Show gtable names and grill
2020-06-08
library(ggplot2)
library(gtable)
## Warning: package 'gtable' was built under R version 4.1.0
library(grid)
dat1 <- data.frame(
gp = factor(rep(letters[1:3], each = 10)),
y = rnorm(30),
cl = sample.int(3, 30, replace=TRUE),
cl2 = sample(c('a','b','c'), 30, replace=TRUE)
)
my.theme <- theme_light()
(
p <- ggplot(dat1, aes(gp, y)) + geom_point() + my.theme
)
![](data:image/png;base64,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)
g <- ggplotGrob(p)
for (i in 1:nrow(g$layout)) {
if (g$layout$name[i] == 'lemon') next
h <- g$heights[[g$layout$t[i]]]
# if h == null
rot <- if (as.character(h) == "1null") 90 else 0
w <- g$widths[[g$layout$l[i]]]
rot <- if (rot == 90 && as.character(w) == "1null") 0 else rot
r <- rectGrob(gp=gpar(col='black', fill='white', alpha=1/4))
t <- textGrob(g$layout$name[i], rot = rot)
g$grobs[[i]] <- grobTree(r, t)
}
grid.newpage()
grid.draw(g)
![](data:image/png;base64,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)
is.small <- function(x) {
#if (is.list(x) & !inherits(x[[1]], 'unit.list') & length(x) == 1) x <- x[[1]]
#if (inherits(x, 'unit.list')) return(FALSE)
if (!is.unit(x)) stop('`h` is not a unit.')
if (is.null(attr(x, 'unit'))) return(FALSE)
if (as.numeric(x) == 1 & attr(x, 'unit') == 'null') return(FALSE)
if (as.numeric(x) == 0) return(TRUE)
n <- as.numeric(x)
r <- switch(attr(x, 'unit'),
'null'= FALSE,
'line'= n < 1,
'pt'= n < 10,
'cm' = n < 1,
'grobheight' = FALSE,
'grobwidth' = FALSE,
NA) # i.e. not implemented
return(r)
}
g <- ggplotGrob(p)
gp.gutter <- gpar(colour='grey', lty='dashed')
g <- gtable_add_cols(g, unit(2, 'line'), 0)
for (i in 2:nrow(g)) {
g <- gtable_add_grob(g, t=i, l=1, clip='off', grobs=grobTree(
textGrob(sprintf('(%d, )', i-1)),
linesGrob(x=unit(c(-100,100), 'npc'), y=1, gp=gp.gutter)
), name='lemon')
if (is.small(g$heights[[i]])) g$heights[[i]] <- unit(1, 'line')
}
g <- gtable_add_rows(g, unit(1, 'line'), 0)
for (i in 2:ncol(g)) {
g <- gtable_add_grob(g, t=1, l=i, clip='off', grobs=grobTree(
textGrob(sprintf('( ,%d)', i-1)),
linesGrob(x=1, unit(c(-100, 100), 'npc'), gp=gp.gutter)
), name='lemon')
if (is.small(g$widths[[i]])) g$widths[[i]] <- unit(2, 'line')
}
grid.newpage()
grid.draw(g)
![](data:image/png;base64,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)
gtable_show_grill <- function(x, plot=TRUE) {
if (is.ggplot(x)) x <- ggplotGrob(x)
gp.gutter <- gpar(colour='grey', lty='dashed')
if (is.null(x$vp)) {
x$vp <- viewport(clip = 'on')
}
x <- gtable_add_cols(x, unit(2, 'line'), 0)
for (i in 2:nrow(x)) {
x <- gtable_add_grob(x, t=i, l=1, clip='off', grobs=grobTree(
textGrob(sprintf('[%d, ]', i-1)),
linesGrob(x=unit(c(-100,100), 'npc'), y=1, gp=gp.gutter)
), name='lemon')
if (is.small(x$heights[[i]])) x$heights[[i]] <- unit(1, 'line')
}
x <- gtable_add_rows(x, unit(1, 'line'), 0)
for (i in 2:ncol(x)) {
x <- gtable_add_grob(x, t=1, l=i, clip='off', grobs=grobTree(
textGrob(sprintf('[ ,%d]', i-1)),
linesGrob(x=1, unit(c(-100, 100), 'npc'), gp=gp.gutter)
), name='lemon')
if (is.small(x$widths[[i]])) x$widths[[i]] <- unit(2, 'line')
}
if (plot) {
grid.newpage()
grid.draw(x)
}
invisible(x)
}
gtable_show_grill(p)
![](data:image/png;base64,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)
gtable_show_names <- function(x, plot=TRUE) {
if (is.ggplot(x)) x <- ggplotGrob(x)
for (i in 1:nrow(x$layout)) {
if (x$layout$name[i] == 'lemon') next
if (grepl('ylab', x$layout$name[i])) {
rot <- 90
} else if (grepl('-l', x$layout$name[i])) {
rot <- 90
} else if (grepl('-r', x$layout$name[i])) {
rot <- 90
} else {
rot <- 0
}
r <- rectGrob(gp=gpar(col='black', fill='white', alpha=1/4))
t <- textGrob(x$layout$name[i], rot = rot)
x$grobs[[i]] <- grobTree(r, t)
}
if (plot) {
grid.newpage()
grid.draw(x)
}
invisible(x)
}
gtable_show_names(p)
![](data:image/png;base64,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)
gtable_show_names(gtable_show_grill(p, plot=FALSE))
![](data:image/png;base64,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)
try(rm(list=c('gtable_show_names','gtable_show_grill')), silent=TRUE)
library(lemon)
print(p)
grid.draw(gtable_show_names(p, plot=FALSE))
![](data:image/png;base64,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)
gp <- ggplotGrob(p)
gp <- gtable_add_rows(gp, g$heights[1], 0)
gp <- gtable_add_cols(gp, unit(1.5, 'line'))
gp <- gtable_add_grob(gp, linesGrob(x=0.5, gp=gpar(colour='grey', lwd=1.2)), t=1, b=nrow(gp), l=ncol(gp))
g <- gtable_show_names(gtable_show_grill(p, plot=FALSE), plot=FALSE)
g <- cbind(gp, g)
grid.newpage()
grid.draw(g)
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)