optimization_history module

Provide functions to study optimization history.

load(folder: Path, flag_constraints: bool = False) → tuple[DataFrame, DataFrame, DataFrame]

Load the threee optimization history files in folder.

get_optimization_objective_names(objectives: DataFrame) → tuple[list[str], list[str]]

Get the columns corresponding to optimization objectives.

Also return columns taken from simulation outputs.

plot_optimization_objectives(objectives: DataFrame, opti_cols: list[str], subplots: bool = False, logy: bool | Literal['sym'] | None = None, **kwargs) → Axis | ndarray

Plot evolution of optimization objectives.

_qty_sim_output(column_name: str) → str

Get the quantity that is stored in the column column_name.

It is expected that the header of the column is qty @ position; it only works for the quantites taken from SimulationOutput and written in the objectives.csv.

_post_treat(df: DataFrame, post_treat: Literal['relative difference', 'difference'] | None = None, make_absolute: bool = False) → tuple[DataFrame, str]

Post-treat the SimulationOutput data.

plot_additional_objectives(objectives: DataFrame, simulation_output_cols: list[str], subplots: bool = False, logy: bool | Literal['sym'] | None = None, post_treat: Literal['relative difference', 'difference'] | None = None, **kwargs) → Axis | ndarray | list

Plot evolution of additional objectives.

main(folder: Path) → DataFrame

Provide an example of complete study.