MagneticOrderingsDocument

class atomate2.common.schemas.magnetism.MagneticOrderingsDocument(*, formula=None, formula_pretty=None, parent_structure=None, outputs=None, ground_state_uuid=None, ground_state_structure=None, ground_state_ordering=None, ground_state_energy=None, ground_state_energy_per_atom=None)

Bases: BaseModel

Final document containing information about calculated magnetic orderings.

Includes description of the ground state ordering. This document is returned by the MagneticOrderingsBuilder corresponding to your DFT code.

Parameters:

• formula (str | None)

• formula_pretty (str | None)

• parent_structure (Structure | None)

• outputs (list[MagneticOrderingOutput] | None)

• ground_state_uuid (str | None)

• ground_state_structure (Structure | None)

• ground_state_ordering (Ordering | None)

• ground_state_energy (float | None)

• ground_state_energy_per_atom (float | None)

classmethod from_outputs(outputs, parent_structure)

Construct a MagneticOrderingDocument from a list of output docs.

This is general and should not need to be implemented for a specific DFT code.

Parameters:

• outputs (list[MagneticOrderingOutput])

• parent_structure (Structure)

Return type:

MagneticOrderingsDocument

classmethod from_tasks(tasks)

Construct a MagneticOrderingsDocument from a list of task dicts.

Note

this function assumes the tasks contain the keys “output” and “metadata”. These keys are automatically constructed when jobflow stores its outputs; however, you may need to put the data in this format if using this manually (as in a postprocessing job).

Parameters:

tasks (list[dict])

Return type:

MagneticOrderingsDocument

model_config = {}

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