model

HyDRAModel(modes, *, input_features, output_features, selector=None, trace_schema=None)

Bases: Model

Model composed of learned continuous modes and an optional selector.

A single-mode model predicts directly with that mode. A multi-mode model needs a selector for batch prediction. Model persistence uses Flowcean's trusted-only pickle-based model serialization.

Source code in src/flowcean/hydra/model.py

def __init__(
    self,
    modes: list[Model],
    *,
    input_features: list[str],
    output_features: list[str],
    selector: HybridDecisionTreeModel | None = None,
    trace_schema: HyDRATraceSchema | None = None,
) -> None:
    super().__init__()
    self.modes = modes
    self.input_features = input_features
    self.output_features = output_features
    self.selector = selector
    self.trace_schema = trace_schema
    self._validate_trace_schema()