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GpawParser to its own file (#21)
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,154 @@ | ||
| # -*- coding: utf-8 -*- | ||
| """Parser implementation for the ``AseCalculation``.""" | ||
| import json | ||
| import math | ||
| import numpy | ||
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| from aiida import parsers | ||
| from aiida import plugins | ||
| from ase.io import read | ||
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| Dict = plugins.DataFactory('dict') | ||
| ArrayData = plugins.DataFactory('array') | ||
| StructureData = plugins.DataFactory('structure') | ||
| TrajectoryData = plugins.DataFactory('array.trajectory') | ||
| AseCalculation = plugins.CalculationFactory('ase.ase') | ||
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| def check_paw_missing(lines): | ||
| """Check if paw potentials are missing and that is the source of the error.""" | ||
| for line in lines: | ||
| if 'Could not find required PAW dataset file' in line: | ||
| return True | ||
| return False | ||
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| def check_attribute_error(lines): | ||
| """Checks if there is an AssertionError printed out in the output file.""" | ||
| for line in lines: | ||
| if 'AttributeError' in line: | ||
| return True | ||
| return False | ||
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| def create_output_parameters(atoms_log, json_params): | ||
| """Create the output parameters from the log file.""" | ||
| results_calc = atoms_log.calc.results | ||
| json_params['energy'] = atoms_log.get_potential_energy() | ||
| json_params['energy_contributions'] = atoms_log.calc.energy_contributions | ||
| json_params['forces'] = atoms_log.get_forces() | ||
| json_params['stress'] = results_calc.pop('stress', None) | ||
| json_params['magmoms'] = results_calc.pop('magmoms', None) | ||
| json_params['dipole'] = results_calc.pop('dipole', None) | ||
| json_params['pbc'] = atoms_log.get_pbc() | ||
| json_params['fermi_energy'] = atoms_log.calc.eFermi | ||
| json_params['eigenvalues'] = atoms_log.calc.get_eigenvalues() | ||
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| def store_to_trajectory_data(all_ase_traj): | ||
| """Store ase atoms object into a TrajectoryFile.""" | ||
| all_aiida_atoms = [] | ||
| for atoms in all_ase_traj: | ||
| structure = StructureData(ase=atoms) | ||
| all_aiida_atoms.append(structure) | ||
| return TrajectoryData(all_aiida_atoms) | ||
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| class GpawParser(parsers.Parser): | ||
| """Parser implementation for GPAW through an ``AseCalculation``.""" | ||
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| def parse(self, **kwargs): # pylint: disable=inconsistent-return-statements,too-many-branches,too-many-locals,too-many-return-statements,too-many-statements | ||
| """Parse the retrieved files from a ``AseCalculation``.""" | ||
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| # check what is inside the folder | ||
| list_of_files = self.retrieved.list_object_names() | ||
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| # check if it was a relaxation | ||
| optimizer = self.node.inputs.parameters.get_dict().pop('optimizer', None) | ||
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| # output json file | ||
| if AseCalculation._OUTPUT_FILE_NAME in list_of_files: # pylint: disable=protected-access | ||
| # This calculation is likely to have been alright | ||
| pass | ||
| elif AseCalculation._TXT_OUTPUT_FILE_NAME in list_of_files: # pylint: disable=protected-access | ||
| # An output structure was not found but there is a txt file | ||
| # Probably helpful for restarts | ||
| self.logger.error('Output results was not found, inspecting log file') | ||
| # Checking for possible errors common to all calculations | ||
| with self.retrieved.open('_scheduler-stderr.txt', 'r') as handle: | ||
| lines = handle.readlines() | ||
| if check_paw_missing(lines): | ||
| self.logger.error('Could not find paw potentials') | ||
| return self.exit_codes.ERROR_PAW_NOT_FOUND | ||
| if check_attribute_error(lines): | ||
| self.logger.error('AttributeError in GPAW') | ||
| return self.exit_codes.ERROR_ATTRIBUTE_ERROR | ||
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| if optimizer is not None: | ||
| # This is a relaxation calculation that did not complete | ||
| # try to get all the structures that are available | ||
| try: | ||
| with self.retrieved.open(self.node.get_attribute('log_filename'), 'r') as handle: | ||
| all_ase_traj = read(handle, index=':', format='gpaw-out') | ||
| trajectory = store_to_trajectory_data(all_ase_traj) | ||
| self.outputs.trajectory = trajectory | ||
| return self.exit_codes.ERROR_RELAX_NOT_COMPLETE | ||
| except Exception: # pylint: disable=broad-except | ||
| # If it made it to here then the error is due to the SCF not completing | ||
| self.logger.error('First relaxation step not completed') | ||
| return self.exit_codes.ERROR_SCF_NOT_COMPLETE | ||
| else: | ||
| # This is an SCF calculation that did not complete | ||
| self.logger.error('SCF did not complete') | ||
| return self.exit_codes.ERROR_SCF_NOT_COMPLETE | ||
| else: | ||
| # Neither log file nor end result file were produced | ||
| # Likely to be bad news | ||
| return self.exit_codes.ERROR_UNEXPECTED_EXCEPTION | ||
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| # Check if output structure is needed | ||
| if optimizer is not None: | ||
| # If we are here the calculation did complete sucessfully | ||
| with self.retrieved.open(AseCalculation._output_aseatoms, 'r') as handle: # pylint: disable=protected-access | ||
| atoms = read(handle, format='json') | ||
| self.out('structure', StructureData(ase=atoms)) | ||
| # Store the trajectory as well | ||
| with self.retrieved.open(self.node.get_attribute('log_filename'), 'r') as handle: | ||
| all_ase_traj = read(handle, index=':', format='gpaw-out') | ||
| self.outputs.trajectory = store_to_trajectory_data(all_ase_traj) | ||
| # load the results dictionary | ||
| with self.retrieved.open(AseCalculation._OUTPUT_FILE_NAME, 'r') as handle: # pylint: disable=protected-access | ||
| json_params = json.load(handle) | ||
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| # get the relavent data from the log file for the final structure | ||
| with self.retrieved.open(self.node.get_attribute('log_filename'), 'r') as handle: | ||
| atoms_log = read(handle, format='gpaw-out') | ||
| create_output_parameters(atoms_log, json_params) | ||
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| # Check that the parameters are not inf or nan | ||
| if math.isnan(json_params['fermi_energy']) or math.isinf(json_params['fermi_energy']): | ||
| self.logger.error('Fermi energy is inf or nan') | ||
| return self.exit_codes.ERROR_FERMI_LEVEL_INF | ||
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| # look at warnings | ||
| with self.retrieved.open('_scheduler-stderr.txt', 'r') as handle: | ||
| errors = handle.read() | ||
| if errors: | ||
| json_params['warnings'] = [errors] | ||
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| # extract arrays from json_params | ||
| dictionary_array = {} | ||
| for k, v in list(json_params.items()): | ||
| if isinstance(v, (list, tuple, numpy.ndarray)): | ||
| dictionary_array[k] = json_params.pop(k) | ||
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| if dictionary_array: | ||
| array_data = ArrayData() | ||
| for k, v in dictionary_array.items(): | ||
| array_data.set_array(k, numpy.array(v)) | ||
| self.out('array', array_data) | ||
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| if json_params: | ||
| self.out('parameters', Dict(dict=json_params)) | ||
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| return |