MAINT: Make MxNE test more robust (mne-tools#13315)

Author: larsoner

mne/inverse_sparse/tests/test_mxne_inverse.py

@@ -549,7 +549,7 @@ def test_mxne_inverse_sure_synthetic(
 
 @pytest.mark.slowtest  # slow on Azure
 @testing.requires_testing_data
-def test_mxne_inverse_sure():
+def test_mxne_inverse_sure_meg():
     """Tests SURE criterion for automatic alpha selection on MEG data."""
 
     def data_fun(times):
@@ -558,10 +558,10 @@ def data_fun(times):
         return data
 
     n_dipoles = 2
-    raw = mne.io.read_raw_fif(fname_raw)
-    info = mne.io.read_info(fname_data)
-    with info._unlock():
-        info["projs"] = []
+    raw = mne.io.read_raw_fif(fname_raw).pick_types("grad", exclude="bads")
+    raw.del_proj()
+    info = raw.info
+    del raw
     noise_cov = mne.make_ad_hoc_cov(info)
     label_names = ["Aud-lh", "Aud-rh"]
     labels = [
@@ -572,10 +572,8 @@ def data_fun(times):
         data_path / "MEG" / "sample" / "sample_audvis_trunc-meg-eeg-oct-4-fwd.fif"
     )
     forward = mne.read_forward_solution(fname_fwd)
-    forward = mne.pick_types_forward(
-        forward, meg="grad", eeg=False, exclude=raw.info["bads"]
-    )
-    times = np.arange(100, dtype=np.float64) / raw.info["sfreq"] - 0.1
+    forward = mne.pick_channels_forward(forward, info["ch_names"])
+    times = np.arange(100, dtype=np.float64) / info["sfreq"] - 0.1
     stc = simulate_sparse_stc(
         forward["src"],
         n_dipoles=n_dipoles,
@@ -584,13 +582,16 @@ def data_fun(times):
         labels=labels,
         data_fun=data_fun,
     )
+    assert len(stc.vertices) == 2
+    assert_array_equal(stc.vertices[0], [89259])
+    assert_array_equal(stc.vertices[1], [70279])
     nave = 30
     evoked = simulate_evoked(
         forward, stc, info, noise_cov, nave=nave, use_cps=False, iir_filter=None
     )
     evoked = evoked.crop(tmin=0, tmax=10e-3)
     stc_ = mixed_norm(
-        evoked, forward, noise_cov, loose=0.9, n_mxne_iter=5, depth=0.9, random_state=0
+        evoked, forward, noise_cov, loose=0.9, n_mxne_iter=5, depth=0.9, random_state=1
     )
     assert len(stc_.vertices) == len(stc.vertices) == 2
     for si in range(len(stc_.vertices)):