如何在ggplot2中对两条线之间的区域进行着色/着色？

Question

我想用两条线绘制一个图，分别代表观测数据和来自特殊模型的数据。还有另外两条线表示其他模型的可变性的最大值和最小值。目标是将这两条线之间的区域涂成灰色，以便前两条线仍然可见。

这里是重现数据的代码：

# create the data set
Month.vec <- c(1:12)
Model.vec <- c(70.33056, 58.91058, 73.40891, 74.42824, 108.45975, 125.85887, 126.02867, 102.54128, 70.66263, 61.30316, 66.04057, 75.75262)
Obs.vec <- c(62.64178, 52.39356, 63.07376, 52.87248, 70.80587, 81.85081, 88.29134, 77.22920, 67.67458, 64.74425, 63.96322, 69.89868)
Up_lim.vec <- c(83.46967, 71.27700,  86.43001,  77.62739, 108.32674, 112.61118, 125.43512,  93.71193,  80.17298,  75.01851,  79.05700,  85.40042)
Low_lim.vec <- c(76.44381, 65.19571, 74.27778, 59.91012, 82.14684, 84.09151, 77.91529, 66.21702, 60.89712, 67.85613, 72.49409, 79.13741)
df <- as.data.frame(cbind(Month.vec, Obs.vec, Model.vec, Up_lim.vec, Low_lim.vec))
colnames(df) <- c("Month", "Observation", "Model", "Upper Limit", "Lower Limit")

四线的“正常”图很容易完成：

# plot 
df %>% 
  as_tibble() %>% 
  pivot_longer(-1) %>% 
  ggplot(aes(Month, value, color = name)) + 
  scale_color_manual("",values= c("blue", "yellow", "red", "black")) +
  scale_x_continuous(breaks = seq(1, 12, by = 1)) +
  scale_y_continuous(breaks = seq(0, 140, by = 20)) +
  ylab("Precipitation [mm]") +
  geom_line() +
  theme_bw()

这会导致以下输出：

所以想法是黑线和蓝线之间的区域用灰色或类似的颜色着色，这样蓝线和黄线仍然可见。

this 问题的结果应该看起来像这样：

我知道这里有一些类似的问题，其中大多数暗示使用geom_ribbon。 我试过了，但只收到以下错误消息：

Error: Aesthetics must be either length 1 or the same as the data (48): ymax and ymin

有人知道怎么做吗？

Answer 1

我认为将数据保存为更宽的格式然后使用geom_ribbon 创建阴影区域会更容易：

df %>% 
  as_tibble() %>% 
  ggplot +
  geom_line(aes(Month, Model, color = 'Model')) +
  geom_line(aes(Month, Observation, color = 'Observation')) +
  geom_ribbon(aes(Month, ymax=`Upper Limit`, ymin=`Lower Limit`), fill="grey", alpha=0.25) +
  scale_x_continuous(breaks = seq(1, 12, by = 1)) +
  scale_y_continuous(breaks = seq(0, 140, by = 20)) +
  scale_color_manual(values = c('Model' = 'yellow','Observation' = 'red')) +
  ylab("Precipitation [mm]") +
  theme_bw() +
  theme(legend.title = element_blank())

Answer 2

如果您想保留 Upper Limit 和 Lower Limit 行，您可以为功能区创建一个数据框（尽管不可否认，它的解决方案不如上面的优雅）：

library(stringr)

df <- df %>% 
  as_tibble() %>% 
  pivot_longer(-1)

ribbon_df <- df %>% filter(str_detect(name, "Limit")) %>%
    pivot_wider(names_from = name, values_from = value) %>%
    mutate(value = `Upper Limit` ) %>%
    mutate(name = "Upper Limit")

df %>% ggplot(aes(Month, value, color = name)) + 
    scale_color_manual("",values= c("blue", "yellow", "red", "black")) +
    scale_x_continuous(breaks = seq(1, 12, by = 1)) +
    scale_y_continuous(breaks = seq(0, 140, by = 20)) +
    ylab("Precipitation [mm]") +
    geom_ribbon(data = ribbon_df, aes(ymin = `Lower Limit`, ymax = `Upper Limit`), fill = "grey") + 
    geom_line() +
    theme_bw()

Answer 3

如果您使用较长的格式，则需要一个宽表来存储 geom_ribbon 数据。

library(tidyverse)
# create the data set
Month.vec <- c(1:12)
Model.vec <- c(70.33056, 58.91058, 73.40891, 74.42824, 108.45975, 125.85887, 126.02867, 102.54128, 70.66263, 61.30316, 66.04057, 75.75262)
Obs.vec <- c(62.64178, 52.39356, 63.07376, 52.87248, 70.80587, 81.85081, 88.29134, 77.22920, 67.67458, 64.74425, 63.96322, 69.89868)
Up_lim.vec <- c(83.46967, 71.27700,  86.43001,  77.62739, 108.32674, 112.61118, 125.43512,  93.71193,  80.17298,  75.01851,  79.05700,  85.40042)
Low_lim.vec <- c(76.44381, 65.19571, 74.27778, 59.91012, 82.14684, 84.09151, 77.91529, 66.21702, 60.89712, 67.85613, 72.49409, 79.13741)
df <- as.data.frame(cbind(Month.vec, Obs.vec, Model.vec, Up_lim.vec, Low_lim.vec))
colnames(df) <- c("Month", "Observation", "Model", "UL", "LL")

df_new <- df %>% 
  as_tibble() %>% 
  pivot_longer(-1)



  ggplot() + 
 # scale_color_manual("",values= c("blue", "yellow", "red", "black")) +
  scale_x_continuous(breaks = seq(1, 12, by = 1)) +
  scale_y_continuous(breaks = seq(0, 140, by = 20)) +
  ylab("Precipitation [mm]") +
  geom_line(data=df_new,aes(Month, value, color = name)) +
  geom_ribbon(data=df, aes(x=Month,ymin = LL, ymax = UL),alpha=0.5)
  theme_bw()

这会导致这个