # TPS, ps
# Huristics to understand if it's correct.
# A better heuristics could also try to fix possible issues
# (in new versions of QE, it's possible to recompile it with
# the __OLD_FORMAT flag to get back the old version format...)
# but I won't do it, as there may be also other columns swapped.
# Better to stop and ask the user to check what's going on.
max_time_difference = abs(
numpy.array(raw_trajectory['times']) -
numpy.array(raw_trajectory['evp_times'])).max()
if max_time_difference > 1.e-4: # It is typically ~1.e-7 due to roundoff errors
# If there is a large discrepancy
# it means there is something very weird going on...
return self.exit(self.exit_codes.ERROR_READING_TRAJECTORY_DATA)
# Delete evp_times in any case, it's a duplicate of 'times'
del raw_trajectory['evp_times']
except IOError:
out_dict['warnings'].append(
'Unable to open the EVP file... skipping.')
# get the symbols from the input
# TODO: I should have kinds in TrajectoryData
input_structure = self.node.inputs.structure
raw_trajectory['symbols'] = [
str(i.kind_name) for i in input_structure.sites
]
traj = TrajectoryData()
traj.set_trajectory(
stepids=raw_trajectory['steps'],
cells=raw_trajectory['cells'],
symbols=raw_trajectory['symbols'],
positions=raw_trajectory['positions_ordered'],
times=raw_trajectory['times'],
velocities=raw_trajectory['velocities_ordered'],
)
for this_name in evp_keys:
try:
traj.set_array(this_name, raw_trajectory[this_name])
except KeyError:
# Some columns may have not been parsed, skip
pass
self.out('output_trajectory', traj)
# Remove big dictionaries that would be redundant
# For atoms and cell, there is a small possibility that nothing is parsed
# but then probably nothing moved.
try:
del out_dict['atoms']
except KeyError:
pass
try:
del out_dict['cell']
except KeyError:
pass
try:
del out_dict['ions_positions_stau']
except KeyError:
pass
try:
del out_dict['ions_positions_svel']
except KeyError:
pass
try:
del out_dict['ions_positions_taui']
except KeyError:
pass
# This should not be needed
try:
del out_dict['atoms_index_list']
except KeyError:
pass
# This should be already in the input
try:
del out_dict['atoms_if_pos_list']
except KeyError:
pass
#
try:
del out_dict['ions_positions_force']
except KeyError:
pass
# convert the dictionary into an AiiDA object
output_params = Dict(dict=out_dict)
self.out('output_parameters', output_params)
def parse(self, **kwargs):
"""
Parses the datafolder, stores results.
"""
# retrieve resources
resources, exit_code = self.get_parsing_resources(
kwargs, traj_in_temp=True, sys_info=True)
if exit_code is not None:
return exit_code
trajectory_filename, trajectory_filepath, info_filepath = resources
# parse log file
log_data, exit_code = self.parse_log_file()
if exit_code is not None:
return exit_code
# parse trajectory file
try:
timestep = self.node.inputs.parameters.dict.timestep
positions, charges, step_ids, cells, symbols, time = read_lammps_trajectory(
trajectory_filepath, timestep=timestep,
log_warning_func=self.logger.warning)
except Exception:
traceback.print_exc()
return self.exit_codes.ERROR_TRAJ_PARSING
# save results into node
output_data = log_data["data"]
if 'units_style' in output_data:
output_data.update(get_units_dict(output_data['units_style'],
["distance", "time", "energy"]))
else:
self.logger.warning("units missing in log")
self.add_warnings_and_errors(output_data)
self.add_standard_info(output_data)
parameters_data = Dict(dict=output_data)
self.out('results', parameters_data)
# save trajectories into node
trajectory_data = TrajectoryData()
trajectory_data.set_trajectory(
symbols, positions, stepids=step_ids, cells=cells, times=time)
if charges is not None:
trajectory_data.set_array('charges', charges)
self.out('trajectory_data', trajectory_data)
# parse the system data file
if info_filepath:
sys_data = ArrayData()
try:
with open(info_filepath) as handle:
names = handle.readline().strip().split()
for i, col in enumerate(np.loadtxt(info_filepath, skiprows=1, unpack=True)):
sys_data.set_array(names[i], col)
except Exception:
traceback.print_exc()
return self.exit_codes.ERROR_INFO_PARSING
sys_data.set_attribute('units_style', output_data.get('units_style', None))
self.out('system_data', sys_data)
if output_data["errors"]:
return self.exit_codes.ERROR_LAMMPS_RUN
def parse(self, **kwargs):
"""
Receives a dictionary of retrieved nodes.retrieved.
Top level logic of operation
"""
try:
retrieved = self.retrieved
except exceptions.NotExistent:
return self.exit_codes.ERROR_NO_RETRIEVED_FOLDER
output_folder = RetrievedFileManager(
retrieved, kwargs.get('retrieved_temporary_folder'))
warnings = []
exit_code_1 = None
# NOTE parser options not used for not
parser_opts = {}
# NOT READILY IN USE
input_dict = {}
# check what is inside the folder
filenames = output_folder.list_object_names()
# Get calculation options
options = self.node.get_options()
seedname = options['seedname']
# at least the stdout should exist
if options['output_filename'] not in filenames:
self.logger.error("Standard output not found")
return self.exit_codes.ERROR_NO_OUTPUT_FILE
# The calculation is failed if there is any err file.
err_filenames = [fname for fname in filenames if '.err' in fname]
if err_filenames:
exit_code_1 = 'ERROR_CASTEP_ERROR'
# Add the content of err files
err_contents = set()
for fname in err_filenames:
err_contents.add(output_folder.get_object_content(fname))
# Trajectory files
has_md_geom = False
out_md_geom_name_content = None
for suffix in ('.geom', '.md'):
fname = seedname + suffix
if fname in filenames:
out_md_geom_name_content = (
fname, output_folder.get_object_content(fname).split('\n'))
has_md_geom = True
break
# Handling bands
fname = seedname + '.bands'
has_bands = fname in filenames
if has_bands:
out_bands_content = output_folder.get_object_content(fname).split(
'\n')
else:
out_bands_content = None
out_file = options['output_filename']
out_file_content = output_folder.get_object_content(out_file).split(
'\n')
###### CALL THE RAW PASSING FUNCTION TO PARSE DATA #######
raw_parser = RawParser(out_lines=out_file_content,
input_dict=input_dict,
md_geom_info=out_md_geom_name_content,
bands_lines=out_bands_content,
**parser_opts)
out_dict, trajectory_data, structure_data, bands_data, exit_code_2\
= raw_parser.parse()
# Combine the exit codes use the more specific error
exit_code = None
for code in calc_exit_code:
if code in (exit_code_2, exit_code_1):
exit_code = code
break
# Append the final value of trajectory_data into out_dict
last_value_keys = [
"free_energy", "total_energy", "zero_K_energy", "spin_density",
"abs_spin_density", "enthalpy"
]
for key in last_value_keys:
add_last_if_exists(trajectory_data, key, out_dict)
# Add warnings from this level
out_dict["warnings"].extend(warnings)
# Add error messages
out_dict["error_messages"] = list(err_contents)
######## --- PROCESSING BANDS DATA -- ########
if has_bands or output_folder.has_file(seedname + '.castep_bin'):
# Only use castep_bin if we are interested in SCF kpoints
if output_folder.has_file(seedname + '.castep_bin') and (
self.castep_task.lower() not in NON_SCF_BAND_TASKS):
self.logger.info("Using castep_bin file for the bands data.")
bands_node = bands_from_castepbin(seedname, output_folder)
if not self._has_empty_bands(bands_node):
# Set if no other errors
out_dict["warnings"].append(
"At least one kpoint has no empty bands, energy/forces returned are not reliable."
)
if exit_code == 'CALC_FINISHED':
exit_code = "ERROR_NO_EMPTY_BANDS"
else:
bands_node = bands_to_bandsdata(**bands_data)
self.out(out_ln['bands'], bands_node)
######## --- PROCESSING STRUCTURE DATA --- ########
no_optimise = False
try:
cell = structure_data["cell"]
positions = structure_data["positions"]
symbols = structure_data["symbols"]
except KeyError:
# Handle special case where CASTEP founds nothing to optimise,
# hence we attached the input geometry as the output
for warning in out_dict["warnings"]:
if "there is nothing to optimise" in warning:
no_optimise = True
if no_optimise is True:
self.out(out_ln['structure'],
deepcopy(self.node.inputs.structure))
else:
structure_node = structure_from_input(cell=cell,
positions=positions,
symbols=symbols)
# Use the output label as the input label
input_structure = self.node.inputs.structure
structure_node = desort_structure(structure_node, input_structure)
structure_node.label = input_structure.label
self.out(out_ln['structure'], structure_node)
######### --- PROCESSING TRAJECTORY DATA --- ########
# If there is anything to save
# It should...
if trajectory_data:
# Resorting indices - for recovering the original ordering of the
# species in the input structure
input_structure = self.node.inputs.structure
idesort = get_desort_args(input_structure)
# If we have .geom file, save as in a trajectory data
if has_md_geom:
try:
positions = np.asarray(
trajectory_data["positions"])[:, idesort]
cells = trajectory_data["cells"]
# Assume symbols do not change - symbols are the same for all frames
symbols = np.asarray(trajectory_data["symbols"])[idesort]
stepids = np.arange(len(positions))
except KeyError:
out_dict["parser_warning"].append(
"Cannot "
"extract data from .geom file.")
