Show gtable names and grill
2024-02-07
library(ggplot2)
library(gtable)
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)
nul <- unit(1, 'null')
for (i in 1:nrow(g$layout)) {
if (g$layout$name[i] == 'lemon') next
h <- g$heights[[g$layout$t[i]]]
rot <- 0
rot <- ifelse(as.character(h) == '1null', 90, 0)
w <- g$widths[[g$layout$l[i]]]
if (rot == 90) {
rot <- ifelse(as.character(w) == '1null', 0, rot)
}
r <- rectGrob(gp=gpar(col='black', fill='white', alpha=1/4))
t <- textGrob(g$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))
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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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)