Source code for aiida_fleur.workflows.scf

# Copyright (c), Forschungszentrum Jülich GmbH, IAS-1/PGI-1, Germany.         #
#                All rights reserved.                                         #
# This file is part of the AiiDA-FLEUR package.                               #
#                                                                             #
# The code is hosted on GitHub at    #
# For further information on the license, see the LICENSE.txt file            #
# For further information please visit or                 #
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In this module you find the workchain 'FleurScfWorkChain' for the self-consistency
cycle management of a FLEUR calculation with AiiDA.
# TODO: more info in output, log warnings
# TODO: make smarter, ggf delete mixing_history or restart with more or less iterations
# you can use the pattern of the density convergence for this
# TODO: maybe write dict schema for wf_parameter inputs, how?
from lxml import etree

from aiida.orm import Code, load_node
from aiida.orm import StructureData, RemoteData, Dict, Bool, Float
from aiida.engine import WorkChain, while_, if_, ToContext
from aiida.engine import calcfunction as cf
from aiida.common.exceptions import NotExistent

from import FleurinpModifier
from import get_inputs_fleur, get_inputs_inpgen
from import test_and_get_codenode
from import find_last_submitted_calcjob
from import create_kpoints_from_distance_parameter
from aiida_fleur.workflows.base_fleur import FleurBaseWorkChain
from aiida_fleur.calculation.fleur import FleurCalculation

from import FleurinpData, get_fleurinp_from_remote_data

from import outxml_parser

[docs]class FleurScfWorkChain(WorkChain): """ Workchain for converging a FLEUR calculation (SCF). It converges the charge density, total energy or the largest force. Two paths are possible: (1) Start from a structure and run the inpgen first optional with calc_parameters (2) Start from a Fleur calculation, with optional remoteData :param wf_parameters: (Dict), Workchain Specifications :param structure: (StructureData), Crystal structure :param calc_parameters: (Dict), Inpgen Parameters :param fleurinp: (FleurinpData), to start with a Fleur calculation :param remote_data: (RemoteData), from a Fleur calculation :param inpgen: (Code) :param fleur: (Code) :return: output_scf_wc_para (Dict), Information of workflow results like Success, last result node, list with convergence behavior """ _workflowversion = '0.5.1' _default_wf_para = { 'fleur_runmax': 4, 'density_converged': 0.00002, 'energy_converged': 0.002, 'force_converged': 0.002, 'kpoints_distance': None, # in 1/A, usually 0.1 'kpoints_force_parity': False, 'kpoints_force_odd': False, 'kpoints_force_false': False, 'kpoints_force_gamma': False, 'nmmp_converged': 0.002, 'mode': 'density', # 'density', 'energy' or 'force' 'add_comp_para': { 'only_even_MPI': False, 'max_queue_nodes': 20, 'max_queue_wallclock_sec': 86400 }, 'itmax_per_run': 30, 'force_dict': { 'qfix': 2, 'forcealpha': 1.0, 'forcemix': 'straight' }, 'use_relax_xml': False, 'inpxml_changes': [], 'straight_iterations': None, 'initial_straight_mixing': False, 'initial_ldau_straight_mixing': False, 'initial_ldau_straight_mix_param': 0.0, #Density matrix frozen by default, since it is the most stable option } _default_options = { 'optimize_resources': True, 'resources': { 'num_machines': 1, 'num_mpiprocs_per_machine': 1 }, 'max_wallclock_seconds': 6 * 60 * 60, 'queue_name': '', 'custom_scheduler_commands': '', 'import_sys_environment': False, 'environment_variables': {} }
[docs] @classmethod def define(cls, spec): super().define(spec) spec.input('fleur', valid_type=Code, required=True) spec.input('inpgen', valid_type=Code, required=False) spec.input('wf_parameters', valid_type=Dict, required=False) spec.input('structure', valid_type=StructureData, required=False) spec.input('calc_parameters', valid_type=Dict, required=False) spec.input('fleurinp', valid_type=FleurinpData, required=False) spec.input('remote_data', valid_type=RemoteData, required=False) spec.input('options', valid_type=Dict, required=False) spec.input('settings', valid_type=Dict, required=False) spec.input('settings_inpgen', valid_type=Dict, required=False) spec.outline(cls.start, cls.validate_input, if_(cls.fleurinpgen_needed)(cls.run_fleurinpgen), cls.run_fleur, cls.inspect_fleur, cls.get_res, while_(cls.condition)(cls.run_fleur, cls.inspect_fleur, cls.get_res), cls.return_results) spec.output('fleurinp', valid_type=FleurinpData) spec.output('output_scf_wc_para', valid_type=Dict) spec.output('last_fleur_calc_output', valid_type=Dict) spec.expose_outputs(FleurBaseWorkChain, namespace='last_calc') # exit codes spec.exit_code(230, 'ERROR_INVALID_INPUT_PARAM', message='Invalid workchain parameters.') spec.exit_code(231, 'ERROR_INVALID_INPUT_CONFIG', message='Invalid input configuration.') spec.exit_code(233, 'ERROR_INVALID_CODE_PROVIDED', message='Input codes do not correspond to fleur or inpgen respectively.') spec.exit_code(235, 'ERROR_CHANGING_FLEURINPUT_FAILED', message='Input file modification failed.') spec.exit_code(236, 'ERROR_INVALID_INPUT_FILE', message="Input file was corrupted after user's modifications.") spec.exit_code(360, 'ERROR_INPGEN_CALCULATION_FAILED', message='Inpgen calculation failed.') spec.exit_code(361, 'ERROR_FLEUR_CALCULATION_FAILED', message='Fleur calculation failed.') spec.exit_code(362, 'ERROR_DID_NOT_CONVERGE', message='SCF cycle did not lead to convergence.')
[docs] def start(self): """ init context and some parameters """'INFO: started convergence workflow version {self._workflowversion}') ####### init ####### # internal para /control para self.ctx.last_base_wc = None self.ctx.loop_count = 0 self.ctx.relax_generated = False self.ctx.calcs = [] self.ctx.abort = False self.ctx.reached_conv = True self.ctx.run_straight_mixing = False wf_default = self._default_wf_para if 'wf_parameters' in self.inputs: wf_dict = self.inputs.wf_parameters.get_dict() else: wf_dict = wf_default for key, val in wf_default.items(): wf_dict[key] = wf_dict.get(key, val) self.ctx.wf_dict = wf_dict fleur = self.inputs.fleur fleur_extras = fleur.extras inpgen_extras = None if 'inpgen' in self.inputs: inpgen = self.inputs.inpgen inpgen_extras = inpgen.extras defaultoptions = self._default_options.copy() user_options = {} if 'options' in self.inputs: user_options = self.inputs.options.get_dict() ''' # extend options by code defaults given in code extras # Maybe do full recursive merge if 'queue_defaults' in fleur_extras: qd = fleur_extras['queue_defaults'] queue = user_options.get('queue', 'default') defaults_queue = qd.get(queue, {}) for key, val in defaultoptions.items(): defaultoptions[key] = defaults_queue.get(key, val) ''' if 'options' in self.inputs: options = user_options else: options = defaultoptions # we use the same options for both codes, inpgen resources get overridden # and queue does not matter in case of direct scheduler # extend options given by user using defaults for key, val in defaultoptions.items(): options[key] = options.get(key, val) self.ctx.options = options self.ctx.max_number_runs = self.ctx.wf_dict.get('fleur_runmax', 4) self.ctx.description_wf = self.inputs.get('description', '') + '|fleur_scf_wc|' self.ctx.label_wf = self.inputs.get('label', 'fleur_scf_wc') self.ctx.default_itmax = self.ctx.wf_dict.get('itmax_per_run', 30) self.ctx.straight_mixing_iters = self.ctx.wf_dict.get('straight_iterations') if self.ctx.straight_mixing_iters is None: self.ctx.straight_mixing_iters = self.ctx.default_itmax # return para/vars self.ctx.successful = True self.ctx.parse_last = True self.ctx.distance = [] self.ctx.all_forces = [] self.ctx.total_energy = [] self.ctx.nmmp_distance = [] self.ctx.energydiff = 10000 self.ctx.forcediff = 10000 self.ctx.last_charge_density = 10000 self.ctx.last_nmmp_distance = -10000 self.ctx.warnings = [] # "debug": {}, self.ctx.errors = [] = [] self.ctx.possible_info = [ 'Consider providing more resources', 'Consider providing a lot more resources', 'Consider changing the mixing scheme', ] self.ctx.fleurinp = None self.ctx.formula = '' self.ctx.total_wall_time = 0
