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)