R基础图形:使用布局重叠来自不同地块的轴记号标签

Question

我在基础图形中使用R的layout命令将堆叠的箱形图和曲线图堆叠在一起。这些图形看起来很棒，除了来自不同绘图的y轴标签重叠(以红色圆圈突出显示)：

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网上也有类似的问题，但都没有使用layout。

我不想扩大地块之间的空间，我不认为这看起来很好。

我已经尝试减小字体大小，但是标签仍然位于绘图区之外。如何设置R的箱图和曲线图，使刻度标签不会高于或低于上图中的红线，即最大/最小y值？

一些示例代码

legend_space <- -0.26
right <- 10.5
bottom <- 0
left <- 5
top <- 0
cex_main = 1
setEPS()
postscript('figure.eps')
g1 <- c()
g2 <- c()
p <- c()
percent <- c()
sum_p <- c()
sum_percent <- c()
g1_means <- c()
g2_means <- c()
xaxis <- c()
sum_p[1] <- 0.0430904
xaxis[1] <- 2984116
p[1] <- 0.0430904
percent[1] <- -65.1758
sum_percent[1] <- -65.1758
g1[1] <- list(c(47.058824,100.000000,100.000000))
g1_means[1] <- 84.482759
g2[1] <- list(c(13.750000,4.123711,96.000000))
g2_means[1] <- 19.306931
sum_p[2] <- 0.0443229
xaxis[2] <- 2984148
p[2] <- 0.0587825
percent[2] <- -73.8956
sum_percent[2] <- -69.332
g1[2] <- list(c(94.285714,94.736842,100.000000))
g1_means[2] <- 95.145631
g2[2] <- list(c(10.588235,0.000000,92.592593))
g2_means[2] <- 21.250000
sum_p[3] <- 0.0444647
xaxis[3] <- 2984157
p[3] <- 0.124606
percent[3] <- -40.2577
sum_percent[3] <- -60.3056
g1[3] <- list(c(76.315789,94.736842,64.705882))
g1_means[3] <- 83.928571
g2[3] <- list(c(63.529412,0.000000,60.000000))
g2_means[3] <- 43.670886
sum_p[4] <- 0.0393696
xaxis[4] <- 2984168
p[4] <- 0.0310268
percent[4] <- -38.4133
sum_percent[4] <- -54.7893
g1[4] <- list(c(59.459459,57.894737,100.000000))
g1_means[4] <- 64.864865
g2[4] <- list(c(35.294118,6.250000,36.363636))
g2_means[4] <- 26.451613
sum_p[5] <- 0.0304293
xaxis[5] <- 2984175
p[5] <- 0.0344261
percent[5] <- -50.5157
sum_percent[5] <- -54.0582
g1[5] <- list(c(62.500000,94.736842,100.000000))
g1_means[5] <- 85.849057
g2[5] <- list(c(52.873563,6.250000,26.666667))
g2_means[5] <- 35.333333
layout(matrix(c(0,0,1,1,2,2,3,3,4,4), nrow = 5, byrow = TRUE), heights = c(0.2,1,1,1,1.4))
par(mar = c(bottom, left, top, right))
boxplot(g1, xaxt = 'n', range = 0, ylab = '%', ylim = c(0,100), col = 'white', cex.lab=1.5, cex.axis=cex_main, cex.main=cex_main, cex.sub=1.5, xlim = c(0.5,length(g1)+0.5))
title('title', outer = TRUE, line = -1.5)
lines(g1_means, col='dark green', lwd = 3)
par(xpd=TRUE)
legend('topright',inset = c(legend_space,0), c('Control', 'Weighted Mean'), col = c('black','dark green'), lwd = c(1,3))
boxplot(g2, xaxt = 'n', range = 0, main = NULL, ylim = c(0,100), ylab = '%', col = 'gray',  cex.lab=1.5, cex.axis=cex_main, cex.main=cex_main, cex.sub=1.5, xlim = c(0.5,length(g2)+0.5))
lines(g2_means, col='dark green', lwd = 3)
par(xpd=TRUE)
legend('topright',inset = c(legend_space,0),c('Case', 'Weighted Mean'), col = c('black','dark green'), lwd = c(1,3))
par(mar = c(bottom, left, top, right))#'mar’ A numerical vector of the form 'c(bottom, left, top, right)’
plot(p, xaxt='n', ylab = 'P', type = 'l', lty = 1, lwd = 3, cex.lab=1.5, cex.axis=1, cex.main=cex_main, cex.sub=1.5, , log = 'y', xlim = c(0.5,length(p)+0.5), ylim = c(min(p,sum_p), max(p, sum_p)))
points(sum_p, xaxt='n', ylab = 'P', type = 'l', col = 'blue', lty = 2, lwd = 3)
legend('topright', inset=c(legend_space,0), c('CpG P', 'Moving P Mean'), col = c('black','blue'), lwd=c(3,3), lty=c(1,2))
par(mar = c(bottom+5, left, top, right))#'mar’ A numerical vector of the form 'c(bottom, left, top, right)’
plot(percent, xaxt='n', ylab = '% Diff.', xlab = 'CpG', type = 'l', lty = 1, lwd = 3, cex.lab=1.5, cex.axis=1, cex.main=cex_main, cex.sub=1.5, xlim = c(0.5,length(percent)+0.5), ylim = c(min(percent, sum_percent), max(percent, sum_percent)))
points(sum_percent, xaxt='n', xlab = 'CpG', type = 'l', col = 'blue', lty = 2, lwd = 3)
par(xpd=TRUE)
legend('topright', inset=c(legend_space,0), c('Percent', 'Moving Mean %'), col = c('black','blue'), lwd=c(3,3), lty=c(1,2))
axis( 1, at=1:length(xaxis), xaxis)
dev.off()

Answer 1

感谢@count，解决方案很简单，只需使用

par设置中的las=2。las=2设置要垂直读取的标签。