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在刻面ggplot2图中独立定位两个图例

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我有一个由ggplot2生成的图,其中包含两个图例 . 传说的放置并不理想,所以我想调整它们 . 我一直试图模仿the answer to "How do I position two legends independently in ggplot"中显示的方法 . 该答案中显示的示例有效 . 但是,我无法让所描述的方法适用于我的情况 .

我在Debian squeeze上使用R 2.15.3(2013-03-01),ggplot2_0.9.3.1,lattice_0.20-13,gtable_0.1.2,gridExtra_0.9.1 .

考虑 minimal.R 生成的图 . 这与我的实际情节类似 .

########################
minimal.R
########################

get_stat <- function()
  {
    n = 20
    q1 = qnorm(seq(3, 17)/20, 14, 5)
    q2 = qnorm(seq(1, 19)/20, 65, 10)
    Stat = data.frame(value = c(q1, q2),
      pvalue = c(dnorm(q1, 14, 5)/max(dnorm(q1, 14, 5)), d = dnorm(q2, 65, 10)/max(dnorm(q2, 65, 10))),
      variable = c(rep('true', length(q1)), rep('data', length(q2))))
    return(Stat)
  }

stat_all<- function()
{
  library(ggplot2)
  library(gridExtra)
  stathuman = get_stat()
  stathuman$dataset = "human"
  statmouse = get_stat()
  statmouse$dataset = "mouse"
  stat = merge(stathuman, statmouse, all=TRUE)
  return(stat)
}

simplot <- function()
  {
    Stat = stat_all()
    Pvalue = subset(Stat, variable=="true")
    pdf(file = "CDF.pdf", width = 5.5, height = 2.7)
    stat = ggplot() + stat_ecdf(data=Stat, n=1000, aes(x=value, colour = variable)) +
      theme(legend.key = element_blank(), legend.background = element_blank(), legend.position=c(.9, .25), legend.title = element_text(face = "bold")) +
        scale_x_continuous("Negative log likelihood") +
          scale_y_continuous("Proportion $<$ x") +
            facet_grid(~ dataset, scales='free') +
              scale_colour_manual(values = c("blue", "red"), name="Data type",
                                  labels=c("Gene segments", "Model"), guide=guide_legend(override.aes = list(size = 2))) +
                geom_area(data=Pvalue, aes(x=value, y=pvalue, fill=variable), position="identity", alpha=0.5) +
                  scale_fill_manual(values = c("gray"), name="Pvalue", labels=c(""))
    print(stat)
    dev.off()
  }

simplot()

这导致以下图 . 可以看出, Data typePvalue 传说定位不佳 . 我将此代码修改为 minimal2.R .

enter image description here

对于版本1,它应该将图例放在顶部,代码运行没有错误,但没有显示图例 .

编辑:显示两个框,一个在另一个上面 . 最上面一个是空白的 . 如果我没有按照@baptiste的说明设置 grid.arrange() 的高度,那么图例和图都都放在底部框中 . 如果我如图所示设置高度,那么我看不到图例 .

EDIT2:似乎 grid.newpage 调用了额外的空白框,我从之前的问题中复制了这个框 . 我'm not sure why it was there. If I don'吨使用那条线,然后我只得到一个盒子/页 .

使用版本2,我收到此错误 .

Error in UseMethod("grid.draw") :
  no applicable method for 'grid.draw' applied to an object of class "c('gg', 'ggplot')"
Calls: simplot -> grid.draw

编辑:如果我按@baptiste的建议使用 print(plotNew) ,那么我得到以下错误

Error in if (empty(data)) { : missing value where TRUE/FALSE needed 
Calls: simplot ... facet_map_layout -> facet_map_layout.grid -> locate_grid.

我试图弄清楚这里发生了什么,但我找不到太多相关信息 .

笔记:

  • 我不知道为什么我会获得经验CDF的阶梯效应 . 我确信有一个明显的解释 . 如果你知道,请告诉我 .

  • 我愿意考虑使用此代码的替代品,甚至ggplot2来生成此图表,如果有人可以提出替代方案,例如matplotlib,我从未认真研究过 .

  • 添加

print(ggplot_gtable(ggplot_build(stat2)))

minimal2.R 给了我

TableGrob (7 x 7) "layout": 12 grobs
    z     cells       name                                 grob
1   0 (1-7,1-7) background       rect[plot.background.rect.186]
2   1 (3-3,4-4)  strip-top absoluteGrob[strip.absoluteGrob.135]
3   2 (3-3,6-6)  strip-top absoluteGrob[strip.absoluteGrob.141]
4   5 (4-4,3-3)     axis-l  absoluteGrob[GRID.absoluteGrob.129]
5   3 (4-4,4-4)      panel                gTree[GRID.gTree.155]
6   4 (4-4,6-6)      panel                gTree[GRID.gTree.169]
7   6 (5-5,4-4)     axis-b  absoluteGrob[GRID.absoluteGrob.117]
8   7 (5-5,6-6)     axis-b  absoluteGrob[GRID.absoluteGrob.123]
9   8 (6-6,4-6)       xlab          text[axis.title.x.text.171]
10  9 (4-4,2-2)       ylab          text[axis.title.y.text.173]
11 10 (4-4,4-6)  guide-box                    gtable[guide-box]
12 11 (2-2,4-6)      title            text[plot.title.text.184]

我不明白这个细分 . 谁能解释一下? guide-box 对应于图例,人们如何知道这一点?

这是我的代码的修改版本, minimal2.R .

