list_prop_attack = [50, 100, 250, 500, 750, 1000, 1500, 2000] dict_number_attacks = { 50: 1, 100: 3, 250: 8, 500: 16, 750: 25, 1000: 33, 1500: 50, 2000: 66 } header = [ "prop_attacks", "num_attacks", "Tmax", "learning_rate", "P", "N", "TP", "FP", "Alerts", "B[0,1,3]", "B[0,1,4]", "B[0,2,5]", "B[0,2,6]" ] list_results = [header] for prop_attack in list_prop_attack: file_logs = beginning_file_logs + str( prop_attack) + "/prop_attacks_" + str( prop_attack) + ".log.parsed.csv" file_aasg = beginning_file_aasg + str(prop_attack) + ".json" result = main(dict_var, file_logs, file_aasg) list_results.append([prop_attack, dict_number_attacks[prop_attack]] + result) write_csv_file("results_experiment_10_2.csv", list_results)
if __name__ == "__main__": beginning_file_logs = "../../datasets/eventgen/max_step_distance/max_step_distance_" beginning_file_aasg = "../aasg/eventgen_aasg/max_step_distance_with_IP_link/max_step_distance_1branch_" dict_var = {"p_t_max": 120, "p_learning_rate": 0.4} list_max_step_distance = [3, 10, 25, 50, 75, 100] dict_equivalence_time = {3: 10, 10: 16, 25: 39, 50: 65, 75: 89, 100: 115} header = [ "max_step_distance", "equivalence_in_seconds", "Tmax", "learning_rate", "P", "N", "TP", "FP", "Alerts", "B[0,1,3]", "B[0,1,4]", "B[0,2,5]", "B[0,2,6]" ] list_results = [header] for max_step_distance in list_max_step_distance: file_logs = beginning_file_logs + str( max_step_distance) + "/max_step_distance_" + str( max_step_distance) + ".log.parsed.csv" file_aasg = beginning_file_aasg + str(max_step_distance) + ".json" result = main(dict_var, file_logs, file_aasg) list_results.append( [max_step_distance, dict_equivalence_time[max_step_distance]] + result) write_csv_file("results_experiment_10_5_with_IP_link.csv", list_results)