organoid_tracker_create_nearest_neighbor_links.py

#!/usr/bin/env python3

"""Creates links between known nucleus positions at different time points. It always assigns nuclei to the nearsest
nucleus in the previous time point, which is a simplistic way of linking. However, if your time resolution is high
enough, it might actually work well."""

from organoid_tracker.config import ConfigFile, config_type_float, config_type_int
from organoid_tracker.imaging import io
from organoid_tracker.linking import nearest_neighbor_linker
from organoid_tracker.linking_analysis import cell_error_finder

# PARAMETERS
print("Hi! Configuration file is stored at " + ConfigFile.FILE_NAME)
config = ConfigFile("create_nearest_neighbor_links")
min_time_point = config.get_or_default("min_time_point", str(0), store_in_defaults=True, type=config_type_int)
max_time_point = config.get_or_default("max_time_point", str(9999), store_in_defaults=True, type=config_type_int)
max_distance_um = config.get_or_default("max_distance_um", "Inf", type=config_type_float,
                                        comment="Maximum distance that a nucleus can move between time points.")
positions_file = config.get_or_prompt("positions_file", "In which file are the positions stored? Please paste the path here.")
links_output_file = config.get_or_default("output_file", "Automatic nearest neighbor links.aut")
config.save_and_exit_if_changed()
# END OF PARAMETERS


print("Loading cell positions and shapes...", positions_file)
experiment = io.load_data_file(positions_file, min_time_point=min_time_point, max_time_point=max_time_point)
print("Performing nearest-neighbor linking...")
link_result = nearest_neighbor_linker.nearest_neighbor(experiment, tolerance=1, back=True, forward=False,
                                                       max_distance_um=max_distance_um)
experiment.links = link_result
print("Checking results for common errors...")
warning_count, no_links_count = cell_error_finder.find_errors_in_experiment(experiment)
print("Writing results to file...")
io.save_data_to_json(experiment, links_output_file)
print(f"Done! Found {warning_count} potential errors in the data. In addition, {no_links_count} positions didn't get"
      f" links.")