def main():
number_of_data = 400
# Create las object and calculate corresponding values
filename = 'tiny'
partition = 70
las_obj = ProcessLas(filename, partition)
pfm = PCPDS_Manager()
dir_name = pfm.generate_collection(filename, partition)
print('Dir:' + str(dir_name))
las_obj.input_las(dir_name)
datafile = open("bdripson70partitions.txt", "a")
#import functions
n_results = 4 # menu.get_n_result_input()
for n in range(number_of_data):
# Generates random idx value for pcpds object
random_idx = str(las_obj.random_grid())
random_pcpds = None
first = True
# TODO: Validate the idx from random_grid is valid, else run random_grid again.
# Generate & validate a random_pcpds to use.
while (not pfm.get_path_manager().validate_file(
os.path.join(dir_name, random_idx + ".json")) or first):
random_idx = str(las_obj.random_grid())
print("Attempting RANDOM ID:", random_idx)
first = False
# Grabs the pcpds object that was generated
random_pcpds = pfm.get_pcpds(random_idx)
# Calculate bottleneck distance, print n_result matches
closest_matches = bottleneck_distances.search_distances(
n_results, random_pcpds.get_persistance_diagram(), dir_name)
datafile.write(str(random_idx))
datafile.write(":")
# Calculate bottleneck distance, print n_result matches
for idx in closest_matches:
datafile.write(str(idx))
print(idx)
datafile.write(",")
datafile.write('\n')
menu.progress(n, number_of_data,
("Processing random grid: " + str(random_idx) + "..."))
print("Job done.")
def generate_files():
print("What LAS file would you like to use?")
filename = menu.get_filename_input()
print("How manny partitions would you like?")
partition = menu.get_int_input()
las_obj = ProcessLas(filename, partition)
dir_name = file_manager.make_folder(filename)
pfm = PCPDS_Manager()
dir_name = pfm.generate_collection(filename, partition)
# TODO: Add multithreading option to input_las?
las_obj.input_las(dir_name)
print("File generation complete.")