scine_chemoton.gears.network_refinement.aggregate_based_refinement

Classes

AggregateBasedRefinement()

Run refinement calculations for structures based on aggregates.

class scine_chemoton.gears.network_refinement.aggregate_based_refinement.AggregateBasedRefinement[source]

Run refinement calculations for structures based on aggregates. For instance, the 10 lowest energy structures in an aggregate may be reoptimized or reevaluated with a different electronic structure method. The selection which aggregates to refine can be steered through the aggregate_filter system used for the elementary step trial selection.

Attributes:
optionsAggregateBasedRefinement.Options
class Options[source]
cache_file_name: str
str

The pickle file’s name for caching.

cycle_time: int
int

The minimum number of seconds between two cycles of the Gear. Cycles are finished independently of this option, hence if a cycle takes longer than the cycle_time will effectively lead to longer cycle times and not cause multiple cycles of the same Gear.

energy_window: float
float

Set up refinement calculations for structures with a free energy difference lower than the given value to the most stable structure in the aggregate. Energy value in kJ/mol.

hessian_model: Model
db.Model

A second electronic structure model along side the pre_refine_model. With this model, the free energy corrections are evaluated. If only a place-holder is given, the pre_refine_model is used.

model: Model
db.Model

The model the Gear is working with.

n_lowest: int
int

Set up refinement calculations for the n structures with the lowest energy in the given aggregate.

only_electronic_energies: bool
bool

If true, all electronic energies are used instead of free energies to evaluate energy differences in the screening.

opt_job: Job
db.Job (Scine::Database::Calculation::Job)

The Job used for optimizing all minima. The default is: the ‘scine_geometry_optimization’ order on a single core.

opt_job_settings: ValueCollection
utils.ValueCollection

Additional settings for optimizing all minima. Empty by default.

post_refine_model: Model
db.Model (Scine::Database::Model)

The Model used for the refinement The default is: DFT

reference_state: ReferenceState
ReferenceState

The thermodynamic reference state (temperature, pressure). If only a place-holder is given, the temperature and pressure are taken from the pre-refine model.

refinement: Dict[str, bool]
sp_job: Job
db.Job (Scine::Database::Calculation::Job)

The Job used for calculating new single point energies. The default is: the ‘scine_single_point’ order on a single core.

sp_job_settings: ValueCollection
utils.ValueCollection

Additional settings for calculating new single point energies. Empty by default.

unset_collections()

Duplicate name to HoldCollections method to be triggered in pickling process, so infinite _parent loops are avoided.

Return type:

None

aggregate_enabling: AggregateEnabling
AggregateEnabling

If given (none place-holder), the aggregate enabling policy is applied and further refinement is skipped if the aggregate_validation succeeds.

aggregate_filter: AggregateFilter
AggregateFilter

Refine only aggregates that pass the given filter.

aggregate_validation: AggregateFilter
AggregateFilter

If this filter succeeds after applying the aggregate_enabling policy, no further refinement is done for the given aggregate.

initialize_collections(manager)
Return type:

None

property name: str
options: Options
static possible_attributes()
Return type:

List[str]

result_enabling: EnableCalculationResults
EnableCalculationResults

If this calculation result enabling policy is given (none place-holder), the result of an already existing calculation is enabled again (if disabled previously).

stop()
Return type:

None

property stop_at_next_break_point: bool
unset_collections()
Return type:

None