[docs] def validate_input(self): """ # validate input and find out which path (1, or 2) to take # return True means run inpgen if false run fleur directly """ extra_keys = [] for key in self.ctx.wf_dict: if key not in self._default_wf_para: extra_keys.append(key) if extra_keys: error = f'ERROR: input wf_parameters for SCF contains extra keys: {extra_keys}' return self.exit_codes.ERROR_INVALID_INPUT_PARAM inputs = self.inputs if 'fleurinp' in inputs: self.ctx.run_inpgen = False if 'structure' in inputs: error = 'ERROR: structure input is not needed because Fleurinp was given' return self.exit_codes.ERROR_INVALID_INPUT_CONFIG if 'inpgen' in inputs: error = 'ERROR: inpgen code is not needed input because Fleurinp was given' return self.exit_codes.ERROR_INVALID_INPUT_CONFIG if 'calc_parameters' in inputs: error = 'ERROR: calc_parameters input is not needed because Fleurinp was given' return self.exit_codes.ERROR_INVALID_INPUT_CONFIG if 'remote_data' in inputs: warning = ('WARNING: Only initial charge density will be copied from the' 'given remote folder because fleurinp is given.') elif 'structure' in inputs: self.ctx.run_inpgen = True if not 'inpgen' in inputs: error = 'ERROR: StructureData was provided, but no inpgen code was provided' return self.exit_codes.ERROR_INVALID_INPUT_CONFIG if 'remote_data' in inputs: warning = ('WARNING: Only initial charge density will be copied from the' 'given remote folder because fleurinp is given.') elif 'remote_data' in inputs: self.ctx.run_inpgen = False else: error = 'ERROR: No StructureData nor FleurinpData nor RemoteData was provided' return self.exit_codes.ERROR_INVALID_INPUT_CONFIG if 'inpgen' in inputs: try: test_and_get_codenode(inputs.inpgen, 'fleur.inpgen') except ValueError: error = 'The code you provided for inpgen of FLEUR does not use the plugin fleur.inpgen' return self.exit_codes.ERROR_INVALID_CODE_PROVIDED if 'fleur' in inputs: try: test_and_get_codenode(inputs.fleur, 'fleur.fleur') except ValueError: error = ('The code you provided for FLEUR does not use the plugin fleur.fleur') return self.exit_codes.ERROR_INVALID_CODE_PROVIDED # check the mode in wf_dict mode = self.ctx.wf_dict.get('mode') if mode not in ['force', 'density', 'energy', 'gw']: error = "ERROR: Wrong mode of convergence: one of 'force', 'density', 'energy' or 'gw' was expected." return self.exit_codes.ERROR_INVALID_INPUT_PARAM max_iters = self.ctx.wf_dict.get('itmax_per_run') if max_iters <= 1: error = "ERROR: 'itmax_per_run' should be equal at least 2" return self.exit_codes.ERROR_INVALID_INPUT_PARAM straight_iterations = self.ctx.wf_dict.get('straight_iterations') if straight_iterations is not None and straight_iterations <= 1: error = "ERROR: 'straight_iterations' should be atleast 2 if given" return self.exit_codes.ERROR_INVALID_INPUT_PARAM self.ctx.run_straight_mixing = self.ctx.wf_dict.get('initial_straight_mixing') or \ self.ctx.wf_dict.get('initial_ldau_straight_mixing') if straight_iterations is not None: if not self.ctx.run_straight_mixing: error = "ERROR: 'initial_straight_mixing' or 'initial_ldau_straight_mixing' should be True if 'straight_iterations' is given" return self.exit_codes.ERROR_INVALID_INPUT_PARAM # check format of inpxml_changes fchanges = self.ctx.wf_dict.get('inpxml_changes', []) if fchanges: for change in fchanges: # somehow the tuple type gets destroyed on the way and becomes a list if not isinstance(change, (tuple, list)): error = f'ERROR: Wrong Input inpxml_changes wrong format of: {change} should be tuple of 2. I abort' return self.exit_codes.ERROR_INVALID_INPUT_PARAM return
[docs] def fleurinpgen_needed(self): """ Returns True if inpgen calculation has to be submitted before fleur calculations """ return self.ctx.run_inpgen
[docs] def run_fleurinpgen(self): """ run the inpgen """ ## prepare inputs for inpgen structure = self.inputs.structure self.ctx.formula = structure.get_formula() label = 'scf: inpgen' description = f'{self.ctx.description_wf} inpgen on {self.ctx.formula}' inpgencode = self.inputs.inpgen if 'calc_parameters' in self.inputs: params = self.inputs.calc_parameters else: params = None if 'settings_inpgen' in self.inputs: settings = self.inputs.settings_inpgen else: settings = None # If given kpt_dist has prio over given calc_parameters kpt_dist = self.ctx.wf_dict.get('kpoints_distance', None) if kpt_dist is not None: cf_para_kpt = Dict( dict={ 'distance': kpt_dist, 'force_parity': self.ctx.wf_dict.get('kpoints_force_parity', False), 'force_even': self.ctx.wf_dict.get('kpoints_force_even', False), 'force_odd': self.ctx.wf_dict.get('kpoints_force_odd', False), 'include_gamma': self.ctx.wf_dict.get('kpoints_force_gamma', False) }) inputs = { 'structure': structure, 'calc_parameters': params, 'cf_para': cf_para_kpt, 'metadata': { 'call_link_label': 'create_kpoints_from_distance' } } params = create_kpoints_from_distance_parameter(**inputs) options = { 'max_wallclock_seconds': int(self.ctx.options.get('max_wallclock_seconds')), 'resources': self.ctx.options.get('resources'), 'queue_name': self.ctx.options.get('queue_name', '') } inputs_build = get_inputs_inpgen(structure, inpgencode, options, label, description, settings=settings, params=params) # Launch inpgen'INFO: run inpgen') future = self.submit(inputs_build) return ToContext(inpgen=future)
[docs] def reset_straight_mixing(self): """ Turn off the straight mixing features again """ if not self.ctx.fleurinp: return self.exit_codes.ERROR_CHANGING_FLEURINPUT_FAILED wf_dict = self.ctx.wf_dict fleurmode = FleurinpModifier(self.ctx.fleurinp) fleurmode.set_inpchanges({'itmax': self.ctx.default_itmax}) #Take out straight mixing if wf_dict.get('initial_straight_mixing'): fleurmode.set_inpchanges({'imix': 'Anderson'}) #TODO: should take the actual value from before if wf_dict.get('initial_ldau_straight_mixing'): fleurmode.set_inpchanges({'l_linmix': False}) # validate? try:, validate=True) except etree.DocumentInvalid: error = ('ERROR: input, user wanted inp.xml changes did not validate') return self.exit_codes.ERROR_INVALID_INPUT_FILE except ValueError as exc: error = ('ERROR: input, user wanted inp.xml changes could not be applied.' f'The following error was raised {exc}') self.control_end_wc(error) return self.exit_codes.ERROR_CHANGING_FLEURINPUT_FAILED # apply out = fleurmode.freeze() self.ctx.fleurinp = out return
[docs] def change_fleurinp(self): """ This routine sets somethings in the fleurinp file before running a fleur calculation. """'INFO: run change_fleurinp') inputs = self.inputs # Has to never crash because corresponding check was done in validate function if self.ctx.fleurinp: # something was already changed return if 'fleurinp' in inputs: fleurin = self.inputs.fleurinp elif 'structure' in inputs: if not self.ctx['inpgen'].is_finished_ok: error = 'Inpgen calculation failed' self.control_end_wc(error) return self.exit_codes.ERROR_INPGEN_CALCULATION_FAILED fleurin = self.ctx['inpgen'].outputs.fleurinpData elif 'remote_data' in inputs: # In this case only remote_data for input structure is given # fleurinp data has to be generated from the remote inp.xml file to use change_fleurinp fleurin = get_fleurinp_from_remote_data(self.inputs.remote_data, store=True) f'INFO: generated FleurinpData from files {fleurin.files} from remote folder pk={}' ) wf_dict = self.ctx.wf_dict force_dict = wf_dict.get('force_dict') converge_mode = wf_dict.get('mode') fchanges = wf_dict.get('inpxml_changes', []) fleurmode = FleurinpModifier(fleurin) itmax = self.ctx.default_itmax if self.ctx.run_straight_mixing: if self.ctx.loop_count == 0: #Set up straight mixing itmax = self.ctx.straight_mixing_iters #Is set further below if wf_dict.get('initial_straight_mixing'): fleurmode.set_inpchanges({'imix': 'straight'}) if wf_dict.get('initial_ldau_straight_mixing'): fleurmode.set_inpchanges({ 'l_linmix': True, 'mixParam': wf_dict.get('initial_ldau_straight_mix_param') }) # set proper convergence parameters in inp.xml if converge_mode == 'density': dist = wf_dict.get('density_converged') fleurmode.set_inpchanges({'itmax': itmax, 'minDistance': dist}) elif converge_mode == 'force': force_converged = wf_dict.get('force_converged') dist = wf_dict.get('density_converged') fleurmode.set_inpchanges({ 'itmax': itmax, 'minDistance': dist, 'force_converged': force_converged, 'l_f': True, 'qfix': force_dict.get('qfix'), 'forcealpha': force_dict.get('forcealpha'), 'forcemix': force_dict.get('forcemix') }) elif converge_mode == 'energy': dist = 0.0 fleurmode.set_inpchanges({'itmax': itmax, 'minDistance': dist}) elif converge_mode == 'gw': dist = 0.0 fleurmode.set_inpchanges({'itmax': itmax, 'minDistance': dist, 'gw': 1}) if 'settings' in self.inputs: self.inputs.settings.append({'additional_retrieve_list': ['basis.hdf', 'pot.hdf', 'ecore']}) self.inputs.settings.append({'additional_remotecopy_list': ['basis.hdf', 'pot.hdf', 'ecore']}) else: self.inputs.settings = { 'additional_retrieve_list': ['basis.hdf', 'pot.hdf', 'ecore'], 'additional_remotecopy_list': ['basis.hdf', 'pot.hdf', 'ecore'] } # apply further user dependend changes if fchanges: try: fleurmode.add_task_list(fchanges) except (ValueError, TypeError) as exc: error = ('ERROR: Changing the inp.xml file failed. Tried to apply inpxml_changes' f', which failed with {exc}. I abort, good luck next time!') self.control_end_wc(error) return self.exit_codes.ERROR_CHANGING_FLEURINPUT_FAILED # validate? try:, validate=True) except etree.DocumentInvalid: error = ('ERROR: input, user wanted inp.xml changes did not validate') return self.exit_codes.ERROR_INVALID_INPUT_FILE except ValueError as exc: error = ('ERROR: input, user wanted inp.xml changes could not be applied.' f'The following error was raised {exc}') self.control_end_wc(error) return self.exit_codes.ERROR_CHANGING_FLEURINPUT_FAILED # apply out = fleurmode.freeze() self.ctx.fleurinp = out return
[docs] def run_fleur(self): """ run a FLEUR calculation """'INFO: run FLEUR') status = self.change_fleurinp() if status: return status if 'settings' in self.inputs: settings = self.inputs.settings else: settings = None if self.ctx.run_straight_mixing and self.ctx.loop_count == 1: status = self.reset_straight_mixing() if status: return status if settings is None: settings = {} else: settings = settings.get_dict() settings.setdefault('remove_from_remotecopy_list', []).append('mixing_history*') fleurin = self.ctx.fleurinp if self.ctx['last_base_wc']: # will this fail if fleur before failed? try needed? remote = self.ctx['last_base_wc'].outputs.remote_folder elif 'remote_data' in self.inputs: remote = self.inputs.remote_data else: remote = None label = ' ' description = ' ' if self.ctx.formula: label = f'scf: fleur run {self.ctx.loop_count + 1}' description = f'{self.ctx.description_wf} fleur run {self.ctx.loop_count + 1} on {self.ctx.formula}' else: label = f'scf: fleur run {self.ctx.loop_count + 1}' description = f'{self.ctx.description_wf} fleur run {self.ctx.loop_count + 1}, fleurinp given' code = self.inputs.fleur options = self.ctx.options.copy() inputs_builder = get_inputs_fleur(code, remote, fleurin, options, label, description, settings, add_comp_para=self.ctx.wf_dict['add_comp_para']) future = self.submit(FleurBaseWorkChain, **inputs_builder) self.ctx.loop_count = self.ctx.loop_count + 1'INFO: run FLEUR number: {self.ctx.loop_count}') self.ctx.calcs.append(future) return ToContext(last_base_wc=future)
[docs] def inspect_fleur(self): """ Analyse the results of the previous Calculation (Fleur or inpgen), checking whether it finished successfully or if not, troubleshoot the cause and adapt the input parameters accordingly before restarting, or abort if unrecoverable error was found """'INFO: inspect FLEUR') try: base_wc = self.ctx.last_base_wc except AttributeError: self.ctx.parse_last = False error = 'ERROR: Something went wrong I do not have a last calculation' self.control_end_wc(error) return self.exit_codes.ERROR_FLEUR_CALCULATION_FAILED exit_status = base_wc.exit_status if not base_wc.is_finished_ok: error = f'ERROR: Last Fleur calculation failed with exit status {exit_status}' self.control_end_wc(error) return self.exit_codes.ERROR_FLEUR_CALCULATION_FAILED self.ctx.parse_last = True
[docs] def get_res(self): """ Check how the last Fleur calculation went Parse some results. """'INFO: get results FLEUR') mode = self.ctx.wf_dict.get('mode') if self.ctx.parse_last: last_base_wc = self.ctx.last_base_wc walltime = last_base_wc.outputs.output_parameters['walltime'] if isinstance(walltime, int): self.ctx.total_wall_time = self.ctx.total_wall_time + walltime with, 'rb') as outxmlfile: output_dict = outxml_parser(outxmlfile, minimal_mode=True, list_return=True, iteration_to_parse='all', ignore_validation=True) energies = output_dict.get('energy_hartree', []) if energies is not None: self.ctx.total_energy.extend(energies) if 'overall_density_convergence' in output_dict: distances = output_dict['overall_density_convergence'] else: distances = output_dict.get('density_convergence', []) if distances is not None: self.ctx.distance.extend(distances) if 'ldau_info' in output_dict: nmmp_distances = output_dict['ldau_info'].get('density_matrix_distance', []) if nmmp_distances is not None: self.ctx.nmmp_distance.extend(nmmp_distances) if mode == 'force': forces = output_dict.get('force_atoms', []) if forces is not None: for force_iter in forces: self.ctx.all_forces.append([force for atom, force in force_iter]) else: errormsg = 'ERROR: scf wc was not successful, check log for details' self.control_end_wc(errormsg) return self.exit_codes.ERROR_FLEUR_CALCULATION_FAILED if not self.ctx.distance: # if fleur relaxes an already converged crystal it stops directly if mode == 'force':'INFO: System already force converged, could not extract distance.') self.ctx.last_charge_density = None else: errormsg = 'ERROR: did not manage to extract charge density from the calculation' self.control_end_wc(errormsg) return self.exit_codes.ERROR_FLEUR_CALCULATION_FAILED else: self.ctx.last_charge_density = self.ctx.distance[-1] if self.ctx.nmmp_distance: if isinstance(self.ctx.nmmp_distance[-1], list): self.ctx.last_nmmp_distance = max(self.ctx.nmmp_distance[-1]) else: self.ctx.last_nmmp_distance = self.ctx.nmmp_distance[-1] if self.ctx.last_nmmp_distance is None:'No LDA+U distance found but only one iteration performed\n' 'Assuming that the calculatin should be continued') self.ctx.last_nmmp_distance = self.ctx.wf_dict.get('nmmp_converged') + 1
