BUG: Fix bug with plot_white

Author: larsoner

doc/changes/dev/13595.bugfix.rst

@@ -0,0 +1 @@
+Fix bug where :func:`mne.viz.plot_evoked_white` did not accept a single "meg" rank value like those returned from :func:`mne.compute_rank`, by `Eric Larson`_.

mne/minimum_norm/tests/test_inverse.py

@@ -23,6 +23,7 @@
     EvokedArray,
     SourceEstimate,
     combine_evoked,
+    compute_rank,
     compute_raw_covariance,
     convert_forward_solution,
     make_ad_hoc_cov,
@@ -992,21 +993,34 @@ def test_make_inverse_operator_diag(evoked, noise_cov, tmp_path, azure_windows):
 
 def test_inverse_operator_noise_cov_rank(evoked, noise_cov):
     """Test MNE inverse operator with a specified noise cov rank."""
-    fwd_op = read_forward_solution_meg(fname_fwd, surf_ori=True)
-    inv = make_inverse_operator(evoked.info, fwd_op, noise_cov, rank=dict(meg=64))
+    fwd_op_meg = read_forward_solution_meg(fname_fwd, surf_ori=True)
+    inv = make_inverse_operator(evoked.info, fwd_op_meg, noise_cov, rank=dict(meg=64))
     assert compute_rank_inverse(inv) == 64
-    inv = make_inverse_operator(evoked.info, fwd_op, noise_cov, rank=dict(meg=64))
+    inv = make_inverse_operator(evoked.info, fwd_op_meg, noise_cov, rank=dict(meg=64))
     assert compute_rank_inverse(inv) == 64
 
     bad_cov = noise_cov.copy()
     bad_cov["data"][0, 0] *= 1e12
     with pytest.warns(RuntimeWarning, match="orders of magnitude"):
-        make_inverse_operator(evoked.info, fwd_op, bad_cov, rank=dict(meg=64))
+        make_inverse_operator(evoked.info, fwd_op_meg, bad_cov, rank=dict(meg=64))
 
-    fwd_op = read_forward_solution_eeg(fname_fwd, surf_ori=True)
-    inv = make_inverse_operator(evoked.info, fwd_op, noise_cov, rank=dict(eeg=20))
+    fwd_op_eeg = read_forward_solution_eeg(fname_fwd, surf_ori=True)
+    inv = make_inverse_operator(evoked.info, fwd_op_eeg, noise_cov, rank=dict(eeg=20))
     assert compute_rank_inverse(inv) == 20
 
+    # with and without rank passed explicitly
+    inv_info = make_inverse_operator(evoked.info, fwd_op_meg, noise_cov, rank="info")
+    info_rank = 302
+    assert compute_rank_inverse(inv_info) == info_rank
+    rank = compute_rank(noise_cov, info=evoked.copy().pick("meg").info, rank="info")
+    assert "meg" in rank
+    assert sum(rank.values()) == info_rank
+    inv_rank = make_inverse_operator(evoked.info, fwd_op_meg, noise_cov, rank=rank)
+    assert compute_rank_inverse(inv_rank) == info_rank
+    evoked_info = apply_inverse(evoked, inv_info, lambda2, "MNE")
+    evoked_rank = apply_inverse(evoked, inv_rank, lambda2, "MNE")
+    assert_allclose(evoked_rank.data, evoked_info.data)
+
 
 def test_inverse_operator_volume(evoked, tmp_path):
     """Test MNE inverse computation on volume source space."""

mne/tests/test_cov.py

@@ -94,6 +94,14 @@ def test_compute_whitener(proj, pca):
         assert pca is False
         assert_allclose(round_trip, np.eye(n_channels), atol=0.05)
 
+    # with and without rank
+    W_info, _ = compute_whitener(cov, raw.info, pca=pca, rank="info", verbose="error")
+    assert_allclose(W_info, W)
+    rank = compute_rank(raw, rank="info", proj=proj)
+    assert W.shape == (n_reduced, n_channels)
+    W_rank, _ = compute_whitener(cov, raw.info, pca=pca, rank=rank, verbose="error")
+    assert_allclose(W_rank, W)
+
     raw.info["bads"] = [raw.ch_names[0]]
     picks = pick_types(raw.info, meg=True, eeg=True, exclude=[])
     with pytest.warns(RuntimeWarning, match="Too few samples"):

mne/viz/evoked.py

@@ -1587,13 +1587,9 @@ def plot_evoked_white(
         evoked.del_proj(idx)
 
     evoked.pick_types(ref_meg=False, exclude="bads", **_PICK_TYPES_DATA_DICT)
-    n_ch_used, rank_list, picks_list, has_sss = _triage_rank_sss(
+    n_ch_used, rank_list, picks_list, meg_combined = _triage_rank_sss(
         evoked.info, noise_cov, rank, scalings=None
     )
-    if has_sss:
-        logger.info(
-            "SSS has been applied to data. Showing mag and grad whitening jointly."
-        )
 
