自动突出显示值高于某个阈值的时间序列图部分的方法? [英] Automatic way to highlight parts of a time series plot that have values higher than a certain threshold?
本文介绍了自动突出显示值高于某个阈值的时间序列图部分的方法?的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我正在寻找一种自动方法来突出显示绘图中 Station2 值大于预定义阈值(在本例中为 0)的某些部分.检查绘图后，我可以通过在数据框 (dateRanges) 中指定 Date 来手动执行此操作.
提前感谢您的任何建议！
库(ggplot2)# 样本数据df <-结构(列表(日期=结构(c(15355L，15356L，15357L，15358L，15359L, 15360L, 15361L, 15362L, 15363L, 15364L, 15365L, 15366L,15367L、15368L、15369L、15370L、15371L、15372L、15373L、15374L、15375L、15376L、15377L、15378L、15379L、15380L、15381L、15382L、15383L、15384L、15385L、15386L、15387L、15388L、15389L、15390L、15391L、15392L、15393L、15394L、15355L、15356L、15357L、15358L、15359L, 15360L, 15361L, 15362L, 15363L, 15364L, 15365L, 15366L,15367L、15368L、15369L、15370L、15371L、15372L、15373L、15374L、15375L、15376L、15377L、15378L、15379L、15380L、15381L、15382L、15383L、15384L、15385L、15386L、15387L、15388L、15389L、15390L、15391L、15392L、15393L、15394L、15355L、15356L、15357L、15358L、15359L, 15360L, 15361L, 15362L, 15363L, 15364L, 15365L, 15366L,15367L、15368L、15369L、15370L、15371L、15372L、15373L、15374L、15375L、15376L、15377L、15378L、15379L、15380L、15381L、15382L、15383L、15384L、15385L、15386L、15387L、15388L、15389L、15390L、15391L, 15392L, 15393L, 15394L), class = "Date"), key = structure(c(1L,1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,2L，2L，2L，2L，2L，2L，2L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，1L，1L，1L，1L，1L，1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("Station1", "Station2","Temp."), class = "factor"), value = c(5277.9, 5254.8, 5207.1,5177.9、5594.7、11665.7、11630.8、13472.8、12738.1、7970.3、6750.3、7147.2、7013.5、6280.1、5879.4、5695.1、5570.4、5412.1、5199.2、5007.9、0、0、0、0、0、0、1600、2100、2100、1199.2、1017.6、1076.5、1054.9、944.2、589.2、570.7、558.1、542.2、0、0、46.6、45.7、46, 46.8, 46.8, 45, 45.1, 44.4, 46, 48, 49.5, 48.7, 47.3, 47.5,48.6、48.6、49.3、49.5、48.6、48.4、5006.3、5009.7、5220.5、7541.8、11472.3、12755、13028.2、11015.3、7998.4、6624、6065.7、5804.3、6852.9、7067.6、7103.7、7896.9、7805.5、15946.9、17949.6、13339.1、0、0、0、0、2100、2100、2100、2100、1604.5、996.5、912.5、582.3、1030.7、1063.1、1070.2、1188.8、1622.6、2100、2100、0、51.8、50.9、50.2、50.5、51.6、52、50.5、50.4、49.6、48.9、50.2、51.1、51.1, 50.5, 49.5, 49.8, 49.5, 49.5, 51.6, 51.1), grp = c("流量 (cfs)",流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流量(cfs)"，流量(cfs)"，流量(cfs)"，流量(cfs)"，温度(F)"，温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、流量 (cfs)"、流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流(cfs)"，流量(cfs)"，流量(cfs)"，流量(cfs)"，流量(cfs)"，温度(F)"，温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、温度 (F)"、"Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)")), class = c("tbl_df","tbl", "data.frame"), row.names = c(NA, -120L))头(df)#># 小标题:6 x 4#>日期键值 grp#><日期><事实><dbl><chr>#>1 2012-01-16 Station1 5278. 流量 (cfs)#>2 2012-01-17 Station1 5255. 流量 (cfs)#>3 2012-01-18 Station1 5207. 流量 (cfs)#>4 2012-01-19 Station1 5178. 流量(cfs)#>5 2012-01-20 Station1 5595. 流量 (cfs)#>6 2012-01-21 Station1 11666. 流量(cfs)# 基础图gg1 <- ggplot(df, aes(Date, value)) +geom_line(aes(group = key, color = key), size = 1) +facet_grid(grp ~ ., switch = 'y', scales = 'free_y') +scale_color_brewer("", 调色板 = "Dark2") +scale_x_date(date_breaks = "1 周", date_labels = "%d-%b") +实验室(x = "", y = "") +theme_bw(base_size = 16) +主题(strip.placement = '外部')+主题(图例.位置='底部')+主题(strip.background.y = element_blank()) +空值# 手动定义和绘制高亮时段dateRanges <- data.frame(从 = as.Date(c("2012-01-20", "2012-02-11")),to = as.Date(c("2012-02-04", "2012-02-23")))gg2 <- gg1 +geom_rect(数据=日期范围，aes(xmin = 从 - 1, xmax = to, ymin = -Inf, ymax = Inf),继承.aes = FALSE，颜色 = 'grey90',阿尔法 = 0.2)gg2由