########################
minimal2.R
########################

get_stat <- function()
  {
    n = 20
    q1 = qnorm(seq(3, 17)/20, 14, 5)
    q2 = qnorm(seq(1, 19)/20, 65, 10)
    Stat = data.frame(value = c(q1, q2),
      pvalue = c(dnorm(q1, 14, 5)/max(dnorm(q1, 14, 5)), d = dnorm(q2, 65, 10)/max(dnorm(q2, 65, 10))),
      variable = c(rep('true', length(q1)), rep('data', length(q2))))
    return(Stat)
  }

stat_all<- function()
{
  library(ggplot2)
  library(gridExtra)
  library(gtable)
  stathuman = get_stat()
  stathuman$dataset = "human"
  statmouse = get_stat()
  statmouse$dataset = "mouse"
  stat = merge(stathuman, statmouse, all=TRUE)
  return(stat)
}

simplot <- function()
  {
    Stat = stat_all()
    Pvalue = subset(Stat, variable=="true")
    pdf(file = "CDF.pdf", width = 5.5, height = 2.7)

    ## only include data type legend
    stat1 = ggplot() + stat_ecdf(data=Stat, n=1000, aes(x=value, colour = variable)) +
      theme(legend.key = element_blank(), legend.background = element_blank(), legend.position=c(.9, .25), legend.title = element_text(face = "bold")) +
        scale_x_continuous("Negative log likelihood") +
          scale_y_continuous("Proportion $<$ x") +
            facet_grid(~ dataset, scales='free') +
              scale_colour_manual(values = c("blue", "red"), name="Data type", labels=c("Gene segments", "Model"), guide=guide_legend(override.aes = list(size = 2))) +
                geom_area(data=Pvalue, aes(x=value, y=pvalue, fill=variable), position="identity", alpha=0.5) +
                  scale_fill_manual(values = c("gray"), name="Pvalue", labels=c(""), guide=FALSE)

    ## Extract data type legend
    dataleg <- gtable_filter(ggplot_gtable(ggplot_build(stat1)), "guide-box")

    ## only include pvalue legend
    stat2 = ggplot() + stat_ecdf(data=Stat, n=1000, aes(x=value, colour = variable)) +
      theme(legend.key = element_blank(), legend.background = element_blank(), legend.position=c(.9, .25), legend.title = element_text(face = "bold")) +
        scale_x_continuous("Negative log likelihood") +
          scale_y_continuous("Proportion $<$ x") +
            facet_grid(~ dataset, scales='free') +
              scale_colour_manual(values = c("blue", "red"), name="Data type", labels=c("Gene segments", "Model"), guide=FALSE) +
                geom_area(data=Pvalue, aes(x=value, y=pvalue, fill=variable), position="identity", alpha=0.5) +
                  scale_fill_manual(values = c("gray"), name="Pvalue", labels=c(""))

    ## Extract pvalue legend
    pvalleg <- gtable_filter(ggplot_gtable(ggplot_build(stat2)), "guide-box")

    ## no legends
    stat = ggplot() + stat_ecdf(data=Stat, n=1000, aes(x=value, colour = variable)) +
      theme(legend.key = element_blank(), legend.background = element_blank(), legend.position=c(.9, .25), legend.title = element_text(face = "bold")) +
        scale_x_continuous("Negative log likelihood") +
          scale_y_continuous("Proportion $<$ x") +
            facet_grid(~ dataset, scales='free') +
              scale_colour_manual(values = c("blue", "red"), name="Data type", labels=c("Gene segments", "Model"), guide=FALSE) +
                geom_area(data=Pvalue, aes(x=value, y=pvalue, fill=variable), position="identity", alpha=0.5) +
                  scale_fill_manual(values = c("gray"), name="Pvalue", labels=c(""), guide=FALSE)

    ## Add data type legend: version 1 (data type legend should be on top)
    ## plotNew <- arrangeGrob(dataleg, stat, heights = unit.c(dataleg$height, unit(1, "npc") - dataleg$height), ncol = 1)

    ## Add data type legend: version 2 (data type legend should be somewhere in the interior)
    ## plotNew <- stat + annotation_custom(grob = dataleg, xmin = 7, xmax = 10, ymin = 0, ymax = 4)

    grid.newpage()
    grid.draw(plotNew)
    dev.off()
  }

simplot()

1 Answer

  • 2

    它可以用grid.arrange和arrangeGrob完成,但是正确调整高度和宽度是一件痛苦的事 .

    grid.arrange(arrangeGrob(dataleg, pvalleg, nrow=1, ncol=2, widths=c(unit(1, "npc"), unit(5, "cm"))), stat, nrow=2, heights=c(unit(.2, "npc"), unit(.8, "npc")))
    

    我通常喜欢用适当的图例创建一个新的情节并使用这个新的图例:

    h <- ggplot(data.frame(a=rnorm(10), b=rnorm(10), c=factor(rbinom(10, 1,.5), labels=c("Gene segments", "Model")), d=factor("")), 
            aes(x=a, y=b)) +
       geom_line(aes(color=c), size=1.3) + geom_polygon(aes(fill=d)) +
       scale_color_manual(values=c("blue", "red"), name="Data type") + 
       scale_fill_manual(values="gray", name="P-value") 
     g_legend<-function(a.gplot){
       tmp <- ggplot_gtable(ggplot_build(a.gplot))
       leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
       legend <- tmp$grobs[[leg]]
       return(legend)
     }
     legend <- g_legend(h)
    
     grid.arrange(stat, legend, nrow=1, ncol=2, widths=c(unit(.8, "npc"), unit(.2, "npc")))
     grid.arrange(legend, stat, nrow=2, ncol=1, heights=c(unit(.2, "npc"), unit(.8, "npc")))
    

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