为 ggplot 2.2.0 破坏的 gtable_add_grob 代码寻求解决方法 [英] Seeking workaround for gtable_add_grob code broken by ggplot 2.2.0
问题描述
在具有多个构面变量的图中，ggplot2 为外部"变量重复构面标签，而不是在内部"变量的所有级别上使用单个跨越构面条.我有一些代码，我一直在使用这些代码使用 gtable 包中的 gtable_add_grob 用单个跨越面带覆盖重复的外面标签.
不幸的是，由于刻面条的 grob 结构发生了变化，此代码不再适用于 ggplot2 2.2.0.具体来说，在以前版本的 ggplot2 中，每行方面标签都有自己的一组 grobs.然而，在 2.2.0 版本中，每个垂直的刻面标签堆栈看起来都是一个单一的 grob.这破坏了我的代码，我不知道如何修复它.
这是一个具体的例子，取自
现在我们将用跨越条覆盖顶部的两个刻面条，以便我们没有重复的条标签:
pg = ggplotGrob(p)# 为物种添加跨越条标签pos = c(4,11)for (i in 1:2) {pg <- gtable_add_grob(pg,列表(rectGrob(gp=gpar(col="grey50", fill="grey90")),textGrob(唯一(密度AGRLKA$物种)[i]，gp=gpar(cex=0.8))), t=3,l=pos[i],b=3,r=pos[i]+7,名称=c("a","b"))}# 为位置添加跨越条标签pos=c(4,7,11,15)for (i in 1:4) {pg = gtable_add_grob(pg,列表(rectGrob(gp = gpar(col =grey50"，fill =grey90"))，textGrob(rep(unique(密度AGRLKA$location),2)[i],gp=gpar(cex=0.8))), t=4,l=pos[i],b=4,r=pos[i]+3,名称 = c("c","d"))}grid.draw(pg)这是这个图在 ggplot2 2.1.0 中的样子:
但是，如果我使用 ggplot2 2.2.0 尝试相同的代码，我会恢复原始图，条带标签没有任何更改.看一下原始图 p 的 grob 结构就可以看出为什么会发生这种情况.我已经粘贴在这个问题底部的 grob 表中.为了节省空间，我只包含了与刻面条相关的行.
查看 cells 列，注意在 2.1.0 版本的绘图中，每行的前两个数字是 3、4 或 5，表示 grob 的垂直位置相对于情节中的其他格罗布.在上面的代码中，gtable_add_grob 的 t 和 l 参数被设置为 3 或 4 的值，因为这些是我需要的分面条行想用跨越条覆盖.
现在看看图的 2.2.0 版本中的 cells 列:请注意，前两个数字始终为 6.另请注意，刻面条仅由 8 个格子组成，而不是24 版本 2.1.0.在 2.2.0 版本中，似乎每堆三个面标签现在都是一个单一的 grob，而不是三个单独的 grob.因此，即使我将 gtable_add_grob 中的 t 和 b 参数更改为 6，也会覆盖所有三个方面条.举个例子:
pg = ggplotGrob(p)# 为物种添加跨越条标签pos = c(4,11)for (i in 1:2) {pg <- gtable_add_grob(pg,列表(rectGrob(gp=gpar(col="grey50", fill="grey90")),textGrob(唯一(密度AGRLKA$物种)[i]，gp=gpar(cex=0.8))), t=6,l=pos[i],b=6,r=pos[i]+7,名称=c("a","b"))}所以，在经过冗长的介绍之后，我的问题是:如何使用 ggplot2 2.2.0 版创建跨面条，使其看起来像我使用 gtable_add_grob 和 ggplot2 2.1 版创建的那些条带.0?我希望有一个简单的调整，但如果它需要大手术，那也没关系.
ggplot 2.1.0
pg<块引用>
TableGrob (9 x 19) "layout": 45 grobsz 单元格名称 grob2 1 ( 3- 3, 4- 4) 条顶absoluteGrob[strip.absoluteGrob.147]3 2 ( 4- 4, 4- 4) 条顶absoluteGrob[strip.absoluteGrob.195]4 3 ( 5- 5, 4- 4) 条顶absoluteGrob[strip.absoluteGrob.243]5 4 ( 3- 3, 6- 6) 条顶absoluteGrob[strip.absoluteGrob.153]6 5 ( 4- 4, 6- 6) 条顶absoluteGrob[strip.absoluteGrob.201]7 6 ( 5- 5, 6- 6) 条顶absoluteGrob[strip.absoluteGrob.249]8 7 ( 3- 3, 8- 8) 条顶absoluteGrob[strip.absoluteGrob.159]9 8 ( 4- 4, 8- 8) 条顶absoluteGrob[strip.absoluteGrob.207]10 9 ( 5- 5, 8- 8) 条顶absoluteGrob[strip.absoluteGrob.255]11 10 ( 3- 3,10-10) 条顶absoluteGrob[strip.absoluteGrob.165]12 11 ( 4- 4,10-10) 条顶absoluteGrob[strip.absoluteGrob.213]13 12 ( 5- 5,10-10) 条顶absoluteGrob[strip.absoluteGrob.261]14 13 ( 3- 3,12-12) 带顶absoluteGrob[strip.absoluteGrob.171]15 14 ( 4- 4,12-12) 条顶absoluteGrob[strip.absoluteGrob.219]16 15 ( 5- 5,12-12) 条顶absoluteGrob[strip.absoluteGrob.267]17 16 ( 3- 3,14-14) 带顶absoluteGrob[strip.absoluteGrob.177]18 17 ( 4- 4,14-14) 带顶absoluteGrob[strip.absoluteGrob.225]19 18 ( 5- 5,14-14) 带顶absoluteGrob[strip.absoluteGrob.273]20 19 ( 3- 3,16-16) 条顶absoluteGrob[strip.absoluteGrob.183]21 20 ( 4- 4,16-16) 条顶absoluteGrob[strip.absoluteGrob.231]22 21 ( 5- 5,16-16) 带顶absoluteGrob[strip.absoluteGrob.279]23 22 ( 3- 3,18-18) 带顶absoluteGrob[strip.absoluteGrob.189]24 23 ( 4- 4,18-18) 带顶absoluteGrob[strip.absoluteGrob.237]25 24 ( 5- 5,18-18) 带顶absoluteGrob[strip.absoluteGrob.285]ggplot2 2.2.0
pg<块引用>
TableGrob (11 x 21) "layout": 42 grobsz 单元格名称 grob28 2 ( 6- 6, 4- 4) strip-t-1 gtable[strip]29 2 ( 6- 6, 6- 6) strip-t-2 gtable[strip]30 2 ( 6- 6, 8- 8) strip-t-3 gtable[strip]31 2 ( 6- 6,10-10) strip-t-4 gtable[strip]32 2 ( 6- 6,12-12) strip-t-5 gtable[strip]33 2 ( 6- 6,14-14) strip-t-6 gtable[strip]34 2 ( 6- 6,16-16) strip-t-7 gtable[strip]35 2 ( 6- 6,18-18) strip-t-8 gtable[strip]确实，ggplot2 v2.2.0 逐列构建复杂的条带，每列一个单独的 grob.这可以通过提取一个条带，然后检查其结构来检查.使用你的情节:
库(ggplot2)图书馆(gtable)图书馆(网格)# 你的数据df =结构(列表(位置=结构(c(1L，1L，1L，1L，1L，1L，1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,2L, 2L), .Label = c("SF", "SS"), class = "factor"), species = 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), .Label = c("AGR", "LKA"), class = "factor"),位置 = 结构(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L,1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,2L), .Label = c("top", "bottom"), class = "factor"), density = c(0.41,0.41, 0.43, 0.33, 0.35, 0.43, 0.34, 0.46, 0.32, 0.32, 0.4,0.4, 0.45, 0.34, 0.39, 0.39, 0.31, 0.38, 0.48, 0.3, 0.42,0.34, 0.35, 0.4, 0.38, 0.42, 0.36, 0.34, 0.46, 0.38, 0.36,0.39, 0.38, 0.39, 0.39, 0.39, 0.36, 0.39, 0.51, 0.38)), .Names = c("location",物种"、位置"、密度")、row.names = c(NA, -40L)、class =data.frame")# 您的 ggplot 具有三个方面级别p=ggplot(df, aes("", 密度)) +geom_boxplot(width=0.7, position=position_dodge(0.7)) +theme_bw() +facet_grid(.