animate_topomap - CSD fix (#12605)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Eric Larson <larson.eric.d@gmail.com>

doc/changes/devel/12605.bugfix.rst

@@ -0,0 +1 @@
+Fixed a bug where :meth:`mne.Evoked.animate_topomap` did not work with :func:`mne.preprocessing.compute_current_source_density` - modified data, by `Michal Žák`_.

mne/_fiff/pick.py

@@ -998,7 +998,7 @@ def _picks_by_type(info, meg_combined=False, ref_meg=False, exclude="bads"):
     exclude = _check_info_exclude(info, exclude)
     if meg_combined == "auto":
         meg_combined = _mag_grad_dependent(info)
-    picks_list = []
+
     picks_list = {ch_type: list() for ch_type in _DATA_CH_TYPES_SPLIT}
     for k in range(info["nchan"]):
         if info["chs"][k]["ch_name"] not in exclude:

mne/viz/tests/test_topomap.py

@@ -14,6 +14,7 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import pytest
+from matplotlib.colors import PowerNorm, TwoSlopeNorm
 from matplotlib.patches import Circle
 from numpy.testing import assert_almost_equal, assert_array_equal, assert_equal
 
@@ -43,7 +44,11 @@
 )
 from mne.datasets import testing
 from mne.io import RawArray, read_info, read_raw_fif
-from mne.preprocessing import compute_bridged_electrodes
+from mne.preprocessing import (
+    ICA,
+    compute_bridged_electrodes,
+    compute_current_source_density,
+)
 from mne.time_frequency.tfr import AverageTFRArray
 from mne.viz import plot_evoked_topomap, plot_projs_topomap, topomap
 from mne.viz.tests.test_raw import _proj_status
@@ -179,7 +184,21 @@ def test_plot_topomap_animation(capsys):
     anim._func(1)  # _animate has to be tested separately on 'Agg' backend.
     out, _ = capsys.readouterr()
     assert "extrapolation mode local to 0" in out
-    plt.close("all")
+
+
+def test_plot_topomap_animation_csd(capsys):
+    """Test topomap plotting of CSD data."""
+    # evoked
+    evoked = read_evokeds(evoked_fname, "Left Auditory", baseline=(None, 0))
+    evoked_csd = compute_current_source_density(evoked)
+
+    # Test animation
+    _, anim = evoked_csd.animate_topomap(
+        ch_type="csd", times=[0, 0.1], butterfly=False, time_unit="s", verbose="debug"
+    )
+    anim._func(1)  # _animate has to be tested separately on 'Agg' backend.
+    out, _ = capsys.readouterr()
+    assert "extrapolation mode head to 0" in out
 
 
 @pytest.mark.filterwarnings("ignore:.*No contour levels.*:UserWarning")
@@ -190,7 +209,6 @@ def test_plot_topomap_animation_nirs(fnirs_evoked, capsys):
     out, _ = capsys.readouterr()
     assert "extrapolation mode head to 0" in out
     assert len(fig.axes) == 2
-    plt.close("all")
 
 
 def test_plot_evoked_topomap_errors(evoked, monkeypatch):
@@ -553,7 +571,6 @@ def patch():
     orig_bads = evoked_grad.info["bads"]
     evoked_grad.plot_topomap(ch_type="grad", times=[0], time_unit="ms")
     assert_array_equal(evoked_grad.info["bads"], orig_bads)
-    plt.close("all")
 
 
 def test_plot_tfr_topomap():
@@ -685,8 +702,6 @@ def test_plot_topomap_neuromag122():
 
 def test_plot_topomap_bads():
     """Test plotting topomap with bad channels (gh-7213)."""
-    import matplotlib.pyplot as plt
-
     data = np.random.RandomState(0).randn(3, 1000)
     raw = RawArray(data, create_info(3, 1000.0, "eeg"))
     ch_pos_dict = {name: pos for name, pos in zip(raw.ch_names, np.eye(3))}
@@ -695,7 +710,6 @@ def test_plot_topomap_bads():
         raw.info["bads"] = raw.ch_names[:count]
         raw.info._check_consistency()
         plot_topomap(data[:, 0], raw.info)
-    plt.close("all")
 
