def setup_class(cls):
cls.ophys_experiment_id = 994278291
dir = Path(__file__).parent.resolve()
test_data_dir = dir / 'test_data'
cls.expected_max = Projections._from_filepath(filepath=str(
test_data_dir / 'max_projection.png'),
pixel_size=.78125)
cls.expected_avg = Projections._from_filepath(filepath=str(
test_data_dir / 'avg_projection.png'),
pixel_size=.78125)
def setup_class(cls):
dir = Path(__file__).parent.resolve()
test_data_dir = dir / 'test_data'
with open(test_data_dir / 'test_input.json') as f:
dict_repr = json.load(f)
dict_repr = dict_repr['session_data']
dict_repr['max_projection_file'] = test_data_dir / \
dict_repr['max_projection_file']
dict_repr['average_intensity_projection_image_file'] = \
test_data_dir / \
dict_repr['average_intensity_projection_image_file']
cls.expected_max = Projections._from_filepath(filepath=str(
test_data_dir / 'max_projection.png'),
pixel_size=.78125)
cls.expected_avg = Projections._from_filepath(filepath=str(
test_data_dir / 'avg_projection.png'),
pixel_size=.78125)
cls.dict_repr = dict_repr
def setup_class(cls):
tj = TestJson()
tj.setup_class()
cls.projections = Projections.from_json(dict_repr=tj.dict_repr)
def test_from_json(self):
projections = Projections.from_json(dict_repr=self.dict_repr)
assert projections.max_projection == self.expected_max
assert projections.avg_projection == self.expected_avg
def test_from_lims(self):
projections = Projections.from_lims(
ophys_experiment_id=self.ophys_experiment_id, lims_db=self.dbconn)
assert projections.max_projection == self.expected_max
assert projections.avg_projection == self.expected_avg
def from_json(cls,
session_data: dict,
eye_tracking_z_threshold: float = 3.0,
eye_tracking_dilation_frames: int = 2,
events_filter_scale: float = 2.0,
events_filter_n_time_steps: int = 20,
exclude_invalid_rois=True,
skip_eye_tracking=False) -> \
"BehaviorOphysExperiment":
"""
Parameters
----------
session_data
eye_tracking_z_threshold
See `BehaviorOphysExperiment.from_nwb`
eye_tracking_dilation_frames
See `BehaviorOphysExperiment.from_nwb`
events_filter_scale
See `BehaviorOphysExperiment.from_nwb`
events_filter_n_time_steps
See `BehaviorOphysExperiment.from_nwb`
exclude_invalid_rois
Whether to exclude invalid rois
skip_eye_tracking
Used to skip returning eye tracking data
"""
def _is_multi_plane_session():
imaging_plane_group_meta = ImagingPlaneGroup.from_json(
dict_repr=session_data)
return cls._is_multi_plane_session(
imaging_plane_group_meta=imaging_plane_group_meta)
def _get_motion_correction():
rigid_motion_transform_file = RigidMotionTransformFile.from_json(
dict_repr=session_data)
return MotionCorrection.from_data_file(
rigid_motion_transform_file=rigid_motion_transform_file)
def _get_eye_tracking_table(sync_file: SyncFile):
eye_tracking_file = EyeTrackingFile.from_json(
dict_repr=session_data)
eye_tracking_table = EyeTrackingTable.from_data_file(
data_file=eye_tracking_file,
sync_file=sync_file,
z_threshold=eye_tracking_z_threshold,
dilation_frames=eye_tracking_dilation_frames)
return eye_tracking_table
sync_file = SyncFile.from_json(dict_repr=session_data)
is_multiplane_session = _is_multi_plane_session()
meta = BehaviorOphysMetadata.from_json(
dict_repr=session_data, is_multiplane=is_multiplane_session)
monitor_delay = calculate_monitor_delay(
sync_file=sync_file, equipment=meta.behavior_metadata.equipment)
behavior_session = BehaviorSession.from_json(
session_data=session_data, monitor_delay=monitor_delay)
if is_multiplane_session:
ophys_timestamps = OphysTimestampsMultiplane.from_sync_file(
sync_file=sync_file,
group_count=meta.ophys_metadata.imaging_plane_group_count,
plane_group=meta.ophys_metadata.imaging_plane_group)
else:
ophys_timestamps = OphysTimestamps.from_sync_file(
sync_file=sync_file)
