CADETProcess.optimization.Population.plot_pairwise#
- Population.plot_pairwise(use_transformed: bool = False, plot_infeasible: bool = True, color_feas: str = 'blue', color_infeas: str = 'red', *args: Any, ax: ndarray[tuple[Any, ...], dtype[Axes]] | None = None, setup_figure_kwargs: dict | None = None, **kwargs: Any) tuple[Figure, ndarray[tuple[Any, ...], dtype[Axes]]][source]#
Create a pairplot using Matplotlib.
- Parameters:
- use_transformedbool, optional
If True, use the transformed independent variables. The default is False.
- plot_infeasiblebool, default=True
If True, plot infeasible points.
- color_feasstr, default=’blue’
Color for feasible points.
- color_infeasstr, default=’red’
Color for infeasible points.
- *argsAny
Additional positional arguments passed to plot_pairwise.
- 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 plot_pairwise.
- Returns:
- tuple[plt.Figure, npt.NDArray[plt.Axes]]
Figure and axes objects.