RMSF Per Residue Aggregation Selection Facade

GitHub Link to Code.

Facade exposing per-residue RMSF aggregation selection.

class mdxplain.analysis.structure.services.rmsf_per_residue_aggregation_selection_facade.RMSFPerResidueAggregationSelectionFacade(pipeline_data: PipelineData | None, metric: Literal['mean', 'median', 'mad'])

Expose per-residue RMSF aggregator selection for a fixed metric.

Provides access to all residue-level aggregation strategies (mean, median, RMS, RMS-median) while preserving the metric context from the parent variant facade. The metric is fixed during construction to enable proper type inference for autocomplete.

Returns

RMSFPerResidueAggregationSelectionFacade: Facade exposing all aggregation options for the configured metric.

Examples

>>> facade = RMSFPerResidueAggregationSelectionFacade(pipeline_data, "mean")
>>> isinstance(facade, RMSFPerResidueAggregationSelectionFacade)
True

__init__(pipeline_data: PipelineData | None, metric: Literal['mean', 'median', 'mad']) → None

Store pipeline context and metric for aggregator facades.

Validates the pipeline context and captures the deviation metric that will be passed to all aggregator facades.

Parameters

pipeline_dataPipelineData | None: Pipeline context injected by the analysis manager. Must not be None.
metric{‘mean’, ‘median’, ‘mad’}: Robust deviation metric passed to all aggregator facades.

Returns

None: The initializer does not return anything.

Examples

>>> facade = RMSFPerResidueAggregationSelectionFacade(pipeline_data, "mean")
>>> facade._metric
'mean'

property with_mean_aggregation: RMSFPerResidueMeanAggFacade

Access residue RMSF facade with mean aggregation.

Returns the facade providing residue-level RMSF calculations using arithmetic mean aggregation for the configured metric.

Parameters

None: This property does not accept parameters.

Returns

RMSFPerResidueMeanAggFacade: Facade exposing mean aggregation with the configured metric.

Examples

>>> facade = RMSFPerResidueAggregationSelectionFacade(pipeline_data, "mean")
>>> agg_facade = facade.with_mean_aggregation
>>> isinstance(agg_facade, RMSFPerResidueMeanAggFacade)
True

property with_median_aggregation: RMSFPerResidueMedianAggFacade

Access residue RMSF facade with median aggregation.

Returns the facade providing residue-level RMSF calculations using median aggregation for the configured metric.

Parameters

None: This property does not accept parameters.

Returns

RMSFPerResidueMedianAggFacade: Facade exposing median aggregation with the configured metric.

Examples

>>> facade = RMSFPerResidueAggregationSelectionFacade(pipeline_data, "mean")
>>> agg_facade = facade.with_median_aggregation
>>> isinstance(agg_facade, RMSFPerResidueMedianAggFacade)
True

property with_rms_aggregation: RMSFPerResidueRmsAggFacade

Access residue RMSF facade with RMS aggregation.

Returns the facade providing residue-level RMSF calculations using root-mean-square aggregation for the configured metric.

Parameters

None: This property does not accept parameters.

Returns

RMSFPerResidueRmsAggFacade: Facade exposing RMS aggregation with the configured metric.

Examples

>>> facade = RMSFPerResidueAggregationSelectionFacade(pipeline_data, "mean")
>>> agg_facade = facade.with_rms_aggregation
>>> isinstance(agg_facade, RMSFPerResidueRmsAggFacade)
True

property with_rms_median_aggregation: RMSFPerResidueRmsMedianAggFacade

Access residue RMSF facade with RMS-median aggregation.

Returns the facade providing residue-level RMSF calculations using RMS-median aggregation for the configured metric.

Parameters

None: This property does not accept parameters.

Returns

RMSFPerResidueRmsMedianAggFacade: Facade exposing RMS-median aggregation with the configured metric.

Examples

>>> facade = RMSFPerResidueAggregationSelectionFacade(pipeline_data, "mean")
>>> agg_facade = facade.with_rms_median_aggregation
>>> isinstance(agg_facade, RMSFPerResidueRmsMedianAggFacade)
True

to_mean_reference(traj_selection: int | str | List[int | str] | all = 'all', atom_selection: str = 'all', cross_trajectory: bool = False, reference_traj_selection: int | str | List[int | str] | all | None = None) → Dict[str, ndarray]

Calculate residue RMSF values relative to the mean structure.

Delegates to RMSFPerResidueMeanAggFacade.to_mean_reference() using the mean aggregation facade while forwarding optional cross-trajectory and reference-topology parameters.

Parameters

traj_selectionUnion[int, str, list[Union[int, str]], ‘all’], optional: Selection describing which trajectories to analyse. Defaults to "all".
atom_selectionstr, optional: MDTraj atom selection string. Defaults to "all".
cross_trajectorybool, optional: Combine all selected trajectories into a single RMSF profile when True. Defaults to False.
reference_traj_selectionUnion[int, str, list[Union[int, str]], ‘all’] | None, optional: Selection describing which trajectory provides the topology for residue aggregation. None defaults to the first trajectory from traj_selection.

Returns

dict[str, np.ndarray]: Mapping of trajectory names – or "combined" when cross_trajectory is True – to per-residue RMSF arrays.

Examples

>>> facade = RMSFPerResidueAggregationSelectionFacade(pipeline_data, "mean")
>>> facade.to_mean_reference(cross_trajectory=True)
{...}