从循环中生成ggplots（并生成文件），而不用在RMarkdown中打印任何可见的输出 [英] Producing ggplots from a loop (and generating the files) without printing any visible output in RMarkdown
问题描述
我正在建造一个混合了数字，文字和图表的表格。我用ggplot构建了我的图，然后将它们添加到表中（请参阅下面的代码）。因为我会（最终）有很多地块，所以我需要使用一个循环来有效地创建它们。但是，因为ggplot似乎需要打印才能为每个图形生成图像链接，所以我无法使用 invisible（），并随后得到讨厌的'[
lapply 返回一个列表。当打印列表时，无论其内容如何，它还会打印列表索引 [[1]] ， [[2]] ， [[3]] ，....如果您改为保存列表， / p>
plot_list < - lapply（seq_along（score_set），FUN = function（x）{plotgen（score_set [[x]]，其他分数）}）
然后在列表中打印每张图 而不是打印整个列表（我们可以用 invisible（）>来包装返回的列表。 b
$ b
不可见（lapply（plot_list，print））
它不会打印列表的索引。因为您将单独打印每个打印图，而不是打印恰好包含图的列表。
在一个简单的列表上演示：
x = list（1，2，3）
print（x）
＃[[ 1]]
＃[1] 1
＃
＃[[2]]
＃[1] 2
＃
＃[[3] ]
＃[1] 3
隐形（lapply（x，print））
＃[1] 1
＃[1] 2
＃ [1] 3
另一种解决方案，不需要不可见因为它没有 return 任何东西，只是一个for循环：
for（i in seq_along（plot_list））print（plot_list [[i]]）
我会留给你看看你喜欢哪一个。
解决循环的会比较慢的担心：
p = ggplot（mtcars，aes（x = hp，y = mpg））+ geom_point（）
plist = list（p，p）
library（microbenchmark）
micro基准（
forloop = {for（i in seq_along（plist））print（plist [[i]]）}，
lapply =不可见（lapply（plist，print）），
times = 10L
）
＃单位：毫秒
＃expr分钟lq平均中位数uq max neval cld
＃forloop 260.4532 271.2784 295.8415 276.1587 289.7507 402.1792 10 a
＃lapply 258.8032 269.5915 296.2268 287.9524 294.8860 398.6803 10 a
差别是几毫秒。
I am building a table with a mixture of numbers, text, and plots. I constructed my plots with ggplot, and added them to the table afterwards (please see code below). Because I will (eventually) have many plots, I need to use a loop to efficiently create them all. However, because ggplot seems to require printing to generate image links for each plot, I am unable to use invisible(), and subsequently get the pesky '[1] [[2]] [[3]]' output at the top of the image below.
How can I compile the document without printing any visible output from ggplot?
```{r score_table, fig.show = "hide", echo = FALSE, fig.height=.75, fig.width=2.5}
#Load libraries
library(knitr)
library(ggplot2)
#Item data
items <- data.frame(text = sapply(1:3, FUN = function(x){
paste0(sample(x = LETTERS, size = 60, replace = T), collapse = "")}))
#Score data
score_set = replicate(n = 3, expr = {data.frame(other = rep("other", 4),
score=sample(1:7,4,TRUE))}, simplify = F)
#Plot function
plotgen<-function(score_set,other,score){
p <- ggplot(score_set, aes(factor(other), score))
p + geom_violin(fill = "#99CCFF") + coord_flip() + scale_x_discrete(name=NULL) +
scale_y_continuous(breaks = round(seq(1, 7, by = 1),1), limits = c(1,7), name=NULL) +
theme(axis.text.y=element_blank(),axis.title.y=element_blank(),axis.ticks.y=elemen t_blank(),
panel.grid.major.y = element_line(colour = "black"),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "white"),
panel.border = element_rect(colour = "black", fill=NA, size=1)) +
geom_hline(yintercept=sample(1:7,1,TRUE), size = 1.5, colour = "#334466")
}
#Generate plots
print(lapply(seq_along(score_set), FUN = function(x){plotgen(score_set[[x]],other,score)}))
out <- cbind(row.names(items), as.character(items$text), sprintf("",
opts_current$get("fig.path"), opts_current$get("label"), 1:nrow(items)))
#Build table
kable(out, col.names = c("ID", "Text", "Scores"))
```
lapply returns a list. When you print a list, regardless of it's contents, it also prints the list indices, [[1]], [[2]], [[3]], .... If you instead save the list,
plot_list <- lapply(seq_along(score_set), FUN = function(x){plotgen(score_set[[x]],other,score)})
and then print each plot in the list instead of printing the whole list (and this we can wrap in invisible() so the returned list isn't printed)
invisible(lapply(plot_list, print))
it won't print the indices of the list. Because you will be printing each plot individually, not printing a list which happens to contain plots.
Demonstrating on a simple list:
x = list(1, 2, 3)
print(x)
# [[1]]
# [1] 1
#
# [[2]]
# [1] 2
#
# [[3]]
# [1] 3
invisible(lapply(x, print))
# [1] 1
# [1] 2
# [1] 3
An alternate solution, not requiring invisible because it doesn't return anything, is just a for loop:
for (i in seq_along(plot_list)) print(plot_list[[i]])
I'll leave it to you to see which you prefer.
Addressing the worry that a for loop would be slower:
p = ggplot(mtcars, aes(x = hp, y = mpg)) + geom_point()
plist = list(p, p)
library(microbenchmark)
microbenchmark(
forloop = {for (i in seq_along(plist)) print(plist[[i]])},
lapply = invisible(lapply(plist, print)),
times = 10L
)
# Unit: milliseconds
# expr min lq mean median uq max neval cld
# forloop 260.4532 271.2784 295.8415 276.1587 289.7507 402.1792 10 a
# lapply 258.8032 269.5915 296.2268 287.9524 294.8860 398.6803 10 a
The difference is a few milliseconds.
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