hopefully at least 80%

almkanal/almkanal.py

@@ -256,7 +256,7 @@ def do_src(
         self,
         data_cov: None | NDArray = None,
         noise_cov: None | NDArray = None,
-        empty_room_path: None | str = None,
+        empty_room: None | str | mne.io.Raw = None,
         return_parc: bool = False,
         subject_id: None | str = None,
         subjects_dir: None | str = None,
@@ -283,7 +283,7 @@ def do_src(
                 data_cov=data_cov,
                 noise_cov=noise_cov,
                 preproc_info=self.info,
-                empty_room_path=empty_room_path,
+                empty_room=empty_room,
             )
 
             if np.logical_and(return_parc, np.logical_and(subject_id is not None, subjects_dir is not None)):

almkanal/src_utils/src_utils.py

@@ -96,12 +96,16 @@ def process_empty_room(
     icas: None | list,
     ica_ids: None | list,
     preproc_info: InfoClass,
-    empty_room_path: str,
+    empty_room: str | mne.io.Raw,
     get_nearest: bool = False,
 ) -> tuple[NDArray, NDArray]:
-    fname_empty_room = get_nearest_empty_room(info, empty_room_dir=empty_room_path) if get_nearest else empty_room_path
-
-    raw_er = mne.io.read_raw(fname_empty_room, preload=True)
+    if np.logical_and(get_nearest, isinstance(empty_room, str)):
+        fname_empty_room = get_nearest_empty_room(info, empty_room_dir=empty_room)
+        raw_er = mne.io.read_raw(fname_empty_room, preload=True)
+    elif np.logical_and(not get_nearest, isinstance(empty_room, str)):
+        raw_er = mne.io.read_raw(empty_room, preload=True)
+    elif isinstance(empty_room, mne.io.Raw):
+        raw_er = empty_room
 
     raw_er = preproc_empty_room(raw_er=raw_er, data=data, preproc_info=preproc_info, icas=icas, ica_ids=ica_ids)
 
@@ -129,7 +133,7 @@ def data2source(
     ica_ids: None | list = None,
     data_cov: None | NDArray = None,
     noise_cov: None | NDArray = None,
-    empty_room_path: None | str = None,
+    empty_room: None | str | mne.io.Raw = None,
 ) -> tuple[mne.SourceEstimate, mne.beamformer.Beamformer]:
     """This function does source reconstruction using lcmv beamformers based on raw data."""
 
@@ -167,7 +171,8 @@ def data2source(
     # per default we take this from an empty room recording
     # importantly this should be preprocessed similarly to the actual data (except for ICA)
     if np.logical_and(n_ch_types > 1, noise_cov is None):
-        assert isinstance(empty_room_path, str), """Please specify either a path that leads directly
+        assert np.logical_or(isinstance(empty_room, str), isinstance(empty_room, mne.io.Raw)), """Please
+        supply either a mne.io.raw object, a path that leads directly
          to an empty_room recording or a folder with a bunch of empty room recordings"""
         true_rank, noise_cov = process_empty_room(
             data=data,
@@ -176,7 +181,7 @@ def data2source(
             preproc_info=preproc_info,
             icas=icas,
             ica_ids=ica_ids,
-            empty_room_path=empty_room_path,
+            empty_room=empty_room,
         )
 
     elif n_ch_types == 1:

tests/test_raw.py

@@ -3,23 +3,18 @@
 from .settings import CH_PICKS, ICA_TRAIN, ICA_EOG, ICA_ECG, ICA_THRESH, ICA_RESAMPLE, ICA_NCOMPS, SOURCE
 import mne
 
-
-
-@pytest.mark.parametrize('ch_picks', CH_PICKS, scope='session')
-def test_src(gen_mne_data_raw, ch_picks): #, ch_picks
+#@pytest.mark.parametrize('ch_picks', CH_PICKS, scope='session')
+def test_src(gen_mne_data_raw): #, ch_picks
     data_path = mne.datasets.sample.data_path()
     meg_path = data_path / 'MEG' / 'sample'
-    raw_fname = meg_path / 'sample_audvis_raw.fif'
     ak = AlmKanal(raw=gen_mne_data_raw)
 
     fwd_fname = meg_path / 'sample_audvis-meg-vol-7-fwd.fif'
     fwd = mne.read_forward_solution(fwd_fname)
-    ak.pick_dict['meg'] = ch_picks
+    ak.pick_dict['meg'] = True
     ak.fwd = fwd
-    if ch_picks:
-        ak.do_src(empty_room_path=raw_fname)
-    else:
-        ak.do_src()
+    ak.do_src(empty_room=gen_mne_data_raw)
+
 
 
 def test_maxwell(gen_mne_data_raw):
@@ -107,3 +102,6 @@ def test_fwd(gen_mne_data_raw, source, atlas):
               atlas=atlas,
               return_parc=True,)
 
+
+
+