Clean up old version usages and SPEC0 pin a few more deps (#14108)

Author: larsoner

doc/changes/dev/14108.bugfix.rst

@@ -0,0 +1,3 @@
+Fixed bug in :meth:`mne.io.Raw.plot` where, with the matplotlib backend and
+``group_by="selection"``, the channel-selection radio buttons no longer all appeared
+selected while in butterfly mode, by `Eric Larson`_.

doc/changes/dev/14108.dependency.rst

@@ -0,0 +1,9 @@
+Raised minimum versions of some optional dependencies to comply with MNE-Python's
+SPEC0-like policy, and added them to the set kept up to date automatically by the
+``spec_zero`` CI job, by `Eric Larson`_:
+
+- Optional dependency ``dipy >= 1.9``
+- Optional dependency ``mne-qt-browser >= 0.6``
+- Optional dependency ``nibabel >= 5.2``
+- Optional dependency ``nilearn >= 0.10``
+- Optional dependency ``numba >= 0.60``

doc/sphinxext/gh_substitutions.py

@@ -2,24 +2,8 @@
 # License: BSD-3-Clause
 # Copyright the MNE-Python contributors.
 
-import docutils
 from docutils.nodes import reference
-
-# Adapted from sphinx
-if docutils.__version_info__[:2] < (0, 22):
-    from docutils.parsers.rst import roles
-
-    def _normalize_options(options):
-        if options is None:
-            return {}
-        n_options = options.copy()
-        roles.set_classes(n_options)
-        return n_options
-
-else:
-    from docutils.parsers.rst.roles import (
-        normalize_options as _normalize_options,
-    )
+from docutils.parsers.rst.roles import normalize_options as _normalize_options
 
 
 def gh_role(name, rawtext, text, lineno, inliner, options={}, content=[]):  # noqa: B006

environment.yml

@@ -10,7 +10,7 @@ dependencies:
   - darkdetect
   - decorator >=5.1
   - defusedxml
-  - dipy >=0.8
+  - dipy >=1.9
   - edfio >=0.4.10
   - eeglabio
   - ffmpeg =8.1.2
@@ -30,13 +30,13 @@ dependencies:
   - mamba
   - matplotlib >=3.9
   - mffpy >=0.11.0
-  - mne-qt-browser
+  - mne-qt-browser >=0.6
   - nest-asyncio2
-  - nibabel >=2.0
-  - nilearn
+  - nibabel >=5.2
+  - nilearn >=0.10
   - nomkl
   - noqt5
-  - numba >=0.35
+  - numba >=0.60
   - numpy >=2.0,<3
   - openmeeg >=2.5.7
   - packaging

examples/decoding/decoding_xdawn_eeg.py

@@ -72,7 +72,7 @@
 
 # Create classification pipeline
 kwargs = dict()
-if check_version("sklearn", "1.8"):
+if check_version("sklearn", "1.8"):  # TODO VERSION remove on sklearn 1.8+
     kwargs["l1_ratio"] = 1
 else:
     kwargs["penalty"] = "l1"

examples/stats/r_interop.py

@@ -30,6 +30,7 @@
 # We use the MNE sample dataset and create epochs for two conditions:
 # auditory/left and auditory/right.
 
+import numpy as np
 import rpy2.robjects as ro
 from rpy2.robjects import default_converter, numpy2ri
 from rpy2.robjects.conversion import localconverter
@@ -142,3 +143,4 @@
 
 print(f"\nt difference: {abs(t_python - t_r):.2e}")
 print(f"p difference: {abs(p_python - p_r):.2e}")
+np.testing.assert_allclose([t_python, p_python], [t_r, p_r], rtol=1e-10)

mne/bem.py

@@ -33,7 +33,7 @@
     write_int_matrix,
     write_string,
 )
-from .fixes import _compare_version, _safe_svd
+from .fixes import _safe_svd
 from .surface import (
     _complete_sphere_surf,
     _compute_nearest,
@@ -356,8 +356,6 @@ def _import_openmeeg(what="compute a BEM solution using OpenMEEG"):
             f"The OpenMEEG module must be installed to {what}, but "
             f'"import openmeeg" resulted in: {exc}'
         ) from None
-    if not _compare_version(om.__version__, ">=", "2.5.6"):
-        raise ImportError(f"OpenMEEG 2.5.6+ is required, got {om.__version__}")
     return om
 
 

mne/conftest.py

@@ -44,7 +44,6 @@
     _pl,
     _record_warnings,
     _TempDir,
-    check_version,
     numerics,
 )
 from mne.viz._figure import use_browser_backend
@@ -667,11 +666,6 @@ def mpl_backend(garbage_collect):
         backend._close_all()
 
 
-# Skip functions or modules for mne-qt-browser < 0.2.0
-pre_2_0_skip_modules = ["mne.viz.tests.test_epochs", "mne.viz.tests.test_ica"]
-pre_2_0_skip_funcs = ["test_plot_raw_white", "test_plot_raw_selection"]
-
-
 def _check_pyqtgraph(request):
     # Check Qt
     qt_version, api = _check_qt_version(return_api=True)
@@ -681,17 +675,6 @@ def _check_pyqtgraph(request):
         )
     try:
         import mne_qt_browser  # noqa: F401
-
-        # Check mne-qt-browser version
-        lower_2_0 = _compare_version(mne_qt_browser.__version__, "<", "0.2.0")
-        m_name = request.function.__module__
-        f_name = request.function.__name__
-        if lower_2_0 and m_name in pre_2_0_skip_modules:
-            pytest.skip(
-                f'Test-Module "{m_name}" was skipped for mne-qt-browser < 0.2.0'
-            )
-        elif lower_2_0 and f_name in pre_2_0_skip_funcs:
-            pytest.skip(f'Test "{f_name}" was skipped for mne-qt-browser < 0.2.0')
     except Exception:
         pytest.skip("Requires mne_qt_browser")
 
@@ -834,7 +817,7 @@ def _check_skip_backend(name):
 def pixel_ratio(qapp):
     """Get the pixel ratio."""
     # _check_qt_version will init an app for us, so no need for us to do it
-    if not check_version("pyvista", "0.32") or not _check_qt_version():
+    if not _check_qt_version():
         return 1.0
     from qtpy.QtCore import Qt
     from qtpy.QtWidgets import QMainWindow

mne/decoding/base.py

@@ -457,7 +457,7 @@ class LinearModel(MetaEstimatorMixin, BaseEstimator):
         "predict",
         "predict_proba",
         "predict_log_proba",
-        "_estimator_type",  # remove after sklearn 1.6
+        "_estimator_type",  # TODO VERSION remove on sklearn 1.6+
         "decision_function",
         "score",
         "classes_",
@@ -505,7 +505,7 @@ def _validate_params(self, X):
                     "(classifier or regressor)"
                 )
 
-        # For sklearn < 1.6
+        # TODO VERSION remove on sklearn 1.6+
         try:
             self._check_n_features(X, reset=True)
         except AttributeError:

mne/decoding/search_light.py

@@ -289,7 +289,6 @@ def decision_function(self, X):
 
     def _check_Xy(self, X, y=None, fit=False):
         """Aux. function to check input data."""
-        # Once we require sklearn 1.1+ we should do something like:
         X = self._check_data(X, y=y, atleast_3d=False, fit=fit)
         is_nd = X.ndim >= 3
         if not is_nd: