plot_all_metric_pareto_front

site.SiteSolutionSet.plot_all_metric_pareto_front(
    height=4,
    show_points=True,
    theme='whitegrid',
    maxx=None,
    maxy=None,
    cols=3,
    **kwargs,
)

Plot Pareto fronts for all pairs of solution metrics.

This method generates a grid of subplots, each showing the Pareto front for a pairwise combination of performance metrics. It provides a comprehensive view of trade-offs between all available objectives.

Parameters

Name Type Description Default
height float Height (in inches) allocated to each subplot. 4
show_points bool If True, all solutions are plotted as points in addition to the Pareto front in each subplot. True
theme str Visual theme passed to the underlying plotting function. "whitegrid"
maxx bool or None If True, x-axis metrics are treated as maximisation objectives when computing Pareto fronts. If False, they are minimised. If None, the direction is inferred per metric. None
maxy bool or None If True, y-axis metrics are treated as maximisation objectives when computing Pareto fronts. If False, they are minimised. If None, the direction is inferred per metric. None
cols int Number of columns in the subplot grid. 3
**kwargs Additional keyword arguments passed to spv.pareto_plot. {}

Returns

Name Type Description
matplotlib.figure.Figure The matplotlib Figure containing all Pareto front subplots.

Notes

The method constructs all pairwise combinations of the following metrics: - “weighted_average” - “unweighted_average” - “90th_percentile” - “max” - “proportion_within_coverage_threshold” (included only if available)

Each subplot visualises the Pareto front for a pair of metrics using the spv.pareto_plot function.

Subplots are arranged in a grid with a specified number of columns, and rows are determined automatically.

Any unused subplot axes (if the grid is larger than required) are removed from the figure.

The figure is closed before returning to prevent duplicate display in some environments (e.g., Jupyter notebooks).

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