MRG, BUG: Fix plot_alignment

doc/changes/latest.inc

@@ -65,6 +65,8 @@ Bugs
 
 - Pass ``rank`` everyhwere in forward preparation for source imaging. This bug affected sparse solvers when using maxfilter data, by `Alex Gramfort`_ (:gh:`8368`)
 
+- Fix bug in :func:`mne.viz.plot_alignment` where ECoG and sEEG channels were not plotted and fNIRS channels were always plotted in the head coordinate frame by `Eric Larson`_
+
 API changes
 ~~~~~~~~~~~
 

mne/viz/_3d.py

@@ -887,7 +887,7 @@ def plot_alignment(info=None, trans=None, subject=None, subjects_dir=None,
     car_loc = list()
     eeg_loc = list()
     eegp_loc = list()
-    other_loc = {key: list() for key in other_keys}
+    other_loc = dict()
     if len(eeg) > 0:
         eeg_loc = np.array([info['chs'][k]['loc'][:3] for k in eeg_picks])
         if len(eeg_loc) > 0:
@@ -947,27 +947,32 @@ def plot_alignment(info=None, trans=None, subject=None, subjects_dir=None,
     del dig
     for key, picks in other_picks.items():
         if other_bools[key] and len(picks):
+            title = DEFAULTS["titles"][key] if key != 'fnirs' else 'fNIRS'
+            if key != 'fnirs' or 'channels' in fnirs:
+                other_loc[key] = np.array([info['chs'][pick]['loc'][:3]
+                                           for pick in picks])
+                logger.info(
+                    f'Plotting {len(other_loc[key])} {title}'
+                    f' location{_pl(other_loc[key])}')
             if key == 'fnirs':
-                if 'channels' in fnirs:
-                    other_loc[key] = np.array([info['chs'][pick]['loc'][:3]
-                                               for pick in picks])
                 if 'sources' in fnirs:
                     other_loc['source'] = np.array(
                         [info['chs'][pick]['loc'][3:6]
                          for pick in picks])
                     logger.info('Plotting %d %s source%s'
                                 % (len(other_loc['source']),
-                                   key, _pl(other_loc['source'])))
+                                   title, _pl(other_loc['source'])))
                 if 'detectors' in fnirs:
                     other_loc['detector'] = np.array(
                         [info['chs'][pick]['loc'][6:9]
                          for pick in picks])
                     logger.info('Plotting %d %s detector%s'
                                 % (len(other_loc['detector']),
-                                   key, _pl(other_loc['detector'])))
-                other_keys = sorted(other_loc.keys())
-            logger.info('Plotting %d %s location%s'
-                        % (len(other_loc[key]), key, _pl(other_loc[key])))
+                                   title, _pl(other_loc['detector'])))
+    for v in other_loc.values():
+        v[:] = apply_trans(head_trans, v)
+    other_keys = sorted(other_loc)  # re-sort and only keep non-empty
+    del other_bools
 
     # initialize figure
     renderer = _get_renderer(fig, bgcolor=(0.5, 0.5, 0.5), size=(800, 800))
@@ -1072,10 +1077,12 @@ def plot_alignment(info=None, trans=None, subject=None, subjects_dir=None,
                               fwd_nn[:, ori, 2],
                               color=color, mode='arrow', scale=1.5e-3)
     if 'pairs' in fnirs and len(fnirs_picks) > 0:
-        fnirs_loc = np.array([info['chs'][k]['loc'][3:9] for k in fnirs_picks])
-        logger.info('Plotting %d fnirs pairs' % (fnirs_loc.shape[0]))
-        renderer.tube(origin=fnirs_loc[:, :3],
-                      destination=fnirs_loc[:, 3:])
+        origin = apply_trans(head_trans, np.array(
+            [info['chs'][k]['loc'][3:6] for k in fnirs_picks]))
+        destination = apply_trans(head_trans, np.array(
+            [info['chs'][k]['loc'][6:9] for k in fnirs_picks]))
+        logger.info(f'Plotting {origin.shape[0]} fNIRS pair{_pl(origin)}')
+        renderer.tube(origin=origin, destination=destination)
 
     renderer.set_camera(azimuth=90, elevation=90,
                         distance=0.6, focalpoint=(0., 0., 0.))

mne/viz/tests/test_3d.py

@@ -227,11 +227,16 @@ def test_plot_alignment(tmpdir, renderer):
     evoked_eeg_ecog_seeg.set_channel_types({'EEG 001': 'ecog',
                                             'EEG 002': 'seeg'})
     with pytest.warns(RuntimeWarning, match='Cannot plot MEG'):
-        plot_alignment(evoked_eeg_ecog_seeg.info, subject='sample',
-                       trans=trans_fname, subjects_dir=subjects_dir,
-                       surfaces=['white', 'outer_skin', 'outer_skull'],
-                       meg=['helmet', 'sensors'],
-                       eeg=['original', 'projected'], ecog=True, seeg=True)
+        with catch_logging() as log:
+            plot_alignment(evoked_eeg_ecog_seeg.info, subject='sample',
+                           trans=trans_fname, subjects_dir=subjects_dir,
