mpciROIs.uuids

int-brain-lab · Oct 13, 2023 · 7c807b6 · 7c807b6
1 parent 2803838
commit 7c807b6
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Showing 2 changed files with 9 additions and 2 deletions.
diff --git a/brainbox/behavior/training.py b/brainbox/behavior/training.py
@@ -83,15 +83,16 @@ class TrainingStatus(IntFlag):
     ... assert TrainingStatus[status.upper()] in ~TrainingStatus.FAILED, 'Subject untrained'
     ... assert TrainingStatus[status.upper()] in TrainingStatus.TRAINED ^ TrainingStatus.READY
 
-    # Get the next training status
+    Get the next training status
+
     >>> next(member for member in sorted(TrainingStatus) if member > TrainingStatus[status.upper()])
     <TrainingStatus.READY4RECORDING: 128>
 
     Notes
     -----
     - ~TrainingStatus.TRAINED means any status but trained 1a or trained 1b.
     - A subject may acheive both TRAINED_1A and TRAINED_1B within a single session, therefore it
-     is possible to have skipped the TRAINED_1A session status.
+      is possible to have skipped the TRAINED_1A session status.
     """
     UNTRAINABLE = auto()
     UNBIASABLE = auto()

diff --git a/ibllib/pipes/mesoscope_tasks.py b/ibllib/pipes/mesoscope_tasks.py
@@ -216,6 +216,7 @@ def signature(self):
                              ('mpciROIs.stackPos.npy', 'alf/FOV*', True),
                              ('mpciROIs.mpciROITypes.npy', 'alf/FOV*', True),
                              ('mpciROIs.cellClassifier.npy', 'alf/FOV*', True),
+                             ('mpciROIs.uuids.csv', 'alf/FOV*', True),
                              ('mpciROITypes.names.tsv', 'alf/FOV*', True),
                              ('mpciROIs.masks.npy', 'alf/FOV*', True),
                              ('mpciROIs.neuropilMasks.npy', 'alf/FOV*', True),
@@ -328,6 +329,11 @@ def _rename_outputs(self, suite2p_dir, frameQC_names, frameQC, rename_dict=None)
                 np.save(fov_dir.joinpath('mpciROIs.stackPos.npy'), np.asarray([(*s['med'], 0) for s in stat], dtype=int))
                 np.save(fov_dir.joinpath('mpciROIs.cellClassifier.npy'), np.asarray(iscell[:, 1], dtype=float))
                 np.save(fov_dir.joinpath('mpciROIs.mpciROITypes.npy'), np.asarray(iscell[:, 0], dtype=np.int16))
+                # clusters uuids
+                uuid_list = ['uuids'] + list(map(str, [uuid.uuid4() for _ in range(len(iscell))]))
+                with open(fov_dir.joinpath('mpciROIs.uuids.csv'), 'w+') as fid:
+                    fid.write('\n'.join(uuid_list))
+
                 pd.DataFrame([(0, 'no cell'), (1, 'cell')], columns=['roi_values', 'roi_labels']
                              ).to_csv(fov_dir.joinpath('mpciROITypes.names.tsv'), sep='\t', index=False)
                 # ROI and neuropil masks