API Reference

compute_operating_profile

from opproplot import compute_operating_profile
profile = compute_operating_profile(y_true, y_score, bins=40, score_range=(0, 1))

• y_true: array-like of shape (n_samples,), binary labels.
• y_score: array-like of shape (n_samples,), predicted scores or probabilities.
• bins: number of score bins (default 40).
• score_range: tuple or None. If None, uses min/max of scores.

Returns an OperatingProfile dataclass with:

• edges, mids, pos_hist, neg_hist, tpr, fpr, accuracy.

operating_profile_plot

from opproplot import operating_profile_plot
fig, ax_hist, ax_metric = operating_profile_plot(
    y_true,
    y_score,
    bins=30,
    show_accuracy=True,
    show_key=True,
    key_location="inside",
    show_grid=False,
    title=None,
)

• y_true: array-like of shape (n_samples,), binary labels.
• y_score: array-like of shape (n_samples,), predicted scores or probabilities.
• bins: number of score bins (default 40).
• score_range: tuple or None. If None, uses min/max of scores.
• show_accuracy: include the dashed accuracy curve (default True).
• show_key: display combined legend for bars and lines (default True).
• key_location: "inside" (axis legend) or "outside" (fig-level, right dock).
• show_grid: draw a background grid on the metric axis (default False).
• grid_kwargs: dict passed to ax_metric.grid, e.g., {"alpha": 0.2, "linestyle": "--"}.
• title: optional title string; defaults to “Opproplot: Operating Profile”.
• ax: optional Matplotlib axis to draw on; otherwise creates a new figure.

Returns (fig, ax_hist, ax_metric) for further styling or saving.