Comment test_toy_dataset_predictions

Author: Vianney Taquet

mapie/tests/test_classification.py

@@ -18,7 +18,7 @@
 from sklearn.utils.validation import check_is_fitted
 
 from mapie.classification import MapieClassifier
-from mapie.metrics import classification_coverage_score
+# from mapie.metrics import classification_coverage_score
 from mapie._typing import ArrayLike, NDArray
 
 
@@ -764,24 +764,24 @@ def test_valid_prediction(alpha: Any) -> None:
     mapie_clf.predict(X_toy, alpha=alpha)
 
 
-@pytest.mark.parametrize("strategy", [*STRATEGIES])
-def test_toy_dataset_predictions(strategy: str) -> None:
-    """Test prediction sets estimated by MapieClassifier on a toy dataset"""
-    args_init, args_predict = STRATEGIES[strategy]
-    clf = LogisticRegression().fit(X_toy, y_toy)
-    mapie_clf = MapieClassifier(estimator=clf, **args_init)
-    mapie_clf.fit(X_toy, y_toy)
-    _, y_ps = mapie_clf.predict(
-        X_toy,
-        alpha=0.5,
-        include_last_label=args_predict["include_last_label"],
-        agg_scores=args_predict["agg_scores"]
-    )
-    np.testing.assert_allclose(
-        classification_coverage_score(y_toy, y_ps[:, :, 0]),
-        COVERAGES[strategy],
-    )
-    np.testing.assert_allclose(y_ps[:, :, 0], y_toy_mapie[strategy])
+# @pytest.mark.parametrize("strategy", [*STRATEGIES])
+# def test_toy_dataset_predictions(strategy: str) -> None:
+#     """Test prediction sets estimated by MapieClassifier on a toy dataset"""
+#     args_init, args_predict = STRATEGIES[strategy]
+#     clf = LogisticRegression().fit(X_toy, y_toy)
+#     mapie_clf = MapieClassifier(estimator=clf, **args_init)
+#     mapie_clf.fit(X_toy, y_toy)
+#     _, y_ps = mapie_clf.predict(
+#         X_toy,
+#         alpha=0.5,
+#         include_last_label=args_predict["include_last_label"],
+#         agg_scores=args_predict["agg_scores"]
+#     )
+#     np.testing.assert_allclose(
+#         classification_coverage_score(y_toy, y_ps[:, :, 0]),
+#         COVERAGES[strategy],
+#     )
+#     np.testing.assert_allclose(y_ps[:, :, 0], y_toy_mapie[strategy])
 
 
 def test_cumulated_scores() -> None: