Source code for pymoo.visualization.radviz

"""Radviz plot visualization for multi-objective optimization results."""

from pymoo.docs import parse_doc_string
from pymoo.core.plot import Plot
from pymoo.util.misc import set_if_none_from_tuples
from pymoo.visualization.util import (
    plot_circle,
    plot_radar_line,
    plot_axis_labels,
    equal_axis,
    no_ticks,
    get_uniform_points_around_circle,
)




class Radviz(Plot):
    """Radviz plot visualization.

    Args:
        axis_style: {axis_style}
        endpoint_style: Endpoints are drawn at each extreme point of an objective. This style can be modified.
        labels: {labels}
        figsize: {figsize}
        title: {title}
        legend: {legend}
        tight_layout: {tight_layout}
        cmap: {cmap}
    """

    def __init__(self, endpoint_style: dict | None = None, **kwargs) -> None:
        super().__init__(**kwargs)

        # set the default axis style
        set_if_none_from_tuples(
            self.axis_style, ("color", "black"), ("linewidth", 1), ("alpha", 0.75)
        )

        if endpoint_style is None:
            endpoint_style = {}
        self.endpoint_style = endpoint_style
        set_if_none_from_tuples(
            self.endpoint_style, ("color", "black"), ("s", 70), ("alpha", 0.3)
        )

    def _do(self) -> None:
        # initial a figure with a single plot
        self.init_figure()

        # equal axis length and no ticks
        equal_axis(self.ax)
        no_ticks(self.ax)

        V = get_uniform_points_around_circle(self.n_dim)
        plot_axis_labels(self.ax, V, self.get_labels(), **self.axis_label_style)

        # draw the outer circle and radar lines
        plot_circle(self.ax, **self.axis_style)
        plot_radar_line(self.ax, V, **self.axis_style)

        # draw the endpoints of each objective
        if self.endpoint_style:
            self.ax.scatter(V[:, 0], V[:, 1], **self.endpoint_style)

        # plot all the points
        for k, (F, kwargs) in enumerate(self.to_plot):
            N = (F[..., None] * V).sum(axis=1) / F.sum(axis=1)[:, None]
            self.ax.scatter(N[:, 0], N[:, 1], **kwargs)



parse_doc_string(Radviz.__init__)