Merge branch 'develop'

strongio · Nov 16, 2023 · a4bb55e · a4bb55e
2 parents a8850ea + fe97969
commit a4bb55e
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Showing 4 changed files with 8 additions and 6 deletions.
diff --git a/foundry/preprocessing/categorical.py b/foundry/preprocessing/categorical.py
@@ -14,7 +14,7 @@ class ToCategorical(TransformerMixin, BaseEstimator):
     def __init__(self):
         self.categories_ = None
 
-    def get_feature_names_out(self, feature_names_in) -> Sequence[str]:
+    def get_feature_names_out(self, feature_names_in=None) -> Sequence[str]:
         return self._feature_names_out
 
     def fit(self, X: pd.DataFrame, y=None) -> 'ToCategorical':

diff --git a/foundry/preprocessing/dates.py b/foundry/preprocessing/dates.py
@@ -40,7 +40,7 @@ def fit(self, X, y=None) -> 'FourierFeatures':
 
         return self
 
-    def get_feature_names_out(self, feature_names_in) -> np.ndarray:
+    def get_feature_names_out(self, feature_names_in=None) -> np.ndarray:
         feature_names_in = _check_feature_names_in(self, feature_names_in)
 
         if len(feature_names_in) == 1:

diff --git a/foundry/preprocessing/sklearn/backports.py b/foundry/preprocessing/sklearn/backports.py
@@ -12,6 +12,8 @@
 from sklearn.utils.validation import _check_feature_names_in
 
 
+# TODO: use sklearn versions if on newer version that implements `get_feature_names_out`
+
 class FunctionTransformer(FunctionTransformerBase):
     """
     Add ``get_feature_names_out()`` to ``FunctionTransformer``
@@ -32,7 +34,7 @@ def fit(self, X, y=None) -> 'FunctionTransformer':
                 self._feature_names_out = [f'x{i}' for i in range(maybe_df.shape[1])]
         return self
 
-    def get_feature_names_out(self, feature_names_in) -> Sequence[str]:
+    def get_feature_names_out(self, feature_names_in=None) -> Sequence[str]:
         if len(feature_names_in) == len(self._feature_names_out):
             return np.asarray([
                 x if x == y else f'{x}_{y}' for x, y in zip(feature_names_in, self._feature_names_out)
@@ -46,8 +48,8 @@ def get_feature_names_out(self, feature_names_in) -> Sequence[str]:
 
 
 class SimpleImputer(SimpleImputerBase):
-    def get_feature_names_out(self, input_features=None):
-        input_features = _check_feature_names_in(self, input_features)
+    def get_feature_names_out(self, feature_names_in=None):
+        input_features = _check_feature_names_in(self, feature_names_in)
         names = input_features[~isna(self.statistics_)]
         if not self.add_indicator:
             return names

diff --git a/foundry/preprocessing/sklearn/interactions.py b/foundry/preprocessing/sklearn/interactions.py
@@ -118,7 +118,7 @@ def transform(self, X: pd.DataFrame, y=None) -> pd.DataFrame:
 
         return X.drop(columns=X.columns[X.columns.isin(new_cols)]).join(df_new_cols)
 
-    def get_feature_names_out(self):
+    def get_feature_names_out(self, feature_names_in=None):
         if self.feature_names_in_ is None:
             raise NotFittedError(f"This {type(self).__name__} is not fitted. Cannot get_feature_names_out.")