可以创建插图吗?

时间:2011-03-07 12:21:34

标签: r graphics ggplot2 insets

我知道当您使用par( fig=c( ... ), new=T )时,您可以创建插图。但是,我想知道是否可以使用ggplot2库来创建“插图”图形。

更新1:我尝试将par()与ggplot2一起使用,但它不起作用。

更新2:我使用grid::viewport()ggplot2 GoogleGroups找到了可行的解决方案。

5 个答案:

答案 0 :(得分:24)

the book的第8.4节解释了如何执行此操作。诀窍是使用grid包的viewport s。

#Any old plot
a_plot <- ggplot(cars, aes(speed, dist)) + geom_line()

#A viewport taking up a fraction of the plot area
vp <- viewport(width = 0.4, height = 0.4, x = 0.8, y = 0.2)

#Just draw the plot twice
png("test.png")
print(a_plot)
print(a_plot, vp = vp)
dev.off()

答案 1 :(得分:13)

我更喜欢使用ggsave的解决方案。经过大量的谷歌搜索后,我得到了这个(这是一个通用的公式,用于定位和调整你插入的图。

library(tidyverse)

plot1 = qplot(1.00*mpg, 1.00*wt, data=mtcars)  # Make sure x and y values are floating values in plot 1
plot2 = qplot(hp, cyl, data=mtcars)
plot(plot1)

# Specify position of plot2 (in percentages of plot1)
# This is in the top left and 25% width and 25% height
xleft   = 0.05
xright  = 0.30
ybottom = 0.70
ytop    = 0.95 

# Calculate position in plot1 coordinates
# Extract x and y values from plot1
l1 = ggplot_build(plot1)
x1 = l1$layout$panel_ranges[[1]]$x.range[1]
x2 = l1$layout$panel_ranges[[1]]$x.range[2]
y1 = l1$layout$panel_ranges[[1]]$y.range[1]
y2 = l1$layout$panel_ranges[[1]]$y.range[2]
xdif = x2-x1
ydif = y2-y1
xmin  = x1 + (xleft*xdif)
xmax  = x1 + (xright*xdif)
ymin  = y1 + (ybottom*ydif)
ymax  = y1 + (ytop*ydif) 

# Get plot2 and make grob
g2 = ggplotGrob(plot2)
plot3 = plot1 + annotation_custom(grob = g2, xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax)
plot(plot3)

ggsave(filename = "test.png", plot = plot3)

# Try and make a weird combination of plots
g1 <- ggplotGrob(plot1)
g2 <- ggplotGrob(plot2)
g3 <- ggplotGrob(plot3)

library(gridExtra)
library(grid)

t1 = arrangeGrob(g1,ncol=1, left = textGrob("A", y = 1, vjust=1, gp=gpar(fontsize=20)))
t2 = arrangeGrob(g2,ncol=1, left = textGrob("B", y = 1, vjust=1, gp=gpar(fontsize=20)))
t3 = arrangeGrob(g3,ncol=1, left = textGrob("C", y = 1, vjust=1, gp=gpar(fontsize=20)))

final = arrangeGrob(t1,t2,t3, layout_matrix = cbind(c(1,2), c(3,3)))
grid.arrange(final)

ggsave(filename = "test2.png", plot = final)

Image showing inset and relatively complex layout

答案 2 :(得分:7)

利用ggplot2egg的更简单的解决方案。最重要的是,此解决方案适用于ggsave

library(tidyverse)
library(egg)
plotx <- ggplot(mpg, aes(displ, hwy)) + geom_point()
plotx + 
  annotation_custom(
    ggplotGrob(plotx), 
    xmin = 5, xmax = 7, ymin = 30, ymax = 44
  )
ggsave(filename = "inset-plot.png")

答案 3 :(得分:5)

或者,可以使用Claus O. Wilke的cowplot R包(cowplotggplot2的强大扩展)。作者举了一个例子,说明如何在this intro vignette中的较大图中绘制插图。这是一些经过修改的代码:

library(cowplot)

main.plot <- 
  ggplot(data = mpg, aes(x = cty, y = hwy, colour = factor(cyl))) + 
  geom_point(size = 2.5)

inset.plot <- main.plot + theme(legend.position = "none")

plot.with.inset <-
  ggdraw() +
  draw_plot(main.plot) +
  draw_plot(inset.plot, x = 0.07, y = .7, width = .3, height = .3)

# Can save the plot with ggsave()
ggsave(filename = "plot.with.inset.png", 
       plot = plot.with.inset,
       width = 17, 
       height = 12,
       units = "cm",
       dpi = 300)

enter image description here

答案 4 :(得分:1)

'ggplot2'> = 3.0.0使添加插值的新方法成为可能,因为现在包含列表作为成员列的tibble对象可以作为数据传递。列表列中的对象甚至可以是整个ggplots ...我的软件包ggpmisc'的最新版本提供了geom_plot()geom_table()geom_grob(),以及使用的版本npc 单位,而不是 native data 单位来定位插图。这些几何可以为每个调用添加多个插图,并遵循构面,而annotation_custom()则不能。我从帮助页面复制了示例,该页面添加了一个带有主图放大细节的插图作为插图。

library(tibble)
library(ggpmisc)
p <-
  ggplot(data = mtcars, mapping = aes(wt, mpg)) +
  geom_point()

df <- tibble(x = 0.01, y = 0.01,
             plot = list(p +
                         coord_cartesian(xlim = c(3, 4),
                                         ylim = c(13, 16)) +
                         labs(x = NULL, y = NULL) +
                         theme_bw(10)))
p +
  expand_limits(x = 0, y = 0) +
  geom_plot_npc(data = df, aes(npcx = x, npcy = y, label = plot))

ggplot with ggplot as inset

或插图小插图,取自包装插图。

library(tibble)
library(ggpmisc)
p <- ggplot(mpg, aes(factor(cyl), hwy, fill = factor(cyl))) +
  stat_summary(geom = "col", fun.y = mean, width = 2/3) +
  labs(x = "Number of cylinders", y = NULL, title = "Means") +
  scale_fill_discrete(guide = FALSE)

data.tb <- tibble(x = 7, y = 44, 
                  plot = list(p +
                                theme_bw(8)))

ggplot(mpg, aes(displ, hwy, colour = factor(cyl))) +
  geom_plot(data = data.tb, aes(x, y, label = plot)) +
  geom_point() +
  labs(x = "Engine displacement (l)", y = "Fuel use efficiency (MPG)",
       colour = "Engine cylinders\n(number)") +
  theme_bw()

enter image description here