5

我使用 R 分析数据，使用 ggplot 创建绘图，使用 tikzDevice 打印它们，最后使用 latex 创建报告。问题是由于乳胶的内存限制，具有许多点的大图会失败。我在这里https://github.com/yihui/tikzDevice/issues/103找到了一个在打印 tikz 文件之前栅格化绘图的解决方案，它允许单独打印点和文本。

require(png)
require(ggplot2)
require(tikzDevice)

## generate data
n=1000000; x=rnorm(n); y=rnorm(n)

## first try primitive
tikz("test.tex",standAlone=TRUE)
plot(x,y)
dev.off()
## fails due to memory
system("pdflatex test.tex")


## rasterise points first
png("inner.png",width=8,height=6,units="in",res=300,bg="transparent")
par(mar=c(0,0,0,0))
plot.new(); plot.window(range(x), range(y))
usr <- par("usr")
points(x,y)
dev.off()
# create tikz file with rasterised points
im <- readPNG("inner.png",native=TRUE)
tikz("test.tex",7,6,standAlone=TRUE)
plot.new()
plot.window(usr[1:2],usr[3:4],xaxs="i",yaxs="i")
rasterImage(im, usr[1],usr[3],usr[2],usr[4])
axis(1); axis(2); box(); title(xlab="x",ylab="y")
dev.off()
## this works
system("pdflatex test.tex")


## now with ggplot
p <- ggplot(data.frame(x=x, y=y), aes(x=x, y=y)) + geom_point()
## what here?

在此示例中，第一个pdflatex失败。由于光栅化，第二个成功。

如何使用 ggplot 应用它？

4

2 回答 2

3

这是一个原理证明来说明所涉及的步骤。正如评论中指出的那样，它不推荐或不实用，但可能是较低级别实现的基础。

require(png)
require(ggplot2)
require(tikzDevice)

n=100; 
d <- data.frame(x=rnorm(n), y=rnorm(n), z=rnorm(n))

p <- ggplot(d, aes(x=x, y=y, colour=z, size=z, alpha=x)) + geom_point()

## draw the layer by itself on a png file
library(grid)
g <- ggplotGrob(p)
# grid.newpage()
gg <- g$grobs[[6]]$children[[3]]
gg$vp <- viewport() # don't ask me
tmp <- tempfile(fileext = "png")
png(tmp, width=10, height=4, bg = "transparent", res = 30, units = "in")
grid.draw(gg)
dev.off()
## import it as a raster layer
rl <- readPNG(tmp, native = TRUE)
unlink(tmp)

## add it to a plot - note that the positions match, 
## but the size can be off unless one ensures that the panel has the same size and aspect ratio
ggplot(d, aes(x=x, y=y)) + geom_point(shape="+",  colour="red") +
  annotation_custom(rasterGrob(rl, width = unit(1,"npc"), height=unit(1,"npc"))) +
  geom_point(aes(size=z), shape=1, colour="red", show.legend = FALSE)

在此处输入图像描述

## to illustrate the practical use, we use a blank layer to train the scales
## and set the panel size to match the png file
pf <-  ggplot(d, aes(x=x, y=y)) + geom_blank() +
  annotation_custom(rasterGrob(rl, width = unit(1,"npc"), height=unit(1,"npc"), interpolate = FALSE))

tikz("test.tex", standAlone=TRUE)
grid.draw(egg::set_panel_size(pf, width=unit(10, "cm"), height=unit(4, "cm")))
dev.off()

system("lualatex test.tex")
system("open test.pdf")

在此处输入图像描述

我们可以放大并检查文本是否基于矢量，而图层（此处为低分辨率用于演示）栅格。

在此处输入图像描述

于 2017-02-06T02:59:09.717 回答
0

好的，我会在这里写它，因为它对于评论框来说太大了。除了将光栅化点添加到具有新比例的 nw 图之外，您实际上可以将原始 grob 替换为 rasterised grob by g$grobs[[6]]$children[[3]] <- rasterGrob(rl)。问题是它不能缩放，所以你必须先知道最终图像的大小。然后你可以这样起诉：

rasterise <- function(ggp,
                      width  = 6,
                      height = 3,
                      res.raster = 300,
                      raster.id=  c(4,3),
                      file = ""){
    ## RASTERISE
    require(grid)
    require(png)
    ## draw the layer by itself on a png file
    gb <- ggplot_build(ggp)
    gt <- ggplot_gtable(gb)
    ## calculate widths
    h <- as.numeric(convertUnit(sum(gt$heights), unitTo="in"))
    w <- as.numeric(convertUnit(sum(gt$widths) , unitTo="in"))
    w.raster <- width-w
    h.raster <- height-h
    ## print points as png
    grid.newpage()
    gg <- gt$grobs[[raster.id[1]]]$children[[raster.id[2]]]
    gg$vp <- viewport() # don't ask me
    tmp <- tempfile(fileext = "png")
    png(tmp, width=w.raster, height=h.raster, bg = "transparent", res = res.raster, units = "in")
    grid.draw(gg)
    dev.off()
    ## import it as a raster layer
    points <- readPNG(tmp, native = TRUE)
    points <- rasterGrob(points, width = w.raster, height = h.raster, default.units = "in")
    unlink(tmp)
    ## ADD TO PLOT
    gt$grobs[[raster.id[1]]]$children[[raster.id[2]]] <- points
    ## PLOT TMP
    ### HERE YOU CAN ONLY PRINT IT IN THIS DIMENSIONS!
    pdf(file, width = width, height = height)
    grid.draw(gt)
    dev.off()
}

然后使用它

data <- data.frame(x = rnorm(1000), y = rnorm(1000))
plot <- ggplot(data, aes(x = x, y = y)) +
    geom_point() +
    annotate("text", x = 2, y = 2, label = "annotation")

rasterise(ggp        = plot,
          width      = 6,
          height     = 3,
          res.raster = 10,
          raster.id  = c(4,2),
          file       = "~/test.pdf")

问题仍然是您要栅格化的 grob 的 ID。我没有找到一种自动找到正确方法的好方法。这取决于您将哪些图层添加到绘图中。

于 2017-02-24T10:38:06.567 回答