R 按潮汐状态对日期/时间进行分类

我想根据

df2

中给出的潮汐状态对

df1

日期/时间进行分类。df2的特点是它给出了潮汐最高峰的准确时间，如

高

或

低

我想更改它，以便它根据

高

和

低

潮汐两侧的3小时间隔对潮汐高度进行分类

 df1 <- data.frame(date_time = as.POSIXct(c("2015-09-06 09:00:00 BST", "2015-09-06 09:48:00 BST", "2015-09-06 10:37:00 BST", "2015-09-06 12:00:00 BST", "2015-09-06 12:48:00 BST","2015-09-06 13:35:00 BST")))

> df1
            date_time
1 2015-09-06 09:00:00
2 2015-09-06 09:48:00
3 2015-09-06 10:37:00
4 2015-09-06 12:00:00
5 2015-09-06 12:48:00
6 2015-09-06 13:35:00

df2 <- data.frame(Date_time = as.POSIXct(c("2015-09-06 07:09:00 GMT", "2015-09-06 13:18:00 GMT", "2015-09-06 19:52:00 GMT", "2015-09-07 02:01:00 GMT", "2015-09-07 08:28:00 GMT", "2015-09-07 14:43:00 GMT")), Tide_state = c("LOW",  "HIGH", "LOW",  "HIGH", "LOW",  "HIGH"))

df2
            Date_time Tide_state
1 2015-09-06 07:09:00        LOW
2 2015-09-06 13:18:00       HIGH
3 2015-09-06 19:52:00        LOW
4 2015-09-07 02:01:00       HIGH
5 2015-09-07 08:28:00        LOW
6 2015-09-07 14:43:00       HIGH

结果:

df1
          date_time tides
1 2015-09-06 09:00:00   LOW
2 2015-09-06 09:48:00   LOW
3 2015-09-06 10:37:00   LOW
4 2015-09-06 12:00:00   LOW
5 2015-09-06 12:48:00   LOW
6 2015-09-06 13:35:00  HIGH

预期结果：（根据涨潮和低潮两侧各3小时的潮汐

df1
 date_time tides
    1 2015-09-06 09:00:00   LOW
    2 2015-09-06 09:48:00   LOW
    3 2015-09-06 10:37:00   HIGH
    4 2015-09-06 12:00:00   HIGH
    5 2015-09-06 12:48:00   HIGH
    6 2015-09-06 13:35:00   HIGH

---

任何帮助都将不胜感激

也许

df2$Tide_state[pmax（findInterval（df1$date_time-3600*3，df2$date_time），findInterval（df1$date_time+3600*3，df2$date_time））

谢谢你的支持-这很有效！但是-当应用到我的主数据时，我发现

错误$
df1
 date_time tides
    1 2015-09-06 09:00:00   LOW
    2 2015-09-06 09:48:00   LOW
    3 2015-09-06 10:37:00   HIGH
    4 2015-09-06 12:00:00   HIGH
    5 2015-09-06 12:48:00   HIGH
    6 2015-09-06 13:35:00   HIGH