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 type
和 Pvalue
传说定位不佳 . 我将此代码修改为 minimal2.R
.
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)))
到 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 回答
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 .
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: