Merge pull request #776 from int-brain-lab/hotfix/2.35.3

Use correct task for timeline acquisitions in make_pipeline

Author: k1o0

ibllib/__init__.py

@@ -2,7 +2,7 @@
 import logging
 import warnings
 
-__version__ = '2.35.2'
+__version__ = '2.35.3'
 warnings.filterwarnings('always', category=DeprecationWarning, module='ibllib')
 
 # if this becomes a full-blown library we should let the logging configuration to the discretion of the dev

ibllib/pipes/dynamic_pipeline.py

@@ -268,7 +268,12 @@ def make_pipeline(session_path, **pkwargs):
                     compute_status = False
                 else:
                     registration_class = btasks.TrialRegisterRaw
-                    behaviour_class = btasks.ChoiceWorldTrialsNidq
+                    if sync_args['sync_namespace'] == 'timeline':
+                        behaviour_class = btasks.ChoiceWorldTrialsTimeline
+                    elif sync_args['sync_namespace'] in ('spikeglx', None):
+                        behaviour_class = btasks.ChoiceWorldTrialsNidq
+                    else:
+                        raise NotImplementedError(f'No trials task available for sync namespace "{sync_args["sync_namespace"]}"')
                     compute_status = True
             else:
                 raise NotImplementedError
@@ -278,7 +283,7 @@ def make_pipeline(session_path, **pkwargs):
             tasks[f'Trials_{protocol}_{i:02}'] = type(f'Trials_{protocol}_{i:02}', (behaviour_class,), {})(
                 **kwargs, **sync_kwargs, **task_kwargs, parents=parents)
             if compute_status:
-                tasks[f"TrainingStatus_{protocol}_{i:02}"] = type(f'TrainingStatus_{protocol}_{i:02}', (
+                tasks[f'TrainingStatus_{protocol}_{i:02}'] = type(f'TrainingStatus_{protocol}_{i:02}', (
                     btasks.TrainingStatus,), {})(**kwargs, **task_kwargs, parents=[tasks[f'Trials_{protocol}_{i:02}']])
 
     # Ephys tasks
@@ -289,7 +294,10 @@ def make_pipeline(session_path, **pkwargs):
         all_probes = []
         register_tasks = []
         for pname, probe_info in devices['neuropixel'].items():
-            meta_file = spikeglx.glob_ephys_files(Path(session_path).joinpath(probe_info['collection']), ext='meta')
+            # Glob to support collections such as _00a, _00b. This doesn't fix the issue of NP2.4
+            # extractions, however.
+            probe_collection = next(session_path.glob(probe_info['collection'] + '*'))
+            meta_file = spikeglx.glob_ephys_files(probe_collection, ext='meta')
             meta_file = meta_file[0].get('ap')
             nptype = spikeglx._get_neuropixel_version_from_meta(spikeglx.read_meta_data(meta_file))
             nshanks = spikeglx._get_nshanks_from_meta(spikeglx.read_meta_data(meta_file))
@@ -482,12 +490,15 @@ def get_trials_tasks(session_path, one=None):
     # If experiment description file then use this to make the pipeline
     if experiment_description is not None:
         tasks = []
-        pipeline = make_pipeline(session_path, one=one)
-        trials_tasks = [t for t in pipeline.tasks if 'Trials' in t]
-        for task in trials_tasks:
-            t = pipeline.tasks.get(task)
-            t.__init__(session_path, **t.kwargs)
-            tasks.append(t)
+        try:
+            pipeline = make_pipeline(session_path, one=one)
+            trials_tasks = [t for t in pipeline.tasks if 'Trials' in t]
+            for task in trials_tasks:
+                t = pipeline.tasks.get(task)
+                t.__init__(session_path, **t.kwargs)
+                tasks.append(t)
+        except NotImplementedError as ex:
+            _logger.warning('Failed to get trials tasks: %s', ex)
     else:
         # Otherwise default to old way of doing things
         if one and one.to_eid(session_path):

ibllib/tests/test_dynamic_pipeline.py

@@ -9,6 +9,7 @@
 import ibllib.tests
 import ibllib.pipes.dynamic_pipeline as dyn
 from ibllib.pipes.tasks import Pipeline, Task
+import ibllib.pipes.behavior_tasks as btasks
 from ibllib.pipes import ephys_preprocessing
 from ibllib.pipes import training_preprocessing
 from ibllib.io import session_params
@@ -65,6 +66,7 @@ def setUp(self):
                            {'ephysChoiceWorld': {'task_collection': 'raw_task_data_00'}},
                            {'passiveChoiceWorld': {'task_collection': 'raw_task_data_01'}},
                        ]}
+        self.description = description
         with open(self.session_path_dynamic / '_ibl_experiment.description.yaml', 'w') as fp:
             yaml.safe_dump(description, fp)
 
@@ -87,8 +89,25 @@ def test_get_trials_tasks(self):
         one.alyx.cache_mode = None  # sneaky hack as this is checked by the pipeline somewhere
         tasks = dyn.get_trials_tasks(self.session_path_dynamic, one)
         self.assertEqual(2, len(tasks))
+        self.assertIsInstance(tasks[0], btasks.ChoiceWorldTrialsNidq)
         one.load_datasets.assert_called()  # check that description file is checked on disk
 
+        # A session with timeline acquisition
+        self.description['sync']['nidq']['acquisition_software'] = 'timeline'
+        with open(self.session_path_dynamic / '_ibl_experiment.description.yaml', 'w') as fp:
+            yaml.safe_dump(self.description, fp)
+        tasks = dyn.get_trials_tasks(self.session_path_dynamic, one)
+        self.assertIsInstance(tasks[0], btasks.ChoiceWorldTrialsTimeline)
+
+        # A session with an unknown sync namespace
+        self.description['sync']['nidq']['acquisition_software'] = 'notepad'
+        with open(self.session_path_dynamic / '_ibl_experiment.description.yaml', 'w') as fp:
+            yaml.safe_dump(self.description, fp)
+        with self.assertLogs(dyn.__name__, 'WARNING') as cm:
+            self.assertEqual([], dyn.get_trials_tasks(self.session_path_dynamic))
+        log_message = cm.records[0].getMessage()
+        self.assertIn('sync namespace "notepad"', log_message)
+
         # An ephys session
         tasks = dyn.get_trials_tasks(self.session_path_legacy)
         self.assertEqual(1, len(tasks))

release_notes.md

@@ -15,6 +15,9 @@
 - Support extraction of repNum for advancedChoiceWorld
 - Support matplotlib v3.9; min slidingRP version now 1.1.1
 
+#### 2.35.3
+- Use correct task for timeline acquisitions in make_pipeline
+
 ## Release Note 2.34.0
 
 ### features