# load cell file
mm3.information('Loading cell data.')
if namespace.cellfile:
cell_file_path = namespace.cellfile
else:
mm3.warning('No cell file specified. Using complete_cells.pkl.')
cell_file_path = os.path.join(p['cell_dir'], 'complete_cells.pkl')
with open(cell_file_path, 'rb') as cell_file:
Cells = pickle.load(cell_file)
# load specs file
specs = mm3.load_specs()
# load time table. Puts in params dictionary
mm3.load_time_table()
# make list of FOVs to process (keys of channel_mask file)
fov_id_list = sorted([fov_id for fov_id in specs.keys()])
### foci analysis
for cell_id, cell in six.iteritems(Cells):
if cell.death is None:
cell.death = np.nan
mm3.information("Starting foci analysis.")
# create dictionary which organizes cells by fov and peak_id
Cells_by_peak = organize_cells_by_channel(Cells, specs)
# for each set of cells in one fov/peak, find the foci
for fov_id in fov_id_list:
user_spec_peaks = []
# set segmentation image name for saving and loading segmented images
if namespace.command == 'cells':
p['seg_img'] = 'seg_unet'
elif namespace.command == 'foci':
p['seg_img'] = 'foci_seg_unet'
else:
sys.exit(
"ERROR: your final argument to {} must be either 'cells' or 'foci'"
.format(sys.argv[0]))
# load specs file
if namespace.chtc:
specs = mm3.load_specs(fname=namespace.specfile)
mm3.load_time_table(fname=namespace.timefile)
else:
specs = mm3.load_specs()
mm3.load_time_table()
if namespace.command == 'cells':
if namespace.phase_file_name:
track_single_file(namespace.phase_file_name,
namespace.seg_file_name, p, namespace)
if not os.path.exists(p['cell_dir']):
os.makedirs(p['cell_dir'])
# make list of FOVs to process (keys of channel_mask file)
fov_id_list = sorted([fov_id for fov_id in specs.keys()])