FIX: Update for newer PyVista and exec() (#698)

Author: larsoner

mne_nirs/io/fold/_fold.py

@@ -52,7 +52,7 @@ def _generate_montage_locations():
 
     Data is returned in the same format as the eeg_positions library.
     """
-    # standard_1020 and standard_1005 are in MNI (fsaverage) space already,
+    # standard_1020 and colin27_1005 are in MNI (fsaverage) space already,
     # but we need to undo the scaling that head_scale will do
     name = "colin27" if check_version("mne", "1.13") else "standard"
     montage = mne.channels.make_standard_montage(

mne_nirs/io/fold/tests/test_fold.py

@@ -13,6 +13,7 @@
 from mne.channels.montage import transform_to_head
 from mne.datasets.testing import data_path, requires_testing_data
 from mne.io import read_fiducials, read_raw_nirx
+from mne.utils import check_version
 from numpy.testing import assert_allclose
 
 from mne_nirs.io import fold_landmark_specificity
@@ -57,7 +58,8 @@ def test_channel_specificity(monkeypatch, tmp_path, fold_files):
     res = fold_channel_specificity(raw, **kwargs)
     assert len(res) == 2
     assert res[0].shape == (n_want, 14)
-    montage = make_standard_montage("standard_1005", head_size=0.09700884729534559)
+    name = "colin27" if check_version("mne", "1.13") else "standard"
+    montage = make_standard_montage(f"{name}_1005", head_size=0.09700884729534559)
     fids = read_fiducials(
         Path(mne.__file__).parent / "data" / "fsaverage" / "fsaverage-fiducials.fif"
     )[0]

mne_nirs/tests/test_examples.py

@@ -57,4 +57,7 @@ def test_examples(fname, requires_pyvista):
     test_file_path = examples_path() + fname
     with open(test_file_path) as fid:
         code = fid.read()
-    exec(code, locals(), locals())
+    # Use a single namespace dict (not separate globals/locals) so that names
+    # defined at module level in the example (e.g. imports) are visible
+    # inside functions the example itself defines.
+    exec(code, {"__name__": "__main__"})

mne_nirs/visualisation/_plot_3d_montage.py

@@ -238,8 +238,8 @@ def plot_3d_montage(
                         vp.GetOrigin()
                     )
                     actor = brain.plotter.add_text(
-                        name,
-                        ch_pos,
+                        text=name,
+                        position=ch_pos,
                         font_size=font_size,
                         color=(0.0, 0.0, 0.0),
                         **add_text_kwargs,