在ggplot2中为每个组添加geom_rug之类的箱线图 [英] Add geom_rug like boxplots per group in ggplot2
本文介绍了在ggplot2中为每个组添加geom_rug之类的箱线图的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我想每组在我的密度图的底部和顶部添加一个地毯箱图.我找不到实现，因此尝试尝试手动创建箱形图，然后将带有注解_自定义的图添加到图中.
I'd like to add a rug boxplot per group to the bottom and top of my density plot. I could not find an implementation, so I tried to manually create the boxplots and then add those with annotation_custom to the plot.
当前存在密度图的x轴与框线图不对齐的问题.我试图提取第一个图的界限，但只能找到一种方法来提取数据的界限.
Currently there is the problem that x axes of the density plot and the boxplots do not align. I tried to extract the limits of the first plot, but could only find a way to extract the limits of the data.
第二个问题是箱形图的精确y对齐，这应该与geom_rug处理它的相同.
The second problem is the exact y alignment of the boxplots, this should be the same as geom_rug handles it.
第三个问题是要确保密度图和箱形图使用相同的填充色.我使用手动方法解决了这个问题，但是如果不必在多个位置指定颜色，显然它将更加通用.
The third problem is to ensure that the same fill colors are used by the density and boxplots. I used a manual approach to solve this, but clearly it would be a lot more general if I do not have to specify the color in multiple places.
set.seed(123)
library(ggplot2)
library(ggpubr)
library(data.table)
Data <- data.table(x = rnorm(100),
group = rep(c("group1", "group2"), times = c(30, 70)))
# Colors for groups
colors <- c("group1" = "#66C2A5", "group2" = "#FC8D62")
p <-
ggplot(Data, aes(x = x, fill = group, color = group)) +
geom_density(alpha = 0.5) +
scale_color_manual(values = colors) +
scale_fill_manual(values = colors)
# Rugs
p +
geom_rug(data = Data[group %in% "group1"]) +
geom_rug(data = Data[group %in% "group2"], sides = "t")
#-----
# Boxplots
boxplot1 <-
ggplot(Data[group %in% "group1"]) +
geom_boxplot(aes(y = x), fill = colors[["group1"]]) +
coord_flip() +
theme_transparent()
boxplot2 <-
ggplot(Data[group %in% "group2"]) +
geom_boxplot(aes(y = x), fill = colors[["group2"]]) +
coord_flip() +
theme_transparent()
boxplot1_grob <- ggplotGrob(boxplot1)
boxplot2_grob <- ggplotGrob(boxplot2)
# Place box plots inside density plot
x <- ggplot_build(p)$layout$panel_scales_x[[1]]$range$range
xmin <- x[1]
xmax <- x[2]
y <- ggplot_build(p)$layout$panel_scales_y[[1]]$range$range
ymin <- y[1]
ymax <- y[2]
yoffset <- (1/28) * ymax
xoffset <- (1/28) * xmax
# Add boxplots with annotation_custom
p2 <- p +
annotation_custom(grob = boxplot1_grob, xmin = xmin, xmax = xmax,
ymin = ymin - yoffset, ymax = ymin + yoffset) +
annotation_custom(grob = boxplot2_grob,
xmin = xmin, xmax = xmax,
ymin = ymax - yoffset, ymax = ymax + yoffset)
p2
# Alignment is not correct
p2 +
geom_rug(data = Data[group %in% "group1"]) +
geom_rug(data = Data[group %in% "group2"], sides = "t")
推荐答案
有时候我做了一些类似的练习，尚未对其进行严格的测试，但它确实适用于您的用例.如果有任何问题，请通知我&我看看是否可以修复它们:
I made something similar for practice sometime back, & have yet to test it rigorously, but it does seem to work for your use case. If anything breaks, let me know & I'll see if I can fix them:
# with boxplots only
p +
geom_marginboxplot(data = Data[Data$group %in% "group1", ],
aes(y = 1), sides = "b") +
geom_marginboxplot(data = Data[Data$group %in% "group2", ],
aes(y = 1), sides = "t")
# with both boxplots & geom_rug (check that they align exactly)
p +
geom_marginboxplot(data = Data[Data$group %in% "group1", ],
aes(y = 1), sides = "b") +
geom_marginboxplot(data = Data[Data$group %in% "group2", ],
aes(y = 1), sides = "t") +
geom_rug(data = Data[group %in% "group1"]) +
geom_rug(data = Data[group %in% "group2"], sides = "t")
边际箱线图的尺寸模仿geom_rug的尺寸，占图板高度/宽度的3％. x& y必须在aes()中进行映射，尽管在这种情况下实际上并不需要y，因此我为它分配了值1作为占位符.
The marginal boxplot's dimensions imitate those of geom_rug, occupying 3% of the plot panel's height / width. Both x & y have to be mapped in aes(), though in this case y isn't actually needed, so I assigned it the value 1 as a placeholder.