I'm looking for an automatic way of highlighting some portions of the plot that have Station2 values greater than a pre-defined threshold which is 0 in this case. I can do it manually by specify the Date in a data frame (dateRanges) after inspecting the plot.
Thanks in advance for any suggestion!
library(ggplot2)
# sample data
df <- structure(list(Date = structure(c(15355L, 15356L, 15357L, 15358L,
15359L, 15360L, 15361L, 15362L, 15363L, 15364L, 15365L, 15366L,
15367L, 15368L, 15369L, 15370L, 15371L, 15372L, 15373L, 15374L,
15375L, 15376L, 15377L, 15378L, 15379L, 15380L, 15381L, 15382L,
15383L, 15384L, 15385L, 15386L, 15387L, 15388L, 15389L, 15390L,
15391L, 15392L, 15393L, 15394L, 15355L, 15356L, 15357L, 15358L,
15359L, 15360L, 15361L, 15362L, 15363L, 15364L, 15365L, 15366L,
15367L, 15368L, 15369L, 15370L, 15371L, 15372L, 15373L, 15374L,
15375L, 15376L, 15377L, 15378L, 15379L, 15380L, 15381L, 15382L,
15383L, 15384L, 15385L, 15386L, 15387L, 15388L, 15389L, 15390L,
15391L, 15392L, 15393L, 15394L, 15355L, 15356L, 15357L, 15358L,
15359L, 15360L, 15361L, 15362L, 15363L, 15364L, 15365L, 15366L,
15367L, 15368L, 15369L, 15370L, 15371L, 15372L, 15373L, 15374L,
15375L, 15376L, 15377L, 15378L, 15379L, 15380L, 15381L, 15382L,
15383L, 15384L, 15385L, 15386L, 15387L, 15388L, 15389L, 15390L,
15391L, 15392L, 15393L, 15394L), class = "Date"), key = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("Station1", "Station2",
"Temp."), class = "factor"), value = c(5277.9, 5254.8, 5207.1,
5177.9, 5594.7, 11665.7, 11630.8, 13472.8, 12738.1, 7970.3, 6750.3,
7147.2, 7013.5, 6280.1, 5879.4, 5695.1, 5570.4, 5412.1, 5199.2,
5007.9, 0, 0, 0, 0, 0, 0, 1600, 2100, 2100, 1199.2, 1017.6, 1076.5,
1054.9, 944.2, 589.2, 570.7, 558.1, 542.2, 0, 0, 46.6, 45.7,
46, 46.8, 46.8, 45, 45.1, 44.4, 46, 48, 49.5, 48.7, 47.3, 47.5,
48.6, 48.6, 49.3, 49.5, 48.6, 48.4, 5006.3, 5009.7, 5220.5, 7541.8,
11472.3, 12755, 13028.2, 11015.3, 7998.4, 6624, 6065.7, 5804.3,
6852.9, 7067.6, 7103.7, 7896.9, 7805.5, 15946.9, 17949.6, 13339.1,
0, 0, 0, 0, 2100, 2100, 2100, 2100, 1604.5, 996.5, 912.5, 582.3,
1030.7, 1063.1, 1070.2, 1188.8, 1622.6, 2100, 2100, 0, 51.8,
50.9, 50.2, 50.5, 51.6, 52, 50.5, 50.4, 49.6, 48.9, 50.2, 51.1,
51.1, 50.5, 49.5, 49.8, 49.5, 49.5, 51.6, 51.1), grp = c("Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Temp. (F)",
"Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)",
"Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)",
"Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)",
"Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)",
"Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Flow (cfs)", "Temp. (F)",
"Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)",
"Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)",
"Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)",