~物种+位置+位置)+主题(panel.spacing=unit(0,"lines"),strip.background=element_rect(color="grey30", fill="grey90"),panel.border=element_rect(color="grey90"),axis.ticks.x=element_blank()) +实验室(x =")# 获取ggplot grobpg = ggplotGrob(p)# 获取最左边的条带索引 = which(pg$layout$name == "strip-t-1")strip1 = pg$grobs[[索引]]# 绘制条带grid.newpage()grid.draw(strip1)# 检查它的布局条1$布局gtable_show_layout(strip1)让外部带标签跨越"内部标签的一种粗略方法是从头开始构建带:
# 从原始图中以列表形式获取条带条 = 列表()for(i 在 1:8) {index = which(pg$layout$name == paste0("strip-t-",i))带[[i]] = pg$grobs[[索引]]}# 构造 gtable 以包含新条带newStrip = gtable(widths = unit(rep(1, 8), "null"), heights = strip[[1]]$heights)## 填充 gtable# 顶行for(i 在 1:2) {newStrip = gtable_add_grob(newStrip, strip[[4*i-3]][1],t = 1, l = 4*i-3, r = 4*i)}# 中间行for(i 在 1:4){newStrip = gtable_add_grob(newStrip, strip[[2*i-1]][2],t = 2, l = 2*i-1, r = 2*i)}# 底行for(i 在 1:8) {newStrip = gtable_add_grob(newStrip, strip[[i]][3],t = 3, l = i)}# 将条带放入绘图中#(最好删除原始条带.# 在这种情况下，用彩色背景，没关系)pgNew = gtable_add_grob(pg, newStrip, t = 7, l = 5, r = 19)# 绘制曲线grid.newpage()grid.draw(pgNew)OR 使用矢量化 gtable_add_grob(见评论):
pg = ggplotGrob(p)# 从原始图中获取条带列表strip = lapply(grep("strip-t", pg$layout$name), function(x) {pg$grobs[[x]]})# 构造 gtable 以包含新条带newStrip = gtable(widths = unit(rep(1, 8), "null"), heights = strip[[1]]$heights)## 填充 gtable# 顶行cols = seq(1, by = 4, length.out = 2)newStrip = gtable_add_grob(newStrip, lapply(strip[cols], `[`, 1), t = 1, l = cols, r = cols + 3)# 中间行cols = seq(1, by = 2, length.out = 4)newStrip = gtable_add_grob(newStrip, lapply(strip[cols], `[`, 2), t = 2, l = cols, r = cols + 1)# 底行newStrip = gtable_add_grob(newStrip, lapply(strip, `[`, 3), t = 3, l = 1:8)# 将条带放入绘图中pgNew = gtable_add_grob(pg, newStrip, t = 7, l = 5, r = 19)# 绘制曲线grid.newpage()grid.draw(pgNew)In plots with multiple facet variables, ggplot2 repeats the facet label for the "outer" variable, rather than having a single spanning facet strip across all the levels of the "inner" variable. I have some code that I've been using to cover the repeated outer facet labels with a single spanning facet strip using gtable_add_grob from the gtable package.
