main.py

import sys, os
import time
import csv
import argparse

from ga import GA

def parse_arguments():
	parser = argparse.ArgumentParser()
	parser.add_argument("-p", type=int, default=50, help="Set an even number population size (default=50)")
	parser.add_argument("-f", type=int, default=1e+4, help="Set fitness evaluation limit (default=10000)")
	parser.add_argument("-r", type=float, default=0.3, help="Set mutation rate (0.0 ~ 1.0, default=0.3)")
	parser.add_argument("-k", type=int, default=3, help="Set mutation limit per child (default=3)")
	parser.add_argument("-c", type=float, default=0.8, help="Set crossover_rate (0.0 ~ 1.0, default=0.8)")
	parser.add_argument("-t", type=int, default=3, help="Set tournament selection k value(default=3)")
	parser.add_argument("-l", action="store_true", help="Use linear ranking (default=tournament selection)")
	parser.add_argument("-e", action="store_true", help="Use elitism (default=generational_replacement)")
	parser.add_argument("-d", type=str, required=True, help="Specify path to testfile")
	parser.add_argument("-s", action="store_true", help="Show progress")

	return parser.parse_args()

if __name__ == '__main__':
	args = parse_arguments()

	testfile = args.d

	testdata = []
	with open(testfile,"r") as f:
		reader = csv.reader(f)
		line_num = -1
		for row in reader:
			if line_num < 0:
				line_num += 1
				continue
			line_num += 1
			testdata.append(row)

	fit_vals = []
	fit_val_1=[5.2, 1.8, 4.8, 8.8, 8.0]
	fit_val_2=[2.1, 9.5, 3.5, 6.1, 7.8]
	fit_val_3=[7.5, 9.1, 4.4, 9.6,-2.1]

	fit_vals.append(fit_val_1)
	fit_vals.append(fit_val_2)
	fit_vals.append(fit_val_3)

	results = []
	headers = ["Filepath", "Target XPath", "Robust XPath 1", "Robust XPath 2", "Robust XPath 3"]
	results.append(headers)

	for row in testdata:
		result = []

		file = row[0]
		xpath = row[1]
		result.append(file)
		result.append(xpath)

		for fit_val in fit_vals:
			ga = GA(
				pop_size=args.p,
				eval_lim=args.f,
				mut_rate=args.r,
				mut_k=args.k,
				crossover_rate=args.c,
				tournament_k=args.t,
				use_elitism=args.e,
				use_lin_ranking=args.l,
				dom_filepath=file,
				xpath=xpath,
				fitness_values=fit_val,
				verbose=args.s
				)
			ga.select_parents()
			ga.evolve()
			result.append(ga.optimum.xpath)
		results.append(result)

	with open("results.csv", "w", newline='') as csvfile:
		writer = csv.writer(csvfile)
		for row in results:
			writer.writerow(row)