tests

Author: MatthewMiddlehurst

aeon/testing/estimator_checking/_yield_collection_anomaly_detection_checks.py

@@ -1,9 +1,69 @@
 """Tests for all collection anomaly detectors."""
 
+from functools import partial
+
+from aeon.base._base import _clone_estimator
+from aeon.testing.testing_data import FULL_TEST_DATA_DICT
+from aeon.testing.utils.estimator_checks import _assert_predict_labels
+from aeon.utils.data_types import COLLECTIONS_DATA_TYPES
+
 
 def _yield_collection_anomaly_detection_checks(
     estimator_class, estimator_instances, datatypes
 ):
     """Yield all collection anomaly detection checks for an aeon estimator."""
-    # nothing currently!
-    return []
+    # only class required
+    yield partial(
+        check_collection_detector_overrides_and_tags, estimator_class=estimator_class
+    )
+
+    # test class instances
+    for i, estimator in enumerate(estimator_instances):
+        # test all data types
+        for datatype in datatypes[i]:
+            yield partial(
+                check_collection_detector_output, estimator=estimator, datatype=datatype
+            )
+
+
+def check_collection_detector_overrides_and_tags(estimator_class):
+    """Test compliance with the detector base class contract."""
+    # Test they don't override final methods, because Python does not enforce this
+    final_methods = [
+        "fit",
+        "predict",
+    ]
+    for method in final_methods:
+        if method in estimator_class.__dict__:
+            raise ValueError(
+                f"Collection anomaly detector {estimator_class} overrides the "
+                f"method {method}. Override _{method} instead."
+            )
+
+    # Test valid tag for X_inner_type
+    X_inner_type = estimator_class.get_class_tag(tag_name="X_inner_type")
+    if isinstance(X_inner_type, str):
+        assert X_inner_type in COLLECTIONS_DATA_TYPES
+    else:  # must be a list
+        assert all([t in COLLECTIONS_DATA_TYPES for t in X_inner_type])
+
+    # one of X_inner_types must be capable of storing unequal length
+    if estimator_class.get_class_tag("capability:unequal_length"):
+        valid_unequal_types = ["np-list", "df-list", "pd-multiindex"]
+        if isinstance(X_inner_type, str):
+            assert X_inner_type in valid_unequal_types
+        else:  # must be a list
+            assert any([t in valid_unequal_types for t in X_inner_type])
+
+
+def check_collection_detector_output(estimator, datatype):
+    """Test detector outputs the correct data types and values."""
+    estimator = _clone_estimator(estimator)
+
+    # run fit and predict
+    estimator.fit(
+        FULL_TEST_DATA_DICT[datatype]["train"][0],
+        FULL_TEST_DATA_DICT[datatype]["train"][1],
+    )
+    y_pred = estimator.predict(FULL_TEST_DATA_DICT[datatype]["test"][0])
+    _assert_predict_labels(y_pred, datatype, unique_labels=[0, 1])