Unfortunately, this code no longer works with ggplot2 2.2.0 due to changes in the grob structure of the facet strips. Specifically, in previous versions of ggplot2, each row of facet labels got their own set of grobs. However, in version 2.2.0 it looks like each vertical stack of facet labels is a single grob. This breaks my code and I'm not sure how to fix it.
Here's a concrete example, taken from an SO question I answered a few months ago:
# Data
df = structure(list(location = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L), .Label = c("SF", "SS"), class = "factor"), species = 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), .Label = c("AGR", "LKA"), class = "factor"),
position = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L), .Label = c("top", "bottom"), class = "factor"), density = c(0.41,
0.41, 0.43, 0.33, 0.35, 0.43, 0.34, 0.46, 0.32, 0.32, 0.4,
0.4, 0.45, 0.34, 0.39, 0.39, 0.31, 0.38, 0.48, 0.3, 0.42,
0.34, 0.35, 0.4, 0.38, 0.42, 0.36, 0.34, 0.46, 0.38, 0.36,
0.39, 0.38, 0.39, 0.39, 0.39, 0.36, 0.39, 0.51, 0.38)), .Names = c("location",
"species", "position", "density"), row.names = c(NA, -40L), class = "data.frame")
# Begin with a regular ggplot with three facet levels
p=ggplot(df, aes("", density)) +
geom_boxplot(width=0.7, position=position_dodge(0.7)) +
theme_bw() +
facet_grid(. ~ species + location + position) +
theme(panel.margin=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
axis.ticks.x=element_blank()) +
labs(x="")
We start with a plot that has three levels of facets.
Now we'll cover the top two facet strips with spanning strips so that we don't have repeated strip labels:
pg = ggplotGrob(p)
# Add spanning strip labels for species
pos = c(4,11)
for (i in 1:2) {
pg <- gtable_add_grob(pg,
list(rectGrob(gp=gpar(col="grey50", fill="grey90")),
textGrob(unique(densityAGRLKA$species)[i],
gp=gpar(cex=0.8))), t=3,l=pos[i],b=3,r=pos[i]+7,
name=c("a","b"))
}
# Add spanning strip labels for location
pos=c(4,7,11,15)
for (i in 1:4) {
pg = gtable_add_grob(pg,
list(rectGrob(gp = gpar(col="grey50", fill="grey90")),
textGrob(rep(unique(densityAGRLKA$location),2)[i],
gp=gpar(cex=0.8))), t=4,l=pos[i],b=4,r=pos[i]+3,
name = c("c","d"))
}
grid.draw(pg)
This is what this plot looks like with ggplot2 2.1.0:
However, if I try the same code with ggplot2 2.2.0, I get the original plot back, with no changes to the strip labels. A look at the grob structure of the original plot p suggests why this is happening. I've pasted in the grob tables at the bottom of this question. In order to save space, I've included only the rows related to the facet strips.
Looking at the cells column, note that in the 2.1.0 version of the plot the first two numbers in each row are either 3, 4, or 5, indicating the vertical position of the grob relative to the other grobs in the plot. In the code above, the t and l arguments to gtable_add_grob are set to values of 3 or 4 because those are the facet strip rows that I wanted to cover with spanning strips.
Now look at the cells column in the 2.2.0 version of the plot: Note that the first two numbers are always 6. Also note that the facet strips are comprised of only 8 grobs instead of 24 in version 2.1.0. In version 2.2.0, it seems that each stack of three facet labels is now a single grob instead of three separate grobs. So even if I change the t and b arguments in gtable_add_grob to 6, all three facet strips are covered. Here's an example:
pg = ggplotGrob(p)
# Add spanning strip labels for species
pos = c(4,11)
for (i in 1:2) {
pg <- gtable_add_grob(pg,
list(rectGrob(gp=gpar(col="grey50", fill="grey90")),
textGrob(unique(densityAGRLKA$species)[i],
gp=gpar(cex=0.8))), t=6,l=pos[i],b=6,r=pos[i]+7,
name=c("a","b"))
}
So, after that very long-winded introduction, here's my question: How can I create spanning facet strips with ggplot2 version 2.2.0 that look like the ones I created using gtable_add_grob with ggplot2 version 2.1.0? I'm hoping there's a simple tweak, but if it requires major surgery, well, that's okay too.
