FIX SplineTransformer.get_feature_names_out returns correct names for extrapolations=periodic (scikit-learn#25296)

thomasjpfan · ogrisel · jjerphan · commit 88aebc774570 · 2023-01-20T15:30:50.000+01:00
Co-authored-by: Olivier Grisel &lt;olivier.grisel@ensta.org&gt;
diff --git a/doc/whats_new/v1.2.rst b/doc/whats_new/v1.2.rst
@@ -60,6 +60,10 @@ Changelog
   supports DataFrames that are all numerical when `check_inverse=True`.
   :pr:`25274` by `Thomas Fan`_.
 
+- |Fix| :meth:`preprocessing.SplineTransformer.get_feature_names_out` correctly
+  returns feature names when `extrapolations="periodic"`. :pr:`25296` by
+  `Thomas Fan`_.
+
 :mod:`sklearn.tree`
 ...................
 
diff --git a/sklearn/preprocessing/_polynomial.py b/sklearn/preprocessing/_polynomial.py
@@ -673,7 +673,8 @@ def get_feature_names_out(self, input_features=None):
         feature_names_out : ndarray of str objects
             Transformed feature names.
         """
-        n_splines = self.bsplines_[0].c.shape[0]
+        n_splines = self.bsplines_[0].c.shape[1]
+
         input_features = _check_feature_names_in(self, input_features)
         feature_names = []
         for i in range(self.n_features_in_):
diff --git a/sklearn/preprocessing/tests/test_polynomial.py b/sklearn/preprocessing/tests/test_polynomial.py
@@ -76,6 +76,25 @@ def test_spline_transformer_feature_names():
     )
 
 
+@pytest.mark.parametrize(
+    "extrapolation",
+    ["constant", "linear", "continue", "periodic"],
+)
+@pytest.mark.parametrize("degree", [2, 3])
+def test_split_transform_feature_names_extrapolation_degree(extrapolation, degree):
+    """Test feature names are correct for different extrapolations and degree.
+
+    Non-regression test for gh-25292.
+    """
+    X = np.arange(20).reshape(10, 2)
+    splt = SplineTransformer(degree=degree, extrapolation=extrapolation).fit(X)
+    feature_names = splt.get_feature_names_out(["a", "b"])
+    assert len(feature_names) == splt.n_features_out_
+
+    X_trans = splt.transform(X)
+    assert X_trans.shape[1] == len(feature_names)
+
+
 @pytest.mark.parametrize("degree", range(1, 5))
 @pytest.mark.parametrize("n_knots", range(3, 5))
 @pytest.mark.parametrize("knots", ["uniform", "quantile"])