运行以下命令以获得geom_marginboxplot:
library(ggplot2)
library(grid)
`%||%` <- function (x, y) if (is.null(x)) y else x
geom_marginboxplot <- function(mapping = NULL, data = NULL,
...,
sides = "bl",
outlier.shape = 16,
outlier.size = 1.5,
outlier.stroke = 0.5,
width = 0.9,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE) {
layer(
data = data,
mapping = mapping,
stat = StatMarginBoxplot,
geom = GeomMarginBoxplot,
position = "identity",
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
sides = sides,
outlier.shape = outlier.shape,
outlier.size = outlier.size,
outlier.stroke = outlier.stroke,
width = width,
notch = FALSE,
notchwidth = 0.5,
varwidth = FALSE,
na.rm = na.rm,
...
)
)
}
StatMarginBoxplot <- ggproto(
"StatMarginBoxplot", Stat,
optional_aes = c("x", "y"),
non_missing_aes = "weight",
setup_data = function(data, params,
sides = "bl") {
if(grepl("l|r", sides)){
data.vertical <- data
data.vertical$orientation <- "vertical"
} else data.vertical <- data.frame()
if(grepl("b|t", sides)){
data.horizontal <- data
data.horizontal$y <- data.horizontal$x
data.horizontal$orientation <- "horizontal"
} else data.horizontal <- data.frame()
data <- remove_missing(rbind(data.vertical,
data.horizontal),
na.rm = FALSE, vars = "x",
"stat_boxplot")
data
},
compute_group = function(data, scales, sides = "bl",
width = 0.9, na.rm = FALSE, coef = 1.5){
if(grepl("l|r", sides)){
df.vertical <- do.call(environment(StatBoxplot$compute_group)$f,
args = list(data = data[data$orientation == "vertical", ],
scales = scales, width = width,
na.rm = na.rm, coef = coef))
df.vertical <- df.vertical[, c("ymin", "lower", "middle", "upper", "ymax", "outliers")]
df.vertical$orientation = "vertical"
} else df.vertical <- data.frame()
if(grepl("b|t", sides)){
df.horizontal <- do.call(environment(StatBoxplot$compute_group)$f,
args = list(data = data[data$orientation == "horizontal", ],
scales = scales, width = width,
na.rm = na.rm, coef = coef))
df.horizontal <- df.horizontal[, c("ymin", "lower", "middle", "upper", "ymax", "outliers")]
df.horizontal$orientation = "horizontal"
} else df.horizontal <- data.frame()
df <- rbind(df.vertical, df.horizontal)
colnames(df) <- gsub("^y", "", colnames(df))
df
}
)
GeomMarginBoxplot <- ggproto(
"GeomMarginBoxplot", Geom,
setup_data = function(data, params, sides = "bl") {
data.vertical <- data[data$orientation == "vertical", ]
if(nrow(data.vertical) > 0) {
colnames(data.vertical)[1:6] <- paste0("y", colnames(data.vertical)[1:6])
}
data.horizontal <- data[data$orientation == "horizontal", ]
if(nrow(data.horizontal) > 0){
colnames(data.horizontal)[1:6] <- paste0("x", colnames(data.horizontal)[1:6])
}
data <- merge(data.vertical, data.horizontal, all = TRUE)
data <- data[, sapply(data, function(x) !all(is.na(x)))]
data
},
draw_group = function(data, panel_params, coord, fatten = 2,
outlier.shape = 19, outlier.stroke = 0.5,
outlier.size = 1.5, width = 0.9,
notch = FALSE, notchwidth = 0.5, varwidth = FALSE,
sides = "bl") {
draw.marginal.box <- function(sides){
if(sides %in% c("l", "b")){
pos1 <- unit(0, "npc"); pos2 <- unit(0.03, "npc")
} else {
pos2 <- unit(0.97, "npc"); pos1 <- unit(1, "npc")
}
if(width > 0 & width < 1){
increment <- (1 - width) / 2
increment <- increment * (pos2 - pos1)
pos1 <- pos1 + increment
pos2 <- pos2 - increment
}
pos3 <- 0.5 * pos1 + 0.5 * pos2
outliers_grob <- NULL
if(sides %in% c("l", "r")) {
data <- data[data$orientation == "vertical", ]
if (!is.null(data$youtliers) && length(data$youtliers[[1]] >= 1)) {
outliers <- data.frame(
y = unlist(data$youtliers[[1]]),
x = 0,
colour = data$colour[1],
fill = data$fill[1],
shape = outlier.shape %||% data$shape[1],
size = outlier.size %||% data$size[1],
stroke = outlier.stroke %||% data$stroke[1],
alpha = data$alpha[1],
stringsAsFactors = FALSE
)
coords <- coord$transform(outliers, panel_params)
x.pos <- rep(pos3, nrow(coords))
y.pos <- unit(coords$y, "native")
outliers_grob <- pointsGrob(
x = x.pos, y = y.pos,
pch = coords$shape,
