ggplot2 study notes arrangement of graphics

Reprinted: https://www.jianshu.com/p/d46cf6934a2f

R language basic drawing functions may be utilized par () and layout () to be arranged in a pattern, but the two functions are not applicable to FIG ggplot, this paper shows how the multi-page multiple graphics ggplot arrayed. Mainly on how to use the package gridExtra, cowplot ggpubr and graphics function are arranged.

Graphing

#load packages
library(gridExtra)
library(cowplot) library(ggpubr) #dataset ToothGrowth and mtcars mtcars$name <- rownames(mtcars) mtcars$cyl <- as.factor(mtcars$cyl) head(mtcars[, c("name", "wt","mpg", "cyl")]) 

 

#First let's create some plots
#Box plot(bxp)
bxp <- ggboxplot(ToothGrowth, x="dose", y="len", color = "dose", palette = "jco") #Dot plot(dp) dp <- ggdotplot(ToothGrowth, x="dose", y="len", color = "dose", palette = "jco", binwidth = 1) #An ordered Bar plot(bp) bp <- ggbarplot(mtcars, x="name", y="mpg", fill="cyl", #change fill color by cyl color="white", #Set bar border colors to white palette = "jco", #jco jourbal color palette sort.val = "asc", #Sort the value in ascending order sort.by.groups = TRUE, #Sort inside each group x.text.angle=90 #Rotate vertically x axis texts ) bp+font("x.text", size = 8) 

 

#Scatter plots(sp)
sp <- ggscatter(mtcars, x="wt", y="mpg", add = "reg.line", #Add regression line conf.int = TRUE, #Add confidence interval color = "cyl", palette = "jco",#Color by group cyl shape = "cyl" #Change point shape by groups cyl )+ stat_cor(aes(color=cyl), label.x = 3) #Add correlation coefficientsp 

 

Graphic arrangement

Multiple arrangement pattern on one side

• ggpubr::ggarrange()

ggarrange(bxp, dp, bp+rremove("x.text"), labels = c("A", "B", "C"), ncol = 2, nrow = 2)

 

• cowplot::plot.grid()

plot_grid(bxp, dp, bp+rremove("x.text"), labels = c("A", "B", "C"), ncol = 2, nrow = 2)

 

• gridExtra::grid.arrange()

grid.arrange(bxp, dp, bp+rremove("x.text"), ncol=2, nrow=2)

 

Arrangement graphical annotation

• ggpubr::annotate_figure()

figure <- ggarrange(sp, bp+font("x.text", size = 10), ncol = 1, nrow = 2)
annotate_figure(figure, top=text_grob("Visualizing mpg", color = "red", 
face = "bold", size=14), bottom = text_grob("Data source:\n mtcars data set", 
color = "blue", hjust = 1, x=1, face = "italic", size=10), left = text_grob("Figure arranged using ggpubr", color = "green", rot = 90), 
right = "I'm done, thanks :-)!", fig.lab = "Figure 1", fig.lab.face = "bold")

 

Drawing panel alignment

• Survival curves were plotted

library(survival)
head(colon[, c(1:4)]) #Fit survival curves fit <- survfit(Surv(time, status)~adhere, data = colon) library(survminer) ggsurv <- ggsurvplot(fit, data = colon, palette = "jco", #jco palette pval = TRUE, pval.coord=c(500, 0.4), #Add p-value risk.table = TRUE #Add risk table) names(ggsurv) 

## [1] "plot" "table" "data.survplot" "data.survtable" 

ggsurv list is a two-part comprising

• plot: survival curve
• table: Table risk
  can ggarrange () are arranged for both

ggarrange(ggsurv$plot, ggsurv$table, heights = c(2, 0.7), ncol = 1, nrow = 2)

 

Figure above axes are not aligned, you can be set by the parameter align

ggarrange(ggsurv$plot, ggsurv$table, heights = c(2, 0.7), ncol = 1, nrow = 2, align = "v")

 

Changing the rows and columns of FIG.

Set two panels in two rows, wherein two sp occupy the first row, and dp BXP disposed two second rows

ggarrange(sp, #First row with scatter plot(sp) 
ggarrange(bxp, dp, ncol = 2, labels = c("B","C")),#Second row with box and dot plot 
nrow = 2, labels = "A" #Labels of the scatter plot)

 

R package cowplot

cowplot :: ggdraw () may be placed in a specific location graphical, ggdraw () initializes a first drawing panel, followed draw_plot () sucked in the initialization graphics rendering graphics panel can be placed in a particular pattern by means of parameterization position.

draw_plot(plot, x=0, y=0, width=1, height=1)

among them:

• plot: to be placed graphics
• x, y: position of the control pattern
• width, height: pattern width and height
• draw_plot_label (): Add tags for graphics

draw_plot_label(label, x=0, y=1, size=16, ...)

among them:

• label: label
• x, y: position of the control tag
• size: label font size

Here an example to explain how a plurality of pattern is placed at a specific position.