projections = Projections.from_json(dict_repr=session_data)
cell_specimens = CellSpecimens.from_json(
dict_repr=session_data,
ophys_timestamps=ophys_timestamps,
segmentation_mask_image_spacing=projections.max_projection.spacing,
events_params=EventsParams(
filter_scale=events_filter_scale,
filter_n_time_steps=events_filter_n_time_steps),
exclude_invalid_rois=exclude_invalid_rois)
motion_correction = _get_motion_correction()
if skip_eye_tracking:
eye_tracking_table = None
eye_tracking_rig_geometry = None
else:
eye_tracking_table = _get_eye_tracking_table(sync_file=sync_file)
eye_tracking_rig_geometry = EyeTrackingRigGeometry.from_json(
dict_repr=session_data)
return BehaviorOphysExperiment(
behavior_session=behavior_session,
cell_specimens=cell_specimens,
ophys_timestamps=ophys_timestamps,
metadata=meta,
projections=projections,
motion_correction=motion_correction,
eye_tracking_table=eye_tracking_table,
eye_tracking_rig_geometry=eye_tracking_rig_geometry,
date_of_acquisition=behavior_session._date_of_acquisition)
def from_nwb(cls,
nwbfile: NWBFile,
eye_tracking_z_threshold: float = 3.0,
eye_tracking_dilation_frames: int = 2,
events_filter_scale: float = 2.0,
events_filter_n_time_steps: int = 20,
exclude_invalid_rois=True) -> "BehaviorOphysExperiment":
"""
Parameters
----------
nwbfile
eye_tracking_z_threshold : float, optional
The z-threshold when determining which frames likely contain
outliers for eye or pupil areas. Influences which frames
are considered 'likely blinks'. By default 3.0
eye_tracking_dilation_frames : int, optional
Determines the number of adjacent frames that will be marked
as 'likely_blink' when performing blink detection for
`eye_tracking` data, by default 2
events_filter_scale : float, optional
Stdev of halfnorm distribution used to convolve ophys events with
a 1d causal half-gaussian filter to smooth it for visualization,
by default 2.0
events_filter_n_time_steps : int, optional
Number of time steps to use for convolution of ophys events
exclude_invalid_rois
Whether to exclude invalid rois
"""
def _is_multi_plane_session():
imaging_plane_group_meta = ImagingPlaneGroup.from_nwb(
nwbfile=nwbfile)
return cls._is_multi_plane_session(
imaging_plane_group_meta=imaging_plane_group_meta)
behavior_session = BehaviorSession.from_nwb(nwbfile=nwbfile)
projections = Projections.from_nwb(nwbfile=nwbfile)
cell_specimens = CellSpecimens.from_nwb(
nwbfile=nwbfile,
segmentation_mask_image_spacing=projections.max_projection.spacing,
events_params=EventsParams(
filter_scale=events_filter_scale,
filter_n_time_steps=events_filter_n_time_steps),
exclude_invalid_rois=exclude_invalid_rois)
eye_tracking_rig_geometry = EyeTrackingRigGeometry.from_nwb(
nwbfile=nwbfile)
eye_tracking_table = EyeTrackingTable.from_nwb(
nwbfile=nwbfile,
z_threshold=eye_tracking_z_threshold,
dilation_frames=eye_tracking_dilation_frames)
motion_correction = MotionCorrection.from_nwb(nwbfile=nwbfile)
is_multiplane_session = _is_multi_plane_session()
metadata = BehaviorOphysMetadata.from_nwb(
nwbfile=nwbfile, is_multiplane=is_multiplane_session)
if is_multiplane_session:
ophys_timestamps = OphysTimestampsMultiplane.from_nwb(
nwbfile=nwbfile)
else:
ophys_timestamps = OphysTimestamps.from_nwb(nwbfile=nwbfile)
date_of_acquisition = DateOfAcquisitionOphys.from_nwb(nwbfile=nwbfile)
return BehaviorOphysExperiment(
behavior_session=behavior_session,
cell_specimens=cell_specimens,
eye_tracking_rig_geometry=eye_tracking_rig_geometry,
eye_tracking_table=eye_tracking_table,
motion_correction=motion_correction,
metadata=metadata,
ophys_timestamps=ophys_timestamps,
projections=projections,
date_of_acquisition=date_of_acquisition)
def from_lims(cls,
ophys_experiment_id: int,
eye_tracking_z_threshold: float = 3.0,
eye_tracking_dilation_frames: int = 2,
events_filter_scale: float = 2.0,
