def get_behavior_ophys_experiment(
self, ophys_experiment_id: int) -> BehaviorOphysExperiment:
"""Returns a BehaviorOphysExperiment object that contains methods
to analyze a single behavior+ophys session.
:param ophys_experiment_id: id that corresponds to an ophys experiment
:type ophys_experiment_id: int
:rtype: BehaviorOphysExperiment
"""
return BehaviorOphysExperiment.from_lims(
ophys_experiment_id=ophys_experiment_id)
def test_legacy_dff_api():
ophys_experiment_id = 792813858
session = BehaviorOphysExperiment.from_lims(
ophys_experiment_id=ophys_experiment_id)
_, dff_array = session.get_dff_traces()
for csid in session.dff_traces.index.values:
dff_trace = session.dff_traces.loc[csid]['dff']
ind = session.cell_specimen_table.index.get_loc(csid)
np.testing.assert_array_almost_equal(dff_trace, dff_array[ind, :])
assert dff_array.shape[0] == session.dff_traces.shape[0]
def test_nwb_end_to_end(tmpdir_factory):
# NOTE: old test oeid 789359614 had no cell specimen ids due to not being
# part of the 2021 Visual Behavior release set which broke a ton
# of things...
oeid = 795073741
tmpdir = 'test_nwb_end_to_end'
nwb_filepath = os.path.join(str(tmpdir_factory.mktemp(tmpdir)),
'nwbfile.nwb')
d1 = BehaviorOphysExperiment.from_lims(oeid)
BehaviorOphysNwbApi(nwb_filepath).save(d1)
d2 = BehaviorOphysExperiment(api=BehaviorOphysNwbApi(nwb_filepath))
assert sessions_are_equal(d1, d2, reraise=True)
def write_behavior_ophys_nwb(session_data: dict, nwb_filepath: str,
skip_eye_tracking: bool):
nwb_filepath_inprogress = nwb_filepath + '.inprogress'
nwb_filepath_error = nwb_filepath + '.error'
# Clean out files from previous runs:
for filename in [
nwb_filepath_inprogress, nwb_filepath_error, nwb_filepath
]:
if os.path.exists(filename):
os.remove(filename)
try:
json_session = BehaviorOphysExperiment.from_json(
session_data=session_data, skip_eye_tracking=skip_eye_tracking)
lims_session = BehaviorOphysExperiment.from_lims(
ophys_experiment_id=session_data['ophys_experiment_id'],
skip_eye_tracking=skip_eye_tracking)
logging.info("Comparing a BehaviorOphysExperiment created from JSON "
"with a BehaviorOphysExperiment created from LIMS")
assert sessions_are_equal(json_session,
lims_session,
reraise=True,
ignore_keys={'metadata': {'project_code'}})
nwbfile = json_session.to_nwb()
with NWBHDF5IO(nwb_filepath_inprogress, 'w') as nwb_file_writer:
nwb_file_writer.write(nwbfile)
logging.info("Comparing a BehaviorOphysExperiment created from JSON "
"with a BehaviorOphysExperiment created from NWB")
nwb_session = BehaviorOphysExperiment.from_nwb(nwbfile=nwbfile)
assert sessions_are_equal(json_session, nwb_session, reraise=True)
os.rename(nwb_filepath_inprogress, nwb_filepath)
return {'output_path': nwb_filepath}
except Exception as e:
if os.path.isfile(nwb_filepath_inprogress):
os.rename(nwb_filepath_inprogress, nwb_filepath_error)
raise e
def test_nwb_end_to_end(tmpdir_factory):
# NOTE: old test oeid 789359614 had no cell specimen ids due to not being
# part of the 2021 Visual Behavior release set which broke a ton
# of things...
oeid = 795073741
tmpdir = 'test_nwb_end_to_end'
nwb_filepath = os.path.join(str(tmpdir_factory.mktemp(tmpdir)),
'nwbfile.nwb')
d1 = BehaviorOphysExperiment.from_lims(oeid)
nwbfile = d1.to_nwb()
with NWBHDF5IO(nwb_filepath, 'w') as nwb_file_writer:
nwb_file_writer.write(nwbfile)
d2 = BehaviorOphysExperiment.from_nwb(nwbfile=nwbfile)
assert sessions_are_equal(d1,
d2,
reraise=True,
ignore_keys={'metadata': {'project_code'}})
def test_event_detection():
ophys_experiment_id = 789359614
session = BehaviorOphysExperiment.from_lims(
ophys_experiment_id=ophys_experiment_id)
events = session.events
assert len(events) > 0
expected_columns = [
'events', 'filtered_events', 'lambda', 'noise_std', 'cell_roi_id'
]
assert len(events.columns) == len(expected_columns)
# Assert they contain the same columns
assert len(set(expected_columns).intersection(
events.columns)) == len(expected_columns)
assert events.index.name == 'cell_specimen_id'
# All events are the same length
event_length = len(set([len(x) for x in events['events']]))
assert event_length == 1
def test_visbeh_ophys_data_set():
ophys_experiment_id = 789359614
data_set = BehaviorOphysExperiment.from_lims(ophys_experiment_id,
exclude_invalid_rois=False)
# TODO: need to improve testing here:
# for _, row in data_set.roi_metrics.iterrows():
# print(np.array(row.to_dict()['mask']).sum())
# print
# for _, row in data_set.roi_masks.iterrows():
# print(np.array(row.to_dict()['mask']).sum())
lims_db = db_connection_creator(
fallback_credentials=LIMS_DB_CREDENTIAL_MAP)
behavior_session_id = BehaviorSessionId.from_lims(
db=lims_db, ophys_experiment_id=ophys_experiment_id)
# All sorts of assert relationships:
assert ForagingId.from_lims(behavior_session_id=behavior_session_id.value,
lims_db=lims_db).value == \
data_set.metadata['behavior_session_uuid']
stimulus_templates = data_set.stimulus_templates
assert len(stimulus_templates) == 8
assert stimulus_templates.loc['im000'].warped.shape == MONITOR_DIMENSIONS
assert stimulus_templates.loc['im000'].unwarped.shape == MONITOR_DIMENSIONS
assert len(data_set.licks) == 2421 and set(data_set.licks.columns) \
== set(['timestamps', 'frame'])
assert len(data_set.rewards) == 85 and set(data_set.rewards.columns) == \
set(['timestamps', 'volume', 'autorewarded'])
assert len(data_set.corrected_fluorescence_traces) == 258 and \
set(data_set.corrected_fluorescence_traces.columns) == \
set(['cell_roi_id', 'corrected_fluorescence'])
np.testing.assert_array_almost_equal(data_set.running_speed.timestamps,
data_set.stimulus_timestamps)
assert len(data_set.cell_specimen_table) == len(data_set.dff_traces)
assert data_set.average_projection.data.shape == \
data_set.max_projection.data.shape
assert set(data_set.motion_correction.columns) == set(['x', 'y'])
assert len(data_set.trials) == 602
expected_metadata = {
'stimulus_frame_rate':
60.0,
'full_genotype':
'Slc17a7-IRES2-Cre/wt;Camk2a-tTA/wt;Ai93('
'TITL-GCaMP6f)/wt',
'ophys_experiment_id':
789359614,
'behavior_session_id':
789295700,
'imaging_plane_group_count':
0,
'ophys_session_id':
789220000,
'session_type':
'OPHYS_6_images_B',
'driver_line': ['Camk2a-tTA', 'Slc17a7-IRES2-Cre'],
'cre_line':
'Slc17a7-IRES2-Cre',
'behavior_session_uuid':
uuid.UUID('69cdbe09-e62b-4b42-aab1-54b5773dfe78'),
'date_of_acquisition':
pytz.utc.localize(datetime.datetime(2018, 11, 30, 23, 28, 37)),
'ophys_frame_rate':
31.0,
'imaging_depth':
375,
'mouse_id':
416369,
'experiment_container_id':
814796558,
'targeted_structure':
'VISp',
'reporter_line':
'Ai93(TITL-GCaMP6f)',
'emission_lambda':
520.0,
'excitation_lambda':
910.0,
'field_of_view_height':
512,
'field_of_view_width':
447,
'indicator':
'GCaMP6f',
'equipment_name':
'CAM2P.5',
'age_in_days':
139,
'sex':
'F',
'imaging_plane_group':
None,
'project_code':
'VisualBehavior'
}
assert data_set.metadata == expected_metadata
assert data_set.task_parameters == {
'reward_volume': 0.007,
'stimulus_distribution': u'geometric',
'stimulus_duration_sec': 0.25,
'stimulus': 'images',
'omitted_flash_fraction': 0.05,
'blank_duration_sec': [0.5, 0.5],
'n_stimulus_frames': 69882,
'task': 'change detection',
'response_window_sec': [0.15, 0.75],
'session_type': u'OPHYS_6_images_B',
'auto_reward_volume': 0.005
}
def test_BehaviorOphysExperiment_property_data():
ophys_experiment_id = 960410026
dataset = BehaviorOphysExperiment.from_lims(ophys_experiment_id)
assert dataset.ophys_session_id == 959458018
assert dataset.ophys_experiment_id == 960410026
def test_eye_tracking(dilation_frames, z_threshold, monkeypatch):
"""A very long test just to test that eye tracking arguments are sent to
EyeTrackingTable factory method from BehaviorOphysExperiment.from_lims"""
expected = EyeTrackingTable(eye_tracking=pd.DataFrame([1, 2, 3]))
EyeTrackingTable_mock = create_autospec(EyeTrackingTable)
EyeTrackingTable_mock.from_data_file.return_value = expected
etf = create_autospec(EyeTrackingFile, instance=True)
sf = create_autospec(SyncFile, instance=True)
with monkeypatch.context() as ctx:
ctx.setattr(
'allensdk.brain_observatory.behavior.'
