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In the field of hydrology, it is common to work with rainfall data from a tipping bucket. It registers every time the bucket is filled with, for instance, 0.2 mm or 0.5 mm of water.
I would like to import this kind of data to R, but could not find a smooth way to do it. I got very good help from answers to the question Creating regular 15-minute time-series from irregular time-series, but I still miss one part of how we usually process the data: smoothing during low-intensity rainfall.
This is a small part of my data from a tipping bucket in Malmö, Sweden. 0.2 is registered for every 0.2 mm of rainfall:
Rainfall Depth[millimeter]:Instantaneous Undefined[undefined]:Instantaneous
Time M05_Bulltofta_vippning Flag
2014-08-31 04:09:22 0.2 0
2014-08-31 04:12:14 0.2 0
2014-08-31 04:17:49 0.2 0
2014-08-31 04:20:00 0.2 0
2014-08-31 04:22:10 0.2 0
2014-08-31 04:23:31 0.2 0
2014-08-31 04:24:49 0.2 0
2014-08-31 04:25:49 0.2 0
2014-08-31 04:28:14 0.2 0
2014-08-31 04:36:22 0.2 0
2014-08-31 04:41:06 0.2 0
2014-08-31 04:42:58 0.2 0
2014-08-31 04:43:33 0.2 0
2014-08-31 04:45:03 0.2 0
2014-08-31 04:47:47 0.2 0
2014-08-31 04:49:49 0.2 0
2014-08-31 04:51:35 0.2 0
2014-08-31 04:52:58 0.2 0
2014-08-31 04:54:32 0.2 0
2014-08-31 04:55:54 0.2 0
2014-08-31 04:58:36 0.2 0
2014-08-31 05:02:17 0.2 0
2014-08-31 05:06:21 0.2 0
2014-08-31 05:09:56 0.2 0
2014-08-31 05:12:57 0.2 0
2014-08-31 05:14:38 0.2 0
2014-08-31 05:16:13 0.2 0
2014-08-31 05:17:42 0.2 0
2014-08-31 05:19:05 0.2 0
2014-08-31 05:20:38 0.2 0
2014-08-31 05:22:44 0.2 0
2014-08-31 05:24:11 0.2 0
2014-08-31 05:25:41 0.2 0
2014-08-31 05:26:48 0.2 0
2014-08-31 05:27:24 0.2 0
2014-08-31 05:27:59 0.2 0
2014-08-31 05:28:59 0.2 0
2014-08-31 05:29:40 0.2 0
2014-08-31 05:30:09 0.2 0
2014-08-31 05:30:33 0.2 0
2014-08-31 05:31:03 0.2 0
2014-08-31 05:31:38 0.2 0
2014-08-31 05:32:30 0.2 0
2014-08-31 05:33:46 0.2 0
2014-08-31 05:35:10 0.2 0
2014-08-31 05:36:25 0.2 0
2014-08-31 05:38:20 0.2 0
2014-08-31 05:40:38 0.2 0
2014-08-31 05:44:23 0.2 0
2014-08-31 05:44:53 0.2 0
2014-08-31 05:45:19 0.2 0
2014-08-31 05:45:55 0.2 0
2014-08-31 05:46:50 0.2 0
2014-08-31 05:47:30 0.2 0
2014-08-31 05:48:09 0.2 0
2014-08-31 05:48:26 0.2 0
2014-08-31 05:48:38 0.2 0
2014-08-31 05:48:47 0.2 0
2014-08-31 05:48:59 0.2 0
2014-08-31 05:49:15 0.2 0
2014-08-31 05:49:34 0.2 0
2014-08-31 05:50:00 0.2 0
2014-08-31 05:50:31 0.2 0
2014-08-31 05:50:51 0.2 0
2014-08-31 05:51:20 0.2 0
2014-08-31 05:52:00 0.2 0
2014-08-31 05:52:39 0.2 0
2014-08-31 05:53:01 0.2 0
2014-08-31 05:53:29 0.2 0
2014-08-31 05:53:54 0.2 0
2014-08-31 05:54:21 0.2 0
2014-08-31 05:54:43 0.2 0
2014-08-31 05:55:04 0.2 0
2014-08-31 05:55:28 0.2 0
2014-08-31 05:55:49 0.2 0
2014-08-31 05:56:05 0.2 0
2014-08-31 05:56:27 0.2 0
2014-08-31 05:56:52 0.2 0
2014-08-31 05:57:24 0.2 0
2014-08-31 05:57:56 0.2 0
2014-08-31 05:58:34 0.2 0
2014-08-31 05:59:08 0.2 0
2014-08-31 05:59:43 0.2 0
2014-08-31 06:00:11 0.2 0
2014-08-31 06:00:36 0.2 0
2014-08-31 06:00:54 0.2 0
2014-08-31 06:01:14 0.2 0
2014-08-31 06:01:28 0.2 0
2014-08-31 06:01:47 0.2 0
2014-08-31 06:02:03 0.2 0
2014-08-31 06:02:22 0.2 0
2014-08-31 06:02:43 0.2 0
2014-08-31 06:03:09 0.2 0
2014-08-31 06:03:40 0.2 0
2014-08-31 06:04:32 0.2 0
2014-08-31 06:05:26 0.2 0
2014-08-31 06:06:18 0.2 0
2014-08-31 06:07:13 0.2 0
2014-08-31 06:08:23 0.2 0
2014-08-31 06:09:24 0.2 0
2014-08-31 06:10:13 0.2 0
2014-08-31 06:10:46 0.2 0
2014-08-31 06:11:24 0.2 0
2014-08-31 06:11:47 0.2 0
2014-08-31 06:12:08 0.2 0
2014-08-31 06:12:23 0.2 0
2014-08-31 06:12:40 0.2 0
2014-08-31 06:12:55 0.2 0
2014-08-31 06:13:14 0.2 0
2014-08-31 06:13:30 0.2 0
2014-08-31 06:13:49 0.2 0
2014-08-31 06:14:08 0.2 0
2014-08-31 06:14:31 0.2 0
2014-08-31 06:14:51 0.2 0
2014-08-31 06:15:12 0.2 0
2014-08-31 06:15:33 0.2 0
2014-08-31 06:15:50 0.2 0
2014-08-31 06:16:07 0.2 0
2014-08-31 06:16:27 0.2 0
2014-08-31 06:16:43 0.2 0
2014-08-31 06:17:01 0.2 0
2014-08-31 06:17:19 0.2 0
2014-08-31 06:17:36 0.2 0
2014-08-31 06:17:51 0.2 0
2014-08-31 06:18:08 0.2 0
2014-08-31 06:18:25 0.2 0
2014-08-31 06:18:46 0.2 0
2014-08-31 06:19:05 0.2 0
2014-08-31 06:19:25 0.2 0
2014-08-31 06:19:42 0.2 0
2014-08-31 06:20:00 0.2 0
2014-08-31 06:20:12 0.2 0
2014-08-31 06:20:24 0.2 0
2014-08-31 06:20:36 0.2 0
2014-08-31 06:20:56 0.2 0
2014-08-31 06:21:14 0.2 0
2014-08-31 06:21:27 0.2 0
2014-08-31 06:21:37 0.2 0
2014-08-31 06:21:48 0.2 0
2014-08-31 06:22:06 0.2 0
2014-08-31 06:22:16 0.2 0
2014-08-31 06:22:29 0.2 0
2014-08-31 06:22:47 0.2 0
2014-08-31 06:23:09 0.2 0
2014-08-31 06:23:30 0.2 0
2014-08-31 06:23:57 0.2 0
2014-08-31 06:24:21 0.2 0
2014-08-31 06:24:39 0.2 0
2014-08-31 06:24:51 0.2 0
2014-08-31 06:25:03 0.2 0
2014-08-31 06:25:16 0.2 0
2014-08-31 06:25:29 0.2 0
2014-08-31 06:25:39 0.2 0
2014-08-31 06:25:49 0.2 0
2014-08-31 06:25:59 0.2 0
2014-08-31 06:26:13 0.2 0
2014-08-31 06:26:29 0.2 0
2014-08-31 06:26:50 0.2 0
2014-08-31 06:27:13 0.2 0
2014-08-31 06:27:49 0.2 0
2014-08-31 06:28:12 0.2 0
