Supporting multimodal datasets. (#191)

* Supporting multimodal datasets.

* Linting

* Running ICALabel only for EEG.

Author: christian-oreilly

pylossless/conftest.py

@@ -19,7 +19,7 @@
 
 @pytest.fixture(scope="session")
 def pipeline_fixture():
-    """Return a namedTuple containing MNE eyetracking raw data and events."""
+    """Return a LosslessPipeline object."""
     raw, config, bids_path = load_openneuro_bids()
     # raw.crop(tmin=0, tmax=60)  # Too short for ICA to converge in some tests.
     annots = Annotations(

pylossless/flagging.py

@@ -115,7 +115,11 @@ def add_flag_cat(self, kind, bad_ch_names, *args):
         logger.debug(f"NEW BAD CHANNELS {bad_ch_names}")
         if isinstance(bad_ch_names, xr.DataArray):
             bad_ch_names = bad_ch_names.values
-        self[kind] = bad_ch_names
+        if kind in self:
+            self[kind] = list(np.unique(np.concatenate((self[kind], bad_ch_names))))
+        else:
+            self[kind] = bad_ch_names
+
 
     def get_flagged(self):
         """Return a list of channels flagged by the lossless pipeline."""
@@ -138,9 +142,12 @@ def rereference(self, inst, **kwargs):
         """
         # Concatenate and remove duplicates
         bad_chs = list(
-            set(self.ll.find_outlier_chs(inst) + self.get_flagged() + inst.info["bads"])
+            set(self.ll.find_outlier_chs(inst, picks="eeg") +
+                self.get_flagged() +
+                inst.info["bads"])
         )
-        ref_chans = [ch for ch in inst.copy().pick("eeg").ch_names if ch not in bad_chs]
+        ref_chans = [ch for ch in inst.copy().pick("eeg").ch_names
+                     if ch not in bad_chs]
         inst.set_eeg_reference(ref_channels=ref_chans, **kwargs)
 
     def save_tsv(self, fname):
@@ -223,7 +230,10 @@ def add_flag_cat(self, kind, bad_epoch_inds, epochs):
             The :class:`mne.Epochs` object created from the Raw object that is
             being assessed by the LosslessPipeline.
         """
-        self[kind] = bad_epoch_inds
+        if kind in self:
+            self[kind] = list(np.unique(np.concatenate((self[kind], bad_epoch_inds))))
+        else:
+            self[kind] = bad_epoch_inds
         self.ll.add_pylossless_annotations(bad_epoch_inds, kind, epochs)
 
     def load_from_raw(self, raw, events, config):