您可以在 gtable 中编辑 grobs，
ggplot(diamonds, aes(carat, price, fill = ..density..)) +
xlim(0, 2) + stat_binhex(na.rm = TRUE) + facet_wrap(~ color, ncol = 4)
for(ii in 1:7)
grid.gedit(gPath(paste0("strip_t-", ii), "strip.text"),
grep=TRUE, label=bquote(gamma[.(ii)]))
或者，如果你想保存一个 grob，
g <- ggplotGrob(d)
gg <- g$grobs
strips <- grep("strip_t", names(gg))
for(ii in strips)
gg[[ii]] <- editGrob(getGrob(gg[[ii]], "strip.text",
grep=TRUE, global=TRUE),
label=bquote(gamma[.(ii)]))
g$grobs <- gg
使用 ggsave 需要额外的（丑陋的）工作，因为必须欺骗 ggplot 类的测试......我认为pdf() ; grid.draw(g); dev.off()明确调用会更容易。
我做了一个小修正并将其包装在一个函数中：
facet_wrap_labeller <- function(gg.plot,labels=NULL) {
#works with R 3.0.1 and ggplot2 0.9.3.1
require(gridExtra)
g <- ggplotGrob(gg.plot)
gg <- g$grobs
strips <- grep("strip_t", names(gg))
for(ii in seq_along(labels)) {
modgrob <- getGrob(gg[[strips[ii]]], "strip.text",
grep=TRUE, global=TRUE)
gg[[strips[ii]]]$children[[modgrob$name]] <- editGrob(modgrob,label=labels[ii])
}
g$grobs <- gg
class(g) = c("arrange", "ggplot",class(g))
g
}
这可以很好地打印，甚至ggsave可以使用。
也许有人在某个时候更改了 edit-Grob 函数的名称。（编辑：它在大约 8 个月前被@hadley 删除。）geditGrob只有 pkg editGrob:grid 似乎有效：
d <- ggplot(diamonds, aes(carat, price, fill = ..density..)) +
xlim(0, 2) + stat_binhex(na.rm = TRUE) + opts(aspect.ratio = 1)
#Note: changes in ggplot2 functions cause this to fail from the very beginning now.
# Frank Harrell's answer this year suggests `facet_warp` now accepts `labeller`
d <- d + facet_wrap(~ color, ncol = 4)
grob <- ggplotGrob(d)
strip_elem <- grid.ls(getGrob(grob, "strip.text.x", grep=TRUE, global=TRUE))$name
#strip.text.x.text.1535
#strip.text.x.text.1541
#strip.text.x.text.1547
#strip.text.x.text.1553
#strip.text.x.text.1559
#strip.text.x.text.1565
#strip.text.x.text.1571
grob <- editGrob(grob, strip_elem[1], label=expression(Y[1]))
grid.draw(grob)
从ggplot22.1.0labeller开始，已经为facet_wrap.
刚刚从 roland 和 baptiste 发现了这个非常有用的函数，但需要一个稍微不同的用例，其中原始的 wrap headers 应该由函数转换而不是作为固定值提供。我发布了原始功能的略微修改版本，以防它对其他人有用。它既允许使用命名（固定值）表达式来换行，也允许使用自定义函数和 ggplot2 已经为facet_grid labeller参数提供的函数（例如label_parsed和label_bquote）。
facet_wrap_labeller <- function(gg.plot, labels = NULL, labeller = label_value) {
#works with R 3.1.2 and ggplot2 1.0.1
require(gridExtra)
# old labels
g <- ggplotGrob(gg.plot)
gg <- g$grobs
strips <- grep("strip_t", names(gg))
modgrobs <- lapply(strips, function(i) {
getGrob(gg[[i]], "strip.text", grep=TRUE, global=TRUE)
})
old_labels <- sapply(modgrobs, function(i) i$label)
# find new labels
if (is.null(labels)) # no labels given, use labeller function
new_labels <- labeller(names(gg.plot$facet$facets), old_labels)
else if (is.null(names(labels))) # unnamed list of labels, take them in order
new_labels <- as.list(labels)
else { # named list of labels, go by name where provided, otherwise keep old
new_labels <- sapply(as.list(old_labels), function(i) {
if (!is.null(labels[[i]])) labels[[i]] else i
})
}
# replace labels
for(i in 1:length(strips)) {
gg[[strips[i]]]$children[[modgrobs[[i]]$name]] <-
editGrob(modgrobs[[i]], label=new_labels[[i]])
}
g$grobs <- gg
class(g) = c("arrange", "ggplot",class(g))
return(g)
}
对于较新版本的gridExtra包，您将Error: No layers in plot在运行此函数时收到错误，因为arrange不再存在gridExtra并且 R 尝试将其解释为ggplot. 您可以通过（重新）引入该类的print函数来解决此问题arrange：
print.arrange <- function(x){
grid::grid.draw(x)
}
这现在应该允许绘图渲染，您可以ggsave()像这样使用例如：ggsave("test.pdf", plot = facet_wrap_labeller(p, labeller = label_parsed))
几个用例示例：
# artificial data frame
data <- data.frame(x=runif(16), y=runif(16), panel = rep(c("alpha", "beta", "gamma","delta"), 4))
p <- ggplot(data, aes(x,y)) + geom_point() + facet_wrap(~panel)
# no changes, wrap panel headers stay the same
facet_wrap_labeller(p)
# replace each panel title statically
facet_wrap_labeller(p, labels = expression(alpha^1, beta^1, gamma^1, delta^1))
# only alpha and delta are replaced
facet_wrap_labeller(p, labels = expression(alpha = alpha^2, delta = delta^2))
# parse original labels
facet_wrap_labeller(p, labeller = label_parsed)
# use original labels but modifying them via bquote
facet_wrap_labeller(p, labeller = label_bquote(.(x)^3))
# custom function (e.g. for latex to expression conversion)
library(latex2exp)
facet_wrap_labeller(p, labeller = function(var, val) {
lapply(paste0("$\\sum\\", val, "$"), latex2exp)
})
感谢您提及的其他答案和评论label_parsed。仍然不清楚如何使用标签解析器，所以我在这里添加一个简单的可重现示例。
library(dplyr)
library(ggplot2)
# Create a first facet variable with examples of math formulas
iris2 <- iris %>%
mutate(species_math = factor(Species,
levels = c("setosa", "versicolor", "virginica"),
labels = c("m^2",
expression(bar(x) == sum(frac(x[i], n), i==1, n) * beta * Q[t-1]),
bquote(pi == .(pi)))))
# Create a second facet variable with mean lengths
# This illustrates how to pass a numeric vector inside a formula
iris_mean <- iris2 %>%
group_by(Species) %>%
summarise(across(ends_with("Length"), mean), .groups="drop")
iris2$mean_length <- factor(iris2$Species,
levels = c("setosa", "versicolor", "virginica"),
labels = mapply(function(p, s) bquote(bar(p) == .(p) ~ bar(s) ==.(s)),
round(iris_mean$Petal.Length,3), round(iris_mean$Sepal.Length,3)))
iris2 %>%
ggplot(aes(x = Petal.Length, y = Petal.Width)) +
geom_point() +
facet_wrap(species_math ~ mean_length + Species, labeller = labeller(species_math = label_parsed, mean_length = label_parsed))
ggsave("~/downloads/formula_in_facet.png",
width = 12, height = 8, units = "cm")
如上例所示，labeller 可以解析：
expression用于更复杂数学的索引bquote在公式中包含数值的输出。另请参阅此答案，了解如何使用bquote多个值的数值向量。species_math变量。语法与 Latex 数学公式不同，因为label_parsed将标签解释为plotmath表达式。例如，索引是用x_iLatex 和x[i]绘图数学表达式编写的，而希腊字母是直接编写的，alpha而不是\alpha用 Latex 编写的。您可以在plotmath函数的帮助页面中找到许多公式 。祝你好运plotmath。