 
 def test_plot_topomap_channel_distance():
@@ -713,35 +727,28 @@ def test_plot_topomap_channel_distance():
     evoked.set_montage(ten_five)
 
     evoked.plot_topomap(sphere=0.05, res=8)
-    plt.close("all")
 
 
 def test_plot_topomap_bads_grad():
     """Test plotting topomap with bad gradiometer channels (gh-8802)."""
-    import matplotlib.pyplot as plt
-
     data = np.random.RandomState(0).randn(203)
     info = read_info(evoked_fname)
     info["bads"] = ["MEG 2242"]
     picks = pick_types(info, meg="grad")
     info = pick_info(info, picks)
     assert len(info["chs"]) == 203
     plot_topomap(data, info, res=8)
-    plt.close("all")
 
 
 def test_plot_topomap_nirs_overlap(fnirs_epochs):
     """Test plotting nirs topomap with overlapping channels (gh-7414)."""
     fig = fnirs_epochs["A"].average(picks="hbo").plot_topomap()
     assert len(fig.axes) == 5
-    plt.close("all")
 
 
 def test_plot_topomap_nirs_ica(fnirs_epochs):
     """Test plotting nirs ica topomap."""
     pytest.importorskip("sklearn")
-    from mne.preprocessing import ICA
-
     fnirs_epochs = fnirs_epochs.load_data().pick(picks="hbo")
     fnirs_epochs = fnirs_epochs.pick(picks=range(30))
 
@@ -754,7 +761,6 @@ def test_plot_topomap_nirs_ica(fnirs_epochs):
     ica = ICA().fit(fnirs_epochs)
     fig = ica.plot_components()
     assert len(fig[0].axes) == 20
-    plt.close("all")
 
 
 def test_plot_cov_topomap():
@@ -763,13 +769,10 @@ def test_plot_cov_topomap():
     info = read_info(evoked_fname)
     cov.plot_topomap(info)
     cov.plot_topomap(info, noise_cov=cov)
-    plt.close("all")
 
 
 def test_plot_topomap_cnorm():
     """Test colormap normalization."""
-    from matplotlib.colors import PowerNorm, TwoSlopeNorm
-
     rng = np.random.default_rng(42)
     v = rng.uniform(low=-1, high=2.5, size=64)
     v[:3] = [-1, 0, 2.5]

mne/viz/topomap.py

@@ -3249,21 +3249,8 @@ def _topomap_animation(
     from matplotlib import pyplot as plt
 
     if ch_type is None:
-        ch_type = _picks_by_type(evoked.info)[0][0]
-    if ch_type not in (
-        "mag",
-        "grad",
-        "eeg",
-        "hbo",
-        "hbr",
-        "fnirs_od",
-        "fnirs_cw_amplitude",
-    ):
-        raise ValueError(
-            "Channel type not supported. Supported channel "
-            "types include 'mag', 'grad', 'eeg'. 'hbo', 'hbr', "
-            "'fnirs_cw_amplitude', and 'fnirs_od'."
-        )
+        ch_type = _get_plot_ch_type(evoked, ch_type)
+
     time_unit, _ = _check_time_unit(time_unit, evoked.times)
     if times is None:
         times = np.linspace(evoked.times[0], evoked.times[-1], 10)

mne/viz/utils.py

@@ -2821,5 +2821,7 @@ def _get_plot_ch_type(inst, ch_type, allow_ref_meg=False):
                 ch_type = type_
                 break
         else:
-            raise RuntimeError("No plottable channel types found")
+            raise RuntimeError(
+                f"No plottable channel types found. Allowed types are: {allowed_types}"
+            )
     return ch_type