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.

Parameters:

• simulation_outputs (SimulationOutput) – All the simulation output instances.

• other_evals (dict[str, list[Any]] | None) – Dictionary with over evaluations to put in the output file. Keys are the column headers, values are corresponding values stored as lists. The default is None, in which case nothing is added.

• project_folder (Path | None) – Where to save the output file.

Returns:

A dataframe holding the evaluations.

Return type:

pd.DataFrame

_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.