创建时间范围时间序列螺旋图
[英]Creating a temporal range time-series spiral plot
问题描述
Similarly to this question , I'm interested in creating time series spirals. 
与这个问题类似，我对创建时间序列螺旋感兴趣。 The solution doesn't necessarily have to be implemented in R or using ggplot, but it seems the majority of solutions have been implemented in R with ggplot, with a handful in Python and one in d3. 该解决方案不一定必须用R或使用ggplot来实现，但是似乎大多数解决方案已经用ggplot在R中实现了，其中少数在Python中，而在d3中。 My attempts so far have all used R. Unlike this question, I'm interested in displaying specific ranges of data without quantizing/binning the data. 到目前为止，我的所有尝试都使用了R。与这个问题不同，我感兴趣的是显示特定范围的数据而不对数据进行量化/合并。 That is, I'd like to display a spiral timeline showing when particular events start and stop, where theta-min and theta-max of every event represent specific points in time. 也就是说，我想显示一个螺旋形的时间轴，显示特定事件的开始和结束时间，其中每个事件的theta-min和theta-max代表特定的时间点。
Consider this travel data: 考虑以下旅行数据：
trip_start trip_stop dist
2017-04-01 17:42:00 2017-04-01 18:34:00 1.95
2017-04-01 18:42:00 2017-04-01 19:05:00 6.54
2017-04-02 01:09:00 2017-04-02 01:12:00 1.07
2017-04-02 01:22:00 2017-04-02 01:27:00 1.03
2017-04-02 08:17:00 2017-04-02 08:23:00 1.98
2017-04-02 11:23:00 2017-04-02 11:30:00 1.98
2017-04-02 15:44:00 2017-04-02 15:56:00 4.15
2017-04-02 16:29:00 2017-04-02 16:45:00 4.08
2017-04-03 10:24:00 2017-04-03 10:55:00 19.76
2017-04-03 14:01:00 2017-04-03 14:18:00 8.21
2017-04-03 14:25:00 2017-04-03 14:31:00 1.49
2017-04-03 14:45:00 2017-04-03 14:50:00 1.59
2017-04-03 15:44:00 2017-04-03 16:10:00 4.44
2017-04-03 16:14:00 2017-04-03 16:37:00 9.96
2017-04-03 16:40:00 2017-04-03 16:45:00 0.7
2017-04-03 17:15:00 2017-04-03 17:46:00 16.92
2017-04-03 17:56:00 2017-04-03 18:19:00 5.23
2017-04-03 18:42:00 2017-04-03 18:45:00 0.49
2017-04-03 19:02:00 2017-04-03 19:04:00 0.48
2017-04-04 07:24:00 2017-04-04 07:27:00 0.66
2017-04-04 07:30:00 2017-04-04 08:04:00 13.55
2017-04-04 08:32:00 2017-04-04 09:25:00 25.09
2017-04-04 13:32:00 2017-04-04 13:40:00 3.06
2017-04-04 13:52:00 2017-04-04 13:57:00 1.3
2017-04-04 14:55:00 2017-04-04 15:01:00 2.47
2017-04-04 18:40:00 2017-04-04 19:12:00 22.71
2017-04-04 22:16:00 2017-04-04 23:54:00 38.28
2017-04-04 23:59:00 2017-04-05 00:03:00 1.02
2017-04-05 11:04:00 2017-04-05 11:49:00 25.73
2017-04-05 12:05:00 2017-04-05 12:18:00 2.97
2017-04-05 15:19:00 2017-04-05 16:25:00 25.13
2017-04-05 16:38:00 2017-04-05 16:40:00 0.41
2017-04-05 18:58:00 2017-04-05 19:02:00 1.25
2017-04-05 19:13:00 2017-04-05 19:18:00 1.09
2017-04-05 19:25:00 2017-04-05 19:48:00 6.63
2017-04-06 10:01:00 2017-04-06 10:44:00 20.81
2017-04-06 13:22:00 2017-04-06 13:33:00 1.63
2017-04-06 20:58:00 2017-04-06 21:25:00 24.85
2017-04-06 21:32:00 2017-04-06 21:56:00 6.06
2017-04-07 10:55:00 2017-04-07 11:37:00 24.53
2017-04-07 17:14:00 2017-04-07 17:48:00 19.66
2017-04-07 17:57:00 2017-04-07 18:07:00 2.12
2017-04-08 20:57:00 2017-04-08 21:06:00 1.06
2017-04-08 21:23:00 2017-04-08 21:36:00 2.97
2017-04-09 08:14:00 2017-04-09 08:19:00 1.99
2017-04-09 11:40:00 2017-04-09 11:50:00 2.24
2017-04-09 11:50:00 2017-04-09 11:57:00 1.64
2017-04-09 16:29:00 2017-04-09 16:34:00 0.53
2017-04-09 16:43:00 2017-04-09 16:45:00 0.5
2017-04-09 17:46:00 2017-04-09 17:48:00 0.44
2017-04-09 17:53:00 2017-04-09 17:56:00 0.4
2017-04-09 21:33:00 2017-04-09 21:56:00 2.48
2017-04-09 21:57:00 2017-04-09 22:14:00 2.92
2017-04-09 22:22:00 2017-04-09 22:25:00 0.9
2017-04-10 10:37:00 2017-04-10 11:22:00 19.27
2017-04-10 16:12:00 2017-04-10 16:59:00 21.31
2017-04-11 11:14:00 2017-04-11 11:18:00 1.24
2017-04-11 11:21:00 2017-04-11 11:48:00 22.95
2017-04-11 18:24:00 2017-04-11 19:05:00 28.64
2017-04-11 19:21:00 2017-04-11 19:34:00 5.37
2017-04-12 11:00:00 2017-04-12 12:08:00 28.91
2017-04-12 14:03:00 2017-04-12 15:20:00 28.56
2017-04-12 20:24:00 2017-04-12 20:29:00 1.17
2017-04-12 20:32:00 2017-04-12 21:09:00 30.89
2017-04-13 01:37:00 2017-04-13 02:09:00 32.3
2017-04-13 08:08:00 2017-04-13 08:39:00 19.39
2017-04-13 10:53:00 2017-04-13 11:23:00 24.59
2017-04-13 18:56:00 2017-04-13 19:22:00 22.74
2017-04-14 01:06:00 2017-04-14 01:37:00 31.36
2017-04-14 01:48:00 2017-04-14 01:51:00 1.03
2017-04-14 12:08:00 2017-04-14 12:22:00 1.94
2017-04-14 12:29:00 2017-04-14 13:01:00 19.07
2017-04-14 16:17:00 2017-04-14 17:03:00 19.74
2017-04-14 17:05:00 2017-04-14 17:32:00 3.99
2017-04-14 21:57:00 2017-04-14 22:02:00 1.98
2017-04-15 01:46:00 2017-04-15 01:49:00 1.07
2017-04-15 01:56:00 2017-04-15 01:58:00 1.03
2017-04-15 07:13:00 2017-04-15 07:15:00 0.45
2017-04-15 07:19:00 2017-04-15 07:21:00 0.41
2017-04-15 15:54:00 2017-04-15 16:05:00 1.94
2017-04-15 22:23:00 2017-04-15 22:26:00 0.86
2017-04-15 22:46:00 2017-04-15 22:47:00 0.25
2017-04-15 22:51:00 2017-04-15 22:53:00 0.71
2017-04-16 11:35:00 2017-04-16 11:54:00 11.4
2017-04-16 11:58:00 2017-04-16 12:15:00 10.43
2017-04-17 10:44:00 2017-04-17 10:53:00 3.04
2017-04-17 10:55:00 2017-04-17 11:22:00 18.26
2017-04-17 18:09:00 2017-04-17 18:12:00 0.85
2017-04-17 18:21:00 2017-04-17 19:07:00 37.22
2017-04-18 02:07:00 2017-04-18 02:47:00 32.41
2017-04-18 10:55:00 2017-04-18 10:57:00 0.41
2017-04-18 11:02:00 2017-04-18 11:12:00 2.3
2017-04-18 11:15:00 2017-04-18 11:52:00 24.05
2017-04-18 16:59:00 2017-04-18 17:55:00 22.66
2017-04-19 00:46:00 2017-04-19 01:35:00 39.25
2017-04-19 10:57:00 2017-04-19 11:44:00 24.06
2017-04-19 13:23:00 2017-04-19 14:10:00 25.96
2017-04-19 16:21:00 2017-04-19 17:07:00 18.05
2017-04-19 23:32:00 2017-04-20 00:19:00 39.67
2017-04-20 10:47:00 2017-04-20 11:13:00 24.07
2017-04-20 16:21:00 2017-04-20 16:30:00 0.86
2017-04-20 16:36:00 2017-04-20 16:58:00 0.85
2017-04-20 17:41:00 2017-04-20 17:44:00 0.37
2017-04-20 17:49:00 2017-04-20 18:40:00 19.32
2017-04-20 22:22:00 2017-04-20 22:53:00 29.2
2017-04-20 23:07:00 2017-04-20 23:27:00 10.94
2017-04-21 08:29:00 2017-04-21 08:40:00 1.91
2017-04-21 11:30:00 2017-04-21 11:32:00 0.42
2017-04-21 11:38:00 2017-04-21 11:40:00 0.4
2017-04-21 11:42:00 2017-04-21 12:15:00 19.09
2017-04-21 16:50:00 2017-04-21 18:17:00 40.61
2017-04-21 18:55:00 2017-04-21 19:11:00 1.73
2017-04-21 22:20:00 2017-04-21 22:53:00 28.26
2017-04-21 23:01:00 2017-04-21 23:22:00 11.76
2017-04-22 08:56:00 2017-04-22 08:58:00 0.63
2017-04-22 09:04:00 2017-04-22 09:08:00 0.3
2017-04-22 09:12:00 2017-04-22 09:15:00 0.42
2017-04-22 16:48:00 2017-04-22 16:52:00 0.54
2017-04-22 17:06:00 2017-04-22 17:09:00 0.51
2017-04-22 17:10:00 2017-04-22 17:13:00 1.03
2017-04-22 17:22:00 2017-04-22 17:27:00 1.1
2017-04-23 08:13:00 2017-04-23 08:15:00 0.41
2017-04-23 08:19:00 2017-04-23 08:20:00 0.4
2017-04-23 08:21:00 2017-04-23 08:25:00 1.99
2017-04-23 11:41:00 2017-04-23 11:48:00 2.04
2017-04-23 12:35:00 2017-04-23 12:50:00 7.59
2017-04-23 14:08:00 2017-04-23 14:21:00 7.31
2017-04-23 14:33:00 2017-04-23 15:38:00 37.6
2017-04-24 00:26:00 2017-04-24 01:18:00 39.21
2017-04-24 10:24:00 2017-04-24 10:26:00 0.41
2017-04-24 10:31:00 2017-04-24 10:35:00 1.37
2017-04-24 10:38:00 2017-04-24 10:43:00 1.19
2017-04-24 10:49:00 2017-04-24 11:15:00 19.58
2017-04-24 17:13:00 2017-04-24 18:20:00 37.42
2017-04-24 19:02:00 2017-04-24 19:08:00 1.76
2017-04-24 19:49:00 2017-04-24 19:55:00 1.79
2017-04-24 20:41:00 2017-04-24 21:16:00 32.31
2017-04-25 10:53:00 2017-04-25 11:25:00 24.83
2017-04-25 15:15:00 2017-04-25 15:24:00 3.07
2017-04-25 15:30:00 2017-04-25 15:40:00 3.01
2017-04-25 17:34:00 2017-04-25 18:18:00 24.8
2017-04-26 09:59:00 2017-04-26 10:28:00 24.05
2017-04-26 12:56:00 2017-04-26 13:40:00 29.13
2017-04-26 14:37:00 2017-04-26 15:34:00 21
2017-04-27 08:57:00 2017-04-27 10:21:00 40.56
2017-04-27 16:12:00 2017-04-27 16:44:00 9.89
2017-04-27 17:09:00 2017-04-27 18:01:00 17.51
2017-04-28 05:18:00 2017-04-28 06:06:00 39.28
2017-04-28 12:57:00 2017-04-28 13:52:00 35.82
2017-04-28 16:48:00 2017-04-28 18:14:00 39.1
2017-05-01 11:41:00 2017-05-01 12:20:00 18.74
2017-05-01 18:53:00 2017-05-01 19:34:00 37.15
2017-05-01 23:08:00 2017-05-01 23:09:00 0.06
2017-05-01 23:18:00 2017-05-02 00:11:00 38.61
2017-05-02 11:05:00 2017-05-02 11:42:00 24.07
2017-05-02 17:34:00 2017-05-02 18:53:00 26.42
2017-05-03 12:13:00 2017-05-03 12:25:00 3.96
2017-05-03 12:25:00 2017-05-03 12:56:00 21.15
2017-05-03 13:26:00 2017-05-03 13:44:00 3.32
2017-05-03 13:57:00 2017-05-03 14:08:00 3.49
2017-05-03 18:39:00 2017-05-03 19:08:00 24.85
2017-05-03 19:09:00 2017-05-03 19:13:00 0.99
2017-05-03 19:29:00 2017-05-03 19:32:00 0.84
2017-05-04 10:38:00 2017-05-04 11:06:00 24.05
2017-05-04 13:34:00 2017-05-04 14:10:00 1.73
2017-05-04 17:14:00 2017-05-04 18:23:00 24.68
2017-05-05 20:38:00 2017-05-05 20:52:00 2.24
2017-05-06 11:45:00 2017-05-06 12:30:00 20.19
2017-05-06 14:36:00 2017-05-06 15:35:00 14.49
2017-05-06 15:48:00 2017-05-06 16:17:00 5.25
2017-05-06 17:11:00 2017-05-06 17:13:00 0.43
2017-05-06 17:19:00 2017-05-06 17:21:00 0.43
2017-05-07 08:16:00 2017-05-07 08:22:00 3.27
2017-05-07 12:09:00 2017-05-07 12:16:00 2.01
2017-05-07 17:28:00 2017-05-07 17:50:00 10.36
2017-05-07 17:54:00 2017-05-07 18:01:00 1.19
2017-05-07 18:02:00 2017-05-07 18:35:00 28.31
2017-05-07 21:48:00 2017-05-07 21:52:00 1.46
2017-05-07 22:01:00 2017-05-07 22:05:00 1.37
2017-05-08 00:59:00 2017-05-08 02:19:00 39.23
2017-05-08 11:30:00 2017-05-08 11:58:00 22.55
2017-05-08 18:08:00 2017-05-08 18:30:00 10.47
2017-05-08 18:33:00 2017-05-08 19:09:00 28.44
2017-05-08 22:25:00 2017-05-08 23:09:00 38.65
2017-05-08 23:14:00 2017-05-08 23:17:00 1.04
2017-05-09 11:35:00 2017-05-09 12:19:00 23.99
2017-05-09 17:57:00 2017-05-09 18:59:00 29.38
2017-05-09 20:03:00 2017-05-09 20:13:00 1.9
2017-05-10 10:18:00 2017-05-10 10:54:00 24.06
2017-05-10 15:43:00 2017-05-10 16:46:00 24.71
2017-05-11 12:28:00 2017-05-11 13:07:00 21.75
2017-05-11 18:00:00 2017-05-11 18:31:00 19.3
2017-05-12 08:26:00 2017-05-12 08:55:00 20.46
2017-05-12 13:00:00 2017-05-12 13:34:00 14.6
2017-05-13 08:44:00 2017-05-13 08:46:00 0.38
2017-05-13 08:57:00 2017-05-13 09:01:00 0.33
2017-05-13 14:22:00 2017-05-13 14:41:00 6.86
2017-05-13 15:17:00 2017-05-13 15:35:00 5.2
2017-05-13 18:10:00 2017-05-13 18:21:00 1.91
2017-05-14 11:22:00 2017-05-14 11:26:00 0.9
2017-05-14 11:36:00 2017-05-14 11:38:00 0.39
2017-05-14 14:56:00 2017-05-14 15:59:00 40.07
2017-05-14 16:34:00 2017-05-14 16:41:00 1.49
2017-05-14 16:56:00 2017-05-14 17:04:00 1.45
2017-05-14 19:05:00 2017-05-14 20:06:00 39.21
2017-05-15 11:24:00 2017-05-15 11:33:00 1.91
2017-05-15 11:41:00 2017-05-15 12:13:00 19.84
2017-05-15 17:41:00 2017-05-15 18:11:00 16
2017-05-15 18:15:00 2017-05-15 19:23:00 31.52
2017-05-15 23:41:00 2017-05-16 00:26:00 39.32
2017-05-16 09:49:00 2017-05-16 11:02:00 24.91
2017-05-16 16:08:00 2017-05-16 16:32:00 3.37
2017-05-16 17:11:00 2017-05-16 17:32:00 4.8
2017-05-16 17:42:00 2017-05-16 17:56:00 1.81
2017-05-16 18:13:00 2017-05-16 18:46:00 24.85
2017-05-16 21:07:00 2017-05-16 21:10:00 1.04
2017-05-16 21:26:00 2017-05-16 21:29:00 1.02
2017-07-28 16:10:00 2017-07-28 16:17:00 2.22
2017-07-28 16:17:00 2017-07-28 16:42:00 7.84
2017-08-10 12:00:00 2017-08-10 12:44:00 24.05
2017-08-10 14:56:00 2017-08-10 15:10:00 1.61
2017-08-10 18:51:00 2017-08-10 19:21:00 24.85
2017-08-10 19:46:00 2017-08-10 19:56:00 1.14
2017-08-10 20:08:00 2017-08-10 20:12:00 1.09
2017-08-11 12:44:00 2017-08-11 12:49:00 0.82
2017-08-11 12:59:00 2017-08-11 13:01:00 0.56
2017-08-11 13:18:00 2017-08-11 15:12:00 1.79
2017-08-11 15:14:00 2017-08-11 16:53:00 34.6
2017-08-11 19:27:00 2017-08-11 20:34:00 34.91
2017-08-12 13:52:00 2017-08-12 13:56:00 1.05
2017-08-12 13:59:00 2017-08-12 14:02:00 0.28
2017-08-12 14:10:00 2017-08-12 14:30:00 1.22
2017-08-12 17:15:00 2017-08-12 17:36:00 11.37
2017-08-12 20:49:00 2017-08-12 21:05:00 10.43
2017-08-13 12:16:00 2017-08-13 12:44:00 12.96
2017-08-13 16:03:00 2017-08-13 16:32:00 14.33
2017-08-13 18:19:00 2017-08-13 18:42:00 9.32
2017-08-13 18:52:00 2017-08-13 19:05:00 3.99
2017-08-13 21:42:00 2017-08-13 21:53:00 5.6
2017-08-14 08:50:00 2017-08-14 09:45:00 24.1
2017-08-14 13:22:00 2017-08-14 13:54:00 24.84
2017-08-14 14:02:00 2017-08-14 15:34:00 36.92
2017-08-14 15:58:00 2017-08-14 17:17:00 35.7
2017-08-14 17:35:00 2017-08-14 17:45:00 1.99
2017-08-14 18:07:00 2017-08-14 18:27:00 9.92
2017-08-15 10:15:00 2017-08-15 10:51:00 25
2017-08-15 19:23:00 2017-08-15 19:29:00 0.4
2017-08-15 19:51:00 2017-08-15 20:45:00 24.39
2017-08-15 20:56:00 2017-08-15 21:04:00 2.78
2017-08-15 21:09:00 2017-08-15 21:37:00 19.22
2017-08-16 00:03:00 2017-08-16 00:27:00 15.51
2017-08-16 00:36:00 2017-08-16 00:41:00 1.23
2017-08-16 00:46:00 2017-08-16 01:18:00 11.35
2017-08-16 09:38:00 2017-08-16 09:41:00 1.21
2017-08-16 09:41:00 2017-08-16 09:43:00 0.08
2017-08-16 09:47:00 2017-08-16 10:32:00 22.89
2017-08-16 16:51:00 2017-08-16 17:11:00 3.14
