Multiple ggplots of different sizes

Question

It's relatively simple using grid.arrange in the gridExtra package to arrange multiple plots in a matrix, but how can you arrange plots (the ones I'm working on are from ggplot2) when some plots are intended to be larger than others? In base, I can use layout() such as in the example below:

 nf <- layout(matrix(c(1,1,1,2,3,1,1,1,4,5,6,7,8,9,9), byrow=TRUE, nrow=3))
 layout.show(nf)

what is the equivalent for ggplot plots?

Some plots for inclusion

library(ggplot2)
p1 <- qplot(x=wt,y=mpg,geom="point",main="Scatterplot of wt vs. mpg", data=mtcars)
p2 <- qplot(x=wt,y=disp,geom="point",main="Scatterplot of wt vs disp", data=mtcars)
p3 <- qplot(wt,data=mtcars)
p4 <- qplot(wt,mpg,data=mtcars,geom="boxplot")
p5 <- qplot(wt,data=mtcars)
p6 <- qplot(mpg,data=mtcars)
p7 <- qplot(disp,data=mtcars)
p8 <- qplot(disp, y=..density.., geom="density", data=mtcars)
p9 <- qplot(mpg, y=..density.., geom="density", data=mtcars)

Answer 1

I appreciate all the other answers, but Didzis Elferts's comment on the OP connected to the answer that I found easiest to implement.

library(ggplot2)
p1 <- qplot(x=wt,y=mpg,geom="point",main="Scatterplot of wt vs. mpg", data=mtcars)
p2 <- qplot(x=wt,y=disp,geom="point",main="Scatterplot of wt vs disp", data=mtcars)
p3 <- qplot(wt,data=mtcars)
p4 <- qplot(wt,mpg,data=mtcars,geom="boxplot")
p5 <- qplot(wt,data=mtcars)
p6 <- qplot(mpg,data=mtcars)
p7 <- qplot(disp,data=mtcars)
p8 <- qplot(disp, y=..density.., geom="density", data=mtcars)
p9 <- qplot(mpg, y=..density.., geom="density", data=mtcars)

vplayout <- function(x, y) viewport(layout.pos.row = x, layout.pos.col = y)

grid.newpage()
pushViewport(viewport(layout = grid.layout(3, 5))) # 3 rows, 5 columns
print(p1, vp = vplayout(1:2, 1:3))  # the big plot covers rows 1:2 and cols 1:3
print(p2, vp = vplayout(1, 4))
print(p3, vp = vplayout(1, 5))
print(p4, vp = vplayout(2, 4))
print(p5, vp = vplayout(2, 5))
print(p6, vp = vplayout(3, 1))
print(p7, vp = vplayout(3, 2))
print(p8, vp = vplayout(3, 3))
print(p9, vp = vplayout(3, 4:5))

Answer 2

You can use nested arrangeGrob calls like this example:

library(ggplot2)
library(gridExtra)

p <- ggplot(data.frame(x=1, y=1), aes(x,y)) + geom_point()

grid.arrange(
  arrangeGrob(
    p, 
    arrangeGrob(p, p, nrow=2),
    ncol=2 ,widths=c(2,1)),
  arrangeGrob(p, p ,p ,ncol=3, widths=rep(1,3)),
  nrow=2)

Edit:

gl <- lapply(1:9, function(ii) grobTree(rectGrob(),textGrob(ii)))

grid.arrange(
  arrangeGrob(gl[[1]],
              do.call(arrangeGrob, c(gl[2:5], ncol=2)),
              nrow=1,
              widths=3:2),
  do.call(arrangeGrob, c(gl[6:9], nrow=1, list(widths=c(1,1,1,2)))),
nrow=2, heights=c(2,1))

Answer 3

An alternative with gtable

library(gtable)

gl <- lapply(1:9, function(ii) grobTree(textGrob(ii), rectGrob()))
# gl <- lapply(1:9, function(ii) ggplotGrob(qplot(1,1) + ggtitle(ii)))

gt <- gtable(widths=unit(rep(1,5), "null"),
             heights=unit(rep(1,3), "null"))

gtable_add_grobs <- gtable_add_grob # alias

gt <- gtable_add_grobs(gt, gl, 
                       l=c(1,4,5,4,5,1,2,3,4),
                       r=c(3,4,5,4,5,1,2,3,5),
                       t=c(1,1,1,2,2,3,3,3,3),
                       b=c(2,1,1,2,2,3,3,3,3))
grid.newpage()
grid.draw(gt)

Answer 4

You can use the same matrix interface as layout with grid.arrange,

library(gridExtra)
library(grid)
gl <- lapply(1:9, function(ii) grobTree(rectGrob(), textGrob(ii)))

grid.arrange(grobs = gl, layout_matrix = rbind(c(1,1,1,2,3),
                                               c(1,1,1,4,5),
                                               c(6,7,8,9,9)))

and the same works for ggplots; note that NA can be used to indicate blank cells. The result is a gtable, compatible with ggsave().

gl <- replicate(9, ggplot(), FALSE)
grid.arrange(grobs = gl, layout_matrix = rbind(c(1,1,1,2,3),
                                               c(1,1,1,4,5),
                                               c(6,7,8,NA,9)))

Answer 5

I like the interface provided by the lay_out function (formerly in the wq package) . It takes arguments of the form list(plot, row(s), column(s)). For your example:

lay_out(list(p1, 1:2, 1:3),
       list(p2, 1, 4),
       list(p3, 1, 5),
       list(p4, 2, 4),
       list(p5, 2, 5),
       list(p6, 3, 1),
       list(p7, 3, 2),
       list(p8, 3, 3),
       list(p9, 3, 4:5))

Which yields:

lay_out = function(...) {    
    x <- list(...)
    n <- max(sapply(x, function(x) max(x[[2]])))
    p <- max(sapply(x, function(x) max(x[[3]])))
    grid::pushViewport(grid::viewport(layout = grid::grid.layout(n, p)))    

    for (i in seq_len(length(x))) {
        print(x[[i]][[1]], vp = grid::viewport(layout.pos.row = x[[i]][[2]], 
            layout.pos.col = x[[i]][[3]]))
    }
} 

(Code sourced from a prior version of the wq package, from the commit history on the unofficial Github CRAN mirror.)