AnalysisOutput#
- class openstef_beam.analysis.AnalysisOutput(**data: Any) None[source]#
Bases:
BaseModelContainer for analysis results from the benchmarking pipeline.
Holds all visualizations generated for a specific analysis scope, organized by lead time filtering conditions. This allows comparing model performance across different forecasting horizons (e.g., 1-hour vs 24-hour ahead predictions).
The output structure enables systematic organization of results from benchmark runs, making it easy to generate reports that compare multiple models across various lead times and targets.
- Variables:
scope – Analysis context defining what was analyzed (targets, runs, aggregation)
visualizations – Generated charts and plots grouped by lead time filtering
- Parameters:
data (
Any)
-
scope:
AnalysisScope#
-
visualizations:
dict[TypeAliasType,list[VisualizationOutput]]#
- model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'protected_namespaces': (), 'ser_json_inf_nan': 'null'}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].