ggplot 2.1.0
pg
TableGrob (9 x 19) "layout": 45 grobs z cells name grob 2 1 ( 3- 3, 4- 4) strip-top absoluteGrob[strip.absoluteGrob.147] 3 2 ( 4- 4, 4- 4) strip-top absoluteGrob[strip.absoluteGrob.195] 4 3 ( 5- 5, 4- 4) strip-top absoluteGrob[strip.absoluteGrob.243] 5 4 ( 3- 3, 6- 6) strip-top absoluteGrob[strip.absoluteGrob.153] 6 5 ( 4- 4, 6- 6) strip-top absoluteGrob[strip.absoluteGrob.201] 7 6 ( 5- 5, 6- 6) strip-top absoluteGrob[strip.absoluteGrob.249] 8 7 ( 3- 3, 8- 8) strip-top absoluteGrob[strip.absoluteGrob.159] 9 8 ( 4- 4, 8- 8) strip-top absoluteGrob[strip.absoluteGrob.207] 10 9 ( 5- 5, 8- 8) strip-top absoluteGrob[strip.absoluteGrob.255] 11 10 ( 3- 3,10-10) strip-top absoluteGrob[strip.absoluteGrob.165] 12 11 ( 4- 4,10-10) strip-top absoluteGrob[strip.absoluteGrob.213] 13 12 ( 5- 5,10-10) strip-top absoluteGrob[strip.absoluteGrob.261] 14 13 ( 3- 3,12-12) strip-top absoluteGrob[strip.absoluteGrob.171] 15 14 ( 4- 4,12-12) strip-top absoluteGrob[strip.absoluteGrob.219] 16 15 ( 5- 5,12-12) strip-top absoluteGrob[strip.absoluteGrob.267] 17 16 ( 3- 3,14-14) strip-top absoluteGrob[strip.absoluteGrob.177] 18 17 ( 4- 4,14-14) strip-top absoluteGrob[strip.absoluteGrob.225] 19 18 ( 5- 5,14-14) strip-top absoluteGrob[strip.absoluteGrob.273] 20 19 ( 3- 3,16-16) strip-top absoluteGrob[strip.absoluteGrob.183] 21 20 ( 4- 4,16-16) strip-top absoluteGrob[strip.absoluteGrob.231] 22 21 ( 5- 5,16-16) strip-top absoluteGrob[strip.absoluteGrob.279] 23 22 ( 3- 3,18-18) strip-top absoluteGrob[strip.absoluteGrob.189] 24 23 ( 4- 4,18-18) strip-top absoluteGrob[strip.absoluteGrob.237] 25 24 ( 5- 5,18-18) strip-top absoluteGrob[strip.absoluteGrob.285]
ggplot2 2.2.0
pg
TableGrob (11 x 21) "layout": 42 grobs z cells name grob 28 2 ( 6- 6, 4- 4) strip-t-1 gtable[strip] 29 2 ( 6- 6, 6- 6) strip-t-2 gtable[strip] 30 2 ( 6- 6, 8- 8) strip-t-3 gtable[strip] 31 2 ( 6- 6,10-10) strip-t-4 gtable[strip] 32 2 ( 6- 6,12-12) strip-t-5 gtable[strip] 33 2 ( 6- 6,14-14) strip-t-6 gtable[strip] 34 2 ( 6- 6,16-16) strip-t-7 gtable[strip] 35 2 ( 6- 6,18-18) strip-t-8 gtable[strip]
Indeed, ggplot2 v2.2.0 constructs complex strips column by column, with each column a single grob. This can be checked by extracting one strip, then examining its structure. Using your plot:
library(ggplot2)
library(gtable)
library(grid)
# Your data
df = structure(list(location = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L), .Label = c("SF", "SS"), class = "factor"), species = 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), .Label = c("AGR", "LKA"), class = "factor"),
position = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L), .Label = c("top", "bottom"), class = "factor"), density = c(0.41,
0.41, 0.43, 0.33, 0.35, 0.43, 0.34, 0.46, 0.32, 0.32, 0.4,