+                           surfaces=['white', 'outer_skin', 'outer_skull'],
+                           meg=['helmet', 'sensors'],
+                           eeg=['original', 'projected'], ecog=True, seeg=True,
+                           verbose=True)
+    log = log.getvalue()
+    assert '1 ECoG location' in log
+    assert '1 sEEG location' in log
     renderer.backend._close_all()
 
     sphere = make_sphere_model(info=evoked.info, r0='auto', head_radius='auto')
@@ -334,60 +339,24 @@ def test_plot_alignment(tmpdir, renderer):
                    trans=trans_fname, fwd=fwd,
                    surfaces='white', coord_frame='head')
 
-    # fNIRS
+    # fNIRS (default is pairs)
     info = read_raw_nirx(nirx_fname).info
     with catch_logging() as log:
         plot_alignment(info, subject='fsaverage', surfaces=(), verbose=True)
     log = log.getvalue()
-    assert '26 fnirs pairs' in log
-
-    with catch_logging() as log:
-        plot_alignment(info, subject='fsaverage', surfaces=(), verbose=True,
-                       fnirs='channels')
-    log = log.getvalue()
-    assert '26 fnirs locations' in log
-
-    with catch_logging() as log:
-        plot_alignment(info, subject='fsaverage', surfaces=(), verbose=True,
-                       fnirs='pairs')
-    log = log.getvalue()
-    assert '26 fnirs pairs' in log
-
-    with catch_logging() as log:
-        plot_alignment(info, subject='fsaverage', surfaces=(), verbose=True,
-                       fnirs='sources')
-    log = log.getvalue()
-    assert '26 fnirs sources' in log
-
-    with catch_logging() as log:
-        plot_alignment(info, subject='fsaverage', surfaces=(), verbose=True,
-                       fnirs='detectors')
-    log = log.getvalue()
-    assert '26 fnirs detectors' in log
-
-    with catch_logging() as log:
-        plot_alignment(info, subject='fsaverage', surfaces=(), verbose=True,
-                       fnirs=['channels', 'pairs'])
-    log = log.getvalue()
-    assert '26 fnirs pairs' in log
-    assert '26 fnirs locations' in log
-
-    with catch_logging() as log:
-        plot_alignment(info, subject='fsaverage', surfaces=(), verbose=True,
-                       fnirs=['pairs', 'sources', 'detectors'])
-    log = log.getvalue()
-    assert '26 fnirs pairs' in log
-    assert '26 fnirs sources' in log
-    assert '26 fnirs detectors' in log
+    assert '26 fNIRS pairs' in log
+    assert '26 fNIRS locations' not in log
+    assert '26 fNIRS sources' not in log
+    assert '26 fNIRS detectors' not in log
 
     with catch_logging() as log:
         plot_alignment(info, subject='fsaverage', surfaces=(), verbose=True,
-                       fnirs=['channels', 'pairs', 'sources', 'detectors'])
+                       fnirs=['channels', 'sources', 'detectors'])
     log = log.getvalue()
-    assert '26 fnirs pairs' in log
-    assert '26 fnirs locations' in log
-    assert '26 fnirs sources' in log
-    assert '26 fnirs detectors' in log
+    assert '26 fNIRS pairs' not in log
+    assert '26 fNIRS locations' in log
+    assert '26 fNIRS sources' in log
+    assert '26 fNIRS detectors' in log
 
     renderer.backend._close_all()
 

tutorials/misc/plot_ecog.py

@@ -33,8 +33,8 @@
 
 ###############################################################################
 # Let's load some ECoG electrode locations and names, and turn them into
-# a :class:`mne.channels.DigMontage` class.
-# First, use pandas to read in the .tsv file.
+# a :class:`mne.channels.DigMontage` class. First, use pandas to read in the
+# ``.tsv`` file.
 
 # In this tutorial, the electrode coordinates are assumed to be in meters
 elec_df = pd.read_csv(misc_path + '/ecog/sample_ecog_electrodes.tsv',

tutorials/preprocessing/plot_70_fnirs_processing.py

@@ -14,7 +14,6 @@
 
 Here we will work with the :ref:`fNIRS motor data <fnirs-motor-dataset>`.
 """
-# sphinx_gallery_thumbnail_number = 1
 
 import os
 import numpy as np
@@ -44,13 +43,13 @@
 
 fig = mne.viz.create_3d_figure(size=(800, 600), bgcolor='white')
 fig = mne.viz.plot_alignment(raw_intensity.info, show_axes=True,
-                             subject='fsaverage',
+                             subject='fsaverage', coord_frame='mri',
                              trans='fsaverage', surfaces=['brain'],
                              fnirs=['channels', 'pairs',
                                     'sources', 'detectors'],
                              subjects_dir=subjects_dir, fig=fig)
-mne.viz.set_3d_view(figure=fig, azimuth=20, elevation=55, distance=0.6)
-
+mne.viz.set_3d_view(figure=fig, azimuth=20, elevation=60, distance=0.4,
+                    focalpoint=(0., -0.01, 0.02))
 
 ###############################################################################
 # Selecting channels appropriate for detecting neural responses