2014-08-31 06:28:42 0.2 0
2014-08-31 06:29:11 0.2 0
2014-08-31 06:29:44 0.2 0
2014-08-31 06:30:14 0.2 0
2014-08-31 06:30:35 0.2 0
2014-08-31 06:30:49 0.2 0
2014-08-31 06:31:06 0.2 0
2014-08-31 06:31:25 0.2 0
2014-08-31 06:31:56 0.2 0
2014-08-31 06:32:45 0.2 0
2014-08-31 06:34:09 0.2 0
2014-08-31 06:34:53 0.2 0
2014-08-31 06:35:27 0.2 0
2014-08-31 06:36:05 0.2 0
2014-08-31 06:36:25 0.2 0
2014-08-31 06:36:39 0.2 0
2014-08-31 06:36:56 0.2 0
2014-08-31 06:37:11 0.2 0
2014-08-31 06:37:24 0.2 0
2014-08-31 06:37:38 0.2 0
2014-08-31 06:37:50 0.2 0
2014-08-31 06:38:00 0.2 0
2014-08-31 06:38:12 0.2 0
2014-08-31 06:38:22 0.2 0
2014-08-31 06:38:32 0.2 0
2014-08-31 06:38:42 0.2 0
2014-08-31 06:38:52 0.2 0
2014-08-31 06:39:02 0.2 0
2014-08-31 06:39:16 0.2 0
2014-08-31 06:39:29 0.2 0
2014-08-31 06:39:42 0.2 0
2014-08-31 06:39:58 0.2 0
2014-08-31 06:40:20 0.2 0
2014-08-31 06:40:48 0.2 0
2014-08-31 06:41:23 0.2 0
2014-08-31 06:42:03 0.2 0
2014-08-31 06:42:42 0.2 0
2014-08-31 06:43:21 0.2 0
2014-08-31 06:43:46 0.2 0
2014-08-31 06:44:14 0.2 0
2014-08-31 06:44:41 0.2 0
2014-08-31 06:45:11 0.2 0
2014-08-31 06:46:01 0.2 0
2014-08-31 06:46:50 0.2 0
2014-08-31 06:47:32 0.2 0
2014-08-31 06:47:56 0.2 0
2014-08-31 06:48:21 0.2 0
2014-08-31 06:48:36 0.2 0
2014-08-31 06:48:51 0.2 0
2014-08-31 06:49:02 0.2 0
2014-08-31 06:49:17 0.2 0
2014-08-31 06:49:37 0.2 0
2014-08-31 06:50:09 0.2 0
2014-08-31 06:50:41 0.2 0
2014-08-31 06:51:24 0.2 0
2014-08-31 06:52:10 0.2 0
2014-08-31 06:52:55 0.2 0
2014-08-31 06:53:34 0.2 0
2014-08-31 06:54:10 0.2 0
2014-08-31 06:54:43 0.2 0
2014-08-31 06:55:34 0.2 0
2014-08-31 06:57:01 0.2 0
2014-08-31 06:58:27 0.2 0
2014-08-31 06:59:10 0.2 0
2014-08-31 07:00:17 0.2 0
2014-08-31 07:01:25 0.2 0
2014-08-31 07:02:19 0.2 0
2014-08-31 07:03:06 0.2 0
2014-08-31 07:04:03 0.2 0
2014-08-31 07:04:48 0.2 0
2014-08-31 07:05:31 0.2 0
2014-08-31 07:06:14 0.2 0
2014-08-31 07:06:58 0.2 0
2014-08-31 07:07:33 0.2 0
2014-08-31 07:08:19 0.2 0
2014-08-31 07:08:58 0.2 0
2014-08-31 07:09:50 0.2 0
2014-08-31 07:10:38 0.2 0
2014-08-31 07:11:34 0.2 0
2014-08-31 07:12:12 0.2 0
2014-08-31 07:13:09 0.2 0
2014-08-31 07:14:16 0.2 0
2014-08-31 07:15:07 0.2 0
2014-08-31 07:15:45 0.2 0
2014-08-31 07:16:21 0.2 0
2014-08-31 07:16:53 0.2 0
2014-08-31 07:17:30 0.2 0
2014-08-31 07:18:33 0.2 0
2014-08-31 07:19:24 0.2 0
2014-08-31 07:20:07 0.2 0
2014-08-31 07:21:06 0.2 0
2014-08-31 07:21:53 0.2 0
2014-08-31 07:22:46 0.2 0
2014-08-31 07:23:45 0.2 0
2014-08-31 07:24:59 0.2 0
2014-08-31 07:25:50 0.2 0
