FIX ColumnKernelizer for newer sklearn versions (#54)

* FIX add kwargs to ColumnKernelizer._hstack for newer sklearn versions

* FIX more fixes to deal with sklearn changes

* FIX,TST fixes for ColumnTransformerNoStack

himalaya/kernel_ridge/_kernelizer.py

@@ -1,16 +1,17 @@
-from sklearn.compose import ColumnTransformer
-from sklearn.compose import make_column_selector  # noqa
+from packaging import version
+
+import sklearn
 from sklearn.base import BaseEstimator, TransformerMixin
+from sklearn.compose import (
+    ColumnTransformer,
+    make_column_selector,  # noqa
+)
+from sklearn.pipeline import _name_estimators, make_pipeline
 from sklearn.utils.validation import check_is_fitted
-from sklearn.pipeline import make_pipeline, _name_estimators
-
-from ..backend import get_backend
-from ..backend import force_cpu_backend
-from ..validation import check_array
-from ..validation import _get_string_dtype
 
-from ._kernels import pairwise_kernels
-from ._kernels import PAIRWISE_KERNEL_FUNCTIONS
+from ..backend import force_cpu_backend, get_backend
+from ..validation import _get_string_dtype, check_array
+from ._kernels import PAIRWISE_KERNEL_FUNCTIONS, pairwise_kernels
 
 
 class Kernelizer(TransformerMixin, BaseEstimator):
@@ -336,7 +337,7 @@ def _iter(self, fitted=False, *args, **kwargs):
 
             yield (name, trans, column, weight)
 
-    def _hstack(self, Xs):
+    def _hstack(self, Xs, **kwargs):
         """Stack the kernels.
 
         In ColumnTransformer, this methods stacks Xs horizontally.
@@ -363,8 +364,17 @@ def get_X_fit(self):
         """
         check_is_fitted(self)
 
+        if version.parse(sklearn.__version__) < version.parse("1.4"):
+            iter_kwargs = {"replace_strings": True}
+        else:
+            iter_kwargs = {
+                "column_as_labels": False, 
+                "skip_drop": True, 
+                "skip_empty_columns": True
+            }
+
         Xs = []
-        for (_, trans, _, _) in self._iter(fitted=True, replace_strings=True):
+        for (_, trans, _, _) in self._iter(fitted=True, **iter_kwargs):
             if hasattr(trans, "get_X_fit"):
                 X = trans.get_X_fit()
             else:

himalaya/ridge/_column.py

@@ -129,7 +129,7 @@ class ColumnTransformerNoStack(ColumnTransformer):
     (2, 4, 4)
     """
 
-    def _hstack(self, Xs):
+    def _hstack(self, Xs, **kwargs):
         """Do *not* stack the feature spaces.
 
         In ColumnTransformer, this methods stacks Xs horizontally.

himalaya/ridge/tests/test_column.py

@@ -40,7 +40,7 @@ def test_column_transformer_remainder(backend):
     backend = set_backend(backend)
     X = np.random.randn(10, 5)
 
-    ct = ColumnTransformerNoStack([("name", "passthrough", [])],
+    ct = ColumnTransformerNoStack([("name", "passthrough", slice(0, 0))],
                                   remainder="passthrough")
     Xt = ct.fit_transform(X)
     assert len(Xt) == 2