Wheel alignment

.gitignore

@@ -7,6 +7,7 @@ __pycache__
 python/scratch
 .idea/*
 .vscode/
+*.code-workspace
 *checkpoint.ipynb
 build/
 venv/

ibllib/ephys/ephysqc.py

@@ -580,7 +580,7 @@ def _qc_from_path(sess_path, display=True):
     sync, chmap = ephys_fpga.get_main_probe_sync(sess_path, bin_exists=False)
     _ = ephys_fpga.extract_all(sess_path, output_path=temp_alf_folder, save=True)
     # check that the output is complete
-    fpga_trials = ephys_fpga.extract_behaviour_sync(sync, chmap=chmap, display=display)
+    fpga_trials, *_ = ephys_fpga.extract_behaviour_sync(sync, chmap=chmap, display=display)
     # align with the bpod
     bpod2fpga = ephys_fpga.align_with_bpod(temp_alf_folder.parent)
     alf_trials = alfio.load_object(temp_alf_folder, 'trials')

ibllib/io/extractors/biased_trials.py

@@ -95,12 +95,12 @@ class TrialsTableBiased(BaseBpodTrialsExtractor):
         intervals, goCue_times, response_times, choice, stimOn_times, contrastLeft, contrastRight,
         feedback_times, feedbackType, rewardVolume, probabilityLeft, firstMovement_times
     Additionally extracts the following wheel data:
-        wheel_timestamps, wheel_position, wheel_moves_intervals, wheel_moves_peak_amplitude
+        wheel_timestamps, wheel_position, wheelMoves_intervals, wheelMoves_peakAmplitude
     """
     save_names = ('_ibl_trials.table.pqt', None, None, '_ibl_wheel.timestamps.npy', '_ibl_wheel.position.npy',
                   '_ibl_wheelMoves.intervals.npy', '_ibl_wheelMoves.peakAmplitude.npy', None, None)
-    var_names = ('table', 'stimOff_times', 'stimFreeze_times', 'wheel_timestamps', 'wheel_position', 'wheel_moves_intervals',
-                 'wheel_moves_peak_amplitude', 'peakVelocity_times', 'is_final_movement')
+    var_names = ('table', 'stimOff_times', 'stimFreeze_times', 'wheel_timestamps', 'wheel_position', 'wheelMoves_intervals',
+                 'wheelMoves_peakAmplitude', 'peakVelocity_times', 'is_final_movement')
 
     def _extract(self, extractor_classes=None, **kwargs):
         base = [Intervals, GoCueTimes, ResponseTimes, Choice, StimOnOffFreezeTimes, ContrastLR, FeedbackTimes, FeedbackType,
@@ -120,13 +120,13 @@ class TrialsTableEphys(BaseBpodTrialsExtractor):
         intervals, goCue_times, response_times, choice, stimOn_times, contrastLeft, contrastRight,
         feedback_times, feedbackType, rewardVolume, probabilityLeft, firstMovement_times
     Additionally extracts the following wheel data:
-        wheel_timestamps, wheel_position, wheel_moves_intervals, wheel_moves_peak_amplitude
+        wheel_timestamps, wheel_position, wheelMoves_intervals, wheelMoves_peakAmplitude
     """
     save_names = ('_ibl_trials.table.pqt', None, None, '_ibl_wheel.timestamps.npy', '_ibl_wheel.position.npy',
                   '_ibl_wheelMoves.intervals.npy', '_ibl_wheelMoves.peakAmplitude.npy', None,
                   None, None, None, '_ibl_trials.quiescencePeriod.npy')
-    var_names = ('table', 'stimOff_times', 'stimFreeze_times', 'wheel_timestamps', 'wheel_position', 'wheel_moves_intervals',
-                 'wheel_moves_peak_amplitude', 'peakVelocity_times', 'is_final_movement',
+    var_names = ('table', 'stimOff_times', 'stimFreeze_times', 'wheel_timestamps', 'wheel_position', 'wheelMoves_intervals',
+                 'wheelMoves_peakAmplitude', 'peakVelocity_times', 'is_final_movement',
                  'phase', 'position', 'quiescence')
 
     def _extract(self, extractor_classes=None, **kwargs):
@@ -154,16 +154,16 @@ class BiasedTrials(BaseBpodTrialsExtractor):
                   None, None, '_ibl_trials.quiescencePeriod.npy')
     var_names = ('goCueTrigger_times', 'stimOnTrigger_times', 'itiIn_times', 'stimOffTrigger_times', 'stimFreezeTrigger_times',
                  'errorCueTrigger_times', 'table', 'stimOff_times', 'stimFreeze_times', 'wheel_timestamps', 'wheel_position',
-                 'wheel_moves_intervals', 'wheel_moves_peak_amplitude', 'peakVelocity_times', 'is_final_movement', 'included',
+                 'wheelMoves_intervals', 'wheelMoves_peakAmplitude', 'peakVelocity_times', 'is_final_movement', 'included',
                  'phase', 'position', 'quiescence')
 
-    def _extract(self, extractor_classes=None, **kwargs):
+    def _extract(self, extractor_classes=None, **kwargs) -> dict:
         base = [GoCueTriggerTimes, StimOnTriggerTimes, ItiInTimes, StimOffTriggerTimes, StimFreezeTriggerTimes,
                 ErrorCueTriggerTimes, TrialsTableBiased, IncludedTrials, PhasePosQuiescence]
         # Exclude from trials table
         out, _ = run_extractor_classes(base, session_path=self.session_path, bpod_trials=self.bpod_trials, settings=self.settings,
                                        save=False, task_collection=self.task_collection)
-        return tuple(out.pop(x) for x in self.var_names)
+        return {k: out[k] for k in self.var_names}
 
 
 class EphysTrials(BaseBpodTrialsExtractor):
@@ -177,16 +177,16 @@ class EphysTrials(BaseBpodTrialsExtractor):
                   '_ibl_trials.included.npy', None, None, '_ibl_trials.quiescencePeriod.npy')
     var_names = ('goCueTrigger_times', 'stimOnTrigger_times', 'itiIn_times', 'stimOffTrigger_times', 'stimFreezeTrigger_times',
                  'errorCueTrigger_times', 'table', 'stimOff_times', 'stimFreeze_times', 'wheel_timestamps', 'wheel_position',
-                 'wheel_moves_intervals', 'wheel_moves_peak_amplitude', 'peakVelocity_times', 'is_final_movement', 'included',
+                 'wheelMoves_intervals', 'wheelMoves_peakAmplitude', 'peakVelocity_times', 'is_final_movement', 'included',
                  'phase', 'position', 'quiescence')
 
-    def _extract(self, extractor_classes=None, **kwargs):
+    def _extract(self, extractor_classes=None, **kwargs) -> dict:
         base = [GoCueTriggerTimes, StimOnTriggerTimes, ItiInTimes, StimOffTriggerTimes, StimFreezeTriggerTimes,
                 ErrorCueTriggerTimes, TrialsTableEphys, IncludedTrials, PhasePosQuiescence]
         # Exclude from trials table
         out, _ = run_extractor_classes(base, session_path=self.session_path, bpod_trials=self.bpod_trials, settings=self.settings,
                                        save=False, task_collection=self.task_collection)
-        return tuple(out.pop(x) for x in self.var_names)
+        return {k: out[k] for k in self.var_names}
 
 
 def extract_all(session_path, save=False, bpod_trials=False, settings=False, extra_classes=None,

ibllib/io/extractors/camera.py

@@ -16,6 +16,7 @@
 from ibllib.io.extractors.base import get_session_extractor_type
 from ibllib.io.extractors.ephys_fpga import get_sync_fronts, get_sync_and_chn_map
 import ibllib.io.raw_data_loaders as raw
+import ibllib.io.extractors.video_motion as vmotion
 from ibllib.io.extractors.base import (
     BaseBpodTrialsExtractor,
     BaseExtractor,
@@ -148,12 +149,30 @@ def _extract(self, sync=None, chmap=None, video_path=None, sync_label='audio',
             except AssertionError as ex:
                 _logger.critical('Failed to extract using %s: %s', sync_label, ex)
 
-        # If you reach here extracting using sync TTLs was not possible
-        _logger.warning('Alignment by wheel data not yet implemented')
+        # If you reach here extracting using sync TTLs was not possible, we attempt to align using wheel motion energy
+        _logger.warning('Attempting to align using wheel')
+
+        try:
+            if self.label not in ['left', 'right']:
+                # Can only use wheel alignment for left and right cameras
+                raise ValueError(f'Wheel alignment not supported for {self.label} camera')
+
+            motion_class = vmotion.MotionAlignmentFullSession(self.session_path, self.label, upload=True)
+            new_times = motion_class.process()
+            if not motion_class.qc_outcome:
+                raise ValueError(f'Wheel alignment failed to pass qc: {motion_class.qc}')
+            else:
+                _logger.warning(f'Wheel alignment successful, qc: {motion_class.qc}')
+                return new_times
+
+        except Exception as err:
+            _logger.critical(f'Failed to align with wheel: {err}')
+
         if length < raw_ts.size:
             df = raw_ts.size - length
             _logger.info(f'Discarding first {df} pulses')
             raw_ts = raw_ts[df:]
+
         return raw_ts
 
 

ibllib/io/extractors/ephys_fpga.py

@@ -17,7 +17,7 @@
 from iblutil.spacer import Spacer
 
 import ibllib.exceptions as err
-from ibllib.io import raw_data_loaders, session_params
+from ibllib.io import raw_data_loaders as raw, session_params
 from ibllib.io.extractors.bpod_trials import extract_all as bpod_extract_all
 import ibllib.io.extractors.base as extractors_base
 from ibllib.io.extractors.training_wheel import extract_wheel_moves
@@ -554,7 +554,7 @@ def extract_behaviour_sync(sync, chmap=None, display=False, bpod_trials=None, tm
         ax.set_yticks([0, 1, 2, 3, 4, 5])
         ax.set_ylim([0, 5])
 
-    return trials
+    return trials, frame2ttl, audio, bpod
 
 
 def extract_sync(session_path, overwrite=False, ephys_files=None, namespace='spikeglx'):
@@ -734,6 +734,7 @@ def __init__(self, *args, bpod_trials=None, bpod_extractor=None, **kwargs):
         super().__init__(*args, **kwargs)
         self.bpod2fpga = None
         self.bpod_trials = bpod_trials
+        self.frame2ttl = self.audio = self.bpod = self.settings = None
         if bpod_extractor:
             self.bpod_extractor = bpod_extractor
             self._update_var_names()
@@ -750,14 +751,37 @@ def _update_var_names(self, bpod_fields=None, bpod_rsync_fields=None):
             A set of Bpod trials fields to keep.
         bpod_rsync_fields : tuple
             A set of Bpod trials fields to sync to the DAQ times.
-
-        TODO Turn into property getter; requires ensuring the output field are the same for legacy
         """
         if self.bpod_extractor:
-            self.var_names = self.bpod_extractor.var_names
-            self.save_names = self.bpod_extractor.save_names
-        self.bpod_rsync_fields = bpod_rsync_fields or self._time_fields(self.bpod_extractor.var_names)
-        self.bpod_fields = bpod_fields or [x for x in self.bpod_extractor.var_names if x not in self.bpod_rsync_fields]
+            for var_name, save_name in zip(self.bpod_extractor.var_names, self.bpod_extractor.save_names):
+                if var_name not in self.var_names:
+                    self.var_names += (var_name,)
+                    self.save_names += (save_name,)
+
+            # self.var_names = self.bpod_extractor.var_names
+            # self.save_names = self.bpod_extractor.save_names
+            self.settings = self.bpod_extractor.settings  # This is used by the TaskQC
+            self.bpod_rsync_fields = bpod_rsync_fields
+            if self.bpod_rsync_fields is None:
+                self.bpod_rsync_fields = tuple(self._time_fields(self.bpod_extractor.var_names))
+                if 'table' in self.bpod_extractor.var_names:
+                    if not self.bpod_trials:
+                        self.bpod_trials = self.bpod_extractor.extract(save=False)
+                    table_keys = alfio.AlfBunch.from_df(self.bpod_trials['table']).keys()
+                    self.bpod_rsync_fields += tuple(self._time_fields(table_keys))
+        elif bpod_rsync_fields:
+            self.bpod_rsync_fields = bpod_rsync_fields
+        excluded = (*self.bpod_rsync_fields, 'table')
+        if bpod_fields:
+            assert not set(self.bpod_fields).intersection(excluded), 'bpod_fields must not also be bpod_rsync_fields'
+            self.bpod_fields = bpod_fields
+        elif self.bpod_extractor:
+            self.bpod_fields = tuple(x for x in self.bpod_extractor.var_names if x not in excluded)
+            if 'table' in self.bpod_extractor.var_names:
+                if not self.bpod_trials:
+                    self.bpod_trials = self.bpod_extractor.extract(save=False)
+                table_keys = alfio.AlfBunch.from_df(self.bpod_trials['table']).keys()
+                self.bpod_fields += (*[x for x in table_keys if x not in excluded], self.sync_field + '_bpod')
 
     @staticmethod
     def _time_fields(trials_attr) -> set:
@@ -778,7 +802,8 @@ def _time_fields(trials_attr) -> set:
         pattern = re.compile(fr'^[_\w]*({"|".join(FIELDS)})[_\w]*$')
         return set(filter(pattern.match, trials_attr))
 
-    def _extract(self, sync=None, chmap=None, sync_collection='raw_ephys_data', task_collection='raw_behavior_data', **kwargs):
+    def _extract(self, sync=None, chmap=None, sync_collection='raw_ephys_data',
+                 task_collection='raw_behavior_data', **kwargs) -> dict:
         """Extracts ephys trials by combining Bpod and FPGA sync pulses"""
         # extract the behaviour data from bpod
         if sync is None or chmap is None:
@@ -804,7 +829,8 @@ def _extract(self, sync=None, chmap=None, sync_collection='raw_ephys_data', task
         else:
             tmin = tmax = None
 