events_filter_n_time_steps: int = 20,
exclude_invalid_rois=True,
skip_eye_tracking=False) -> \
"BehaviorOphysExperiment":
"""
Parameters
----------
ophys_experiment_id
eye_tracking_z_threshold
See `BehaviorOphysExperiment.from_nwb`
eye_tracking_dilation_frames
See `BehaviorOphysExperiment.from_nwb`
events_filter_scale
See `BehaviorOphysExperiment.from_nwb`
events_filter_n_time_steps
See `BehaviorOphysExperiment.from_nwb`
exclude_invalid_rois
Whether to exclude invalid rois
skip_eye_tracking
Used to skip returning eye tracking data
"""
def _is_multi_plane_session():
imaging_plane_group_meta = ImagingPlaneGroup.from_lims(
ophys_experiment_id=ophys_experiment_id, lims_db=lims_db)
return cls._is_multi_plane_session(
imaging_plane_group_meta=imaging_plane_group_meta)
def _get_motion_correction():
rigid_motion_transform_file = RigidMotionTransformFile.from_lims(
ophys_experiment_id=ophys_experiment_id, db=lims_db)
return MotionCorrection.from_data_file(
rigid_motion_transform_file=rigid_motion_transform_file)
def _get_eye_tracking_table(sync_file: SyncFile):
eye_tracking_file = EyeTrackingFile.from_lims(
db=lims_db, ophys_experiment_id=ophys_experiment_id)
eye_tracking_table = EyeTrackingTable.from_data_file(
data_file=eye_tracking_file,
sync_file=sync_file,
z_threshold=eye_tracking_z_threshold,
dilation_frames=eye_tracking_dilation_frames)
return eye_tracking_table
lims_db = db_connection_creator(
fallback_credentials=LIMS_DB_CREDENTIAL_MAP)
sync_file = SyncFile.from_lims(db=lims_db,
ophys_experiment_id=ophys_experiment_id)
stimulus_timestamps = StimulusTimestamps.from_sync_file(
sync_file=sync_file)
behavior_session_id = BehaviorSessionId.from_lims(
db=lims_db, ophys_experiment_id=ophys_experiment_id)
is_multiplane_session = _is_multi_plane_session()
meta = BehaviorOphysMetadata.from_lims(
ophys_experiment_id=ophys_experiment_id,
lims_db=lims_db,
is_multiplane=is_multiplane_session)
monitor_delay = calculate_monitor_delay(
sync_file=sync_file, equipment=meta.behavior_metadata.equipment)
date_of_acquisition = DateOfAcquisitionOphys.from_lims(
ophys_experiment_id=ophys_experiment_id, lims_db=lims_db)
behavior_session = BehaviorSession.from_lims(
lims_db=lims_db,
behavior_session_id=behavior_session_id.value,
stimulus_timestamps=stimulus_timestamps,
monitor_delay=monitor_delay,
date_of_acquisition=date_of_acquisition)
if is_multiplane_session:
ophys_timestamps = OphysTimestampsMultiplane.from_sync_file(
sync_file=sync_file,
group_count=meta.ophys_metadata.imaging_plane_group_count,
plane_group=meta.ophys_metadata.imaging_plane_group)
else:
ophys_timestamps = OphysTimestamps.from_sync_file(
sync_file=sync_file)
projections = Projections.from_lims(
ophys_experiment_id=ophys_experiment_id, lims_db=lims_db)
cell_specimens = CellSpecimens.from_lims(
ophys_experiment_id=ophys_experiment_id,
lims_db=lims_db,
ophys_timestamps=ophys_timestamps,
segmentation_mask_image_spacing=projections.max_projection.spacing,
events_params=EventsParams(
filter_scale=events_filter_scale,
filter_n_time_steps=events_filter_n_time_steps),
exclude_invalid_rois=exclude_invalid_rois)
motion_correction = _get_motion_correction()
if skip_eye_tracking:
eye_tracking_table = None
eye_tracking_rig_geometry = None
else:
eye_tracking_table = _get_eye_tracking_table(sync_file=sync_file)
eye_tracking_rig_geometry = EyeTrackingRigGeometry.from_lims(
ophys_experiment_id=ophys_experiment_id, lims_db=lims_db)
return BehaviorOphysExperiment(
behavior_session=behavior_session,
cell_specimens=cell_specimens,
ophys_timestamps=ophys_timestamps,
metadata=meta,
projections=projections,
motion_correction=motion_correction,
eye_tracking_table=eye_tracking_table,
eye_tracking_rig_geometry=eye_tracking_rig_geometry,
date_of_acquisition=date_of_acquisition)