[docs] def condition(self): """ check convergence condition """'INFO: checking condition FLEUR') mode = self.ctx.wf_dict.get('mode') ldau_notconverged = False energy = self.ctx.total_energy if len(energy) >= 2: self.ctx.energydiff = abs(energy[-1] - energy[-2]) if mode == 'force': forces = self.ctx.all_forces if len(forces) >= 2: self.ctx.forcediff = max( abs(forces[-1][i][k] - forces[-2][i][k]) for i in range(len(forces[-1])) for k in range(3)) else: self.ctx.forcediff = 'can not be determined' if self.ctx.last_nmmp_distance > 0.0 and \ self.ctx.last_nmmp_distance >= self.ctx.wf_dict.get('nmmp_converged'): ldau_notconverged = True if mode == 'density': if self.ctx.wf_dict.get('density_converged') >= self.ctx.last_charge_density: if not ldau_notconverged: return False elif mode in ('energy', 'gw'): if self.ctx.wf_dict.get('energy_converged') >= self.ctx.energydiff: if not ldau_notconverged: return False elif mode == 'force': if self.ctx.last_charge_density is None: try: _ = self.ctx.last_base_wc.outputs.relax_parameters except NotExistent: pass else: if not ldau_notconverged: return False elif self.ctx.wf_dict.get('density_converged') >= self.ctx.last_charge_density: try: _ = self.ctx.last_base_wc.outputs.relax_parameters except NotExistent: pass else: if not ldau_notconverged: return False if self.ctx.loop_count >= self.ctx.max_number_runs: self.ctx.reached_conv = False return False return True
[docs] def return_results(self): """ return the results of the calculations This should run through and produce output nodes even if everything failed, therefore it only uses results from context. """ if self.ctx.last_base_wc: try: last_calc_uuid = find_last_submitted_calcjob(self.ctx.last_base_wc) except NotExistent: last_calc_uuid = None else: last_calc_uuid = None try: # if something failed, we still might be able to retrieve something last_calc_out = self.ctx.last_base_wc.outputs.output_parameters retrieved = self.ctx.last_base_wc.outputs.retrieved last_calc_out_dict = last_calc_out.get_dict() except (NotExistent, AttributeError): last_calc_out = None last_calc_out_dict = {} retrieved = None last_nmmp_distance = None if self.ctx.last_nmmp_distance > 0.0: last_nmmp_distance = self.ctx.last_nmmp_distance outputnode_dict = {} outputnode_dict['workflow_name'] = self.__class__.__name__ outputnode_dict['workflow_version'] = self._workflowversion outputnode_dict['material'] = self.ctx.formula outputnode_dict['conv_mode'] = self.ctx.wf_dict.get('mode') outputnode_dict['loop_count'] = self.ctx.loop_count outputnode_dict['iterations_total'] = last_calc_out_dict.get('number_of_iterations_total', None) outputnode_dict['distance_charge'] = self.ctx.last_charge_density outputnode_dict['distance_charge_all'] = self.ctx.distance outputnode_dict['total_energy'] = last_calc_out_dict.get('energy_hartree', None) outputnode_dict['total_energy_all'] = self.ctx.total_energy outputnode_dict['force_diff_last'] = self.ctx.forcediff outputnode_dict['force_largest'] = last_calc_out_dict.get('force_largest', None) outputnode_dict['distance_charge_units'] = 'me/bohr^3' outputnode_dict['total_energy_units'] = 'Htr' outputnode_dict['nmmp_distance'] = last_nmmp_distance outputnode_dict['nmmp_distance_all'] = self.ctx.nmmp_distance outputnode_dict['last_calc_uuid'] = last_calc_uuid outputnode_dict['total_wall_time'] = self.ctx.total_wall_time outputnode_dict['total_wall_time_units'] = 's' outputnode_dict['info'] = outputnode_dict['warnings'] = self.ctx.warnings outputnode_dict['errors'] = self.ctx.errors num_iterations = last_calc_out_dict.get('number_of_iterations_total', None) if self.ctx.successful and self.ctx.reached_conv: if len(self.ctx.total_energy) <= 1: # then len(self.ctx.all_forces) <= 1 too'STATUS: Done, the convergence criteria are reached.\n' 'INFO: The charge density of the FLEUR calculation ' f'converged after {self.ctx.loop_count} FLEUR runs, {num_iterations} ' f'iterations and {self.ctx.total_wall_time} sec ' f'walltime to {outputnode_dict["distance_charge"]} "me/bohr^3" \n' 'INFO: Did not manage to get energy and largest force difference ' 'between two last iterations, probably converged in a single iteration') else:'STATUS: Done, the convergence criteria are reached.