BUG: Fix bug with regress_artifact picking

doc/changes/devel/bugfix.rst

@@ -0,0 +1 @@
+Fix bug where :func:`mne.preprocessing.regress_artifact` projection check was not specific to the channels being processed, by `Eric Larson`_.

mne/_fiff/pick.py

@@ -649,7 +649,8 @@ def pick_info(info, sel=(), copy=True, verbose=None):
         return info
     elif len(sel) == 0:
         raise ValueError("No channels match the selection.")
-    n_unique = len(np.unique(np.arange(len(info["ch_names"]))[sel]))
+    ch_set = set(info["ch_names"][k] for k in sel)
+    n_unique = len(ch_set)
     if n_unique != len(sel):
         raise ValueError(
             "Found %d / %d unique names, sel is not unique" % (n_unique, len(sel))
@@ -687,6 +688,15 @@ def pick_info(info, sel=(), copy=True, verbose=None):
     if info.get("custom_ref_applied", False) and not _electrode_types(info):
         with info._unlock():
             info["custom_ref_applied"] = FIFF.FIFFV_MNE_CUSTOM_REF_OFF
+    # remove unused projectors
+    if info.get("projs", []):
+        projs = list()
+        for p in info["projs"]:
+            if any(ch_name in ch_set for ch_name in p["data"]["col_names"]):
+                projs.append(p)
+        if len(projs) != len(info["projs"]):
+            with info._unlock():
+                info["projs"] = projs
     info._check_consistency()
 
     return info

mne/_fiff/tests/test_pick.py

@@ -558,11 +558,17 @@ def test_clean_info_bads():
     # simulate the bad channels
     raw.info["bads"] = eeg_bad_ch + meg_bad_ch
 
+    assert len(raw.info["projs"]) == 3
+    raw.set_eeg_reference(projection=True)
+    assert len(raw.info["projs"]) == 4
+
     # simulate the call to pick_info excluding the bad eeg channels
     info_eeg = pick_info(raw.info, picks_eeg)
+    assert len(info_eeg["projs"]) == 1
 
     # simulate the call to pick_info excluding the bad meg channels
     info_meg = pick_info(raw.info, picks_meg)
+    assert len(info_meg["projs"]) == 3
 
     assert info_eeg["bads"] == eeg_bad_ch
     assert info_meg["bads"] == meg_bad_ch

mne/preprocessing/_regress.py

@@ -6,7 +6,7 @@
 
 import numpy as np
 
-from .._fiff.pick import _picks_to_idx
+from .._fiff.pick import _picks_to_idx, pick_info
 from ..defaults import _BORDER_DEFAULT, _EXTRAPOLATE_DEFAULT, _INTERPOLATION_DEFAULT
 from ..epochs import BaseEpochs
 from ..evoked import Evoked
@@ -178,9 +178,7 @@ def fit(self, inst):
         reference (see :func:`mne.set_eeg_reference`) before performing EOG
         regression.
         """
-        self._check_inst(inst)
-        picks = _picks_to_idx(inst.info, self.picks, none="data", exclude=self.exclude)
-        picks_artifact = _picks_to_idx(inst.info, self.picks_artifact)
+        picks, picks_artifact = self._check_inst(inst)
 
         # Calculate regression coefficients. Add a row of ones to also fit the
         # intercept.
@@ -232,9 +230,7 @@ def apply(self, inst, copy=True):
         """
         if copy:
             inst = inst.copy()
-        self._check_inst(inst)
-        picks = _picks_to_idx(inst.info, self.picks, none="data", exclude=self.exclude)
-        picks_artifact = _picks_to_idx(inst.info, self.picks_artifact)
+        picks, picks_artifact = self._check_inst(inst)
 
         # Check that the channels are compatible with the regression weights.
         ref_picks = _picks_to_idx(
@@ -324,19 +320,25 @@ def _check_inst(self, inst):
         _validate_type(
             inst, (BaseRaw, BaseEpochs, Evoked), "inst", "Raw, Epochs, Evoked"
         )
-        if _needs_eeg_average_ref_proj(inst.info):
+        picks = _picks_to_idx(inst.info, self.picks, none="data", exclude=self.exclude)
+        picks_artifact = _picks_to_idx(inst.info, self.picks_artifact)
+        all_picks = np.unique(np.concatenate([picks, picks_artifact]))
+        use_info = pick_info(inst.info, all_picks)
+        del all_picks
+        if _needs_eeg_average_ref_proj(use_info):
             raise RuntimeError(
-                "No reference for the EEG channels has been "
-                "set. Use inst.set_eeg_reference() to do so."
+                "No average reference for the EEG channels has been "
+                "set. Use inst.set_eeg_reference(projection=True) to do so."
             )
         if self.proj and not inst.proj:
             inst.apply_proj()
-        if not inst.proj and len(inst.info.get("projs", [])) > 0:
+        if not inst.proj and len(use_info.get("projs", [])) > 0:
             raise RuntimeError(
                 "Projections need to be applied before "
                 "regression can be performed. Use the "
                 ".apply_proj() method to do so."
             )
+        return picks, picks_artifact
 
     def __repr__(self):
         """Produce a string representation of this object."""

mne/preprocessing/tests/test_regress.py

@@ -42,6 +42,19 @@ def test_regress_artifact():
     epochs, betas = regress_artifact(epochs, picks="eog", picks_artifact="eog")
     assert np.ptp(epochs.get_data("eog")) < 1e-15  # constant value
     assert_allclose(betas, 1)
+    # proj should only be required of channels being processed
+    raw = read_raw_fif(raw_fname).crop(0, 1).load_data()
+    raw.del_proj()
+    raw.set_eeg_reference(projection=True)
+    model = EOGRegression(proj=False, picks="meg", picks_artifact="eog")
+    model.fit(raw)
+    model.apply(raw)
+    model = EOGRegression(proj=False, picks="eeg", picks_artifact="eog")
+    with pytest.raises(RuntimeError, match="Projections need to be applied"):
+        model.fit(raw)
+    raw.del_proj()
+    with pytest.raises(RuntimeError, match="No average reference for the EEG"):
+        model.fit(raw)
 
 
 @testing.requires_testing_data