Hi Hadley,
I just tried out your suggestion, but it does not look like the
get_legends function is working correctly. Instead of returning a grob
back to me it returns NULL.
Here is my modified code and the results of running it.
Any help would be appreciated. I believe that once I can get the legend
in grob form then I can figure out how to deconstruct it myself.
Thanks,
Kaom
> p.legend <- get_legends(p)
> grid.draw(p.legend)
Error in grid.draw(p.legend) : no applicable method for "grid.draw"
> p.legend
NULL
>
BEGIN CODE
## Obtained from http://pastie.textmate.org/95755
get_legends <- function(plot) {
if (length(plot$layers) == 0) stop("No layers to plot", call.=FALSE)
# Apply function to layer and matching data
dlapply <- function(f) mapply(f, data, layers, SIMPLIFY=FALSE)
plot <- plot_clone(plot)
layers <- plot$layers
scales <- plot$scales
facet <- plot$facet
cs <- plot$coordinates
# Evaluate aesthetics
data <- lapply(layers, function(x) x$make_aesthetics(plot))
# Facet
data <- mapply(function(d, p) facet$stamp_data(d), data, layers,
SIMPLIFY=FALSE)
# Transform scales where possible. Also need to train so statisics
# (e.g. stat_smooth) have access to info
data <- dlapply(function(d, p) p$scales_transform(d, scales))
dlapply(function(d, p) p$scales_train(d, scales))
# Apply statistics
data <- dlapply(function(d, p) p$calc_statistics(d, scales))
data <- dlapply(function(d, p) p$map_statistics(d, plot))
# Adjust position before scaling
data <- dlapply(function(d, p) p$adjust_position(d, scales, "before"))
# Transform, train and map scales
# data <- dlapply(function(d, p) p$scales_transform(d, scales))
dlapply(function(d, p) p$scales_train(d, scales, adjust=TRUE))
data <- dlapply(function(d, p) p$scales_map(d, scales))
# Adjust position after scaling
data <- dlapply(function(d, p) p$adjust_position(d, scales, "after"))
scales <- scales$minus(plot$scales$get_scales(c("x", "y", "z")))
legends(scales, FALSE)
}
library(ggplot2)
data(mtcars)
grid.newpage()
hide_colour <- scale_colour_continuous()
hide_colour$legend <- FALSE
pushViewport(viewport(layout = grid.layout(2, 2)))
p <- ggplot(data = mtcars) +
geom_point(mapping = aes(x = hp, y = mpg, colour = cyl)) +
hide_colour
pushViewport(viewport(layout.pos.col = 1,
layout.pos.row = 1))
print(p, vp = current.viewport())
upViewport()
p <- ggplot(data = mtcars) +
geom_point(mapping = aes(x = drat, y = disp, colour = cyl)) +
hide_colour
pushViewport(viewport(layout.pos.col = 2,
layout.pos.row = 1))
print(p, vp = current.viewport())
upViewport()
p <- ggplot(data = mtcars) +
geom_point(mapping = aes(x = qsec, y = mpg, colour = cyl)) +
hide_colour
pushViewport(viewport(layout.pos.col = 1,
layout.pos.row = 2))
print(p, vp = current.viewport())
upViewport()
pushViewport(viewport(layout.pos.col = 2,
layout.pos.row = 2))
grid.rect()
p.legend <- get_legends(p)
grid.draw(p.legend)
------END CODE
-Original Message-
From: hadley wickham [mailto:[EMAIL PROTECTED]
Sent: Monday, September 10, 2007 7:58 AM
To: Te, Kaom
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] ggplot legend consolidation
> I have recently been introduced to the ggplot package by Hadley
> Wickham and must say I am quite impressed so far at how easy it is to
> make attractive plots, but one thing I am struggling over is how to
> consolidate legends.
It's not currently possible to consolidate them (although in the distant
future that would be something nice to have), but you can turn them off:
hide_colour <- scale_colour_continuous() hide_colour$legend <- FALSE
p <- ggplot(data = mtcars) +
geom_point(mapping = aes(x = hp, y = mpg, colour = cyl)) +
hide_colour
You'll also need to twiddle your viewports a little so that you still
have space for the viewport, since space will not be allocated
automatically anymore.
The next thing is to extract the grob for the legend itself - this is a
little tricker, because there's currently no way to get at the scales
after they have been "trained" with the data. Load get_legends from
http://pastie.textmate.org/95755, and then you can do:
grid.newpage(); grid.draw(get_legends(p))
If you're not familiar enough with grid to stitch all of these pieces
together, please let me know, but this should be enough to get you
started.
Hadley
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