Updating or adapting the Fleur Parsers¶

Each input and output file for Fleur has a correspong XML-Schema, where the structure of these files are defined.

To be able to parse such files efficiently and without hardcoding their structure we extract all necessary information about the schemas in create_inpschema_dict() and create_outschema_dict(). The resulting python dictionaries can be accessed via the classes InputSchemaDict and OutputSchemaDict. The easiest way to instantiate one of these objects is to use the fromVersion() or fromVersion() methods by providing the desired version string.

Adding/modifying a Fleur Schema:¶

The add_fleur_schema() function can be used if a new `FleurInputSchema.xsd` or `FleurOutputSchema.xsd` are to be added to the available versions:

from masci_tools.io.parsers.fleur.fleur_schema import add_fleur_schema

#This function adds the Schemas to the folder with the corresponding version
#and creates the parsed dicitionaries
add_fleur_schema('/path/to/folder/with/schema/')

#If the schema with the found version is found the above call will raise an exception
#use overwrite=True to replace the schemas
add_fleur_schema('/path/to/folder/with/schema/', overwrite=True)

Adapting the outxml_parser:¶

In contrast to the input file parser inpxml_parser(), which parses all information available, the outxml_parser() has to be more flexible. The out file has much more information which might not be always useful for users. Therefore the selection of what is parsed has to be much more specific.

This selection is expressed in the context of tasks. In general this corresponds to things like:

Total energy
Charge density distances
Magnetic moments
and so on …

These are expressed in a definition in form of a dictionary. Below a simple example (Total energy) is shown, which parses the `value` and `units` attribute of the `totalEnergy` tag. The hardcoded known parsing tasks can be found in default_parse_tasks

total_energy_definition = {
    'energy_hartree': {
        'parse_type': 'singleValue',
        'path_spec': {
            'name': 'totalEnergy'
        }
    },
}

The definition of a task can consist of multiple keys (in this case only `energy_hartree`), which by default correspond to the keys in the resulting output dictionary. Each key has to contain the `parse_type` and `path_spec` key. The `parse_type` defines the method used to extract the information.

The following are possible:

attrib: Will parse the value of the given attribute
text: Will parse the text of the given tag
numberNodes: Will return the number of nodes for the given tag
exists: Will return, whether the given tag exists
attrib_exists: Will return, whether the given attribute exists
allAttribs: Will parse all known attributes at the given tag into a dictionary
parentAttribs: Will parse all known attributes at the given tag into a dictionary, but for the parent of the tag
singleValue: Special case of allAttribs to parse value and units attribute for the given tag

The `path_spec` key specifies how the key can be uniquely identified.

It can contain the following specifications:

name: Name of the wanted tag/attribute
contains: A phrase, which has to occur in the path
not_contains: A phrase, which has to not occur in the path
exclude: list of str. Only valid for attributes (these are sorted into different categories `unique`, `unique_path` and `other`). This attribute can exclude one or more of these categories

All except the `name` key are optional and should be constructed so that there is only one possible choice. Otherwise an exception is raised. There are other keywords, which can be entered here. These control how the parsed data is entered into the output dictionary. For a definition of these keywords, please refer to default_parse_tasks.

Each task can also contain a number of control keys, determining when to peform the tasks. Each of these keys begins with an underscore. All of these are optional. The following are valid:

_general

bool, if True (default False) the task is not performed for each iteration but once on the root of the file

_minimal

bool, if True the task is peformed even when `minimal_mode = True` is given

_modes

list of tuples specifying requirements on the `fleur_modes` for the task. For example `[('jspins', 2), ('soc', True)]` will only perform the task for a magnetic SOC calculation

_conversions

list of str, giving the names of functions to call after this task. Functions given here have to be decorated with the conversion_function() decorator

_special

bool, if True (default False) this task is NEVER added automatically and has to be added by hand

Migrating the parsing tasks¶

These task definitions might have to be adapted for new fleur versions. Some changes might be possible to make in default_parse_tasks directly without breaking backwards compatibility. If this is not possible there is a decorator register_migration() to define a function that is recognized by the class ParseTasks to convert between versions. A usage example is shown below.

from masci_tools.util.parse_tasks_decorators import register_migration
import copy

@register_migration(base_version='0.33', target_version='0.34')
def migrate_033_to034(definition_dict):
  """
  Ficticious migration from 0.33 to 0.34
  Moves the `number_of_atom_types` attribute from reading a simple
  attribute to counting the number of atomGroups in the input section
  And removes orbital_magnetic_moments task
  """

  #IMPORTANT: First copy the original dict
  new_dict = copy.deepcopy(definition_dict)

  #If a task is incompatible remove it from the defintion_dict
  new_dict.pop('orbital_magnetic_moments')

  new_dict['general_out_info'].pop('number_of_atom_types')
  new_dict['general_inp_info']['number_of_atom_types'] = {
      'parse_type': 'numberNodes',
      'path_spec': {
          'name': 'atomGroup'
      }
  }

  return new_dict