gp = gpar(col = coords$colour,
fill = alpha(coords$fill, coords$alpha),
fontsize = coords$size * .pt + coords$stroke * .stroke/2,
lwd = coords$stroke * .stroke/2))
}
box.whiskers <- data.frame(
y = c(data$ymin, data$ylower, data$ymiddle, data$yupper, data$ymax),
x = 0,
colour = data$colour[1],
fill = data$fill[1],
size = data$size[1],
alpha = data$alpha[1],
stringsAsFactors = FALSE
)
box.whiskers <- coord$transform(box.whiskers, panel_params)
whiskers_grob <- segmentsGrob(
x0 = rep(pos3, 2),
x1 = rep(pos3, 2),
y0 = unit(c(box.whiskers$y[1], box.whiskers$y[5]), "native"),
y1 = unit(c(box.whiskers$y[2], box.whiskers$y[4]), "native"),
gp = gpar(col = box.whiskers$colour,
lwd = box.whiskers$size * .pt,
lty = box.whiskers$linetype))
box_grob <- rectGrob(
x = pos1,
y = unit(box.whiskers$y[4], "native"),
width = pos2 - pos1,
height = unit(box.whiskers$y[4] - box.whiskers$y[2], "native"),
just = c("left", "top"),
gp = gpar(col = box.whiskers$colour,
fill = alpha(box.whiskers$fill, box.whiskers$alpha),
lwd = box.whiskers$size * .pt,
lty = box.whiskers$linetype))
median_grob <- segmentsGrob(
x0 = rep(pos1, 2),
x1 = rep(pos2, 2),
y0 = unit(box.whiskers$y[3], "native"),
y1 = unit(box.whiskers$y[3], "native"),
gp = gpar(col = box.whiskers$colour,
lwd = box.whiskers$size * .pt,
lty = box.whiskers$linetype))
}
if(sides %in% c("b", "t")) {
data <- data[data$orientation == "horizontal", ]
if (!is.null(data$xoutliers) && length(data$xoutliers[[1]] >= 1)) {
outliers <- data.frame(
x = unlist(data$xoutliers[[1]]),
y = 0,
colour = data$colour[1],
fill = data$fill[1],
shape = outlier.shape %||% data$shape[1],
size = outlier.size %||% data$size[1],
stroke = outlier.stroke %||% data$stroke[1],
alpha = data$alpha[1],
stringsAsFactors = FALSE
)
coords <- coord$transform(outliers, panel_params)
x.pos <- unit(coords$x, "native")
y.pos <- rep(pos3, nrow(coords))
outliers_grob <- pointsGrob(
x = x.pos, y = y.pos,
pch = coords$shape,
gp = gpar(col = coords$colour,
fill = alpha(coords$fill, coords$alpha),
fontsize = coords$size * .pt + coords$stroke * .stroke/2,
lwd = coords$stroke * .stroke/2))
}
box.whiskers <- data.frame(
x = c(data$xmin, data$xlower, data$xmiddle, data$xupper, data$xmax),
y = 0,
colour = data$colour[1],
fill = data$fill[1],
size = data$size[1],
alpha = data$alpha[1],
stringsAsFactors = FALSE
)
box.whiskers <- coord$transform(box.whiskers, panel_params)
whiskers_grob <- segmentsGrob(
y0 = rep(pos3, 2),
y1 = rep(pos3, 2),
x0 = unit(c(box.whiskers$x[1], box.whiskers$x[5]), "native"),
x1 = unit(c(box.whiskers$x[2], box.whiskers$x[4]), "native"),
gp = gpar(col = box.whiskers$colour,
lwd = box.whiskers$size * .pt,
lty = box.whiskers$linetype))
box_grob <- rectGrob(
y = pos2,
x = unit(box.whiskers$x[2], "native"),
height = pos2 - pos1,
width = unit(box.whiskers$x[4] - box.whiskers$x[2], "native"),
just = c("left", "top"),
gp = gpar(col = box.whiskers$colour,
fill = alpha(box.whiskers$fill, box.whiskers$alpha),
lwd = box.whiskers$size * .pt,
lty = box.whiskers$linetype))
median_grob <- segmentsGrob(
y0 = rep(pos1, 2),
y1 = rep(pos2, 2),
x0 = unit(box.whiskers$x[3], "native"),
x1 = unit(box.whiskers$x[3], "native"),
gp = gpar(col = box.whiskers$colour,
lwd = box.whiskers$size * .pt,
lty = box.whiskers$linetype))
}
grobTree(outliers_grob,
whiskers_grob,
box_grob,
median_grob)
}
result <- list()
if(grepl("l", sides)) result$l <- draw.marginal.box("l")
if(grepl("r", sides)) result$r <- draw.marginal.box("r")
if(grepl("b", sides)) result$b <- draw.marginal.box("b")
if(grepl("t", sides)) result$t <- draw.marginal.box("t")
gTree(children = do.call("gList", result))
},
draw_key = draw_key_boxplot,
default_aes = aes(weight = 1, colour = "grey20", fill = "white",
size = 0.5, stroke = 0.5,
alpha = 0.75, shape = 16, linetype = "solid",
sides = "bl"),
optional_aes = c("lower", "upper", "middle", "min", "max")
)
会话信息:R 3.5.1，ggplot2 3.0.0.
Session info: R 3.5.1, ggplot2 3.0.0.
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