Merge branch 'main' into specconn_tfr_support

.pre-commit-config.yaml

@@ -1,7 +1,7 @@
 repos:
   # Ruff mne_connectivity
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.6.4
+    rev: v0.6.5
     hooks:
       - id: ruff
         name: ruff lint mne_connectivity
@@ -10,7 +10,7 @@ repos:
 
   # Ruff tutorials and examples
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.6.4
+    rev: v0.6.5
     hooks:
       - id: ruff
         name: ruff lint tutorials and examples

doc/conf.py

@@ -149,6 +149,9 @@
     "Axes3D": "mpl_toolkits.mplot3d.axes3d.Axes3D",
     "PolarAxes": "matplotlib.projections.polar.PolarAxes",
     "ColorbarBase": "matplotlib.colorbar.ColorbarBase",
+    # sklearn
+    "MetadataRequest": "sklearn.utils.metadata_routing.MetadataRequest",
+    "estimator": "sklearn.base.BaseEstimator",
     # joblib
     "joblib.Parallel": "joblib.Parallel",
     # nibabel
@@ -360,3 +363,30 @@
 suppress_warnings = [
     "config.cache",  # our rebuild is okay
 ]
+
+
+def fix_sklearn_inherited_docstrings(app, what, name, obj, options, lines):
+    """Fix sklearn docstrings because they use autolink and we do not."""
+    if (
+        name.startswith("mne_connectivity.decoding.")
+    ) and name.endswith(
+        (
+            ".get_metadata_routing",
+            ".fit",
+            ".fit_transform",
+            ".set_output",
+            ".transform",
+        )
+    ):
+        if ":Parameters:" in lines:
+            loc = lines.index(":Parameters:")
+        else:
+            loc = lines.index(":Returns:")
+        lines.insert(loc, "")
+        lines.insert(loc, ".. default-role:: autolink")
+        lines.insert(loc, "")
+
+
+def setup(app):
+    """Set up the Sphinx app."""
+    app.connect("autodoc-process-docstring", fix_sklearn_inherited_docstrings)

mne_connectivity/decoding/decomposition.py

@@ -8,13 +8,12 @@
 import numpy as np
 from mne import Info
 from mne._fiff.pick import pick_info
-from mne.decoding.mixin import TransformerMixin
 from mne.defaults import _BORDER_DEFAULT, _EXTRAPOLATE_DEFAULT, _INTERPOLATION_DEFAULT
 from mne.evoked import EvokedArray
-from mne.fixes import BaseEstimator
 from mne.time_frequency import csd_array_fourier, csd_array_morlet, csd_array_multitaper
 from mne.utils import _check_option, _validate_type
 from mne.viz.utils import plt_show
+from sklearn.base import BaseEstimator, TransformerMixin
 
 from ..spectral.epochs_multivariate import (
     _CaCohEst,
@@ -222,6 +221,7 @@ def __init__(
         # n_jobs and verbose will be checked downstream
 
         # Store inputs
+        self.method = method
         self.info = info
         self._conn_estimator_class = _conn_estimator_class
         self._indices = _indices  # uses getter/setter for public parameter

mne_connectivity/decoding/tests/test_decomposition.py

@@ -174,9 +174,9 @@ def test_spectral_decomposition(method, mode):
     epochs_transformed_2 = decomp_class_2.transform(
         X=epochs[: n_epochs // 2].get_data()
     )
-    assert_allclose(epochs_transformed, epochs_transformed_2, atol=1e-9)
-    assert_allclose(decomp_class.filters_, decomp_class_2.filters_, atol=1e-9)
-    assert_allclose(decomp_class.patterns_, decomp_class_2.patterns_, atol=1e-9)
+    assert_allclose(epochs_transformed, epochs_transformed_2, atol=1e-8)
+    assert_allclose(decomp_class.filters_, decomp_class_2.filters_, atol=1e-8)
+    assert_allclose(decomp_class.patterns_, decomp_class_2.patterns_, atol=1e-8)
 
     # TEST FITTING ON ONE PIECE OF DATA AND TRANSFORMING ANOTHER
     con_mv_class_unseen_data = spectral_connectivity_epochs(

pyproject.toml

@@ -23,6 +23,7 @@ dependencies = [
   'netCDF4 >= 1.6.5',
   'numpy >= 1.21',
   'pandas >= 1.3.2',
+  'scikit-learn >= 1.2',
   'scipy >= 1.4.0',
   'tqdm',
   'xarray >= 2023.11.0',