ggdraw()+ draw_plot(bxp, x=0, y=0.5, width=0.5, height = 0.5)+
draw_plot(dp, x=0.5, y=0.5, width = 0.5, height = 0.5)+ 
draw_plot(bp, x=0, y=0, width = 1.5, height = 0.5)+ 
draw_plot_label(label = c("A", "B", "C"), size = 15, x=c(0, 0.5, 0), y=c(1, 1, 0.5))

 

R package gridExtra

gridExtra :: arrangeGrop () to change the distribution of ranks

The following sp on the first line and across the two, and are distributed bxp dp and two in the second row

grid.arrange(sp, #First row with one plot spaning over 2 columns arrangeGrob(bxp, dp, ncol = 2), #Second row with 2plots in 2 different columns nrow=2) #number of rows 

 

You may also be provided by a complex function grid.arrange graphical layout of layout_matrix

grid.arrange(bp, #bar plot spaning two columns 
bxp, sp, #box plot amd scatter plot 
ncol=2, nrow=2, layout_matrix=rbind(c(1, 1), c(2, 3)))

 

要相对grid.arrange()以及arrangeGrob()的输出进行注释，首先要利用as_ggplot()将其转化为ggplot图形，进而利用函数draw_plot_label()对其进行注释。

gt <- arrangeGrob(bp, bxp, sp, layout_matrix = rbind(c(1,1),c(2, 3)))
p <- as_ggplot(gt)+ 
draw_plot_label(label = c("A", "B", "C"), size = 15, x=c(0, 0, 0.5), y=c(1, 0.5, 0.5))
p

 

R包grid

R包grid中的grid.layout()可以设置复杂的图形布局，viewport()可以定义一个区域用来安置图形排列，print()则用来将图形置于特定区域。 总结起来步骤如下：

• 创建图形p1,p2,p3,…
• grid.newpage()创建一个画布
• 创建图形布局，几行几列
• 定义布局的矩形区域
• print：将图形置于特定区域

library(grid)
#Move to a new page
grid.newpage() #Create layout:nrow=3, ncol=2 pushViewport(viewport(layout = grid.layout(nrow=3, ncol=2))) #A helper function to define a region on the layout define_region <- function(row, col){ viewport(layout.pos.row = row, layout.pos.col = col)} #Arrange the plots print(sp, vp=define_region(row=1, col=1:2)) #Span over two columns print(bxp, vp=define_region(row=2, col=1)) print(dp, vp=define_region(row=2, col=2)) print(bp+rremove("x.text"), vp=define_region(row=3, col=1:2)) 

设置共同图例

ggpubr::ggarrange()可以为组合图形添加共同图例

• common.legeng=TRUE:在图形旁边添加图例
• legend：指定legend的位置，主要选项有：top、bottom、left、right。

ggarrange(bxp, dp, labels = c("A", "B"), common.legend = TRUE, legend = "bottom") 

 

含有边际密度图的散点图

sp <- ggscatter(iris, x="Sepal.Length", y="Sepal.Width", color="Species", palette = "jco", size=3, alpha=0.6)+border() #Marginal density plot of x(top panel) and y(right panel) xplot <- ggdensity(iris, "Sepal.Length", fill="Species",palette = "jco") yplot <- ggdensity(iris, "Sepal.Width", fill="Species", palette = "jco")+rotate() #Clean the plots xplot <- xplot+clean_theme() yplot <- yplot+clean_theme() #Arrange the plots ggarrange(xplot, NULL, sp, yplot, ncol = 2, nrow = 2, align = "hv", widths = c(2, 1), heights = c(1, 2), common.legend = TRUE) 

 

ggplot图、文本、表格组合

density.p <- ggdensity(iris, x="Sepal.Length", fill="Species", palette = "jco") #Compute the summary table of Sepal.Length stable <- desc_statby(iris, measure.var = "Sepal.Length", grps = "Species") stable <- stable[, c("Species", "length", "mean", "sd")] #Summary table plot, medium and theme stable.p <- ggtexttable(stable, rows = NULL, theme = ttheme("mOrange")) text <- paste("iris data set gives the measurements in cm", "of the variables sepal length and width", "and petal length and width, respectively,", "for 50 flowers from each of 3 species of iris.", "The species are Iris setosa, versicolor, and virginica.", sep = " ") text.p <- ggparagraph(text = text, face = "italic", size = 11, color = "black") #Arrange the plots on the same page ggarrange(density.p, stable.p, text.p, ncol = 1, nrow = 3, heights = c(1, 0.5, 0.3)) 

 

ggplot图形中嵌入图形元素

ggplot2::annotation_custom()可以添加各种图形元素到ggplot图中

annotation_custom(grob, xmin, xmax, ymin, ymax)

其中：

• grob:要添加的图形元素
• xmin, xmax: x轴方向位置（水平方向）
• ymin, ymax: y轴方向位置（竖直方向）

ggplot图形中添加table

density.p+annotation_custom(ggplotGrob(stable.p), xmin = 5.5, xmax = 8, ymin = 0.7)