else:
traj = TrajectoryData()
traj.set_trajectory(stepids=np.asarray(stepids),
cells=np.asarray(cells),
symbols=np.asarray(symbols),
positions=np.asarray(positions))
# Save the rest
for name, value in trajectory_data.items():
# Skip saving empty arrays
if len(value) == 0:
continue
array = np.asarray(value)
# For forces/velocities we also need to resort the array
if ("force" in name) or ("velocities" in name):
array = array[:, idesort]
traj.set_array(name, np.asarray(value))
self.out(out_ln['trajectory'], traj)
# Or may there is nothing to optimise? still save a Trajectory data
elif no_optimise is True:
traj = TrajectoryData()
input_structure = self.node.inputs.structure
traj.set_trajectory(stepids=np.asarray([1]),
cells=np.asarray([input_structure.cell]),
symbols=np.asarray([
site.kind_name
for site in input_structure.sites
]),
positions=np.asarray([[
site.position
for site in input_structure.sites
]]))
# Save the rest
for name, value in trajectory_data.items():
# Skip saving empty arrays
if len(value) == 0:
continue
array = np.asarray(value)
# For forces/velocities we also need to resort the array
if ("force" in name) or ("velocities" in name):
array = array[:, idesort]
traj.set_array(name, np.asarray(value))
self.out(out_ln['trajectory'], traj)
# Otherwise, save data into a ArrayData node
else:
out_array = ArrayData()
for name, value in trajectory_data.items():
# Skip saving empty arrays
if len(value) == 0:
continue
array = np.asarray(value)
if ("force" in name) or ("velocities" in name):
array = array[:, idesort]
out_array.set_array(name, np.asarray(value))
self.out(out_ln['array'], out_array)
######## ---- PROCESSING OUTPUT DATA --- ########
output_params = Dict(dict=out_dict)
self.out(out_ln['results'], output_params)
# Return the exit code
return self.exit_codes.__getattr__(exit_code)
def _parse_trajectory(self):
"""Abinit trajectory parser."""
def _voigt_to_tensor(voigt):
tensor = np.zeros((3, 3))
tensor[0, 0] = voigt[0]
tensor[1, 1] = voigt[1]
tensor[2, 2] = voigt[2]
tensor[1, 2] = voigt[3]
tensor[0, 2] = voigt[4]
tensor[0, 1] = voigt[5]
tensor[2, 1] = tensor[1, 2]
tensor[2, 0] = tensor[0, 2]
tensor[1, 0] = tensor[0, 1]
return tensor
# Absolute path of the folder in which aiidao_GSR.nc is stored
path = self.node.get_remote_workdir()
# HIST Abinit NetCDF file - Default name is aiidao_HIST.nc
fname = f'{self.node.get_attribute("prefix")}o_HIST.nc'
if fname not in self.retrieved.list_object_names():
return self.exit_codes.ERROR_MISSING_OUTPUT_FILES
with HistFile(path + '/' + fname) as hist_file:
structures = hist_file.structures
output_structure = StructureData(pymatgen=structures[-1])
with nc.Dataset(path + '/' + fname, 'r') as data_set: # pylint: disable=no-member
n_steps = data_set.dimensions['time'].size
energy_ha = data_set.variables['etotal'][:].data # Ha
energy_kin_ha = data_set.variables['ekin'][:].data # Ha
forces_cart_ha_bohr = data_set.variables[
'fcart'][:, :, :].data # Ha/bohr
positions_cart_bohr = data_set.variables[
'xcart'][:, :, :].data # bohr
stress_voigt = data_set.variables['strten'][:, :].data # Ha/bohr^3
stepids = np.arange(n_steps)
symbols = np.array([specie.symbol for specie in structures[0].species],
dtype='<U2')
cells = np.array(
[structure.lattice.matrix for structure in structures]).reshape(
(n_steps, 3, 3))
energy = energy_ha * units.Ha_to_eV
energy_kin = energy_kin_ha * units.Ha_to_eV
forces = forces_cart_ha_bohr * units.Ha_to_eV / units.bohr_to_ang
positions = positions_cart_bohr * units.bohr_to_ang
stress = np.array([_voigt_to_tensor(sv) for sv in stress_voigt
]) * units.Ha_to_eV / units.bohr_to_ang**3
total_force = np.array([np.sum(f) for f in forces_cart_ha_bohr
]) * units.Ha_to_eV / units.bohr_to_ang
output_trajectory = TrajectoryData()
output_trajectory.set_trajectory(stepids=stepids,
cells=cells,
symbols=symbols,
positions=positions)
output_trajectory.set_array('energy', energy) # eV
output_trajectory.set_array('energy_kin', energy_kin) # eV
output_trajectory.set_array('forces', forces) # eV/angstrom
output_trajectory.set_array('stress', stress) # eV/angstrom^3
output_trajectory.set_array('total_force', total_force) # eV/angstrom
self.out('output_trajectory', output_trajectory)
self.out('output_structure', output_structure)