fix!: rename cosine_similarity to paired_cosine_distances (#393)

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Fixes #<issue_number_goes_here> 🦕

Author: GarrettWu

bigframes/ml/metrics/pairwise.py

@@ -20,15 +20,17 @@
 import third_party.bigframes_vendored.sklearn.metrics.pairwise as vendored_metrics_pairwise
 
 
-def cosine_similarity(
+def paired_cosine_distances(
     X: Union[bpd.DataFrame, bpd.Series], Y: Union[bpd.DataFrame, bpd.Series]
 ) -> bpd.DataFrame:
     X, Y = utils.convert_to_dataframe(X, Y)
     if len(X.columns) != 1 or len(Y.columns) != 1:
         raise ValueError("Inputs X and Y can only contain 1 column.")
 
     base_bqml = core.BaseBqml(session=X._session)
-    return base_bqml.distance(X, Y, type="COSINE", name="cosine_similarity")
+    return base_bqml.distance(X, Y, type="COSINE", name="cosine_distance")
 
 
-cosine_similarity.__doc__ = inspect.getdoc(vendored_metrics_pairwise.cosine_similarity)
+paired_cosine_distances.__doc__ = inspect.getdoc(
+    vendored_metrics_pairwise.paired_cosine_distances
+)

tests/system/small/ml/test_metrics_pairwise.py

@@ -19,15 +19,15 @@
 import bigframes.pandas as bpd
 
 
-def test_cosine_similarity():
+def test_paired_cosine_distances():
     x_col = [np.array([4.1, 0.5, 1.0])]
     y_col = [np.array([3.0, 0.0, 2.5])]
     X = bpd.read_pandas(pd.DataFrame({"X": x_col}))
     Y = bpd.read_pandas(pd.DataFrame({"Y": y_col}))
 
-    result = metrics.pairwise.cosine_similarity(X, Y)
+    result = metrics.pairwise.paired_cosine_distances(X, Y)
     expected_pd_df = pd.DataFrame(
-        {"X": x_col, "Y": y_col, "cosine_similarity": [0.108199]}
+        {"X": x_col, "Y": y_col, "cosine_distance": [0.108199]}
     )
 
     pd.testing.assert_frame_equal(

third_party/bigframes_vendored/sklearn/metrics/pairwise.py

@@ -11,13 +11,8 @@
 import bigframes.pandas as bpd
 
 
-def cosine_similarity(X, Y) -> bpd.DataFrame:
-    """Compute cosine similarity between samples in X and Y.
-
-    Cosine similarity, or the cosine kernel, computes similarity as the
-    normalized dot product of X and Y:
-
-        K(X, Y) = <X, Y> / (||X||*||Y||)
+def paired_cosine_distances(X, Y) -> bpd.DataFrame:
+    """Compute the paired cosine distances between X and Y.
 
     Args:
         X (Series or single column DataFrame of array of numeric type):
@@ -26,6 +21,6 @@ def cosine_similarity(X, Y) -> bpd.DataFrame:
             Input data. X and Y are mapped by indexes, must have the same index.
 
     Returns:
-        bigframes.dataframe.DataFrame: DataFrame with columns of X, Y and cosine_similarity
+        bigframes.dataframe.DataFrame: DataFrame with columns of X, Y and cosine_distance
     """
     raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)