CADETProcess.optimization.OptimizationResults.plot_pareto#
- OptimizationResults.plot_pareto(plot_pareto: bool = True, plot_evolution: bool = False, *args: Any, ax: ndarray[Axes] | None = None, setup_figure_kwargs: dict | None = None, **kwargs: Any) tuple[Figure, ndarray[Axes]][source]#
Plot Pareto fronts for each generation in the optimization.
The Pareto front represents the optimal solutions that cannot be improved in one objective without sacrificing another. The method shows a pairwise Pareto plot, where each objective is plotted against every other objective in a scatter plot, allowing for a visualization of the trade-offs between the objectives. To highlight the progress, a colormap is used where later generations are plotted with darker blueish colors.
- Parameters:
- plot_paretobool, default=False
If True, only Pareto front members of each generation are plotted. Otherwise, all evaluated individuals are plotted.
- plot_evolutionbool, optional
If True, the Pareto front is plotted for each generation. Else, only final Pareto front is plotted. The default is False.
- *argsAny
Additional positional arguments passed to gen.plot_pareto.
- axnp.ndarray[plt.Axes] | None, default=None
Optional array of Matplotlib Axes. If not provided, a new figure is created.
- setup_figure_kwargsdict | None, default=None
Additional options to setup the figure.
- **kwargsAny
Additional keyword arguments passed to gen.plot_pareto.
- Returns:
- tuple[plt.Figure, np.ndarray[plt.Axes]]
A tuple containing: - The Matplotlib Figure object. - An array of Axes objects representing the subplots.