     # get one whitened evoked per cov
     evokeds_white = [
@@ -1663,8 +1659,8 @@ def whitened_gfp(x, rank=None):
     # hacks to get it to plot all channels in the same axes, namely setting
     # the channel unit (most important) and coil type (for consistency) of
     # all MEG channels to be the same.
-    meg_idx = sss_title = None
-    if has_sss:
+    meg_idx = combined_title = None
+    if meg_combined:
         titles_["meg"] = "MEG (combined)"
         meg_idx = [
             pi for pi, (ch_type, _) in enumerate(picks_list) if ch_type == "meg"
@@ -1675,7 +1671,7 @@ def whitened_gfp(x, rank=None):
             use = evokeds_white[0].info["chs"][picks[0]][key]
             for pick in picks:
                 evokeds_white[0].info["chs"][pick][key] = use
-        sss_title = f"{titles_['meg']} ({len(picks)} channel{_pl(picks)})"
+        combined_title = f"{titles_['meg']} ({len(picks)} channel{_pl(picks)})"
     evokeds_white[0].plot(
         unit=False,
         axes=axes_evoked,
@@ -1684,8 +1680,8 @@ def whitened_gfp(x, rank=None):
         time_unit=time_unit,
         spatial_colors=spatial_colors,
     )
-    if has_sss:
-        axes_evoked[meg_idx].set(title=sss_title)
+    if meg_combined:
+        axes_evoked[meg_idx].set(title=combined_title)
 
     # Now plot the GFP for all covs if indicated.
     for evoked_white, noise_cov, rank_, color in iter_gfp:

mne/viz/tests/test_evoked.py

@@ -18,6 +18,7 @@
     Epochs,
     compute_covariance,
     compute_proj_evoked,
+    compute_rank,
     make_fixed_length_events,
     read_cov,
     read_events,
@@ -357,6 +358,21 @@ def test_plot_evoked_image():
         evoked.plot_image(clim=[-4, 4])
 
 
+def test_plot_white_rank():
+    """Test plot_white with a combined-MEG rank arg."""
+    cov = read_cov(cov_fname)
+    cov["method"] = "empirical"
+    cov["projs"] = []  # avoid warnings
+    evoked = _get_epochs().average()
+    evoked.set_eeg_reference("average")  # Avoid warnings
+    rank = compute_rank(evoked, "info")
+    assert "grad" not in rank
+    assert "mag" not in rank
+    assert "meg" in rank
+    evoked.plot_white(cov)
+    evoked.plot_white(cov, rank=rank)
+
+
 def test_plot_white():
     """Test plot_white."""
     cov = read_cov(cov_fname)
@@ -373,9 +389,9 @@ def test_plot_white():
     evoked.plot_white(cov, rank={"grad": 8}, time_unit="s", axes=fig.axes[:4])
     with pytest.raises(ValueError, match=r"must have shape \(4,\), got \(2,"):
         evoked.plot_white(cov, axes=fig.axes[:2])
-    with pytest.raises(ValueError, match="When not using SSS"):
+    with pytest.raises(ValueError, match="exceeds the number"):
         evoked.plot_white(cov, rank={"meg": 306})
-    evoked.plot_white([cov, cov], time_unit="s")
+    evoked.plot_white([cov, cov], rank={"meg": 9}, time_unit="s")
     plt.close("all")
 
     fig = plot_evoked_white(evoked, [cov, cov])

mne/viz/utils.py

@@ -2070,14 +2070,20 @@ def _triage_rank_sss(info, covs, rank=None, scalings=None):
                 '(separate rank values for "mag" or "grad" are '
                 "meaningless)."
             )
+        meg_combined = True
     elif "meg" in rank:
-        raise ValueError(
-            "When not using SSS, pass separate rank values "
-            'for "mag" and "grad" (do not use "meg").'
-        )
+        if has_sss:
+            start = "SSS has been applied to data"
+        else:
+            start = "Got a single MEG rank value"
+        logger.info("%s. Showing mag and grad whitening jointly.", start)
+        meg_combined = True
+    else:
+        meg_combined = False
+    del has_sss
 
-    picks_list = _picks_by_type(info, meg_combined=has_sss)
-    if has_sss:
+    picks_list = _picks_by_type(info, meg_combined=meg_combined)
+    if meg_combined:
         # reduce ch_used to combined mag grad
         ch_used = list(zip(*picks_list))[0]
     # order pick list by ch_used (required for compat with plot_evoked)
@@ -2121,7 +2127,7 @@ def _triage_rank_sss(info, covs, rank=None, scalings=None):
                 this_rank[ch_type] = rank[ch_type]
 
         rank_list.append(this_rank)
-    return n_ch_used, rank_list, picks_list, has_sss
+    return n_ch_used, rank_list, picks_list, meg_combined
 
 
 def _check_cov(noise_cov, info):