'behavior_ophys_experiment.db_connection_creator',
create_autospec(db_connection_creator, instance=True))
ctx.setattr(SyncFile, 'from_lims', lambda db, ophys_experiment_id: sf)
ctx.setattr(
StimulusTimestamps, 'from_sync_file',
lambda sync_file: create_autospec(StimulusTimestamps,
instance=True))
ctx.setattr(
BehaviorSessionId, 'from_lims',
lambda db, ophys_experiment_id: create_autospec(BehaviorSessionId,
instance=True))
ctx.setattr(ImagingPlaneGroup, 'from_lims',
lambda lims_db, ophys_experiment_id: None)
ctx.setattr(
BehaviorOphysMetadata, 'from_lims',
lambda lims_db, ophys_experiment_id, is_multiplane:
create_autospec(BehaviorOphysMetadata, instance=True))
ctx.setattr(
'allensdk.brain_observatory.behavior.'
'behavior_ophys_experiment.calculate_monitor_delay',
create_autospec(calculate_monitor_delay))
ctx.setattr(
DateOfAcquisitionOphys, 'from_lims',
lambda lims_db, ophys_experiment_id: create_autospec(
DateOfAcquisitionOphys, instance=True))
ctx.setattr(
BehaviorSession, 'from_lims',
lambda lims_db, behavior_session_id, stimulus_timestamps,
monitor_delay, date_of_acquisition: BehaviorSession(
behavior_session_id=None,
stimulus_timestamps=None,
running_acquisition=None,
raw_running_speed=None,
running_speed=None,
licks=None,
rewards=None,
stimuli=None,
task_parameters=None,
trials=None,
metadata=None,
date_of_acquisition=None,
))
ctx.setattr(
OphysTimestamps, 'from_sync_file',
lambda sync_file: create_autospec(OphysTimestamps, instance=True))
ctx.setattr(
Projections, 'from_lims', lambda lims_db, ophys_experiment_id:
create_autospec(Projections, instance=True))
ctx.setattr(
CellSpecimens, 'from_lims', lambda lims_db, ophys_experiment_id,
ophys_timestamps, segmentation_mask_image_spacing, events_params,
exclude_invalid_rois: create_autospec(BehaviorSession,
instance=True))
ctx.setattr(
RigidMotionTransformFile, 'from_lims',
lambda db, ophys_experiment_id: create_autospec(
RigidMotionTransformFile, instance=True))
ctx.setattr(EyeTrackingFile, 'from_lims',
lambda db, ophys_experiment_id: etf)
ctx.setattr(
EyeTrackingTable, 'from_data_file', lambda data_file, sync_file,
z_threshold, dilation_frames: EyeTrackingTable_mock.from_data_file(
data_file=data_file,
sync_file=sync_file,
z_threshold=z_threshold,
dilation_frames=dilation_frames))
ctx.setattr(
EyeTrackingRigGeometry, 'from_lims',
lambda lims_db, ophys_experiment_id: create_autospec(
EyeTrackingRigGeometry, instance=True))
boe = BehaviorOphysExperiment.from_lims(
ophys_experiment_id=1,
eye_tracking_z_threshold=z_threshold,
eye_tracking_dilation_frames=dilation_frames)
obtained = boe.eye_tracking
assert obtained.equals(expected.value)
EyeTrackingTable_mock.from_data_file.assert_called_with(
data_file=etf,
sync_file=sf,
z_threshold=z_threshold,
dilation_frames=dilation_frames)
def test_stimulus_presentations_omitted(ophys_experiment_id, number_omitted):
session = BehaviorOphysExperiment.from_lims(ophys_experiment_id)
df = session.stimulus_presentations
assert df['omitted'].sum() == number_omitted