feature: Update BaseMetric class

tests/metrics/test_base_metric.py

@@ -1,3 +1,5 @@
+"""Unit tests for the BaseMetric class in the wefe.metrics.base_metric module."""
+
 import pytest
 
 from wefe.metrics.base_metric import BaseMetric
@@ -10,6 +12,21 @@ def test_base_metric_input_checking(
     query_2t2a_1: Query,
     query_3t2a_1: Query,
 ) -> None:
+    """Test input validation for the BaseMetric class.
+    This test verifies that the `_check_input` method of `BaseMetric` correctly
+    raises exceptions when provided with invalid inputs, such as incorrect types
+    for `query` and `model`, or mismatched cardinalities for target and attribute sets.
+
+    Parameters
+    ----------
+    model : WordEmbeddingModel
+        A word embedding model instance used for metric evaluation.
+    query_2t2a_1 : Query
+        A query instance with 2 target sets and 2 attribute sets.
+    query_3t2a_1 : Query
+        A query instance with 3 target sets and 2 attribute sets.
+
+    """
     # Create and configure base metric testing.
     # disable abstract methods.
 
@@ -21,84 +38,74 @@ def test_base_metric_input_checking(
     base_metric.metric_short_name = "TM"
 
     with pytest.raises(TypeError, match="query should be a Query instance, got*"):
-        base_metric._check_input(None, model, {})
-
-    with pytest.raises(
-        TypeError, match="word_embedding should be a WordEmbeddingModel instance, got*"
-    ):
-        base_metric._check_input(query_2t2a_1, None, {})
-
-    with pytest.raises(
-        Exception,
-        match="The cardinality of the set of target words of the 'Flowers, Weapons and "
-        "Instruments wrt Pleasant and Unpleasant' query does not match with the "
-        "cardinality required by TM. Provided query: 3, metric: 2",
-    ):
-        base_metric._check_input(query_3t2a_1, model, {})
-
-    with pytest.raises(
-        Exception,
-        match=(
-            "The cardinality of the set of attribute words of the 'Flowers and Insects "
-            "wrt Pleasant and Unpleasant' query does not match with the cardinality "
-            "required by TM. Provided query: 2, metric: 3"
-        ),
-    ):
-        base_metric._check_input(query_2t2a_1, model, {})
-
-
-def test_validate_old_preprocessor_args_inputs(
-    model: WordEmbeddingModel,
-    query_2t2a_1: Query,
-) -> None:
-    # instance test metric
-    BaseMetric.__abstractmethods__ = frozenset()
-    base_metric = BaseMetric()
-    base_metric.metric_template = (2, 2)
-    base_metric.metric_name = "Test Metric"
-    base_metric.metric_short_name = "TM"
+        base_metric._check_input(
+            query=None,
+            model=model,
+            lost_vocabulary_threshold=0.2,
+            warn_not_found_words=True,
+        )
 
     with pytest.raises(
-        DeprecationWarning,
-        match=(
-            r"preprocessor_args argument is deprecated. "
-            r"Use preprocessors=\[\{'uppercase': True\}\] instead.*."
-        ),
+        TypeError,
+        match="model should be a WordEmbeddingModel instance, got: <class 'NoneType'>.",
     ):
         base_metric._check_input(
-            query_2t2a_1, model, {"preprocessor_args": {"uppercase": True}}
+            query=query_2t2a_1,
+            model=None,
+            lost_vocabulary_threshold=0.2,
+            warn_not_found_words=True,
         )
 
     with pytest.raises(
-        DeprecationWarning,
+        Exception,
         match=(
-            r"secondary_preprocessor_args is deprecated. "
-            r"Use preprocessors=\[\{\}, \{'uppercase': True\}\] instead.*."
+            r"The cardinality of the target sets of the 'Flowers, Weapons and "
+            r"Instruments wrt Pleasant and Unpleasant' query \(3\) does not match "
+            r"the cardinality required by TM \(2\)."
         ),
     ):
         base_metric._check_input(
-            query_2t2a_1, model, {"secondary_preprocessor_args": {"uppercase": True}}
+            query=query_3t2a_1,
+            model=model,
+            lost_vocabulary_threshold=0.2,
+            warn_not_found_words=True,
         )
 
     with pytest.raises(
-        DeprecationWarning,
+        Exception,
         match=(
-            r"preprocessor_args and secondary_preprocessor_args arguments are "
-            r"deprecated. Use preprocessors=\[\{'uppercase': True\}, \{'uppercase': "
-            r"True\}\] instead."
+            r"The cardinality of the attribute sets of the 'Flowers and Insects wrt "
+            r"Pleasant and Unpleasant' query \(2\) does not match the cardinality "
+            r"required by TM \(3\)."
         ),
     ):
         base_metric._check_input(
-            query_2t2a_1,
-            model,
-            {
-                "preprocessor_args": {"uppercase": True},
-                "secondary_preprocessor_args": {"uppercase": True},
-            },
+            query=query_2t2a_1,
+            model=model,
+            lost_vocabulary_threshold=0.2,
+            warn_not_found_words=True,
         )
 
