class matlantis_features.features.md.post_features.diffusion.OldPostMDDiffusionFeature#

Bases: FeatureBase

The matlantis-feature for calculating the diffusion coefficient using the MD trajectory.

Methods

__init__()

Initialize an instance.

__call__(md_results[, init_time, stride, …])

Calculate the diffusion coefficient from the MD trajectory.

attach_ctx([ctx])

Attach the feature to matlantis_features.utils.Context.

check_estimator_fn(estimator_fn)

Checks if the given estimator function is None and output a warning if so.

cost_estimate([atoms])

Estimate the cost of the feature.

from_dict(res)

Construct a FeatureBase object from serialized dict.

get_savedir_from_ctx()

Get the temporary save directory from the context.

init_scope()

Context manager that enable to set attribution of the feature.

repeat(n_repeat)

Set the maximum number of times that allowed to run the __call__ function.

to_dict()

Dictionary representation of the FeatureBase.
__init__() → None#

Initialize an instance.

__call__(md_results: MDFeatureResult, init_time: float = 0.0, stride: int = 1, atom_indices: Optional[List[int]] = None, molecule: bool = False, number_of_segments: int = 1) → OldPostMDDiffusionFeatureResult#

Calculate the diffusion coefficient from the MD trajectory. This feature class use the ASE’s DiffusionCoefficent implementation.

Parameters

  • md_results (MDFeatureResult) – MD feature’s result object containing the trajectory.

  • init_time (float, optional) – Trajectory frames before this time (in fs) is ignored for the calculation.
    Defaults to 0.0 (i.e., all frames are used for calculation).

  • stride (int, optional) – Size of the skip strie of the trajectory frames.
    Defaults to 1 (i.e., all frames are used for calculation).

  • atom_indices (list[int] or None, optional) – The indices of atoms whose diffusion coefficient is
    to be calculated explicitly.
    Defaults to None.

  • molecule (bool, optional) – Indicate if we are studying a molecule instead of atoms,
    therefore use centre of mass in calculations.
    Defaults to False.

  • number_of_segments (int, optional) – Divides the given trajectory in to segments to allow statistical analysis.
    Defaults to 1.

Returns

Result dataclass object.

Return type

OldPostMDDiffusionFeatureResult

attach_ctx(ctx: Optional[Context] = None) → None#

Attach the feature to matlantis_features.utils.Context.

Parameters

ctx (Context or None, optional) – The matlantis_features.utils.Context object. Defaults to None.

check_estimator_fn(estimator_fn: Optional[Callable[[], Estimator]]) → None#

Checks if the given estimator function is None and output a warning if so.

Parameters

estimator_fn (EstimatorFnType or None, optional) – A factory method to create a custom estimator.
Please refer Customizing estimator used in matlantis-features for detail. Defaults to None.

cost_estimate(atoms: Optional[Union[Atoms, MatlantisAtoms]] = None) → FeatureCost#

Estimate the cost of the feature.

Parameters

atoms (ASEAtoms or MatlantisAtoms or None, optional) – The input atoms. Defaults to None.

Returns

The cost of the feature.

Return type

FeatureCost

classmethod from_dict(res: Dict[str, Any]) → FeatureBase#

Construct a FeatureBase object from serialized dict.

Parameters

res (dict[str, Any]) – A dict containing a serialized FeatureBase from to_dict().

Returns

The deserialized object from provided dict.

Return type

FeatureBase

get_savedir_from_ctx() → Path#

Get the temporary save directory from the context.

Returns

The temporary save directory .

Return type

pathlib.Path

init_scope() → Iterator[None]#

Context manager that enable to set attribution of the feature.

Returns

Init_scope context manager.

Return type

Iterator[None]

repeat(n_repeat: int) → Self#

Set the maximum number of times that allowed to run the __call__ function.

Parameters

n_repeat (int) – The maximum number of repeats.

Returns

The feature.

Return type

Self

to_dict() → Dict[str, Any]#

Dictionary representation of the FeatureBase.

Returns

A dict containing a serialized FeatureBase.

Return type

dict[str, Any]