2014-08-31 07:26:41 0.2 0
2014-08-31 07:27:18 0.2 0
2014-08-31 07:27:59 0.2 0
2014-08-31 07:28:29 0.2 0
2014-08-31 07:29:01 0.2 0
2014-08-31 07:29:54 0.2 0
2014-08-31 07:30:51 0.2 0
2014-08-31 07:31:53 0.2 0
2014-08-31 07:32:25 0.2 0
2014-08-31 07:32:53 0.2 0
2014-08-31 07:33:21 0.2 0
2014-08-31 07:33:47 0.2 0
2014-08-31 07:34:08 0.2 0
2014-08-31 07:34:22 0.2 0
2014-08-31 07:34:42 0.2 0
2014-08-31 07:35:07 0.2 0
2014-08-31 07:35:30 0.2 0
2014-08-31 07:35:52 0.2 0
2014-08-31 07:36:18 0.2 0
2014-08-31 07:36:45 0.2 0
2014-08-31 07:37:13 0.2 0
2014-08-31 07:37:32 0.2 0
2014-08-31 07:37:49 0.2 0
2014-08-31 07:38:07 0.2 0
2014-08-31 07:38:28 0.2 0
2014-08-31 07:38:49 0.2 0
2014-08-31 07:39:04 0.2 0
2014-08-31 07:39:14 0.2 0
2014-08-31 07:39:25 0.2 0
2014-08-31 07:39:35 0.2 0
2014-08-31 07:39:45 0.2 0
2014-08-31 07:40:42 0.2 0
2014-08-31 07:40:57 0.2 0
2014-08-31 07:41:36 0.2 0
2014-08-31 07:42:23 0.2 0
2014-08-31 07:42:42 0.2 0
2014-08-31 07:43:16 0.2 0
2014-08-31 07:44:21 0.2 0
2014-08-31 07:45:19 0.2 0
2014-08-31 07:46:02 0.2 0
2014-08-31 07:47:12 0.2 0
2014-08-31 07:47:39 0.2 0
2014-08-31 07:47:58 0.2 0
2014-08-31 07:48:14 0.2 0
2014-08-31 07:48:25 0.2 0
2014-08-31 07:48:36 0.2 0
2014-08-31 07:48:48 0.2 0
2014-08-31 07:49:04 0.2 0
2014-08-31 07:49:18 0.2 0
2014-08-31 07:49:31 0.2 0
2014-08-31 07:49:52 0.2 0
2014-08-31 07:50:28 0.2 0
2014-08-31 07:51:22 0.2 0
2014-08-31 07:52:20 0.2 0
2014-08-31 07:53:13 0.2 0
2014-08-31 07:54:09 0.2 0
2014-08-31 07:55:22 0.2 0
2014-08-31 07:56:25 0.2 0
2014-08-31 07:57:17 0.2 0
2014-08-31 07:57:46 0.2 0
2014-08-31 07:58:06 0.2 0
2014-08-31 07:58:26 0.2 0
2014-08-31 07:58:43 0.2 0
2014-08-31 07:59:02 0.2 0
2014-08-31 07:59:20 0.2 0
2014-08-31 07:59:32 0.2 0
2014-08-31 07:59:48 0.2 0
2014-08-31 08:00:06 0.2 0
2014-08-31 08:00:29 0.2 0
2014-08-31 08:00:50 0.2 0
2014-08-31 08:01:14 0.2 0
2014-08-31 08:01:36 0.2 0
2014-08-31 08:02:01 0.2 0
2014-08-31 08:02:24 0.2 0
2014-08-31 08:02:41 0.2 0
2014-08-31 08:02:53 0.2 0
2014-08-31 08:03:08 0.2 0
2014-08-31 08:03:23 0.2 0
2014-08-31 08:03:37 0.2 0
2014-08-31 08:03:51 0.2 0
2014-08-31 08:04:05 0.2 0
2014-08-31 08:04:22 0.2 0
2014-08-31 08:04:40 0.2 0
2014-08-31 08:05:00 0.2 0
2014-08-31 08:05:26 0.2 0
2014-08-31 08:05:54 0.2 0
2014-08-31 08:06:23 0.2 0
2014-08-31 08:06:49 0.2 0
2014-08-31 08:07:20 0.2 0
2014-08-31 08:07:53 0.2 0
2014-08-31 08:08:32 0.2 0
2014-08-31 08:09:00 0.2 0
2014-08-31 08:09:25 0.2 0
2014-08-31 08:09:46 0.2 0
2014-08-31 08:10:12 0.2 0