 
-def test_run_query(model: WordEmbeddingModel, query_2t2a_1: Query) -> None:
+def test_run_query(
+    model: WordEmbeddingModel,
+    query_2t2a_1: Query,
+) -> None:
+    """Test that the `run_query` method of `BaseMetric` raises a NotImplementedError.
+
+    Parameters
+    ----------
+    model : WordEmbeddingModel
+        The word embedding model to be used in the query.
+    query_2t2a_1 : Query
+        The query object to be passed to the metric.
+
+    Raises
+    ------
+    NotImplementedError
+        If the `run_query` method is not implemented in `BaseMetric`.
+
+    """
     # disable abstract methods.
     BaseMetric.__abstractmethods__ = frozenset()
     base_metric = BaseMetric()
@@ -110,4 +117,4 @@ def test_run_query(model: WordEmbeddingModel, query_2t2a_1: Query) -> None:
     with pytest.raises(
         NotImplementedError,
     ):
-        base_metric.run_query(query_2t2a_1, model)
+        base_metric.run_query(query=query_2t2a_1, model=model)

wefe/metrics/ECT.py

@@ -160,7 +160,12 @@ def run_query(
 
         """
         # check the types of the provided arguments (only the defaults).
-        self._check_input(query, model, locals())
+        self._check_input(
+            query=query,
+            model=model,
+            lost_vocabulary_threshold=lost_vocabulary_threshold,
+            warn_not_found_words=warn_not_found_words,
+        )
 
         # transform query word sets into embeddings
         embeddings = get_embeddings_from_query(

wefe/metrics/MAC.py

@@ -448,7 +448,12 @@ def run_query(
 
         """  # noqa: E501
         # check the types of the provided arguments (only the defaults).
-        self._check_input(query, model, locals())
+        self._check_input(
+            query=query,
+            model=model,
+            lost_vocabulary_threshold=lost_vocabulary_threshold,
+            warn_not_found_words=warn_not_found_words,
+        )
 
         # transform query word sets into embeddings
         embeddings = get_embeddings_from_query(

wefe/metrics/RIPA.py

@@ -268,7 +268,12 @@ def run_query(
 
         """
         # check the types of the provided arguments (only the defaults).
-        self._check_input(query, model, locals())
+        self._check_input(
+            query=query,
+            model=model,
+            lost_vocabulary_threshold=lost_vocabulary_threshold,
+            warn_not_found_words=warn_not_found_words,
+        )
 
         # transform query word sets into embeddings
         embeddings = get_embeddings_from_query(

wefe/metrics/RND.py

@@ -261,7 +261,12 @@ def run_query(
 
         """
         # check the types of the provided arguments (only the defaults).
-        self._check_input(query, model, locals())
+        self._check_input(
+            query=query,
+            model=model,
+            lost_vocabulary_threshold=lost_vocabulary_threshold,
+            warn_not_found_words=warn_not_found_words,
+        )
 
         # transform query word sets into embeddings
         embeddings = get_embeddings_from_query(

wefe/metrics/RNSB.py

@@ -792,7 +792,12 @@ def run_query(
 
         """
         # check the types of the provided arguments (only the defaults).
-        self._check_input(query, model, locals())
+        self._check_input(
+            query=query,
+            model=model,
+            lost_vocabulary_threshold=lost_vocabulary_threshold,
+            warn_not_found_words=warn_not_found_words,
+        )
 
         if n_iterations > 1 and random_state is not None:
             raise ValueError(

wefe/metrics/WEAT.py

@@ -439,7 +439,12 @@ def run_query(
 
         """
         # check the types of the provided arguments (only the defaults).
-        self._check_input(query, model, locals())
+        self._check_input(
+            query=query,
+            model=model,
+            lost_vocabulary_threshold=lost_vocabulary_threshold,
+            warn_not_found_words=warn_not_found_words,
+        )
 
         # transform query word sets into embeddings
         embeddings = get_embeddings_from_query(