FIX: Green?

Author: larsoner

mne/decoding/base.py

@@ -85,7 +85,11 @@ def __sklearn_tags__(self):
         """Get sklearn tags."""
         from sklearn.utils import get_tags  # added in 1.6
 
-        return get_tags(self.model)
+        # fit method below does not allow sparse data via check_data, we could
+        # eventually make it smarter if we had to
+        tags = get_tags(self.model)
+        tags.input_tags.sparse = False
+        return tags
 
     def __getattr__(self, attr):
         """Wrap to model for some attributes."""

mne/decoding/transformer.py

@@ -238,7 +238,7 @@ def inverse_transform(self, epochs_data):
         return out
 
 
-class Vectorizer(TransformerMixin):
+class Vectorizer(TransformerMixin, BaseEstimator):
     """Transform n-dimensional array into 2D array of n_samples by n_features.
 
     This class reshapes an n-dimensional array into an n_samples * n_features
@@ -343,7 +343,7 @@ def inverse_transform(self, X):
 
 
 @fill_doc
-class PSDEstimator(TransformerMixin):
+class PSDEstimator(TransformerMixin, BaseEstimator):
     """Compute power spectral density (PSD) using a multi-taper method.
 
     Parameters
@@ -452,7 +452,7 @@ def transform(self, epochs_data):
 
 
 @fill_doc
-class FilterEstimator(TransformerMixin):
+class FilterEstimator(TransformerMixin, BaseEstimator):
     """Estimator to filter RtEpochs.
 
     Applies a zero-phase low-pass, high-pass, band-pass, or band-stop
@@ -743,7 +743,7 @@ def _apply_method(self, X, method):
 
 
 @fill_doc
-class TemporalFilter(TransformerMixin):
+class TemporalFilter(TransformerMixin, BaseEstimator):
     """Estimator to filter data array along the last dimension.
 
     Applies a zero-phase low-pass, high-pass, band-pass, or band-stop

tools/install_pre_requirements.sh

@@ -18,10 +18,11 @@ python -m pip install $STD_ARGS pip setuptools packaging \
 	py-cpuinfo blosc2 hatchling
 echo "NumPy/SciPy/pandas etc."
 python -m pip uninstall -yq numpy
+python -m pip install --upgrade matplotlib  # TODO: Until https://github.com/matplotlib/matplotlib/pull/29427 lands
 python -m pip install $STD_ARGS --only-binary ":all:" --default-timeout=60 \
 	--index-url "https://pypi.anaconda.org/scientific-python-nightly-wheels/simple" \
 	"numpy>=2.1.0.dev0" "scikit-learn>=1.6.dev0" "scipy>=1.15.0.dev0" \
-	"pandas>=3.0.0.dev0" "matplotlib>=3.10.0.dev0" \
+	"pandas>=3.0.0.dev0" \
 	"h5py>=3.12.1" "dipy>=1.10.0.dev0" "pyarrow>=19.0.0.dev0" "tables>=3.10.2.dev0"
 
 # statsmodels requires formulaic@main so we need to use --extra-index-url