2014-08-31 08:10:48 0.2 0
2014-08-31 08:11:27 0.2 0
2014-08-31 08:12:09 0.2 0
2014-08-31 08:13:06 0.2 0
2014-08-31 08:14:07 0.2 0
2014-08-31 08:14:33 0.2 0
2014-08-31 08:15:01 0.2 0
2014-08-31 08:15:23 0.2 0
2014-08-31 08:15:55 0.2 0
2014-08-31 08:16:22 0.2 0
2014-08-31 08:16:49 0.2 0
2014-08-31 08:17:17 0.2 0
2014-08-31 08:17:33 0.2 0
2014-08-31 08:17:48 0.2 0
2014-08-31 08:17:59 0.2 0
2014-08-31 08:18:12 0.2 0
2014-08-31 08:18:23 0.2 0
2014-08-31 08:18:35 0.2 0
2014-08-31 08:18:46 0.2 0
2014-08-31 08:18:59 0.2 0
2014-08-31 08:19:12 0.2 0
2014-08-31 08:19:26 0.2 0
2014-08-31 08:19:43 0.2 0
2014-08-31 08:20:07 0.2 0
2014-08-31 08:20:30 0.2 0
2014-08-31 08:20:50 0.2 0
2014-08-31 08:21:09 0.2 0
2014-08-31 08:21:30 0.2 0
2014-08-31 08:21:49 0.2 0
2014-08-31 08:22:08 0.2 0
2014-08-31 08:22:23 0.2 0
2014-08-31 08:22:38 0.2 0
2014-08-31 08:22:54 0.2 0
2014-08-31 08:23:16 0.2 0
2014-08-31 08:23:36 0.2 0
2014-08-31 08:24:00 0.2 0
2014-08-31 08:24:24 0.2 0
2014-08-31 08:24:46 0.2 0
2014-08-31 08:25:04 0.2 0
2014-08-31 08:25:20 0.2 0
2014-08-31 08:25:37 0.2 0
2014-08-31 08:25:54 0.2 0
2014-08-31 08:26:06 0.2 0
2014-08-31 08:26:15 0.2 0
2014-08-31 08:26:32 0.2 0
2014-08-31 08:26:51 0.2 0
2014-08-31 08:27:03 0.2 0
2014-08-31 08:27:15 0.2 0
2014-08-31 08:27:28 0.2 0
2014-08-31 08:27:42 0.2 0
2014-08-31 08:27:55 0.2 0
2014-08-31 08:28:11 0.2 0
2014-08-31 08:28:25 0.2 0
2014-08-31 08:28:39 0.2 0
2014-08-31 08:28:53 0.2 0
2014-08-31 08:29:08 0.2 0
2014-08-31 08:29:18 0.2 0
2014-08-31 08:29:31 0.2 0
2014-08-31 08:29:47 0.2 0
2014-08-31 08:30:00 0.2 0
2014-08-31 08:30:18 0.2 0
2014-08-31 08:30:32 0.2 0
2014-08-31 08:30:49 0.2 0
2014-08-31 08:31:05 0.2 0
2014-08-31 08:31:22 0.2 0
2014-08-31 08:31:39 0.2 0
2014-08-31 08:31:55 0.2 0
2014-08-31 08:32:09 0.2 0
2014-08-31 08:32:18 0.2 0
2014-08-31 08:32:27 0.2 0
2014-08-31 08:32:36 0.2 0
2014-08-31 08:32:45 0.2 0
2014-08-31 08:33:22 0.2 0
2014-08-31 08:33:39 0.2 0
2014-08-31 08:33:48 0.2 0
2014-08-31 08:34:06 0.2 0
2014-08-31 08:34:27 0.2 0
2014-08-31 08:34:41 0.2 0
2014-08-31 08:35:04 0.2 0
2014-08-31 08:36:58 0.2 0
2014-08-31 08:37:52 0.2 0
2014-08-31 08:38:31 0.2 0
2014-08-31 08:39:05 0.2 0
2014-08-31 08:39:38 0.2 0
2014-08-31 08:40:12 0.2 0
2014-08-31 08:40:38 0.2 0
2014-08-31 08:40:50 0.2 0
2014-08-31 08:41:01 0.2 0
2014-08-31 08:41:28 0.2 0
2014-08-31 08:41:37 0.2 0
2014-08-31 08:41:46 0.2 0
2014-08-31 08:42:04 0.2 0
2014-08-31 08:42:25 0.2 0
2014-08-31 08:42:36 0.2 0
2014-08-31 08:42:50 0.2 0
2014-08-31 08:43:03 0.2 0
