def METHOD_NAME(self):
    dp_random.seed(0)
    data0 = DeepmdDataSystem(["system_0", "system_1"], 5, 10, 1.0)
    data0.add("energy", 1, must=True)
    dp_random.seed(0)
    data1 = DeepmdDataSystem(["system_0", "system_1"], 5, 10, 1.0)
    data1.add("energy", 1, must=True)
    dp_random.seed(0)
    data2 = DeepmdDataSystem(["system_0", "system_1"], 5, 10, 1.0)
    data2.add("energy", 1, must=True)
    dp_random.seed(0)
    all_stat_0 = make_stat_input(data0, 10, merge_sys=False)
    dp_random.seed(0)
    all_stat_1 = make_stat_input(data1, 10, merge_sys=True)
    all_stat_2 = merge_sys_stat(all_stat_0)
    dp_random.seed(0)
    all_stat_3 = _make_all_stat_ref(data2, 10)
    ####################################
    # only check if the energy is concatenated correctly
    ####################################
    dd = "energy"
    # if 'find_' in dd: continue
    # if 'natoms_vec' in dd: continue
    # if 'default_mesh' in dd: continue
    # print(all_stat_2[dd])
    # print(dd, all_stat_1[dd])
    d1 = np.array(all_stat_1[dd])
    d2 = np.array(all_stat_2[dd])
    d3 = np.array(all_stat_3[dd])
    # print(dd)
    # print(d1.shape)
    # print(d2.shape)
    # self.assertEqual(all_stat_2[dd], all_stat_1[dd])
    self._comp_data(d1, d2)
    self._comp_data(d1, d3)