lb_filenames.py
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	#!/usr/bin/env python3
	# -- coding: utf-8 --
	"""
	Created on Tue Feb 11 19:02:06 2025

	@author: samarth
	"""

	import pandas as pd
	import os
	import sys
	from pathlib import Path
	from joblib import Parallel, delayed
	from matplotlib import pyplot as plt
	import numpy as np
	from sklearn.linear_model import LinearRegression
	from random import random, seed
	import subprocess

	#def voronoi(config_filename, result_filename):

	#command="../../postprocessing/bin/voronoi_volumes "+config_filename+" "+ result_filename
	#os.system(command)


	all_folders = []

	with open("list-samarth-configs.txt", "r") as file:
	for line in file:
	all_folders.append(line)

	foi = ['high_porosity_scaling', 'scaling_ns']
	config_filenames = []

	for name in foi:
	for folder in all_folders:

	if name in folder:
	config_filenames.append(folder.strip())

	result_filenames = []

	for filename in config_filenames:

	filename = filename.replace('config_files', 'results')
	idx = filename.rfind('/')
	filename = filename[:idx+1]+'lb_'+filename[idx+1:]
	result_filenames.append(filename.strip())


	with open('lb_filenames.txt', 'w') as f:
	for line in result_filenames:
	f.write(f"{line}\n")


	#os.system('cd ../../simulation_files; make simulation')
	#os.system('cd ../../postprocessing/; make all')

	#num_processors = 80
	#Parallel(n_jobs=num_processors)(delayed(voronoi)(config_filenames[i], result_filenames[i]) for i in range(size))

	#os.system('cd ../../simulation_files/; make clean')
	#os.system('cd ../../postprocessing/; make clean')