"Temp. (F)", "Temp. (F)", "Temp. (F)", "Temp. (F)")), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -120L))
head(df)
#> # A tibble: 6 x 4
#> Date key value grp
#> <date> <fct> <dbl> <chr>
#> 1 2012-01-16 Station1 5278. Flow (cfs)
#> 2 2012-01-17 Station1 5255. Flow (cfs)
#> 3 2012-01-18 Station1 5207. Flow (cfs)
#> 4 2012-01-19 Station1 5178. Flow (cfs)
#> 5 2012-01-20 Station1 5595. Flow (cfs)
#> 6 2012-01-21 Station1 11666. Flow (cfs)
# base plot
gg1 <- ggplot(df, aes(Date, value)) +
geom_line(aes(group = key, color = key), size = 1) +
facet_grid(grp ~ ., switch = 'y', scales = 'free_y') +
scale_color_brewer("", palette = "Dark2") +
scale_x_date(date_breaks = "1 week", date_labels = "%d-%b") +
labs(x = "", y = "") +
theme_bw(base_size = 16) +
theme(strip.placement = 'outside') +
theme(legend.position = 'bottom') +
theme(strip.background.y = element_blank()) +
NULL
# define and plot the highlight period manually
dateRanges <- data.frame(
from = as.Date(c("2012-01-20", "2012-02-11")),
to = as.Date(c("2012-02-04", "2012-02-23"))
)
gg2 <- gg1 +
geom_rect(data = dateRanges,
aes(xmin = from - 1, xmax = to, ymin = -Inf, ymax = Inf),
inherit.aes = FALSE,
color = 'grey90',
alpha = 0.2)
gg2
Created on 2019-06-28 by the reprex package (v0.3.0)
解决方案
Here's a way using dplyr and tidyr from the tidyverse meta-package to create one rect per positive range of Station2 Flow:
First I isolate Station2's Flow rows, then filter for the zeros before or after positive values, then gather and spread to create a start and end for each contiguous section:
library(tidyverse)
dateRanges <- df %>%
filter(key == "Station2", grp == "Flow (cfs)") %>%
mutate(from = value == 0 & lead(value, default = -1) > 0,
to = value == 0 & lag(value, default = -1) > 0,
highlight_num = cumsum(from)) %>%
gather(type, val, from:to) %>%
filter(val) %>%
select(type, Date, highlight_num) %>%
spread(type, Date)
> dateRanges
# A tibble: 2 x 3
highlight_num from to
<int> <date> <date>
1 1 2012-02-10 2012-02-23
2 2 2012-01-19 2012-02-04
Note, my range specifications are a bit different here, since it looks like your ranges start from the first positive value but continue to the zero following a positive range. For my code, you'd plot:
...
geom_rect(data = dateRanges,
aes(xmin = from, xmax = to, ymin = -Inf, ymax = Inf),
...
Edit #2:
The original poster provided a larger sample of data that exposed two edge cases I hadn't considered. 1) NA's in value; easy to filter for. 2) occasions where a single day goes to zero, thus being both the start and end of a range. One approach to deal with this is to define the start and end as the first and last positive values. The code below seemed to work on the larger data.
dateRanges <- df %>%
filter(!is.na(value)) %>%
filter(key == "Station2", grp == "Flow (cfs)") %>%
mutate(positive = value > 0,
border = positive != lag(positive, default = TRUE),
from = border & positive,
to = border & !positive,
highlight_num = cumsum(from)) %>%
gather(type, val, from:to) %>%
filter(val) %>%
select(type, Date, highlight_num) %>%
spread(type, Date) %>%
filter(!is.na(from), !is.na(to))
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