feat(Labeling): purge overlapping events, sort dataframe at loading time (#226)

* feat(Labeling): purge overlapping events, sort dataframe at loading time

* fix(Linter): ran

* refactor(Labeling): moved purge_overlapping_events one abstraction level higher

* fix(Data): renamed class

* fix(Data): corrected parameter name

* fix(Config): parameters

* fix(Data): fixed path

* fix(Data): uncommented required code

* feat(EventFilters): use vol based CUSUM

* fix(Config): only retrain every 2000 samples

* fix(Config): filter out even more events

* fix(Inference): added remove_overlapping_events

* refactor(Types): simplified type hierarchy

training/types.py

@@ -12,7 +12,7 @@ TransformationsOverTime = list[pd.Series]
 
 
 @dataclass
-class TrainingOutcome:
+class TrainingOutcomeWithoutTransformations:
     model_id: str
     predictions: PredictionsSeries
     probabilities: ProbabilitiesDataFrame
@@ -20,24 +20,22 @@ class TrainingOutcome:
     model_over_time: ModelOverTime
 
 
+@dataclass
+class TrainingOutcome(TrainingOutcomeWithoutTransformations):
+    transformations: TransformationsOverTime
+
+
 @dataclass
 class BetSizingWithMetaOutcome:
     model_id: str
     meta_training: TrainingOutcome
-    meta_transformations: TransformationsOverTime
     weights: WeightsSeries
     stats: Optional[Stats]
 
 
-@dataclass
-class DirectionalTrainingOutcome:
-    training: TrainingOutcome
-    transformations: TransformationsOverTime
-
-
 @dataclass
 class PipelineOutcome:
-    directional_training: DirectionalTrainingOutcome
+    directional_training: TrainingOutcome
     bet_sizing: BetSizingWithMetaOutcome
 
     def get_output_weights(self) -> WeightsSeries: