Merge branch 'main' into neuromodulatorsExtraction

.github/workflows/checks.yaml

@@ -0,0 +1,37 @@
+name: Version Check
+
+on:
+  pull_request:
+    branches:
+      - main
+
+jobs:
+  checks:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v3
+    - name: Setup Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.11'
+        cache: 'pip'
+        cache-dependency-path: 'pyproject.toml'
+    - name: Install dependencies
+      run: |
+        pip install --editable .
+        pip install packaging
+    - name: Fetch versions
+      run: |
+        git fetch origin --tags
+        previous_version=$(git describe --tags --match="[0-9]*" origin/main)
+        latest_version=$(pip show project_extraction | awk '/^Version: / {sub("^Version: ", ""); print}')
+        echo "Version tag on main: $previous_version"
+        echo "Version tag on this branch: $latest_version"
+        echo "PREVIOUS_VERSION=$previous_version" >> $GITHUB_ENV
+        echo "LATEST_VERSION=$latest_version" >> $GITHUB_ENV
+    - name: Assert version
+      run: |
+        python <<EOP
+        import sys; from packaging import version
+        sys.exit(int(version.parse("$PREVIOUS_VERSION") >= version.parse("$LATEST_VERSION")))
+        EOP

.github/workflows/deploy.yaml

@@ -0,0 +1,38 @@
+name: Version Tag
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v3
+      with:
+        ref: ${{ github.head_ref }}
+        fetch-depth: 0
+    - name: Setup Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.11'
+        cache: 'pip'
+        cache-dependency-path: 'pyproject.toml'
+    - name: Install dependencies
+      run: |
+        pip install --editable .
+    - name: Fetch version
+      run: |
+        latest_version=$(pip show project_extraction | awk '/^Version: / {sub("^Version: ", ""); print}')
+        echo "LATEST_VERSION=$latest_version" >> $GITHUB_ENV
+    - name: Create tag
+      run: |
+        git config --local user.email "[email protected]"
+        git config --local user.name "GitHub Action"
+        git tag -a "$LATEST_VERSION" HEAD -m "Version v$LATEST_VERSION"
+    - name: Push changes
+      uses: ad-m/github-push-action@master
+      with:
+        force: true
+        tags: true

iblrig_custom_tasks/nate_optoBiasedChoiceWorld/task.py

@@ -62,6 +62,11 @@ def __init__(
         self.task_params['OPTO_STIM_STATES'] = opto_stim_states
         self.task_params['PROBABILITY_OPTO_STIM'] = probability_opto_stim
 
+        # loads in the settings in order to determine the main sync and thus the pipeline extractor tasks
+        is_main_sync = self.hardware_settings.get('MAIN_SYNC', False)
+        trials_task = 'OptoTrialsBpod' if is_main_sync else 'OptoTrialsNidq'
+        self.extractor_tasks = ['TrialRegisterRaw', trials_task, 'TrainingStatus']
+
         # generates the opto stimulation for each trial
         self.trials_table['opto_stimulation'] = np.random.choice(
             [0, 1], p=[1 - probability_opto_stim, probability_opto_stim], size=NTRIALS_INIT
@@ -105,7 +110,7 @@ def extra_parser():
             default=DEFAULTS['OPTO_STIM_STATES'],
             nargs='+',
             type=str,
-            help=f'list of the state machine states where opto stim should be delivered',
+            help='list of the state machine states where opto stim should be delivered',
         )
         return parser
 

iblrig_custom_tasks/nate_optoBiasedChoiceWorld/test_nate_optoBiasedChoiceWorld.py

@@ -7,3 +7,4 @@
 
 
 assert task.task_params.get('PROBABILITY_OPTO_STIM', None) is not None
+assert any(t.startswith('OptoTrials') for t in task.extractor_tasks or [])

projects/extraction_tasks.py

@@ -6,3 +6,4 @@
 NB: This may need changing in the future if one of these modules requires optional dependencies.
 """
 from projects.samuel_cuedBiasedChoiceWorld import CuedBiasedTrials, CuedBiasedTrialsTimeline
+from projects.nate_optoBiasedChoiceWorld import OptoTrialsNidq, OptoTrialsBpod

projects/nate_optoBiasedChoiceWorld.py

@@ -0,0 +1,64 @@
+"""Bpod extractor for nate_optoBiasedChoiceWorld task.
+
+This is the same as biasedChoiceWorld with the addition of one dataset, `laserStimulation.intervals`; The times the
+laser was on.
+
+The pipeline task subclasses, OptoTrialsBpod and OptoTrialsNidq, aren't strictly necessary. They simply assert that the
+laserStimulation datasets were indeed saved and registered by the Bpod extractor class.
+"""
+import numpy as np
+import ibllib.io.raw_data_loaders as raw
+from ibllib.io.extractors.base import BaseBpodTrialsExtractor, run_extractor_classes
+from ibllib.io.extractors.bpod_trials import BiasedTrials
+from ibllib.pipes.behavior_tasks import ChoiceWorldTrialsNidq, ChoiceWorldTrialsBpod
+
+
+class OptoTrialsBpod(ChoiceWorldTrialsBpod):
+    """Extract bpod only trials and laser stimulation data."""
+
+    @property
+    def signature(self):
+        signature = super().signature
+        signature['output_files'].append(('*laserStimulation.intervals.npy', self.output_collection, True))
+        return signature
+
+
+class OptoTrialsNidq(ChoiceWorldTrialsNidq):
+    """Extract trials and laser stimulation data aligned to NI-DAQ clock."""
+
+    @property
+    def signature(self):
+        signature = super().signature
+        signature['output_files'].append(('*laserStimulation.intervals.npy', self.output_collection, True))
+        return signature
+
+
+class TrialsOpto(BaseBpodTrialsExtractor):
+    var_names = BiasedTrials.var_names + ('laser_intervals',)
+    save_names = BiasedTrials.save_names + ('_ibl_laserStimulation.intervals.npy',)
+
+    def _extract(self, extractor_classes=None, **kwargs) -> dict:
+        settings = self.settings.copy()
+        if 'OPTO_STIM_STATES' in settings:
+            # It seems older versions did not distinguish start and stop states
+            settings['OPTO_TTL_STATES'] = settings['OPTO_STIM_STATES'][:1]
+            settings['OPTO_STOP_STATES'] = settings['OPTO_STIM_STATES'][1:]
+        assert {'OPTO_STOP_STATES', 'OPTO_TTL_STATES', 'PROBABILITY_OPTO_STIM'} <= set(settings)
+        # Get all detected TTLs. These are stored for QC purposes
+        self.frame2ttl, self.audio = raw.load_bpod_fronts(self.session_path, data=self.bpod_trials)
+        # Extract common biased choice world datasets
+        out, _ = run_extractor_classes(
+            [BiasedTrials], session_path=self.session_path, bpod_trials=self.bpod_trials,
+            settings=settings, save=False, task_collection=self.task_collection)
+
+        # Extract laser dataset
+        laser_intervals = []
+        for trial in filter(lambda t: t['opto_stimulation'], self.bpod_trials):
+            states = trial['behavior_data']['States timestamps']
+            # Assumes one of these states per trial: takes the timestamp of the first matching state
+            start = next((v[0][0] for k, v in states.items() if k in settings['OPTO_TTL_STATES']), np.nan)
+            stop = next((v[0][0] for k, v in states.items() if k in settings['OPTO_STOP_STATES']), np.nan)
+            laser_intervals.append((start, stop))
+        out['laser_intervals'] = np.array(laser_intervals, dtype=np.float64)
+
+        return {k: out[k] for k in self.var_names}  # Ensures all datasets present and ordered

projects/task_extractor_map.json

@@ -1,5 +1,5 @@
 {
   "samuel_cuedBiasedChoiceWorld": "BiasedTrials",
-  "nate_optoBiasedChoiceWorld": "EphysTrials",
   "_iblrig_tasks_neuromodulatorChoiceWorld": "projects.neuromodulators.TrialsTableNeuromodulator"
+  "nate_optoBiasedChoiceWorld": "projects.nate_optoBiasedChoiceWorld.TrialsOpto"
 }

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name            = "project_extraction"
-version         = "0.2.0"
+version         = "0.2.1.post0"
 description     = "Custom extractors for satellite tasks"
 dynamic         = [ "readme" ]
 keywords        = [ "IBL", "neuro-science" ]