0.4, 0.45, 0.34, 0.39, 0.39, 0.31, 0.38, 0.48, 0.3, 0.42,
0.34, 0.35, 0.4, 0.38, 0.42, 0.36, 0.34, 0.46, 0.38, 0.36,
0.39, 0.38, 0.39, 0.39, 0.39, 0.36, 0.39, 0.51, 0.38)), .Names = c("location",
"species", "position", "density"), row.names = c(NA, -40L), class = "data.frame")
# Your ggplot with three facet levels
p=ggplot(df, aes("", density)) +
geom_boxplot(width=0.7, position=position_dodge(0.7)) +
theme_bw() +
facet_grid(. ~ species + location + position) +
theme(panel.spacing=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
axis.ticks.x=element_blank()) +
labs(x="")
# Get the ggplot grob
pg = ggplotGrob(p)
# Get the left most strip
index = which(pg$layout$name == "strip-t-1")
strip1 = pg$grobs[[index]]
# Draw the strip
grid.newpage()
grid.draw(strip1)
# Examine its layout
strip1$layout
gtable_show_layout(strip1)
One crude way to get outer strip labels 'spanning' inner labels is to construct the strip from scratch:
# Get the strips, as a list, from the original plot
strip = list()
for(i in 1:8) {
index = which(pg$layout$name == paste0("strip-t-",i))
strip[[i]] = pg$grobs[[index]]
}
# Construct gtable to contain the new strip
newStrip = gtable(widths = unit(rep(1, 8), "null"), heights = strip[[1]]$heights)
## Populate the gtable
# Top row
for(i in 1:2) {
newStrip = gtable_add_grob(newStrip, strip[[4*i-3]][1],
t = 1, l = 4*i-3, r = 4*i)
}
# Middle row
for(i in 1:4){
newStrip = gtable_add_grob(newStrip, strip[[2*i-1]][2],
t = 2, l = 2*i-1, r = 2*i)
}
# Bottom row
for(i in 1:8) {
newStrip = gtable_add_grob(newStrip, strip[[i]][3],
t = 3, l = i)
}
# Put the strip into the plot
# (It could be better to remove the original strip.
# In this case, with a coloured background, it doesn't matter)
pgNew = gtable_add_grob(pg, newStrip, t = 7, l = 5, r = 19)
# Draw the plot
grid.newpage()
grid.draw(pgNew)
OR using vectorised gtable_add_grob (see the comments):
pg = ggplotGrob(p)
# Get a list of strips from the original plot
strip = lapply(grep("strip-t", pg$layout$name), function(x) {pg$grobs[[x]]})
# Construct gtable to contain the new strip
newStrip = gtable(widths = unit(rep(1, 8), "null"), heights = strip[[1]]$heights)
## Populate the gtable
# Top row
cols = seq(1, by = 4, length.out = 2)
newStrip = gtable_add_grob(newStrip, lapply(strip[cols], `[`, 1), t = 1, l = cols, r = cols + 3)
# Middle row
cols = seq(1, by = 2, length.out = 4)
newStrip = gtable_add_grob(newStrip, lapply(strip[cols], `[`, 2), t = 2, l = cols, r = cols + 1)
# Bottom row
newStrip = gtable_add_grob(newStrip, lapply(strip, `[`, 3), t = 3, l = 1:8)
# Put the strip into the plot
pgNew = gtable_add_grob(pg, newStrip, t = 7, l = 5, r = 19)
# Draw the plot
grid.newpage()
grid.draw(pgNew)
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