2014-08-31 08:43:25 0.2 0
2014-08-31 08:43:47 0.2 0
2014-08-31 08:44:13 0.2 0
2014-08-31 08:44:37 0.2 0
2014-08-31 08:44:54 0.2 0
2014-08-31 08:45:14 0.2 0
2014-08-31 08:45:58 0.2 0
2014-08-31 08:47:25 0.2 0
2014-08-31 08:54:43 0.2 0
2014-08-31 08:56:44 0.2 0
2014-08-31 08:58:20 0.2 0
2014-08-31 08:58:51 0.2 0
2014-08-31 08:59:19 0.2 0
2014-08-31 08:59:54 0.2 0
2014-08-31 09:00:31 0.2 0
2014-08-31 09:01:44 0.2 0
2014-08-31 09:03:41 0.2 0
2014-08-31 09:05:37 0.2 0
2014-08-31 09:06:45 0.2 0
2014-08-31 09:07:35 0.2 0
2014-08-31 09:08:09 0.2 0
2014-08-31 09:08:24 0.2 0
2014-08-31 09:08:39 0.2 0
2014-08-31 09:08:58 0.2 0
2014-08-31 09:09:20 0.2 0
2014-08-31 09:09:42 0.2 0
2014-08-31 09:10:10 0.2 0
2014-08-31 09:10:40 0.2 0
2014-08-31 09:11:05 0.2 0
2014-08-31 09:11:24 0.2 0
2014-08-31 09:11:39 0.2 0
2014-08-31 09:11:56 0.2 0
2014-08-31 09:12:29 0.2 0
2014-08-31 09:13:19 0.2 0
2014-08-31 09:13:57 0.2 0
2014-08-31 09:14:20 0.2 0
2014-08-31 09:14:40 0.2 0
2014-08-31 09:15:04 0.2 0
2014-08-31 09:15:26 0.2 0
2014-08-31 09:15:43 0.2 0
2014-08-31 09:16:01 0.2 0
2014-08-31 09:16:23 0.2 0
2014-08-31 09:16:57 0.2 0
2014-08-31 09:17:25 0.2 0
2014-08-31 09:23:53 0.2 0
2014-08-31 09:24:48 0.2 0
2014-08-31 09:25:29 0.2 0
2014-08-31 09:26:02 0.2 0
2014-08-31 09:26:26 0.2 0
2014-08-31 09:26:48 0.2 0
2014-08-31 09:27:08 0.2 0
2014-08-31 09:27:29 0.2 0
2014-08-31 09:27:53 0.2 0
2014-08-31 09:28:16 0.2 0
2014-08-31 09:28:38 0.2 0
2014-08-31 09:29:02 0.2 0
2014-08-31 09:29:31 0.2 0
2014-08-31 09:29:50 0.2 0
2014-08-31 09:30:10 0.2 0
2014-08-31 09:30:29 0.2 0
2014-08-31 09:30:54 0.2 0
2014-08-31 09:31:16 0.2 0
2014-08-31 09:31:39 0.2 0
2014-08-31 09:34:22 0.2 0
2014-08-31 09:34:51 0.2 0
2014-08-31 09:35:06 0.2 0
2014-08-31 09:35:16 0.2 0
2014-08-31 09:36:08 0.2 0
2014-08-31 09:36:56 0.2 0
2014-08-31 09:37:53 0.2 0
2014-08-31 09:58:37 0.2 0
2014-08-31 10:02:40 0.2 0
2014-08-31 12:16:12 0.2 0
2014-08-31 12:34:54 0.2 0
2014-08-31 13:29:46 0.2 0
2014-08-31 13:52:40 0.2 0
2014-08-31 14:32:00 0.2 0
2014-08-31 14:38:58 0.2 0
2014-08-31 14:42:59 0.2 0
2014-08-31 14:50:12 0.2 0
2014-08-31 15:05:28 0.2 0
2014-08-31 15:25:45 0.2 0
2014-08-31 15:49:25 0.2 0
2014-08-31 16:10:28 0.2 0
2014-08-31 17:26:46 0.2 0
2014-08-31 18:24:37 0.2 0
2014-08-31 18:31:37 0.2 0
2014-08-31 18:39:27 0.2 0
2014-08-31 18:41:31 0.2 0
2014-08-31 18:44:10 0.2 0
2014-08-31 18:48:17 0.2 0
2014-08-31 18:50:58 0.2 0
2014-08-31 18:52:46 0.2 0
2014-08-31 18:55:23 0.2 0
2014-08-31 19:00:23 0.2 0
