在两个不同（“网格排列”）图之间绘制线

因此，我设法创建了两个ggplot-graphs并将它们与完美对齐grid.arrange。现在，我想将箱线图的最小值，1Q，3Q和最大值与左侧图中的分布联系起来。我geom_hline在两个图中都绘制了水平（红色条纹）线，但是我想将这些线连接起来，所以也要遍历两个图之间的空白。有什么建议么？这是图形：

噢，是的，复杂的因素是：正确的图形的坐标被翻转了！

这是一个可重现的示例：

library(ggplot2)
library(scales)
library(gridExtra)

# create some data
df_ahn <- data.frame(yh=rnorm(1000,0.23,0.05))
df_peil <- data.frame(hoogte = rnorm(1000,0,1))

# vector met de hoogtes
Summary_df <- summary(df_ahn$yh)

p_peil <- ggplot(df_peil,aes(x=hoogte))+
  geom_histogram(aes(y=cumsum((..count..)/sum(..count..))), binwidth = 0.01,fill="gray")+
  stat_bin(aes(y=cumsum((..count..)/sum(..count..))),binwidth = 0.01,geom="line",color="black") +
  geom_vline(aes(xintercept = as.vector(Summary_df[1])), lty = 2,color =2)+
  geom_vline(aes(xintercept = as.vector(Summary_df[2])), lty = 2,color =2)+
  geom_vline(aes(xintercept = as.vector(Summary_df[5])), lty = 2,color =2)+
  geom_vline(aes(xintercept = as.vector(Summary_df[6])), lty = 2,color =2)+
  coord_flip() +
  ggtitle("Onderschrijdingsfrequentie\n waterstand in kreek") +
  xlab("Hoogte in meter NAP") +
  ylab("Onderschrijdingsfrequentie in % (10% = 36,5 dagen/jaar)") +
  scale_y_continuous(limits = c(0, 1),labels = percent, breaks=seq(0,1,by=0.1)) +
  scale_x_continuous(limits = c(-0.5, 0.6), breaks=seq(-0.5,0.6,by=0.1)) +
  theme(panel.background = element_rect(fill = "transparent",colour = "black"),
        panel.grid.major = element_line(colour = "darkgray"),
        panel.grid.minor = element_line(colour = "gray"),
        strip.background = element_rect(fill="gray"),
        strip.text = element_text(size=14, color="black"),
        axis.ticks.y = element_line(colour = "black"),
        axis.ticks.x = element_line(colour = "black"),
        axis.text.x = element_text(size=14, color="black"),
        axis.text.y = element_text(size=14, color="black"),
        axis.title = element_text(size=14, color="black")
  )

p_ahn <-    ggplot(df_ahn, aes(x=1, y=yh)) +
  geom_boxplot(outlier.size=3, outlier.shape=1) +
  geom_hline(aes(yintercept = as.vector(Summary_df[1])), lty = 2,color =2)+
  geom_hline(aes(yintercept = as.vector(Summary_df[2])), lty = 2,color =2)+
  geom_hline(aes(yintercept = as.vector(Summary_df[5])), lty = 2,color =2)+
  geom_hline(aes(yintercept = as.vector(Summary_df[6])), lty = 2,color =2)+
  scale_y_continuous(limits = c(-0.5,0.6), breaks=seq(-0.5,0.6,by=0.1)) +
  ggtitle("Hoogte groeiplaatsen\nKruipend moerascherm") +
  ylab("") +
  xlab("") +
  theme(panel.background = element_rect(fill = "transparent",colour = "black"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        strip.background = element_rect(fill="gray"),
        strip.text = element_text(size=14, color="black"),
        axis.ticks.y = element_line(colour = "black"),
        axis.ticks.x = element_line(colour = "white"),
        axis.text.x = element_text(size=14, color="white"),
        axis.text.y = element_text(size=14, color="black"),
        axis.title = element_text(size=14, color="black", face="bold")

  ) 
grid.arrange(p_peil,p_ahn, layout_matrix = matrix(c(1,1,1,2), nrow=1, byrow=TRUE), ncol = 4)