sbi.analysis.pp_plot#
- pp_plot(scores, scores_null, true_scores_null, conf_alpha, n_alphas=100, labels=None, colors=None, ax=None, **kwargs)[source]#
Probability - Probability (P-P) plot for hypothesis tests to assess the validity of one (or several) estimator(s).
See here for more details.
- Parameters:
scores (List[ndarray] | Dict[Any, ndarray]) – test scores estimated on observed data and evaluated on the test set, of shape (n_eval,). One array per estimator.
scores_null (List[ndarray] | Dict[Any, ndarray]) – test scores estimated under the null hypothesis and evaluated on the test set, of shape (n_eval,). One array per null trial.
true_scores_null (ndarray) – theoretical true scores under the null hypothesis, of shape (n_eval,).
labels (List[str] | None) – labels for the estimators, defaults to None.
colors (List[str] | None) – colors for the estimators, defaults to None.
conf_alpha (float) – significanecee level of the hypothesis test.
n_alphas (int) – number of cdf-values to compute the P-P plot, defaults to 100.
ax (Axes | None) – axis to plot on, defaults to None.
kwargs (Any) – additional arguments for matplotlib plotting.
- Returns:
axes with the P-P plot.
- Return type:
ax