-        fpga_trials = extract_behaviour_sync(
+        # Store the cleaned frame2ttl, audio, and bpod pulses as this will be used for QC
+        fpga_trials, self.frame2ttl, self.audio, self.bpod = extract_behaviour_sync(
             sync=sync, chmap=chmap, bpod_trials=self.bpod_trials, tmin=tmin, tmax=tmax)
         assert self.sync_field in self.bpod_trials and self.sync_field in fpga_trials
         self.bpod_trials[f'{self.sync_field}_bpod'] = np.copy(self.bpod_trials[self.sync_field])
@@ -827,18 +853,20 @@ def _extract(self, sync=None, chmap=None, sync_collection='raw_ephys_data', task
         # extract the wheel data
         wheel, moves = self.get_wheel_positions(sync=sync, chmap=chmap, tmin=tmin, tmax=tmax)
         from ibllib.io.extractors.training_wheel import extract_first_movement_times
-        settings = raw_data_loaders.load_settings(session_path=self.session_path, task_collection=task_collection)
-        min_qt = settings.get('QUIESCENT_PERIOD', None)
+        if not self.settings:
+            self.settings = raw.load_settings(session_path=self.session_path, task_collection=task_collection)
+        min_qt = self.settings.get('QUIESCENT_PERIOD', None)
         first_move_onsets, *_ = extract_first_movement_times(moves, out, min_qt=min_qt)
         out.update({'firstMovement_times': first_move_onsets})
         # Re-create trials table
         trials_table = alfio.AlfBunch({x: out.pop(x) for x in table_columns})
         out['table'] = trials_table.to_df()
 
+        out.update({f'wheel_{k}': v for k, v in wheel.items()})
+        out.update({f'wheelMoves_{k}': v for k, v in moves.items()})
         out = {k: out[k] for k in self.var_names if k in out}  # Reorder output
-        assert tuple(filter(lambda x: 'wheel' not in x, self.var_names)) == tuple(out.keys())
-        return [out[k] for k in out] + [wheel['timestamps'], wheel['position'],
-                                        moves['intervals'], moves['peakAmplitude']]
+        assert self.var_names == tuple(out.keys())
+        return out
 
     def get_wheel_positions(self, *args, **kwargs):
         """Extract wheel and wheelMoves objects.
@@ -882,7 +910,7 @@ def extract_all(session_path, sync_collection='raw_ephys_data', save=True, save_
         If save is True, a list of file paths to the extracted data.
     """
     # Extract Bpod trials
-    bpod_raw = raw_data_loaders.load_data(session_path, task_collection=task_collection)
+    bpod_raw = raw.load_data(session_path, task_collection=task_collection)
     assert bpod_raw is not None, 'No task trials data in raw_behavior_data - Exit'
     bpod_trials, *_ = bpod_extract_all(
         session_path=session_path, bpod_trials=bpod_raw, task_collection=task_collection,

ibllib/io/extractors/habituation_trials.py

@@ -15,16 +15,15 @@ class HabituationTrials(BaseBpodTrialsExtractor):
     var_names = ('feedbackType', 'rewardVolume', 'stimOff_times', 'contrastLeft', 'contrastRight',
                  'feedback_times', 'stimOn_times', 'stimOnTrigger_times', 'intervals',
                  'goCue_times', 'goCueTrigger_times', 'itiIn_times', 'stimOffTrigger_times',
-                 'stimCenterTrigger_times', 'stimCenter_times')
+                 'stimCenterTrigger_times', 'stimCenter_times', 'position', 'phase')
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
-        exclude = ['itiIn_times', 'stimOffTrigger_times',
-                   'stimCenter_times', 'stimCenterTrigger_times']
-        self.save_names = tuple([f'_ibl_trials.{x}.npy' if x not in exclude else None
-                                 for x in self.var_names])
+        exclude = ['itiIn_times', 'stimOffTrigger_times', 'stimCenter_times',
+                   'stimCenterTrigger_times', 'position', 'phase']
+        self.save_names = tuple(f'_ibl_trials.{x}.npy' if x not in exclude else None for x in self.var_names)
 
-    def _extract(self):
+    def _extract(self) -> dict:
         # Extract all trials...
 
         # Get all stim_sync events detected
@@ -101,9 +100,14 @@ def _extract(self):
              ["iti"][0][0] for tr in self.bpod_trials]
         )
 
+        # Phase and position
+        out['position'] = np.array([t['position'] for t in self.bpod_trials])
+        out['phase'] = np.array([t['stim_phase'] for t in self.bpod_trials])
+
         # NB: We lose the last trial because the stim off event occurs at trial_num + 1
         n_trials = out['stimOff_times'].size
-        return [out[k][:n_trials] for k in self.var_names]
+        # return [out[k][:n_trials] for k in self.var_names]
+        return {k: out[k][:n_trials] for k in self.var_names}
 
 
 def extract_all(session_path, save=False, bpod_trials=False, settings=False, task_collection='raw_behavior_data', save_path=None):