def test_nwb_end_to_end(tmpdir_factory):
oeid = 789359614
nwb_filepath = os.path.join(str(tmpdir_factory.mktemp('test_nwb_end_to_end')), 'nwbfile.nwb')
d1 = BehaviorOphysSession.from_lims(oeid)
BehaviorOphysNwbApi(nwb_filepath).save(d1)
d2 = BehaviorOphysSession(api=BehaviorOphysNwbApi(nwb_filepath))
equals(d1, d2, reraise=True)
def test_get_corrected_fluorescence_traces(nwbfile, roundtrip,
filter_invalid_rois, valid_roi_ids,
roundtripper, dff_traces,
corrected_fluorescence_traces,
cell_specimen_table, metadata,
ophys_timestamps):
nwb.add_metadata(nwbfile, metadata)
nwb.add_cell_specimen_table(nwbfile, cell_specimen_table)
nwb.add_dff_traces(nwbfile, dff_traces, ophys_timestamps)
nwb.add_corrected_fluorescence_traces(nwbfile,
corrected_fluorescence_traces)
if roundtrip:
obt = roundtripper(nwbfile,
BehaviorOphysNwbApi,
filter_invalid_rois=filter_invalid_rois)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(
nwbfile, filter_invalid_rois=filter_invalid_rois)
if filter_invalid_rois:
corrected_fluorescence_traces = corrected_fluorescence_traces[
corrected_fluorescence_traces["cell_roi_id"].isin(valid_roi_ids)]
pd.testing.assert_frame_equal(corrected_fluorescence_traces,
obt.get_corrected_fluorescence_traces(),
check_dtype=False)
def test_add_stimulus_timestamps(nwbfile, stimulus_timestamps, roundtrip, roundtripper):
nwb.add_stimulus_timestamps(nwbfile, stimulus_timestamps)
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)
np.testing.assert_array_almost_equal(stimulus_timestamps, obt.get_stimulus_timestamps())
def test_add_average_image(nwbfile, roundtrip, roundtripper, average_image, image_api):
nwb.add_average_image(nwbfile, average_image)
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)
assert image_api.deserialize(average_image) == image_api.deserialize(obt.get_average_projection())
def test_segmentation_mask_image(nwbfile, roundtrip, roundtripper, segmentation_mask_image, image_api):
nwb.add_segmentation_mask_image(nwbfile, segmentation_mask_image)
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)
assert image_api.deserialize(segmentation_mask_image) == image_api.deserialize(obt.get_segmentation_mask_image())
def test_add_max_projection(nwbfile, roundtrip, roundtripper, max_projection, image_api):
nwb.add_max_projection(nwbfile, max_projection)
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)
assert image_api.deserialize(max_projection) == image_api.deserialize(obt.get_max_projection())
def test_add_trials(nwbfile, roundtrip, roundtripper, trials):
nwb.add_trials(nwbfile, trials, {})
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)
pd.testing.assert_frame_equal(trials, obt.get_trials(), check_dtype=False)
def test_add_running_data_df_to_nwbfile(nwbfile, running_data_df, roundtrip, roundtripper):
unit_dict = {'v_sig': 'V', 'v_in': 'V', 'speed': 'cm/s', 'timestamps': 's', 'dx': 'cm'}
nwbfile = nwb.add_running_data_df_to_nwbfile(nwbfile, running_data_df, unit_dict)
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)
pd.testing.assert_frame_equal(running_data_df, obt.get_running_data_df())
def test_add_stimulus_templates(nwbfile, stimulus_templates, roundtrip, roundtripper):
for key, val in stimulus_templates.items():
nwb.add_stimulus_template(nwbfile, val, key)
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)
stimulus_templates_obt = obt.get_stimulus_templates()
for key in set(stimulus_templates.keys()).union(set(stimulus_templates_obt.keys())):
np.testing.assert_array_almost_equal(stimulus_templates[key], stimulus_templates_obt[key])
def test_add_running_speed_to_nwbfile(nwbfile, running_speed, roundtrip, roundtripper):
nwbfile = nwb.add_running_speed_to_nwbfile(nwbfile, running_speed)
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)
running_speed_obt = obt.get_running_speed()
assert np.allclose(running_speed.timestamps, running_speed_obt.timestamps)
assert np.allclose(running_speed.values, running_speed_obt.values)
def test_get_motion_correction(nwbfile, roundtrip, roundtripper, motion_correction, ophys_timestamps, metadata, cell_specimen_table, dff_traces):
nwb.add_metadata(nwbfile, metadata)
nwb.add_cell_specimen_table(nwbfile, cell_specimen_table)
nwb.add_dff_traces(nwbfile, dff_traces, ophys_timestamps)
nwb.add_motion_correction(nwbfile, motion_correction)
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)
pd.testing.assert_frame_equal(motion_correction, obt.get_motion_correction(), check_dtype=False)
def test_add_metadata(nwbfile, roundtrip, roundtripper, metadata):
nwb.add_metadata(nwbfile, metadata)
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)
metadata_obt = obt.get_metadata()
assert len(metadata_obt) == len(metadata)
for key, val in metadata.items():
