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)