2014-08-31 19:04:27 0.2 0
2014-08-31 19:07:12 0.2 0
2014-08-31 19:10:45 0.2 0
2014-08-31 19:13:40 0.2 0
2014-08-31 19:19:03 0.2 0
2014-08-31 19:25:23 0.2 0
2014-08-31 19:34:27 0.2 0
2014-08-31 19:44:11 0.2 0
2014-08-31 20:00:15 0.2 0
2014-08-31 20:01:15 0.2 0
2014-08-31 20:01:40 0.2 0
2014-08-31 20:01:53 0.2 0
2014-08-31 20:02:07 0.2 0
2014-08-31 20:02:26 0.2 0
2014-08-31 20:02:58 0.2 0
2014-08-31 20:03:42 0.2 0
2014-08-31 20:04:22 0.2 0
2014-08-31 20:04:58 0.2 0
2014-08-31 20:05:28 0.2 0
2014-08-31 20:06:02 0.2 0
2014-08-31 20:08:01 0.2 0
2014-08-31 20:11:21 0.2 0
2014-08-31 20:13:14 0.2 0
2014-08-31 20:14:53 0.2 0
2014-08-31 20:16:32 0.2 0
2014-08-31 20:18:32 0.2 0
2014-08-31 20:20:26 0.2 0
2014-08-31 20:22:43 0.2 0
2014-08-31 20:26:41 0.2 0
2014-08-31 20:30:14 0.2 0
2014-08-31 20:33:32 0.2 0
2014-08-31 20:36:54 0.2 0
2014-08-31 20:41:37 0.2 0
2014-08-31 20:42:58 0.2 0
2014-08-31 20:43:46 0.2 0
2014-08-31 20:44:35 0.2 0
2014-08-31 20:47:10 0.2 0
2014-08-31 20:56:03 0.2 0
This is my code so far:
library(xts)
## Import data from txt file
tip_time <- read.table("../Rainfall/Malmo_regndata/fasta/M01_Turbinen_vippning.txt", header = TRUE, check.names=FALSE, sep = "\t", skip = 1)
tip_time$Time <- as.POSIXct(tip_time$Time) # Convert to POSIXct
tip_time = xts(tip_time[,-1], order.by=tip_time[,1]) # Convert to xts
acc_tip <- cumsum(tip_time[,1]) # Accumulated rainfall (here in mm)
## Make time series with regular time steps
step <- 5
days <- 1
n <- days*24*60/step
timesteps <- ISOdatetime(2014,08,31,0,0,0) + seq(0:(n-1))*step*60 # Make timesteps
ts <- xts(rep(NA,n), order.by=timesteps) # Make xts with timesteps and NA
## Merge data into time series with regular time steps
ts_tip <- merge(ts, na.locf(merge(ts, acc_tip)[,2]), join="inner")[,2] # Merge acc_tip with ts
ts_tip[is.na(ts_tip)] <- 0 # Make 0 of NA
## Calculate intesities from accumulated rainfall
intensity <- diff(ts_tip, lag = 1) # Calculate intensities (here in mm/5 min)
intensity[is.na(intensity)] <- 0 # Make 0 of NA
plot(intensity, main="rainfall intensity [mm/5 min]")
Between 10.00 and 18.00, the rainfall intensity was mostly lower than 0.2 mm. This means that we need to smoothen the time series out. Every 0.2 mm of rainfall should be distributed evenly among the time steps before, if there is one or more time steps without any tip, as we assume that it the rain fell evenly during these time steps. How can this be achieved in R? I am grateful if anyone has a good idea on how to solve this.