2017-08-16 17:12:00 2017-08-16 17:25:00 2.76
2017-08-16 17:41:00 2017-08-16 18:36:00 24.78
2017-08-17 09:34:00 2017-08-17 10:13:00 24.03
2017-08-17 12:32:00 2017-08-17 13:07:00 24.82
2017-08-17 13:35:00 2017-08-17 13:40:00 0.4
2017-08-17 13:47:00 2017-08-17 15:07:00 36.06
2017-08-17 15:18:00 2017-08-17 15:24:00 0.06
2017-08-17 16:03:00 2017-08-17 18:05:00 35.16
2017-08-18 09:47:00 2017-08-18 10:23:00 24.47
2017-08-18 16:04:00 2017-08-18 16:42:00 1.63
2017-08-18 17:56:00 2017-08-18 18:25:00 10.74
2017-08-18 18:27:00 2017-08-18 18:48:00 1.85
2017-08-19 00:07:00 2017-08-19 00:41:00 18.92
2017-08-19 00:52:00 2017-08-19 00:55:00 0.99
2017-08-19 11:52:00 2017-08-19 12:14:00 7.56
2017-08-19 15:57:00 2017-08-19 16:12:00 4.02
2017-08-19 16:37:00 2017-08-19 16:56:00 5.32
2017-08-19 23:32:00 2017-08-19 23:50:00 7.54
2017-08-19 23:51:00 2017-08-20 00:17:00 9.59
2017-08-20 09:03:00 2017-08-20 09:16:00 5.22
2017-08-20 19:17:00 2017-08-20 19:32:00 4.69
2017-08-21 09:24:00 2017-08-21 09:40:00 2.31
2017-08-21 10:59:00 2017-08-21 11:02:00 0.47
2017-08-21 13:40:00 2017-08-21 15:29:00 36.09
2017-08-21 15:54:00 2017-08-21 16:48:00 2.24
2017-08-21 16:57:00 2017-08-21 18:15:00 32.3
2017-08-22 08:38:00 2017-08-22 09:06:00 0.65
2017-08-22 09:18:00 2017-08-22 09:19:00 0.04
2017-08-22 09:22:00 2017-08-22 10:05:00 23.49
2017-08-22 14:30:00 2017-08-22 15:02:00 1.7
2017-08-22 16:37:00 2017-08-22 17:41:00 24.8
2017-08-23 17:16:00 2017-08-23 18:14:00 24.01
2017-08-23 18:27:00 2017-08-23 18:32:00 1.05
2017-08-23 19:24:00 2017-08-23 20:04:00 18.14
2017-08-23 22:01:00 2017-08-23 22:28:00 16.33
2017-08-23 22:46:00 2017-08-23 22:50:00 1.04
2017-08-24 09:41:00 2017-08-24 09:44:00 0.02
2017-08-24 09:59:00 2017-08-24 10:00:00 0.02
2017-08-24 13:57:00 2017-08-24 15:33:00 42.51
2017-08-24 16:43:00 2017-08-24 17:00:00 0.07
2017-08-24 17:06:00 2017-08-24 17:33:00 10.01
2017-08-24 18:12:00 2017-08-24 19:03:00 27.67
2017-08-25 09:36:00 2017-08-25 09:55:00 2.63
2017-08-25 10:01:00 2017-08-25 10:32:00 20.92
2017-08-25 20:40:00 2017-08-25 21:45:00 17.41
2017-08-25 21:49:00 2017-08-25 22:14:00 16.02
2017-08-26 00:10:00 2017-08-26 02:14:00 29.77
2017-08-26 16:31:00 2017-08-26 16:55:00 7.15
2017-08-26 17:54:00 2017-08-26 18:19:00 10
2017-08-26 20:07:00 2017-08-26 20:08:00 0.19
2017-08-26 20:08:00 2017-08-26 20:11:00 1.35
2017-08-27 12:39:00 2017-08-27 12:54:00 1
2017-08-27 12:55:00 2017-08-27 13:48:00 9.29
2017-08-27 14:00:00 2017-08-27 14:34:00 3.86
2017-08-27 15:56:00 2017-08-27 16:37:00 10.45
2017-08-27 16:44:00 2017-08-27 16:51:00 1.8
2017-08-27 16:55:00 2017-08-27 17:00:00 0.68
2017-08-27 17:04:00 2017-08-27 17:19:00 4.96
2017-08-27 17:28:00 2017-08-27 17:39:00 2.33
2017-08-27 17:47:00 2017-08-27 18:58:00 24.19
2017-08-27 22:17:00 2017-08-27 22:41:00 16.24
2017-08-28 00:33:00 2017-08-28 01:22:00 13.62
2017-08-28 12:48:00 2017-08-28 12:51:00 0.47
2017-08-28 14:01:00 2017-08-28 14:03:00 0.4
2017-08-28 14:12:00 2017-08-28 15:31:00 34.86
2017-08-28 15:56:00 2017-08-28 17:04:00 34.47
2017-08-28 22:15:00 2017-08-28 22:38:00 18.57
2017-08-29 01:42:00 2017-08-29 02:05:00 18.88
2017-08-29 11:40:00 2017-08-29 11:44:00 1.04
2017-08-29 11:48:00 2017-08-29 12:09:00 0.03
2017-08-29 12:18:00 2017-08-29 12:21:00 0.03
2017-08-29 12:26:00 2017-08-29 12:32:00 1.05
2017-08-29 12:35:00 2017-08-29 13:15:00 24.05
2017-08-29 19:40:00 2017-08-29 19:42:00 0.35
2017-08-29 19:50:00 2017-08-29 20:19:00 27.72
2017-08-29 20:25:00 2017-08-29 20:41:00 10.42
2017-08-30 10:00:00 2017-08-30 10:47:00 24.25
2017-08-30 14:31:00 2017-08-30 14:56:00 1.68
2017-08-30 17:19:00 2017-08-30 17:43:00 0.04
2017-08-30 17:43:00 2017-08-30 17:50:00 0.29
2017-08-30 17:56:00 2017-08-30 18:40:00 16.85
2017-08-30 22:57:00 2017-08-30 23:35:00 17.31
2017-08-31 11:30:00 2017-08-31 11:41:00 0.43
2017-08-31 14:04:00 2017-08-31 14:06:00 0.41
2017-08-31 14:24:00 2017-08-31 14:26:00 0.68
2017-08-31 14:31:00 2017-08-31 15:42:00 34.88
2017-08-31 16:01:00 2017-08-31 17:07:00 30.45
2017-08-31 20:54:00 2017-08-31 21:21:00 19.6
2017-09-01 10:30:00 2017-09-01 10:59:00 17.63
2017-09-01 14:07:00 2017-09-01 15:07:00 27.45
2017-09-01 17:17:00 2017-09-01 17:36:00 1.93
2017-09-01 18:16:00 2017-09-01 19:19:00 20.58
2017-09-01 19:25:00 2017-09-01 19:38:00 4.8
2017-09-01 21:30:00 2017-09-01 21:54:00 1.94
2017-09-02 15:46:00 2017-09-02 16:06:00 0.99
2017-09-02 16:13:00 2017-09-02 16:16:00 1.01
2017-09-02 16:56:00 2017-09-02 16:59:00 0.42
2017-09-02 17:04:00 2017-09-02 17:06:00 0.4
2017-09-02 22:52:00 2017-09-02 22:54:00 0.07
2017-09-02 22:55:00 2017-09-02 23:15:00 18.62
2017-09-03 01:46:00 2017-09-03 02:10:00 18.9
2017-09-03 14:49:00 2017-09-03 15:04:00 3.14
2017-09-03 15:50:00 2017-09-03 16:07:00 10.17
2017-09-03 16:21:00 2017-09-03 16:38:00 7.79
2017-09-03 16:47:00 2017-09-03 16:52:00 1.11
2017-09-03 18:32:00 2017-09-03 18:37:00 1.2
2017-09-03 18:37:00 2017-09-03 18:44:00 0.91
2017-09-04 15:50:00 2017-09-04 15:54:00 0.42
2017-09-04 15:59:00 2017-09-04 16:11:00 2.3
2017-09-04 16:21:00 2017-09-04 16:43:00 8.31
2017-09-04 17:05:00 2017-09-04 17:15:00 2.54
2017-09-04 17:26:00 2017-09-04 17:41:00 4.52
2017-09-04 17:49:00 2017-09-04 18:25:00 29.55
2017-09-04 19:36:00 2017-09-04 19:51:00 0.93
2017-09-04 19:54:00 2017-09-04 19:59:00 0.5
2017-09-04 21:21:00 2017-09-04 21:55:00 29.37
2017-09-05 11:08:00 2017-09-05 11:51:00 35.5
2017-09-05 12:36:00 2017-09-05 13:07:00 2.29
2017-09-05 13:19:00 2017-09-05 13:22:00 0.51
2017-09-05 13:26:00 2017-09-05 14:03:00 33.09
2017-09-05 14:13:00 2017-09-05 15:01:00 24.03
2017-09-05 17:33:00 2017-09-05 18:11:00 14.55
2017-09-05 19:01:00 2017-09-05 19:19:00 11.31
2017-09-06 09:21:00 2017-09-06 09:39:00 7.73
2017-09-06 10:14:00 2017-09-06 10:30:00 7.75
2017-09-06 10:37:00 2017-09-06 11:13:00 24.13
2017-09-06 16:48:00 2017-09-06 17:35:00 25.3
2017-09-06 17:49:00 2017-09-06 17:55:00 0.18
2017-09-06 17:58:00 2017-09-06 18:00:00 0.39
2017-09-06 18:38:00 2017-09-06 19:04:00 15.93
2017-09-06 23:45:00 2017-09-07 00:14:00 19.45
2017-09-07 00:26:00 2017-09-07 00:30:00 1.01
2017-09-07 10:42:00 2017-09-07 11:35:00 31.74
2017-09-07 14:04:00 2017-09-07 14:39:00 27.38
2017-09-07 14:43:00 2017-09-07 14:52:00 3.06
2017-09-07 14:54:00 2017-09-07 16:00:00 32.96
2017-09-07 16:32:00 2017-09-07 16:33:00 0.07
2017-09-07 16:38:00 2017-09-07 17:04:00 2.31
2017-09-07 17:23:00 2017-09-07 18:14:00 33.03
2017-09-08 10:02:00 2017-09-08 10:30:00 19.73
2017-09-08 18:09:00 2017-09-08 18:37:00 18.97
2017-09-08 19:04:00 2017-09-08 19:18:00 1.87
2017-09-09 02:25:00 2017-09-09 02:28:00 1.1
2017-09-09 02:33:00 2017-09-09 02:35:00 1.05
2017-09-10 17:09:00 2017-09-10 17:44:00 14.25
2017-09-10 22:50:00 2017-09-10 22:53:00 0.25
2017-09-10 22:56:00 2017-09-10 22:57:00 0.02
2017-09-10 23:00:00 2017-09-10 23:23:00 16.18
2017-09-11 00:01:00 2017-09-11 00:19:00 1.83
2017-09-11 09:59:00 2017-09-11 10:06:00 1.91
2017-09-11 10:12:00 2017-09-11 10:51:00 27.49
2017-09-11 13:39:00 2017-09-11 14:13:00 27.23
2017-09-11 14:31:00 2017-09-11 15:31:00 35.45
2017-09-11 16:03:00 2017-09-11 17:09:00 36.01
2017-09-11 17:39:00 2017-09-11 18:01:00 9.88
2017-09-11 23:01:00 2017-09-11 23:05:00 1.14
2017-09-11 23:16:00 2017-09-11 23:30:00 5.93
2017-09-11 23:30:00 2017-09-11 23:54:00 4.94
2017-09-12 02:56:00 2017-09-12 04:00:00 25.87
2017-09-12 10:06:00 2017-09-12 10:46:00 24.84
2017-09-12 16:33:00 2017-09-12 17:20:00 22.43
2017-09-12 19:38:00 2017-09-12 20:14:00 21.79
2017-09-13 06:24:00 2017-09-13 06:59:00 25.84
2017-09-13 07:02:00 2017-09-13 07:14:00 5.77
2017-09-13 11:14:00 2017-09-13 11:36:00 16.26
2017-09-13 16:01:00 2017-09-13 16:57:00 24.79
2017-09-13 17:07:00 2017-09-13 17:48:00 15.94
2017-09-13 23:13:00 2017-09-13 23:35:00 16.73
2017-09-14 12:00:00 2017-09-14 12:27:00 19.71
2017-09-14 12:28:00 2017-09-14 12:30:00 0.18
2017-09-14 14:36:00 2017-09-14 15:06:00 14.98
2017-09-14 15:11:00 2017-09-14 15:17:00 2.99
2017-09-14 15:26:00 2017-09-14 16:44:00 37.48
2017-09-14 17:03:00 2017-09-14 18:17:00 34.18
2017-09-14 18:32:00 2017-09-14 18:41:00 3.03
2017-09-15 10:25:00 2017-09-15 10:26:00 0.05
2017-09-15 10:45:00 2017-09-15 10:48:00 0.29
2017-09-15 10:59:00 2017-09-15 11:05:00 0.3
2017-09-15 11:09:00 2017-09-15 11:36:00 10.82
2017-09-15 13:00:00 2017-09-15 13:17:00 8.37
2017-09-15 13:36:00 2017-09-15 14:30:00 25.19
2017-09-15 14:37:00 2017-09-15 15:01:00 0.45
2017-09-15 15:04:00 2017-09-15 16:59:00 85.51
2017-09-15 17:06:00 2017-09-15 18:57:00 129.72
2017-09-15 19:03:00 2017-09-15 20:02:00 60.96
