system_model_interface

Provides the interface for a PredictionTask.

class SystemModelInterface(*args, **kwargs)

Bases: Protocol

Defines the interface for a PredictionTask.

apply_noisifier(signal: DataFrame) → DataFrame

Applies the objects noisifier to a signal.

Parameters:

signal – (pd.DataFrame) The signal.

apply_sparsifier(signal: DataFrame) → DataFrame

Applies the objects sparsifier to a signal.

Parameters:

signal – (pd.DataFrame) The signal.

property deriv: Callable[[float, list[float], dict[str, KineticParameterType]], tuple[float, ...]]

Returns the deriv.

get_clean_signal(start_values: dict[str, Any], sample_id: int, deriv_noised: bool = True) → DataFrame

Creates a clean signal.

Parameters:

• start_values – Start values for the simulation.

• sample_id – The id of the sample.

• deriv_noised – Whether the derivative is noised.

property kinetic_parameters: Dict[str, KineticParameter[KineticParameterType]]

Returns the kinetic_parameters.

property name: str

Returns the name.

sample_start_values_from_hypercube(n: int) → dict[str, Any]

Creates a config dict.

Parameters:

n – Number of samples.

property specieses: dict[str, simba_ml.simulation.species.Species]

Returns the specieses.