list_of_simulation_output_evaluators module

Define an object to regroup several SimulationOutputEvaluator.

We also define some factory functions to facilitate their creation.

class ListOfSimulationOutputEvaluators(evaluators: list[SimulationOutputEvaluator])

Bases: list

A simple list of SimulationOutputEvaluator.

__init__(evaluators: list[SimulationOutputEvaluator]) → None: Create the objects (factory).

run(*simulation_outputs: SimulationOutput, other_evals: dict[str, list[Any]] | None = None, project_folder: Path | None = None, **files_kw) → DataFrame: Run all the evaluations.

_unpack_other_evals(other_evals: dict[str, list[Any]] | None) → tuple[list[str], list[list[Any]]]: Extract column names and data.

_set_indexes(*simulation_outputs: SimulationOutput) → list[str]: Set the indexes of the pandas dataframe.

_set_columns(other_columns: list[str]) → list[str]: Set the columns of the pandas dataframe.

_get_evaluations(other_data: list[list[Any]], *simulation_outputs: SimulationOutput) → list[list[float | bool | timedelta]]

class FaultScenarioSimulationOutputEvaluators(quantities: tuple[str], faults: list[Fault], simulation_outputs: tuple[SimulationOutputEvaluator], additional_elts: tuple[Element | str] | None = None)

Bases: object

A more specific class to evaluate settings found for a FaultScenario.

This class was designed to be used when all the faults of a FaultScenario are fixed, to output several performance indicators in a compact way. No plot is produced.

__init__(quantities: tuple[str], faults: list[Fault], simulation_outputs: tuple[SimulationOutputEvaluator], additional_elts: tuple[Element | str] | None = None) → None

_set_evaluation_elements(faults: list[Fault], additional_elts: tuple[Element | str] | None = None) → tuple[list[Element | str], list[str]]

Set where the relative difference of quantities will be evaluated.

It is at the end of each compensation zone, plus at the exit of additional elements if given. Also set columns to ease pandas DataFrame creation.

_create_simulation_output_evaluators(ref_simulation_output: SimulationOutput) → list[SimulationOutputEvaluator]: Create the proper SimulationOutputEvaluator s.

run(output: bool = True) → DataFrame: Perform all the simulation output evaluations.

_to_pandas_dataframe(evaluations: list[float | bool | None], precision: int = 3) → DataFrame: Convert all the evaluations to a compact pd.DataFrame.

_format_evaluations(evaluations: list[float | bool | None], precision: int = 3) → list[str]: Prepare the evaluations array for a nice output.

_output(evaluations: DataFrame) → None: Print out the given pd.DataFrame.