2017-09-16 10:18:00 2017-09-16 10:39:00 16.04
2017-09-16 11:52:00 2017-09-16 12:12:00 16.68
2017-09-16 12:28:00 2017-09-16 13:29:00 49
2017-09-16 18:36:00 2017-09-16 19:30:00 45.7
2017-09-16 19:39:00 2017-09-16 19:47:00 2.1
2017-09-17 13:32:00 2017-09-17 13:41:00 2.24
2017-09-17 14:19:00 2017-09-17 14:48:00 14.68
2017-09-17 18:25:00 2017-09-17 18:26:00 0.05
2017-09-17 18:36:00 2017-09-17 19:03:00 12.26
2017-09-18 07:52:00 2017-09-18 08:03:00 2.04
2017-09-18 08:21:00 2017-09-18 08:56:00 37.94
2017-09-18 09:01:00 2017-09-18 09:53:00 65.7
2017-09-18 10:04:00 2017-09-18 10:34:00 39.43
2017-09-18 10:46:00 2017-09-18 11:07:00 14.25
2017-09-18 11:19:00 2017-09-18 13:29:00 138.98
2017-09-18 14:24:00 2017-09-18 14:26:00 0.04
2017-09-18 14:28:00 2017-09-18 15:23:00 35.52
2017-09-18 15:53:00 2017-09-18 17:49:00 36.64
2017-09-19 09:24:00 2017-09-19 10:22:00 24.37
2017-09-19 15:55:00 2017-09-19 16:53:00 15.87
2017-09-19 16:53:00 2017-09-19 17:20:00 0.85
2017-09-19 17:33:00 2017-09-19 18:06:00 10.95
2017-09-19 18:10:00 2017-09-19 18:34:00 8.41
2017-09-19 21:06:00 2017-09-19 21:10:00 1.24
2017-09-19 21:17:00 2017-09-19 21:21:00 1.05
2017-09-20 11:12:00 2017-09-20 11:16:00 1.22
2017-09-20 11:18:00 2017-09-20 11:59:00 24.15
2017-09-20 17:20:00 2017-09-20 18:07:00 24.15
2017-09-20 18:50:00 2017-09-20 19:17:00 16.02
2017-09-20 22:05:00 2017-09-20 22:32:00 17.5
2017-09-21 13:38:00 2017-09-21 13:44:00 0.72
2017-09-21 13:50:00 2017-09-21 15:26:00 35.81
2017-09-21 15:59:00 2017-09-21 16:15:00 8.26
2017-09-21 16:19:00 2017-09-21 17:32:00 28.1
2017-09-21 18:49:00 2017-09-21 19:25:00 16.05
2017-09-21 22:30:00 2017-09-21 22:59:00 16.97
2017-09-22 10:19:00 2017-09-22 10:21:00 0.43
2017-09-22 10:25:00 2017-09-22 10:26:00 0.4
2017-09-22 10:30:00 2017-09-22 10:54:00 19.15
2017-09-22 11:58:00 2017-09-22 12:02:00 1.05
2017-09-22 18:32:00 2017-09-22 18:59:00 20.95
2017-09-23 08:34:00 2017-09-23 08:51:00 1.15
2017-09-23 09:19:00 2017-09-23 10:31:00 37.57
2017-09-23 11:09:00 2017-09-23 11:23:00 5.67
2017-09-23 11:51:00 2017-09-23 12:15:00 4.64
2017-09-23 12:47:00 2017-09-23 13:40:00 8.45
2017-09-23 13:56:00 2017-09-23 15:08:00 34.62
2017-09-23 15:37:00 2017-09-23 16:07:00 1.56
2017-09-24 14:59:00 2017-09-24 15:02:00 0.43
2017-09-24 15:14:00 2017-09-24 17:09:00 6.6
2017-09-24 17:37:00 2017-09-24 18:01:00 7.05
2017-09-24 18:05:00 2017-09-24 18:07:00 0.41
2017-09-24 19:35:00 2017-09-24 20:31:00 25.28
2017-09-25 00:24:00 2017-09-25 00:26:00 0.42
2017-09-25 00:30:00 2017-09-25 01:10:00 23.13
2017-09-25 12:12:00 2017-09-25 12:38:00 19.45
2017-09-25 14:22:00 2017-09-25 14:50:00 19.86
2017-09-25 14:52:00 2017-09-25 15:54:00 35.53
2017-09-25 16:37:00 2017-09-25 18:17:00 34.54
2017-09-25 20:36:00 2017-09-25 21:08:00 28.91
2017-09-26 01:46:00 2017-09-26 02:21:00 26.32
2017-09-26 09:36:00 2017-09-26 10:18:00 24.02
2017-09-26 14:05:00 2017-09-26 14:39:00 25.3
2017-09-26 15:49:00 2017-09-26 15:58:00 1.53
2017-09-26 16:15:00 2017-09-26 16:22:00 1.1
2017-09-27 09:15:00 2017-09-27 10:16:00 24.76
2017-09-27 16:26:00 2017-09-27 17:49:00 35.87
2017-09-27 17:58:00 2017-09-27 18:46:00 27.64
2017-09-27 18:51:00 2017-09-27 18:59:00 2.08
2017-09-27 19:10:00 2017-09-27 20:17:00 21.17
2017-09-27 20:25:00 2017-09-27 21:56:00 3.6
2017-09-27 22:04:00 2017-09-27 22:32:00 16.56
2017-09-28 06:46:00 2017-09-28 07:19:00 14.4
2017-09-28 09:05:00 2017-09-28 09:29:00 8.06
2017-09-28 10:41:00 2017-09-28 11:21:00 22.34
2017-09-28 14:26:00 2017-09-28 16:05:00 35.57
2017-09-28 16:09:00 2017-09-28 16:21:00 1.17
2017-09-28 20:37:00 2017-09-28 20:40:00 1.1
2017-09-28 20:56:00 2017-09-28 21:00:00 1.15
2017-09-29 09:32:00 2017-09-29 10:02:00 19.73
I'd like to plot these discrete events the same way the below plots do, but where 2pi is one week rather than 24 hours in order to illuminate the periodicity of these events, where color represents distance. 我想像下面的图一样绘制这些离散事件，但是2pi是一周而不是24小时，以便阐明这些事件的周期性，其中颜色表示距离。
I've attempted modifying the solution linked at the beginning of this question, but it hasn't gotten me anywhere. 我曾尝试修改此问题开头的链接解决方案，但它并没有帮助我。 My new approach is to modify this solution , but I'm having a difficult time getting anything but horizontal and vertical lines scattered about a spiral. 我的新方法是修改此解决方案 ，但是除了水平和垂直线围绕螺旋形散布之外，我很难获得其他任何东西。 Making them curve and display in the correct locations is tough. 使它们弯曲并显示在正确的位置非常困难。
I'm open to any approach that successfully displays the data in a spiral plot without quantizing/binning it into specific intervals but rather allows the intervals themselves to describe discrete events along a continuous spiralling timeline. 我愿意接受任何方法来成功地在螺旋图中显示数据，而无需将其量化/组合为特定间隔，而是允许间隔本身描述沿连续螺旋时间轴的离散事件。 Likewise, I'm not interested in converting this to a raw single-point time series format where I'd have a great deal of data representing the time between trips. 同样，我对将其转换为原始的单点时间序列格式不感兴趣，在该格式中，我将有大量数据表示旅行之间的时间。 I'd like to achieve this in a temporal format (one that describes a time window rather than an event at a particular time). 我想以一种时间格式（一种描述时间窗口而不是特定时间的事件）来实现这一目标。
3 个解决方案
解决方案1
16 已采纳 2018-05-18 08:34:25
Still needs work, but it's a start, with python and matplotlib. 仍然需要工作，但这是从python和matplotlib开始的。
The idea is to plot a spiral timeline in polar coordinates with 1 week period, each event is an arc of this spiral with a color depending on dist data. 这个想法是在极坐标中绘制一个螺旋时间轴，周期为1周，每个事件都是该螺旋的弧线，其颜色取决于dist数据。
There are lots of overlapping intervals though that this visualization tends to hide... maybe semitransparent arcs could be better, with a carefully chosen colormap. 尽管有很多重叠的时间间隔，但这种可视化效果往往会隐藏起来……如果精心选择颜色表，半透明的弧可能会更好。
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.patheffects as mpe
import pandas as pd
# styling
LINEWIDTH=4
EDGEWIDTH=1
CAPSTYLE="projecting"
COLORMAP="viridis_r"
ALPHA=1
FIRSTDAY=6 # 0=Mon, 6=Sun
# load dataset and parse timestamps
df = pd.read_csv('trips.csv')
df[['trip_start', 'trip_stop']] = df[['trip_start', 'trip_stop']].apply(pd.to_datetime)
# set origin at the first FIRSTDAY before the first trip, midnight
first_trip = df['trip_start'].min()
origin = (first_trip - pd.to_timedelta(first_trip.weekday() - FIRSTDAY, unit='d')).replace(hour=0, minute=0, second=0)
weekdays = pd.date_range(origin, origin + np.timedelta64(1, 'W')).strftime("%a").tolist()
# # convert trip timestamps to week fractions
df['start'] = (df['trip_start'] - origin) / np.timedelta64(1, 'W')
df['stop'] = (df['trip_stop'] - origin) / np.timedelta64(1, 'W')
# sort dataset so shortest trips are plotted last
# should prevent longer events to cover shorter ones, still suboptimal
df = df.sort_values('dist', ascending=False).reset_index()
fig = plt.figure(figsize=(8, 6))
ax = fig.gca(projection="polar")
for idx, event in df.iterrows():
# sample normalized distance from colormap
ndist = event['dist'] / df['dist'].max()
color = plt.cm.get_cmap(COLORMAP)(ndist)
tstart, tstop = event.loc[['start', 'stop']]
# timestamps are in week fractions, 2pi is one week
nsamples = int(1000. * (tstop - tstart))
t = np.linspace(tstart, tstop, nsamples)
theta = 2 * np.pi * t
arc, = ax.plot(theta, t, lw=LINEWIDTH, color=color, solid_capstyle=CAPSTYLE, alpha=ALPHA)
if EDGEWIDTH > 0:
arc.set_path_effects([mpe.Stroke(linewidth=LINEWIDTH+EDGEWIDTH, foreground='black'), mpe.Normal()])
# grid and labels
ax.set_rticks([])
ax.set_theta_zero_location("N")
ax.set_theta_direction(-1)
ax.set_xticks(np.linspace(0, 2*np.pi, 7, endpoint=False))
ax.set_xticklabels(weekdays)
ax.tick_params('x', pad=2)
ax.grid(True)
# setup a custom colorbar, everything's always a bit tricky with mpl colorbars
vmin = df['dist'].min()
vmax = df['dist'].max()
norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
sm = plt.cm.ScalarMappable(cmap=COLORMAP, norm=norm)
sm.set_array([])
plt.colorbar(sm, ticks=np.linspace(vmin, vmax, 10), fraction=0.04, aspect=60, pad=0.1, label="distance", ax=ax)
plt.savefig("spiral.png", pad_inches=0, bbox_inches="tight")
Full timeline 完整时间表
To see it's a spiral that never overlaps and it works for longer events too you can plot the full timeline (here with LINEWIDTH=3.5 to limit moiré fringing). 要查看这是一个永不重叠的螺旋线，它也适用于较长的事件，您也可以绘制完整的时间线（此处使用LINEWIDTH=3.5来限制莫尔条纹）。
fullt = np.linspace(df['start'].min(), df['stop'].max(), 10000)
theta = 2 * np.pi * fullt
ax.plot(theta, fullt, lw=LINEWIDTH,
path_effects=[mpe.Stroke(linewidth=LINEWIDTH+LINEBORDER, foreground='black'), mpe.Normal()])
Example with a random set... 带有随机集的示例...