\n' 'INFO: The charge density of the FLEUR calculation ' f'converged after {self.ctx.loop_count} FLEUR runs, {num_iterations} ' f'iterations and {self.ctx.total_wall_time} sec ' f'walltime to {outputnode_dict["distance_charge"]} "me/bohr^3" \n' 'INFO: The total energy difference of the last two iterations ' f'is {self.ctx.energydiff} Htr and largest force difference is ' f'{self.ctx.forcediff} Htr/bohr') elif self.ctx.successful and not self.ctx.reached_conv: if len(self.ctx.total_energy) <= 1: # then len(self.ctx.all_forces) <= 1 too'STATUS/WARNING: Done, the maximum number of runs ' 'was reached.\n INFO: The ' 'charge density of the FLEUR calculation, ' f'after {self.ctx.loop_count} FLEUR runs, {num_iterations} ' f' iterations and {self.ctx.total_wall_time} sec ' f'walltime is {outputnode_dict["distance_charge"]} "me/bohr^3"\n' 'INFO: can not extract energy and largest force difference between' ' two last iterations, probably converged in a single iteration') else:'STATUS/WARNING: Done, the maximum number of runs ' 'was reached.\n INFO: The ' 'charge density of the FLEUR calculation, ' f'after {self.ctx.loop_count} FLEUR runs, {num_iterations} ' f' iterations and {self.ctx.total_wall_time} sec ' f'walltime is {outputnode_dict["distance_charge"]} "me/bohr^3"\n' 'INFO: The total energy difference of the last two iterations ' f'is {self.ctx.energydiff} Htr and largest force difference is' f'{self.ctx.forcediff} Htr/bohr\n') else: # Termination ok, but not converged yet... if self.ctx.abort: # some error occurred, do not use the output.'STATUS/ERROR: I abort, see logs and errors/warning/hints in output_scf_wc_para') if self.ctx.last_nmmp_distance > 0.0:'INFO: The LDA+U density matrix is converged to {self.ctx.last_nmmp_distance} change ' 'of all matrix elements') outputnode_t = Dict(dict=outputnode_dict) # this is unsafe so far, because last_calc_out could not exist... if last_calc_out: outdict = create_scf_result_node(outpara=outputnode_t, last_calc_out=last_calc_out, last_calc_retrieved=retrieved) else: outdict = create_scf_result_node(outpara=outputnode_t) # Now it always returns changed fleurinp that was actually used in the calculation if self.ctx.fleurinp is not None: outdict['fleurinp'] = self.ctx.fleurinp if last_calc_out: outdict['last_fleur_calc_output'] = last_calc_out if self.ctx.last_base_wc: self.out_many(self.exposed_outputs(self.ctx.last_base_wc, FleurBaseWorkChain, namespace='last_calc')) #outdict['output_scf_wc_para'] = outputnode for link_name, node in outdict.items(): self.out(link_name, node) if not self.ctx.reached_conv: return self.exit_codes.ERROR_DID_NOT_CONVERGE
[docs] def control_end_wc(self, errormsg): """ Controlled way to shutdown the workchain. will initialize the output nodes The shutdown of the workchain will has to be done afterwards """ self.ctx.successful = False self.ctx.abort = True # because return_results still fails somewhen self.ctx.errors.append(errormsg) self.return_results()
[docs]@cf def create_scf_result_node(**kwargs): """ This is a pseudo wf, to create the right graph structure of AiiDA. This wokfunction will create the output node in the database. It also connects the output_node to all nodes the information commes from. So far it is just also parsed in as argument, because so far we are to lazy to put most of the code overworked from return_results in here. """ for key, val in kwargs.items(): if key == 'outpara': # should be always there outpara = val outdict = {} outputnode = outpara.clone() outputnode.label = 'output_scf_wc_para' outputnode.description = ('Contains self-consistency results and information of an fleur_scf_wc run.') outdict['output_scf_wc_para'] = outputnode # copy, because we rather produce the same node twice then have a circle in the database for now #output_para = args[0] # return {'output_eos_wc_para'} return outdict