temp_arr_x.append(observers[j].x) temp_arr_y.append(observers[j].y) if (len(temp_arr_x) and len(temp_arr_y)): mean_x = mean(temp_arr_x) mean_y = mean(temp_arr_y) targets[i].update_target(x_limit, y_limit, mean_x, mean_y) for i in observers: i.update(x_limit, y_limit) for i in targets: i.update(x_limit, y_limit) step += 1 ans_dict = update_for_observers1(observers, targets) for i in ans_dict: for j in ans_dict[i]: total_count += 1 return total_count # ORIGINAL MAIN END sm = 0 for k in range(5): no_targets, no_observers, no_obstacles, targets, observers, obstacles = initialize_param( 15, 1) targets1 = deepcopy(targets) observers1 = deepcopy(observers) m = main_orig(no_targets, no_observers, targets1, observers1) print(m) sm += m print(sm / 5)
for j in ans_dict[i]: total_count += 1 return total_count # ORIGINAL MAIN END orig = 0 obs = 0 naive = 0 for i in no_observers_arr: for j in no_targets_arr: for no_obst in range(5): for k in range(10): no_targets, no_observers, no_obstacles, targets, observers, obstacles = initialize_param( j, i, no_obst) targets1 = deepcopy(targets) observers1 = deepcopy(observers) obstacles1 = deepcopy(obstacles) targets2 = deepcopy(targets) observers2 = deepcopy(observers) mo = main_obstacle_3(no_targets, no_observers, no_obstacles, targets, observers, obstacles) mn = main_naive(no_targets, no_observers, no_obstacles, targets1, observers1, obstacles1) m = main_orig(no_targets, no_observers, targets2, observers2) print(i, j, no_obst, m, mn, mo) orig += m naive += mn obs += mo print("FINAL", orig, naive, obs)