This is a small example from the textbook Afløbsteknik by Winther et al. (2011, Polyteknisk forlag, Lyngby). It shows the desired result (tip_corrected). Note that the first registrated tip stays the same, while the smoothing takes place during the rainfall. There are no smoothing between rainfall events. One could assume that there should be 2 hours between two rainfall events to make them individual rainfall events.
tip<-c(1,rep(0,9),2,1,2,0,0,1,rep(0,14),1)
tip_corrected<-c(1,rep(0.1,9),1.1,1,2,0.333,0.333,0.333,rep(0.0667,15))
windows()
plot(tip, pch = 1)
points(tip_corrected, pch = 4)
legend(23,2, legend = c("tip", "tip_corrected"), pch = c(1,4))
518
If I understand what you're trying to do, rather than doing the merge for ts_tip, you could use the approx function with suitable rules to linearly interpolate cumulative rainfall at the regularly spaced times. rule=1:2 leaves NA's in the series prior to first rainfall and fills the values past the last acc_tip time with the last acc_tip value as shown below. The remainder of your code is as before.
## Merge data into time series with regular time steps
# ts_tip <- merge(ts, na.locf(merge(ts, acc_tip)[,2]), join="inner")[,2] # Merge acc_tip with ts
# ts_tip[is.na(ts_tip)] <- 0 # Make 0 of NA
#
# interpolation of cumulative rainfall at equi-spaced times using approx function
ts_tip <- xts(approx(index(acc_tip), acc_tip, rule=1:2, xout=index(ts))$y, order.by=index(ts))
ts_tip[is.na(ts_tip)] <- 0 # changes NA's at start of series to 0's
This is probably not the most elegant way and I would be glad to see better solutions, but the following should work:
library(xts)
library(plyr)
## Import data from txt file
## I copied your data dump to dat.txt and added "Date" as first column name. (I import 4 columns and merge "Date" and "Time" afterwards.)
tip_time <- read.table("dat.txt", header = TRUE,
sep = " ", stringsAsFactors = FALSE)
tip_time$Time <- paste(tip_time$Date, tip_time$Time)
tip_time[,"Date"] <- NULL
tip_time$Time <- as.POSIXct(tip_time$Time) # Convert to POSIXct
colnames(tip_time) <- c("Time", "bucket", "Flag")
## Make "time series" with regular time steps.
regularSteps <- data.frame(
Time =
seq(from = trunc(tip_time[1, 1], "day"),
to = trunc(tail(tip_time[, 1], n = 1), "day") + 60*60*24 - 1,
by = 1))
tip_regular <- merge(regularSteps, tip_time, by = "Time", all = TRUE)
tip_regular[is.na(tip_regular)] <- 0
## To aggregate, create groups of 5 minutes.
tip_regular$group <- floor(as.numeric(tip_regular$Time) / (5*60))
res <- ddply(.data = tip_regular, .variables = "group", .fun = function(x) {
return(data.frame(Time = tail(x$Time, n = 1), buckets = sum(x$bucket)))
})[, -1]
# To check the result afterwards:
res$original <- res$buckets
# Smoothing:
bucketsize <- 0.2
while(any(res$buckets == 0)) { # Do the following as long as there are empty buckets (or until all empty buckets are at the end of the data set.)
# These 3 lines could probably be simplified:
firstEmpty <- which(res$buckets == 0)[1]
allFull <- which(res$buckets != 0)
firstFullAfterEmpty <- allFull[allFull > firstEmpty][1]
if(is.na(firstFullAfterEmpty)) break
# Take one bucket out, this bucket will be redistributed:
res[firstFullAfterEmpty, "buckets"] <- res[firstFullAfterEmpty, "buckets"] - bucketsize
toFill <- firstFullAfterEmpty - firstEmpty + 1 # # Number of buckets to fill
res[firstEmpty:firstFullAfterEmpty, "buckets"] <- bucketsize / toFill # equally redistribute the water
}
tip_ts <- xts(x = res$buckets, order.by = res$Time)
plot(tip_ts, main="rainfall intensity [mm/5 min]")
44
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