torchcell.metabolism.parameters.PredictorRegistry

class PredictorRegistry(*, predictors: list[object] = <factory>)

Bases: BaseModel

The predictors a run is allowed to use, in priority order.

Empty by default: a run that fills gaps with predictions has to say so, and the resulting parameter table records which predictor supplied each value.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

first_emitting_km() → object | None

The highest-priority registered predictor that also produces K_M.