使用 R 的持续时间和强度直方图
Historgram of duration and intensity using R
我有以下数据文件。这是每日降雨数据，有四列（YY、MM、DD、RR）。抱歉，这是我可以生成的最小数据。
structure(list(YY = c(1979L, 1979L, 1979L, 1979L, 1979L, 1979L,
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L,
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L,
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1980L, 1980L,
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L,
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L,
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L,
1980L, 1980L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L,
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L,
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L,
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1982L, 1982L, 1982L,
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L,
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L,
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L,
1982L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L,
1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L,
1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L,
1983L, 1983L, 1983L, 1983L, 1983L, 1984L, 1984L, 1984L, 1984L,
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L,
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L,
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L,
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L,
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L,
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L,
1985L, 1985L, 1985L, 1985L, 1986L, 1986L, 1986L, 1986L, 1986L,
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L,
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L,
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1987L,
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L,
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L,
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L,
1987L, 1987L, 1987L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L,
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L,
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L,
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1989L, 1989L,
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L,
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L,
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L,
1989L, 1989L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L,
1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L,
1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L,
1990L, 1990L, 1990L, 1990L, 1990L, 1990L), MM = c(10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L), DD = c(1L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L,
21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L,
17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L,
30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L,
13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L,
26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L,
22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L,
18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L,
31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L,
14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L,
27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L,
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L,
23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L,
5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L,
19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L,
28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L,
24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L,
7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L,
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L,
29L, 30L, 31L), RR = c(65.3, 2.6, 3.8, 93.5, 0, 0, 1, 0, 0, 0,
20.6, 3.4, 0, 0, 0, 0, 0, 0, 29.2, 6.6, 0.5, 1, 18.5, 3.3, 0,
2, 2.8, 0, 0, 12.8, 15.8, 0, 1.6, 0.3, 25, 3.6, 0, 19.6, 1.8,
0, 0, 0, 0, 25.9, 0, 6.6, 15.7, 1.3, 30, 0, 0, 0, 0.5, 17, 14.7,
6.1, 0.5, 67.6, 133.8, 114.6, 0, 0, 0, 25.1, 1.8, 1.4, 0, 0,
0, 0, 0, 2, 55.7, 36.9, 65, 3.1, 0, 0, 0, 0, 0, 0, 0, 41.4, 13.2,
29.8, 1, 170.7, 115, 72.9, 25.9, 18, 15.7, 1.3, 4, 0, 0, 0, 8.9,
0, 1, 0, 0, 6.1, 9.4, 21.6, 11, 13.1, 2.3, 0, 11.3, 4.9, 0.8,
0, 0.3, 0, 0, 0, 0.3, 6.4, 0, 0, 2.3, 6.9, 21.4, 57.7, 0.3, 35.5,
2.3, 0, 8.1, 0, 0, 108.2, 7.1, 8.2, 9.4, 14.2, 42.7, 0, 0, 1.3,
0, 45.2, 203.2, 14.5, 9.2, 22.2, 2.9, 0, 59.5, 19.9, 162.9, 0,
1, 0, 0, 0, 1.8, 9.9, 54, 8.1, 9.4, 0, 0.8, 0, 0, 0, 0, 0.3,
0, 0, 7.4, 28.5, 101.2, 87.9, 26.9, 128.9, 78.1, 3.6, 0, 0, 77.5,
130.1, 262.5, 105.5, 14.9, 0, 0, 0, 2.5, 2.3, 15.5, 28.8, 4.6,
34.8, 22.1, 60.5, 0.5, 24.1, 0, 0, 37, 128.3, 26, 27.8, 2.3,
2.3, 195.9, 227.7, 0.8, 2.8, 0, 0, 5.1, 0.3, 0, 0, 0, 0, 9.7,
125.9, 64.9, 78.3, 3.3, 0, 0, 46.2, 52.6, 3, 24.9, 22.1, 14.2,
0, 0, 170.6, 64.5, 30.3, 35.8, 204.5, 5.3, 0.5, 3.1, 0, 0, 17.2,
136.6, 37.9, 0.8, 0, 0.3, 5.1, 2.4, 0, 9.8, 0, 0, 0, 0.2, 0,
0.3, 0, 0.3, 1.5, 1, 0, 0, 0, 0, 0, 0.8, 1.3, 7.8, 0, 12, 25.2,
74.3, 26.5, 1.6, 11.2, 0, 0, 0, 0, 5.4, 186.1, 99.7, 46.3, 2.8,
7.6, 5.6, 22.9, 81, 2, 0, 7.1, 24, 68, 121.8, 10.4, 0, 24.4,
77.1, 18, 8.9, 0.8, 0, 18.6, 0, 2, 1.3, 0, 18.8, 0, 0, 8.6, 5.6,
0, 0.5, 61.8, 146.6, 16.5, 0, 18.6, 0, 0, 0, 8.1, 59.4, 8.5,
1, 54.8, 0, 21.6, 0, 0, 0, 0, 0, 0, 0, 44.2, 0.5, 0, 1.3, 0,
1.8, 1, 0, 9.7, 93.5, 48.5, 158.3, 78.5, 2.8, 4.1, 13, 98.8,
55.2, 76.3, 56.3, 0, 6.1, 0, 0, 0, 0, 5.3, 0, 14.5, 0, 0)), row.names =
c(274L,
275L, 276L, 277L, 278L, 279L, 280L, 281L, 282L, 283L, 284L, 285L,
286L, 287L, 288L, 289L, 290L, 291L, 292L, 293L, 294L, 295L, 296L,
297L, 298L, 299L, 300L, 301L, 302L, 303L, 304L, 640L, 641L, 642L,
643L, 644L, 645L, 646L, 647L, 648L, 649L, 650L, 651L, 652L, 653L,
654L, 655L, 656L, 657L, 658L, 659L, 660L, 661L, 662L, 663L, 664L,
665L, 666L, 667L, 668L, 669L, 670L, 1005L, 1006L, 1007L, 1008L,
1009L, 1010L, 1011L, 1012L, 1013L, 1014L, 1015L, 1016L, 1017L,
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), class = "data.frame")
我想：
[1] 获取超过长期每月第 95 个百分位数的天数。
[2] 绘制持续时间的直方图（即连续事件的数量，因此计数与持续时间）
[3] 绘制强度直方图（即发生频率与降雨值）
我要做到的：
代码：
thresh<-quantile(dat$RR,0.95,na.rm=T)
extreme<-dat[which(dat$RR>=thresh),]
hist(extreme$RR)
我可以做 [1] 和 [3]，但我无法绘制 [2]。如何获取唯一事件的长度并绘制其直方图？
我想统计有多少事件只有 1 天持续时间、连续 2 天持续时间、连续 3 天持续时间。然后绘制这个的直方图。
我认为 rle 会满足您的需求。但是，您目前没有按月计算分位数，我们可以使用 dplyr 中的 group_by。
library(dplyr)
dat2 <- dat %>%
group_by(YY,MM) %>%
mutate(extreme = RR > quantile(RR,0.95,na.rm=TRUE))
# A tibble: 372 x 5
# Groups: YY, MM [12]
YY MM DD RR extreme
<int> <int> <int> <dbl> <lgl>
1 1979 10 1 65.3 TRUE
2 1979 10 2 2.6 FALSE
3 1979 10 3 3.8 FALSE
4 1979 10 4 93.5 TRUE
5 1979 10 5 0 FALSE
6 1979 10 6 0 FALSE
7 1979 10 7 1 FALSE
8 1979 10 8 0 FALSE
9 1979 10 9 0 FALSE
10 1979 10 10 0 FALSE
# … with 362 more rows
现在我们可以使用rle来获取事件之间的长度：
result <- rle(dat2$extreme)
result
#Run Length Encoding
# lengths: int [1:36] 1 2 1 54 2 27 2 16 1 1 ...
# values : logi [1:36] TRUE FALSE TRUE FALSE TRUE FALSE ...
result$lengths[result$values]
[1] 1 1 2 2 1 1 1 1 2 2 1 1 2 1 1 2 1 1
hist(result$lengths[result$values],breaks = c(0:5), xlab = "Length of extreme events", main = "")
我有以下数据文件。这是每日降雨数据，有四列（YY、MM、DD、RR）。抱歉，这是我可以生成的最小数据。
structure(list(YY = c(1979L, 1979L, 1979L, 1979L, 1979L, 1979L,
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L,
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L,
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1980L, 1980L,
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L,
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L,
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L,
1980L, 1980L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L,
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L,
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L,
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1982L, 1982L, 1982L,
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L,
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L,
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L,
1982L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L,
1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L,
1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L,
1983L, 1983L, 1983L, 1983L, 1983L, 1984L, 1984L, 1984L, 1984L,
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L,
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L,
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L,
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L,
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L,
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L,
1985L, 1985L, 1985L, 1985L, 1986L, 1986L, 1986L, 1986L, 1986L,
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L,
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L,
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1987L,
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L,
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L,
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L,
1987L, 1987L, 1987L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L,
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L,
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L,
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1989L, 1989L,
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L,
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L,
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L,
1989L, 1989L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L,
1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L,
1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L,
1990L, 1990L, 1990L, 1990L, 1990L, 1990L), MM = c(10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L), DD = c(1L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L,
21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L,
17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L,
30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L,
13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L,
26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L,
22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L,
18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L,
31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L,
14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L,
27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L,
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L,
23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L,
5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L,
19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L,
28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L,
24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L,
7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L,
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L,
29L, 30L, 31L), RR = c(65.3, 2.6, 3.8, 93.5, 0, 0, 1, 0, 0, 0,
20.6, 3.4, 0, 0, 0, 0, 0, 0, 29.2, 6.6, 0.5, 1, 18.5, 3.3, 0,
2, 2.8, 0, 0, 12.8, 15.8, 0, 1.6, 0.3, 25, 3.6, 0, 19.6, 1.8,
0, 0, 0, 0, 25.9, 0, 6.6, 15.7, 1.3, 30, 0, 0, 0, 0.5, 17, 14.7,
6.1, 0.5, 67.6, 133.8, 114.6, 0, 0, 0, 25.1, 1.8, 1.4, 0, 0,
0, 0, 0, 2, 55.7, 36.9, 65, 3.1, 0, 0, 0, 0, 0, 0, 0, 41.4, 13.2,
29.8, 1, 170.7, 115, 72.9, 25.9, 18, 15.7, 1.3, 4, 0, 0, 0, 8.9,
0, 1, 0, 0, 6.1, 9.4, 21.6, 11, 13.1, 2.3, 0, 11.3, 4.9, 0.8,
0, 0.3, 0, 0, 0, 0.3, 6.4, 0, 0, 2.3, 6.9, 21.4, 57.7, 0.3, 35.5,
2.3, 0, 8.1, 0, 0, 108.2, 7.1, 8.2, 9.4, 14.2, 42.7, 0, 0, 1.3,
0, 45.2, 203.2, 14.5, 9.2, 22.2, 2.9, 0, 59.5, 19.9, 162.9, 0,
1, 0, 0, 0, 1.8, 9.9, 54, 8.1, 9.4, 0, 0.8, 0, 0, 0, 0, 0.3,
0, 0, 7.4, 28.5, 101.2, 87.9, 26.9, 128.9, 78.1, 3.6, 0, 0, 77.5,
130.1, 262.5, 105.5, 14.9, 0, 0, 0, 2.5, 2.3, 15.5, 28.8, 4.6,
34.8, 22.1, 60.5, 0.5, 24.1, 0, 0, 37, 128.3, 26, 27.8, 2.3,
2.3, 195.9, 227.7, 0.8, 2.8, 0, 0, 5.1, 0.3, 0, 0, 0, 0, 9.7,
125.9, 64.9, 78.3, 3.3, 0, 0, 46.2, 52.6, 3, 24.9, 22.1, 14.2,
0, 0, 170.6, 64.5, 30.3, 35.8, 204.5, 5.3, 0.5, 3.1, 0, 0, 17.2,
136.6, 37.9, 0.8, 0, 0.3, 5.1, 2.4, 0, 9.8, 0, 0, 0, 0.2, 0,
0.3, 0, 0.3, 1.5, 1, 0, 0, 0, 0, 0, 0.8, 1.3, 7.8, 0, 12, 25.2,
74.3, 26.5, 1.6, 11.2, 0, 0, 0, 0, 5.4, 186.1, 99.7, 46.3, 2.8,
7.6, 5.6, 22.9, 81, 2, 0, 7.1, 24, 68, 121.8, 10.4, 0, 24.4,
77.1, 18, 8.9, 0.8, 0, 18.6, 0, 2, 1.3, 0, 18.8, 0, 0, 8.6, 5.6,
0, 0.5, 61.8, 146.6, 16.5, 0, 18.6, 0, 0, 0, 8.1, 59.4, 8.5,
1, 54.8, 0, 21.6, 0, 0, 0, 0, 0, 0, 0, 44.2, 0.5, 0, 1.3, 0,
1.8, 1, 0, 9.7, 93.5, 48.5, 158.3, 78.5, 2.8, 4.1, 13, 98.8,
55.2, 76.3, 56.3, 0, 6.1, 0, 0, 0, 0, 5.3, 0, 14.5, 0, 0)), row.names =
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), class = "data.frame")
我想：
[1] 获取超过长期每月第 95 个百分位数的天数。
[2] 绘制持续时间的直方图（即连续事件的数量，因此计数与持续时间）
[3] 绘制强度直方图（即发生频率与降雨值）
我要做到的：
代码：
thresh<-quantile(dat$RR,0.95,na.rm=T)
extreme<-dat[which(dat$RR>=thresh),]
hist(extreme$RR)
我可以做 [1] 和 [3]，但我无法绘制 [2]。如何获取唯一事件的长度并绘制其直方图？
我想统计有多少事件只有 1 天持续时间、连续 2 天持续时间、连续 3 天持续时间。然后绘制这个的直方图。
我认为 rle 会满足您的需求。但是，您目前没有按月计算分位数，我们可以使用 dplyr 中的 group_by。
library(dplyr)
dat2 <- dat %>%
group_by(YY,MM) %>%
mutate(extreme = RR > quantile(RR,0.95,na.rm=TRUE))
# A tibble: 372 x 5
# Groups: YY, MM [12]
YY MM DD RR extreme
<int> <int> <int> <dbl> <lgl>
1 1979 10 1 65.3 TRUE
2 1979 10 2 2.6 FALSE
3 1979 10 3 3.8 FALSE
4 1979 10 4 93.5 TRUE
5 1979 10 5 0 FALSE
6 1979 10 6 0 FALSE
7 1979 10 7 1 FALSE
8 1979 10 8 0 FALSE
9 1979 10 9 0 FALSE
10 1979 10 10 0 FALSE
# … with 362 more rows
现在我们可以使用rle来获取事件之间的长度：
result <- rle(dat2$extreme)
result
#Run Length Encoding
# lengths: int [1:36] 1 2 1 54 2 27 2 16 1 1 ...
# values : logi [1:36] TRUE FALSE TRUE FALSE TRUE FALSE ...
result$lengths[result$values]
[1] 1 1 2 2 1 1 1 1 2 2 1 1 2 1 1 2 1 1
hist(result$lengths[result$values],breaks = c(0:5), xlab = "Length of extreme events", main = "")