CADETProcess.optimization.OptimizationResults.plot_convergence#
- OptimizationResults.plot_convergence(target: Literal['objectives', 'nonlinear_constraints', 'meta_scores'] = 'objectives', plot_avg: bool = True, autoscale: bool = True, ax: ndarray[tuple[Any, ...], dtype[Axes]] | None = None, setup_figure_kwargs: dict | None = None) tuple[Figure, ndarray[tuple[Any, ...], dtype[Axes]]][source]#
Plot the convergence of optimization metrics over evaluations.
- Parameters:
- targetLiteral[“objectives”, “nonlinear_constraints”, “meta_scores”]
The target metrics to plot. The default is “objectives”.
- plot_avgbool, default=True
If True, plot the average trajectory per generation.
- autoscalebool, default=True
If True, autoscale the y-axis.
- axnpt.NDArray[plt.Axes] | None, default=None
Axes to plot on. If not provided, a new figure is created.
- setup_figure_kwargsdict | None, default=None
Additional options to setup the figure.
- Returns:
- tuple[plt.Figure, npt.NDArray[plt.Axes]]
Figure and array of Axes objects.