Here's the plot for a random dataset of 200 mainly short trips with the occasional 1 to 2 weeks long ones. 这是一个随机数据集的图，该数据集包含200主要是短途旅行，偶尔还有1-2周的长途旅行。
N = 200
df = pd.DataFrame()
df["start"] = np.random.uniform(0, 20, size=N)
df["stop"] = df["start"] + np.random.choice([np.random.uniform(0, 0.1),
np.random.uniform(1., 2.)], p=[0.98, 0.02], size=N)
df["dist"] = np.random.random(size=N)
... and different styles ...以及不同的风格
inferno_r color map, rounded or butted linecaps, semitransparent, bolder edges, etc ( click for full size ) inferno_r颜色图，圆形或对接的线帽，半透明，较粗的边缘等（ 点击查看大图 ）
解决方案2
7 2017-10-05 03:00:29
Here's a start. 这是一个开始。 Let me know if this is what you had in mind. 让我知道您是否打算这样做。
I began with your data sample and put trip_start and trip_stop into POSIXct format before continuing with the code below. 我从您的数据样本开始，然后将trip_start和trip_stop为POSIXct格式，然后继续下面的代码。
library(tidyverse)
library(lubridate)
dat = dat %>%
mutate(start=(hour(trip_start)*60 + minute(trip_start) + second(trip_start))/(24*60) + wday(trip_start),
stop=(hour(trip_stop)*60 + minute(trip_stop) + second(trip_stop))/(24*60) + wday(trip_stop),
tod = case_when(hour(trip_start) < 6 ~ "night",
hour(trip_start) < 12 ~ "morning",
hour(trip_start) < 18 ~ "afternoon",
hour(trip_start) < 24 ~ "evening"))
ggplot(dat) +
geom_segment(aes(x=start, xend=stop,
y=trip_start,
yend=trip_stop,
colour=tod),
size=5, show.legend = FALSE) +
coord_polar() +
scale_y_datetime(breaks=seq(as.POSIXct("2017-09-01"), as.POSIXct("2017-12-31"), by="week")) +
scale_x_continuous(limits=c(1,8), breaks=1:7,
labels=weekdays(x=as.Date(seq(7)+2, origin="1970-01-01"),
abbreviate=TRUE))+
expand_limits(y=as.POSIXct("2017-08-25")) +
theme_bw() +
scale_colour_manual(values=c(night="black", morning="orange",
afternoon="orange", evening="blue")) +
labs(x="",y="")
解决方案3
7 2018-05-23 10:24:39
This could be achieved relatively straightforwardly with d3. 使用d3可以相对直接地实现这一点。 I'll use your data to create a rough template of one basic possible approach. 我将使用您的数据创建一种可能的基本方法的粗略模板。 Here's what the result of this approach might look like: 这种方法的结果如下所示：
The key ingredient is d3's radial line component that lets us define a line by plotting angle and radius ( here's a recent answer showing another spiral graph, that answer started me down the path on this answer). 关键因素是d3的径向线分量，它使我们能够通过绘制角度和半径来定义一条线（ 这是一个最近的答案，显示了另一个螺旋图，该答案使我沿着这个答案开始了。）
All we need to do is scale angle and radius to be able to use this effectively (for which we need the first time and last time in the dataset): 我们需要做的就是缩放角度和半径，以便能够有效地使用它（为此，我们需要数据集中的第一次和最后一次）：
var angle = d3.scaleTime()
.domain([start,end])
.range([0,Math.PI * 2 * numberWeeks])
var radius = d3.scaleTime()
.domain([start,end])
.range([minInnerRadius,maxOuterRadius])
And from there we can create a spiral quite easily, we sample some dates throughout the interval and then pass them to the radial line function: 从那里我们可以很容易地创建一个螺旋，我们在整个间隔中对一些日期进行采样，然后将它们传递给径向线函数：
var spiral = d3.radialLine()
.curve(d3.curveCardinal)
.angle(angle)
.radius(radius);
Here's a quick demonstration of just the spiral covering your time period. 这是覆盖您时间段的螺旋式的快速演示 。 I'm assuming a base familiarity with d3 for this answer, so have not touched on a few parts of the code. 我假设这个答案对d3基本熟悉，所以没有涉及代码的某些部分。
Once we have that, it's just a matter of adding sections from the data. 一旦有了这些，只需添加数据中的部分即可。 The most simple way would be to plainly draw a stroke with some width and color it appropriately. 最简单的方法是简单地绘制具有一定宽度的笔触，并对其进行适当的着色。 This requires the same as above, but rather than sampling points from the start and end times of the dataset, we just need the start and end times of each datum: 这需要与上述相同，但是我们不需要从数据集的开始和结束时间采样点，而是只需要每个数据的开始和结束时间：
// append segments on spiral:
var segments = g.selectAll()
.data(data)
.enter()
.append("path")
.attr("d", function(d) {
return /* sample points and feed to spiral function here */;
})
.style("stroke-width", /* appropriate width here */ )
.style("stroke",function(d) { return /* color logic here */ })
This might look something like this (with data mouseover). 这可能看起来像这样 （带有数据鼠标悬停）。
This is just a proof of concept, if you were looking for more control and a nicer look, you could create a polygonal path for each data entry and use both fill & stroke. 这只是概念上的证明，如果您希望获得更多的控制和更好的外观，则可以为每个数据条目创建一个多边形路径，并同时使用填充和描边。 As is, you'll have to make do with layering strokes to get borders if desired and svg manipulations like line capping options. 照原样，如果需要，您将不得不使用分层笔触来获得边框，并进行诸如行上限选项之类的svg操作。
Also, as it's d3, and longer timespans may be hard to show all at once, you could show less time but rotate the spiral so that it animates through your time span, dropping off events at the end and creating them in the origin. 另外，由于它是d3，因此可能很难一次显示较长的时间跨度，因此您可以显示较少的时间，但可以旋转螺旋线，以使其在整个时间跨度中呈现动画效果，并在事件的末尾放下事件并在源中创建它们。 The actual chart might need to be canvas for this to happen smoothly depending on number of nodes, but to convert to canvas is relatively trivial in this case. 实际的图表可能需要是画布，才能使此过程顺利进行，具体取决于节点数，但是在这种情况下，转换为画布相对来说并不容易。
For the sake of filling out the visualization a little with a legend and day labels, this is what I have. 为了给可视化添加一些图例和日期标签， 这就是我所拥有的。
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