def process_series(_experiment, _series_id, _overwrite=False):
_series_image_path = paths.serieses(_experiment, _series_id)
_image_properties = load.image_properties(_experiment, _series_id)
_series_image = tifffile.imread(_series_image_path)
_cells_coordinates = load.cell_coordinates_tracked_series_file_data(
_experiment, _series_id)
_series_image_by_time_frames = [
np.array([
_z[IMAGE_FIBER_CHANNEL_INDEX] for _z in _series_image[_time_frame]
]) for _time_frame in range(_series_image.shape[0])
]
_tuples = load.experiment_groups_as_tuples(_experiment)
_tuples = organize.by_experiment(_tuples)[_experiment]
_tuples = filtering.by_real_pairs(_tuples)
_tuples = filtering.by_real_fake_pairs(_tuples, _real_fake_pairs=False)
_tuples = filtering.by_series_id(_tuples, _series_id)
for _tuple in _tuples:
_experiment, _series_id, _group = _tuple
_cell_1_id, _cell_2_id = [
int(_value) for _value in _group.split('_')[1:]
]
process_group(
_experiment=_experiment,
_series_id=_series_id,
_cells_coordinates=_cells_coordinates,
_cell_1_id=_cell_1_id,
_cell_2_id=_cell_2_id,
_series_image_by_time_frames=_series_image_by_time_frames,
_resolutions=_image_properties['resolutions'],
_image_properties=_image_properties,
_overwrite=_overwrite)
def process_experiment(_experiment, _overwrite=False):
_arguments = []
for _tuple in load.experiment_groups_as_tuples(_experiment):
_experiment, _series_id, _group = _tuple
_arguments.append((_experiment, _series_id, _group, _overwrite))
_p = Pool(CPUS_TO_USE)
_p.starmap(process_group, _arguments)
_p.close()
def process_experiments(_experiments, _pairs=True):
_tuples = []
for _experiment in _experiments:
_tuples += load.experiment_groups_as_tuples(_experiment)
_p = Pool(CPUS_TO_USE)
if _pairs:
_answers = _p.starmap(process_group_pairs, _tuples)
else:
_answers = _p.starmap(process_group_single_cells, _tuples)
_p.close()
def main():
# single cells
print('Single cells')
_single_cells = load.experiments_groups_as_tuples(SINGLE_CELLS)
_single_cells = filtering.by_main_cell(_single_cells)
_single_cells = organize.by_single_cell_id(_single_cells)
print('\tTotal single cell experiments:', len(_single_cells))
# cell pairs
_cell_pairs = load.experiments_groups_as_tuples(CELL_PAIRS)
print('\nTotal cell pairs:', len(_cell_pairs))
for _distance_range in DISTANCE_RANGES:
print('Cell pairs distance range:', _distance_range)
# total
_distance_range_cell_pairs = filtering.by_pair_distance_range(_cell_pairs, _distance_range=_distance_range)
print('\tTotal cell pairs:', len(_distance_range_cell_pairs))
for _experiment in CELL_PAIRS:
print('\tExperiment:', _experiment)
_experiment_cell_pairs = load.experiment_groups_as_tuples(_experiment)
_distance_range_experiment_cell_pairs = \
filtering.by_pair_distance_range(_experiment_cell_pairs, _distance_range=_distance_range)
print('\t\tTotal cell pairs:', len(_distance_range_experiment_cell_pairs))
# real cell pairs
_real_cell_pairs = filtering.by_real_pairs(_distance_range_experiment_cell_pairs)
print('\t\tTotal real cell pairs:', len(_real_cell_pairs))
_real_cell_pairs_with_band = filtering.by_band(_real_cell_pairs)
print('\t\tTotal real cell pairs with band:', len(_real_cell_pairs_with_band))
# fake cell pairs
_fake_cell_pairs = filtering.by_real_pairs(_distance_range_experiment_cell_pairs, _real_pairs=False)
print('\t\tTotal fake cell pairs:', len(_fake_cell_pairs))
_fake_static_cell_pairs = filtering.by_fake_static_pairs(_fake_cell_pairs)
print('\t\tTotal fake static cell pairs:', len(_fake_static_cell_pairs))
_fake_following_cell_pairs = filtering.by_fake_static_pairs(_fake_cell_pairs, _fake_static_pairs=False)
print('\t\tTotal fake following cell pairs:', len(_fake_following_cell_pairs))
_fake_following_cell_pairs_with_band = filtering.by_band(_fake_following_cell_pairs)
print('\t\tTotal fake following cell pairs with band:', len(_fake_following_cell_pairs_with_band))
def main():
_experiment = 'LiveDead_201220'
_band = False
_tuples = load.experiment_groups_as_tuples(_experiment)
print('Total tuples:', len(_tuples))
for _tuple in _tuples:
print(_tuple)
_experiment, _series_id, _group = _tuple
_properties = load.group_properties(_experiment, _series_id, _group)
_properties['band'] = _band
_group_structured_path = paths.structured(_experiment, _series_id,
_group)
_properties_json_path = os.path.join(_group_structured_path,
'properties.json')
save_lib.to_json(_properties, _properties_json_path)
def main():
_experiment = 'DeadDead_201208'
_tuples = load.experiment_groups_as_tuples(_experiment)
_cell_ids = {}
for _tuple in _tuples:
_experiment, _series_id, _group = _tuple
_group_split = _group.split('_')
_cell_1_id = int(_group_split[1])
_cell_2_id = int(_group_split[2])
if _series_id not in _cell_ids:
_cell_ids[_series_id] = [_cell_1_id, _cell_2_id]
else:
if _cell_1_id not in _cell_ids[_series_id]:
_cell_ids[_series_id].append(_cell_1_id)
if _cell_2_id not in _cell_ids[_series_id]:
_cell_ids[_series_id].append(_cell_2_id)
for _series_id in _cell_ids.keys():
_properties = load.image_properties(_experiment, _series_id)
_properties['dead_cell_ids'] = _cell_ids[_series_id]
save.image_properties(_experiment, _series_id, _properties)
print(_experiment, _series_id, sep='\t')
def process_experiment(_experiment):
for _tuple in load.experiment_groups_as_tuples(_experiment):
_experiment, _series_id, _group = _tuple
process_group(_experiment, _series_id, _group)