這裏咱們使用grid對ggplot的畫圖對象進行佈局ide
# Multiple plot function
#
# ggplot objects can be passed in ..., or to plotlist (as a list of ggplot
# objects)
# - cols: Number of columns in layout
# - layout: A matrix specifying the layout. If present, 'cols' is ignored.
#
# If the layout is something like matrix(c(1,2,3,3), nrow=2, byrow=TRUE),
# then plot 1 will go in the upper left, 2 will go in the upper right, and
# 3 will go all the way across the bottom.
# e=0.15, # extra height needed for last plot (vertical layout),
# or extra width for first plot (horizontal layout)
multiplot <- function(..., plotlist=NULL, file, cols=1,
layout=NULL, horizontal=FALSE, e=0.15) {
require(grid)
# Make a list from the ... arguments and plotlist
plots = c(list(...), plotlist)
numPlots = length(plots)
#message(paste0('>>>>>>>INFO: num plots 2 = ', numPlots), '\n')
# If layout is NULL, then use 'cols' to determine layout
if (is.null(layout)) {
# Make the panel
# ncol: Number of columns of plots
# nrow: Number of rows needed, calculated from # of cols
layout = matrix(seq(1, cols * ceiling(numPlots/cols)),
ncol = cols, nrow = ceiling(numPlots/cols))
}
if (numPlots==1) {
print(plots[[1]])
} else {
## set up heights/widths of plots
# extra height needed for last plot (vertical layout),
# or extra width for first plot (horizontal layout)
hei = rep(1, numPlots)
# bottom plot is taller
hei[numPlots] = hei[numPlots]*(1+e)
wid = rep(1, numPlots)
# first left plot is wider
wid[1] = wid[1]*(1+e)
# Set up the page
grid.newpage()
if(horizontal){
pushViewport(viewport(layout = grid.layout(nrow(layout),
ncol(layout), widths=wid)))
}else{
pushViewport(viewport(layout = grid.layout(nrow(layout),
ncol(layout), heights=hei)))
}
# Make each plot, in the correct location
for (i in 1:numPlots) {
# Get i,j matrix positions of the regions containing this subplot
matchidx = as.data.frame(which(layout == i, arr.ind = TRUE))
print(plots[[i]], vp = viewport(layout.pos.row = matchidx$row,
layout.pos.col = matchidx$col))
}
}
}
library(ggplot2)
p1 <- ggplot(iris, aes(x = Sepal.Length)) + geom_histogram() + theme_bw()
p2 <- ggplot(iris, aes(x = Sepal.Length, y = Petal.Width)) + geom_point() + theme_bw()
# 直接使用ggplot對象畫圖
multiplot(p1,p2)
# 將ggplot對象放入列表中，再用列表畫圖, 並設置兩列的排列方式
plot_lst <- list()
plot_lst[[1]] <- p1
plot_lst[[2]] <- p2
multiplot(plotlist = plot_lst, cols = 2)
ClonEvol: clonal ordering and visualization in cancer
sequencing文獻裏面CloneEvol包裏面boxplot.r函數函數