assert val == metadata_obt[key]
def test_get_cell_specimen_table(nwbfile, roundtrip, filter_invalid_rois, valid_roi_ids, roundtripper, cell_specimen_table, metadata, ophys_timestamps):
nwb.add_metadata(nwbfile, metadata)
nwb.add_cell_specimen_table(nwbfile, cell_specimen_table)
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi, filter_invalid_rois=filter_invalid_rois)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile, filter_invalid_rois=filter_invalid_rois)
if filter_invalid_rois:
cell_specimen_table = cell_specimen_table[cell_specimen_table["cell_roi_id"].isin(valid_roi_ids)]
pd.testing.assert_frame_equal(cell_specimen_table, obt.get_cell_specimen_table(), check_dtype=False)
def write_behavior_ophys_nwb(session_data, nwb_filepath):
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:
session = BehaviorOphysSession(api=BehaviorOphysJsonApi(session_data))
BehaviorOphysNwbApi(nwb_filepath_inprogress).save(session)
assert equals(
session,
BehaviorOphysSession(
api=BehaviorOphysNwbApi(nwb_filepath_inprogress)))
os.rename(nwb_filepath_inprogress, nwb_filepath)
return {'output_path': nwb_filepath}
except Exception as e:
os.rename(nwb_filepath_inprogress, nwb_filepath_error)
raise e
def test_add_stimulus_presentations(nwbfile, stimulus_presentations_behavior, stimulus_timestamps, roundtrip, roundtripper, stimulus_templates):
nwb.add_stimulus_timestamps(nwbfile, stimulus_timestamps)
nwb.add_stimulus_presentations(nwbfile, stimulus_presentations_behavior)
for key, val in stimulus_templates.items():
nwb.add_stimulus_template(nwbfile, val, key)
# Add index for this template to NWB in-memory object:
nwb_template = nwbfile.stimulus_template[key]
curr_stimulus_index = stimulus_presentations_behavior[stimulus_presentations_behavior['image_set'] == nwb_template.name]
nwb.add_stimulus_index(nwbfile, curr_stimulus_index, nwb_template)
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)
pd.testing.assert_frame_equal(stimulus_presentations_behavior, obt.get_stimulus_presentations(), check_dtype=False)
def test_add_task_parameters(nwbfile, roundtrip, roundtripper, task_parameters):
nwb.add_task_parameters(nwbfile, task_parameters)
if roundtrip:
obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
else:
obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)
task_parameters_obt = obt.get_task_parameters()
assert len(task_parameters_obt) == len(task_parameters)
for key, val in task_parameters.items():
if key == 'omitted_flash_fraction':
if math.isnan(val):
assert math.isnan(task_parameters_obt[key])
if math.isnan(task_parameters_obt[key]):
assert math.isnan(val)
else:
assert val == task_parameters_obt[key]
experiment_id = sys.argv[1]
# Define the cache
cache_json = {
'manifest_path':
'/allen/programs/braintv/workgroups/nc-ophys/visual_behavior/SWDB_2019/visual_behavior_data_manifest.csv',
'nwb_base_dir':
'/allen/programs/braintv/workgroups/nc-ophys/visual_behavior/SWDB_2019/nwb_files',
'analysis_files_base_dir':
'/allen/programs/braintv/workgroups/nc-ophys/visual_behavior/SWDB_2019/extra_files'
}
# load the session
cache = bpc.BehaviorProjectCache(cache_json)
nwb_path = cache.get_nwb_filepath(experiment_id)
api = BehaviorOphysNwbApi(nwb_path, filter_invalid_rois=True)
session = BehaviorOphysSession(api)
# Where to save the results
output_path = '/allen/programs/braintv/workgroups/nc-ophys/visual_behavior/SWDB_2019/flash_response_500msec_response'
# Define parameters for dff_trace, and response_window
response_analysis_params = {
'window_around_timepoint_seconds': [-.5, .75], # -500ms, 750ms
'response_window_duration_seconds': 0.5,
'baseline_window_duration_seconds': 0.5
}
# compute the base flash_response_df
flash_response_df = get_flash_response_df(session,
response_analysis_params)
def from_nwb_path(cls, nwb_path: str,
**api_kwargs: Any) -> "BehaviorOphysSession":
api_kwargs["filter_invalid_rois"] = api_kwargs.get(
"filter_invalid_rois", True)
return cls(
api=BehaviorOphysNwbApi.from_path(path=nwb_path, **api_kwargs))
import os
from allensdk.brain_observatory.behavior.behavior_ophys_api.behavior_ophys_nwb_api import BehaviorOphysNwbApi
from allensdk.brain_observatory.behavior.behavior_ophys_session import BehaviorOphysSession
basedir = '/allen/aibs/technology/nicholasc/behavior_ophys'
rel_filepath_list = [
'behavior_ophys_session_805784331.nwb',
'behavior_ophys_session_789359614.nwb',
'behavior_ophys_session_803736273.nwb',
'behavior_ophys_session_808621958.nwb',
'behavior_ophys_session_795948257.nwb'
]
for rel_filepath in rel_filepath_list:
full_filepath = os.path.join(basedir, rel_filepath)
session = BehaviorOphysSession(api=BehaviorOphysNwbApi(full_filepath))
print(session.metadata['ophys_experiment_id'])
