dragonfruit.vasp.workflows package

Submodules

Module contents

class dragonfruit.vasp.workflows.ConvergenceWorkflow(*_args, **_kwargs)

Bases: dragonfruit.mince.process.Process, abc.ABC

abstract property atoms: ase.atoms.Atoms: Return the current final atoms objecct

abstract property converged: bool: Check if the workflow is converged

abstract create_copy(initial_atoms, initial_settings, *args, **kwargs): Create a copy of self with new initial atoms and settings

abstract get_vasp_task() → Optional[<class 'dragonfruit.vasp.base.VaspTask'>]: Return the latest VaspTask. Returns None if it doesn’t have any yet.

abstract property initial_atoms: ase.atoms.Atoms: Return the initial atoms object

abstract property initial_settings: Dict[str, Any]: Return the initial settings dictionary

abstract run() → bool: Execute the workflow

class dragonfruit.vasp.workflows.ConvergenceWorkflowChain(*_args, **_kwargs)

Bases: dragonfruit.mince.process.Process, dragonfruit.ase_utils.AseVisualizable

ATTRS = (AttrSpec(name='_workflows', as_ref=True), 'workflow_args', 'workflow_kwargs', '_settings_changes', AttrSpec(name='_initial_atoms', as_ref=True), '_base_settings')

TYPE_ID = UUID('6e8f7d41-8238-4330-9239-377e1a312359')

property atoms: ase.atoms.Atoms: Return the current working atoms object

property base_settings: Dict[str, Any]

property converged: bool: We only consider the workflow converged when the final workflow is converged

property current_workflow: <class 'dragonfruit.vasp.workflows.workflows.ConvergenceWorkflow'>: Get the current workflow for running

get_vasp_task() → Optional[<class 'dragonfruit.vasp.base.VaspTask'>]: Return the latest VaspTask. Returns None if it doesn’t have any yet.

get_visualizable()

property initial_atoms: ase.atoms.Atoms

make_new_settings(changes: Dict[str, Any]) → Dict[str, Any]

make_new_workflow(settings_changes: Dict[str, Any]) → <class 'dragonfruit.vasp.workflows.workflows.ConvergenceWorkflow'>: Make a new workflow, continuing from the final atoms of the previous workflow

property num_settings: int

property num_workflows: int

run() → None: Execute the workflow. Will resume from the last un-completed workflow, if any such exist. If all workflows are done, nothing will be done.

property settings_changes: Dict[str, Any]

property workflows

class dragonfruit.vasp.workflows.SingleTaskWorkflow(*_args, **_kwargs)

Bases: dragonfruit.vasp.workflows.workflows.ConvergenceWorkflow, dragonfruit.ase_utils.AseVisualizable

ATTRS = (AttrSpec(name='_vasp_task', as_ref=True), 'error_handlers', 'description', AttrSpec(name='_initial_atoms', as_ref=True), '_initial_settings')

TYPE_ID = UUID('370a8705-d4cf-4f7b-b47e-d2e85a28576f')

property atoms: ase.atoms.Atoms: Return the current final atoms objecct

property converged: bool: Has the workflow converged?

create_copy(initial_atoms, initial_settings, *args, **kwargs): Create a copy of self with new initial atoms and settings

get_vasp_task() → <class 'dragonfruit.vasp.base.VaspTask'>: Return the latest VaspTask. Returns None if it doesn’t have any yet.

get_visualizable()

property initial_atoms: ase.atoms.Atoms: Return the initial atoms object

property initial_settings: dict: Return the initial settings dictionary

run() → bool: Execute the workflow

save_instance_state(saver) → dict: Save the instance state of an object, should return a saved instance

property vasp_task: <class 'dragonfruit.vasp.base.VaspTask'>

class dragonfruit.vasp.workflows.VolumeMetaConvergence(*_args, **_kwargs)

Bases: dragonfruit.vasp.workflows.workflows.ConvergenceWorkflow, dragonfruit.ase_utils.AseVisualizable

ATTRS = ('volume_threshold', 'max_iter', '_task_list', 'error_handlers', 'description')

TYPE_ID = UUID('d2bdda75-9de2-488b-9d05-90f52d467f31')

property atoms: ase.atoms.Atoms: Return the current final atoms objecct

property atoms_history: Get a list of all the atoms from this workflow (spanning all tasks)

property converged: bool: Check if the workflow is converged

create_copy(initial_atoms, initial_settings, *args, **kwargs): Create a copy of self with new initial atoms and settings

get_vasp_task() → Optional[<class 'dragonfruit.vasp.base.VaspTask'>]: Return the latest VaspTask. Returns None if it doesn’t have any yet.

get_visualizable()

property initial_atoms: Return the initial atoms of the workflow

property initial_settings: Return the initial settings of the workflow

run() → bool: Run the meta converger workchain. Returns a boolean indicating if convergence was reached

save_instance_state(saver) → dict: Save the instance state of an object, should return a saved instance

property task_list: Sequence[<class 'dragonfruit.vasp.base.VaspTask'>]

dragonfruit.vasp.workflows.create_next_run(vasp_task: <class 'dragonfruit.vasp.base.VaspTask'>) → <class 'dragonfruit.vasp.base.VaspRun'>: Create a new VaspRun, either by constructing a new VaspRun on the initial, or applying restarters on the latest vasp_run

dragonfruit.vasp.workflows.create_restart(vasp_task: <class 'dragonfruit.vasp.base.VaspTask'>) → <class 'dragonfruit.vasp.base.VaspRun'>: Apply the restarter objects from a VaspTask, and return a new VaspRun

dragonfruit.vasp.workflows.run_with_restart(vasp_task: <class 'dragonfruit.vasp.base.VaspTask'>) → <class 'dragonfruit.vasp.base.VaspRun'>: Run a vasp task, applying the restarters until convergence or a failure Returns the final VaspRun object, which achieved convergence