 

ggplot图形中添加box plot

sp <- ggscatter(iris, x="Sepal.Length", y="Sepal.Width", color = "Species", palette = "jco", size = 3, alpha=0.6)
xbp <- ggboxplot(iris$Sepal.Length, width = 0.3, fill = "lightgray")+ rotate()+theme_transparent()
ybp <- ggboxplot(iris$Sepal.Width, width = 0.3, fill="lightgray")+theme_transparent()
# Create the external graphical objects
# called a "grop" in Grid terminology
xbp_grob <- ggplotGrob(xbp)
ybp_grob <- ggplotGrob(ybp)
#place box plots inside the scatter plot
xmin <- min(iris$Sepal.Length)
xmax <- max(iris$Sepal.Length)
ymin <- min(iris$Sepal.Width)
ymax <- max(iris$Sepal.Width)
yoffset <- (1/15)*ymax
xoffset <- (1/15)*xmax
# Insert xbp_grob inside the scatter plots
p+annotation_custom(grob = xbp_grob, xmin = xmin, xmax = xmax, 
ymin = ymin-yoffset, ymax = ymin+yoffset)+
# Insert ybp_grob inside the scatter plot
annotation_custom(grob = ybp_grob, xmin = xmin-xoffset, 
xmax=xmin+xoffset, ymin=ymin, ymax=ymax)

 

ggplot图形添加背景

#import the imageimg.file <- system.file(file.path("images", "background-image.png"), package = "ggpubr")
img <- png::readPNG(img.file)

利用ggpubr::background_image()为ggplot图形添加背景图

library(ggplot2)
library(ggpubr)
ggplot(iris, aes(Species,Sepal.Length))+
background_image(img)+
geom_boxplot(aes(fill=Species), color="white")+ fill_palette("jco")

 

修改透明度

ggplot(iris, aes(Species,Sepal.Length))+
background_image(img)+geom_boxplot(aes(fill=Species), color="white", alpha=0.5)+ 
fill_palette("jco")

 

多页排列

日常工作中我们有时要绘制许多图，假如我们有16幅图，每页排列4张的话就需要4页才能排完，而ggpubr::ggarrange()可以通过制定行列数自动在多页之间进行图形排列

multi.page <-ggarrange(bxp, dp, bp, sp, nrow = 1, ncol = 2)

上述代码返回两页每页两图

multi.page[[1]]

 

multi.page[[2]]

 

利用ggarrange()嵌套布局

p1 <- ggarrange(sp, bp+font("x.text", size = 9), ncol = 1, nrow = 2)
p2 <- ggarrange(density.p, stable.p, text.p, ncol = 1, nrow = 3, 
heights = c(1, 0.5, 0.3))
ggarrange(p1, p2, ncol = 2, nrow = 1)

 

SessionInfo

sessionInfo()
## R version 3.4.1 (2017-06-30)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 15063)
## 
## Matrix products: default
## 
## locale:
## [1] LC_COLLATE=Chinese (Simplified)_China.936 
## [2] LC_CTYPE=Chinese (Simplified)_China.936 
## [3] LC_MONETARY=Chinese (Simplified)_China.936
## [4] LC_NUMERIC=C
## [5] LC_TIME=Chinese (Simplified)_China.936 
## 
## attached base packages:
## [1] grid stats graphics grDevices utils datasets methods 
## [8] base 
## 
## other attached packages:
## [1] survminer_0.4.0 survival_2.41-3 ggpubr_0.1.5 magrittr_1.5 
## [5] cowplot_0.8.0 ggplot2_2.2.1 gridExtra_2.2.1
## 
## loaded via a namespace (and not attached):
## [1] zoo_1.8-0 purrr_0.2.3 reshape2_1.4.2 
## [4] splines_3.4.1 lattice_0.20-35 colorspace_1.3-2 
## [7] htmltools_0.3.6 yaml_2.1.14 survMisc_0.5.4
## [10] rlang_0.1.2 foreign_0.8-69 glue_1.1.1 
## [13] bindrcpp_0.2 bindr_0.1 plyr_1.8.4 
## [16] stringr_1.2.0 munsell_0.4.3 gtable_0.2.0 
## [19] ggsci_2.7 psych_1.7.5 evaluate_0.10.1 
## [22] labeling_0.3 knitr_1.17 parallel_3.4.1 
## [25] broom_0.4.2 Rcpp_0.12.12 xtable_1.8-2 
## [28] scales_0.4.1 backports_1.1.0 cmprsk_2.2-7 
## [31] km.ci_0.5-2 mnormt_1.5-5 png_0.1-7 
## [34] digest_0.6.12 stringi_1.1.5 dplyr_0.7.2 
## [37] KMsurv_0.1-5 rprojroot_1.2 tools_3.4.1 
## [40] lazyeval_0.2.0 tibble_1.3.3 tidyr_0.7.0 
## [43] pkgconfig_2.0.1 Matrix_1.2-11 data.table_1.10.4
## [46] assertthat_0.2.0 rmarkdown_1.6 R6_2.2.2 
## [49] nlme_3.1-131 compiler_3.4.1