def find_dobre_kurwa_param(self, I, D):
        #najpierw dla proporcjonalnego
        min_measured_error = 100000
        optimal_Kp = 0
        for Kp in self.frange(0.5, 2.2, 0.05):
            self.clear_data()
            self.test_pid(Kp, I, D, 30, PID.PID.p_mode)
            sum_err = np.sum(np.abs(self.error_list))
            print(str(sum_err) + "   " + str(Kp))
            if min_measured_error > sum_err:
                optimal_Kp = Kp
                min_measured_error = sum_err
        self.clear_data()
        return optimal_Kp