DisorderedTaskDoc

class emmet.core.disorder.DisorderedTaskDoc(**data)

Bases: CoreTaskDoc

Document for a disordered structure task, extending the CoreTaskDoc with additional metadata to capture disorder-specific information and its relationship to the ordered structure.

Parameters:

  • nsites (int | None)

  • elements (list[Annotated[ElementTypeVar, BeforeValidator(func=~emmet.core.types.pymatgen_types.element_adapter.<lambda>, json_schema_input_type=PydanticUndefined), WrapSerializer(func=~emmet.core.types.pymatgen_types.element_adapter.<lambda>, return_type=str, when_used=always)]] | None)

  • nelements (int | None)

  • composition (Annotated[CompositionTypeVar, BeforeValidator(func=~emmet.core.types.pymatgen_types.composition_adapter.<lambda>, json_schema_input_type=PydanticUndefined), WrapSerializer(func=~emmet.core.types.pymatgen_types.composition_adapter.<lambda>, return_type=dict[str, float], when_used=always)] | None)

  • composition_reduced (Annotated[CompositionTypeVar, BeforeValidator(func=~emmet.core.types.pymatgen_types.composition_adapter.<lambda>, json_schema_input_type=PydanticUndefined), WrapSerializer(func=~emmet.core.types.pymatgen_types.composition_adapter.<lambda>, return_type=dict[str, float], when_used=always)] | None)

  • formula_pretty (str | None)

  • formula_anonymous (str | None)

  • chemsys (str | None)

  • volume (float | None)

  • density (float | None)

  • density_atomic (float | None)

  • symmetry (SymmetryData | None)

  • batch_id (str | None)

  • calc_type (CalcType | None)

  • completed_at (Annotated[datetime | None, FieldInfo(annotation=NoneType, required=False, default_factory=utcnow), BeforeValidator(func=~emmet.core.utils.convert_datetime, json_schema_input_type=PydanticUndefined)])

  • dir_name (str | None)

  • icsd_id (int | None)

  • input (CalculationInput | None)

  • last_updated (Annotated[datetime, FieldInfo(annotation=NoneType, required=False, default_factory=utcnow), BeforeValidator(func=~emmet.core.utils.convert_datetime, json_schema_input_type=PydanticUndefined)])

  • orig_inputs (CalculationInput | None)

  • output (CoreCalculationOutput | None)

  • run_type (RunType | None)

  • structure (Annotated[StructureTypeVar, BeforeValidator(func=~emmet.core.types.pymatgen_types.structure_adapter.pop_empty_structure_keys, json_schema_input_type=PydanticUndefined), WrapSerializer(func=~emmet.core.types.pymatgen_types.structure_adapter.<lambda>, return_type=~emmet.core.types.pymatgen_types.structure_adapter.TypedStructureDict, when_used=always)] | None)

  • tags (list[str] | None)

  • task_id (Annotated[MPID | AlphaID, BeforeValidator(func=~emmet.core.types.typing._fault_tolerant_id_serde, json_schema_input_type=PydanticUndefined), PlainSerializer(func=~emmet.core.types.typing.<lambda>, return_type=PydanticUndefined, when_used=always)] | None)

  • task_type (TaskType | CalcType | None)

  • transformations (Annotated[dict[str, Any] | None, BeforeValidator(func=~emmet.core.types.typing._deser_json_like, json_schema_input_type=PydanticUndefined), WrapSerializer(func=~emmet.core.types.typing._ser_json_like, return_type=PydanticUndefined, when_used=always)])

  • vasp_objects (Annotated[dict[VaspObject, Any] | None, BeforeValidator(func=~emmet.core.types.typing._deser_json_like, json_schema_input_type=PydanticUndefined), WrapSerializer(func=~emmet.core.types.typing._ser_json_like, return_type=PydanticUndefined, when_used=always)])

  • ordered_task_id (Annotated[MPID | AlphaID, BeforeValidator(func=~emmet.core.types.typing._fault_tolerant_id_serde, json_schema_input_type=PydanticUndefined), PlainSerializer(func=~emmet.core.types.typing.<lambda>, return_type=PydanticUndefined, when_used=always)])

  • reference_structure (Annotated[StructureTypeVar, BeforeValidator(func=~emmet.core.types.pymatgen_types.structure_adapter.pop_empty_structure_keys, json_schema_input_type=PydanticUndefined), WrapSerializer(func=~emmet.core.types.pymatgen_types.structure_adapter.<lambda>, return_type=~emmet.core.types.pymatgen_types.structure_adapter.TypedStructureDict, when_used=always)])

  • supercell_diag (tuple[int, int, int])

  • prototype (str)

  • prototype_params (dict[str, float])

  • composition_map (dict[str, dict[str, int]])

  • versions (dict[str, str])

classmethod from_directory(dir_name, volumetric_files=_VOLUMETRIC_FILES, **vasp_calculation_kwargs)

Create a CoreTaskDoc and corresponding CoreTrajectory from a directory containing VASP files.

Only parses a single calculation. Use TaskDoc.from_directory(…) to parse multiple calculations.

Return type:

tuple[Self, RelaxTrajectory]

Parameters:

  • dir_name (Path | str)

  • volumetric_files (tuple[str, ...])

Parameters

dir_name

The path to the folder containing the calculation outputs.

volumetric_files

Volumetric files to search for.

**vasp_calculation_kwargs

Additional parsing options that will be passed to the Calculation.from_vasp_files function.

Returns

CoreTaskDoc

A slim task document for the calculation.

RelaxTrajectory

A low memory document for the calculation’s trajectory.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].