ggplot2 annotate layer position in R - r

In my plot I have both legends and text annotations. For legends, I can specify
legend.justification=c(1,0), legend.position=c(1,0)
to locate the position relative to the plotting region (e.g. topright, bottomleft). However, when I put an annotate layer (http://docs.ggplot2.org/0.9.3.1/annotate.html), it seems that I can only specify the coordinates of the text
annotate("text", x = 8e-7, y = 1e-5, label=data.note, size = 5)
instead of the position of the plotting region (I want to put the text in the bottomleft corner). The length of the text (label) may vary for different plots. Is there a way to achieve this? Thanks!

You can use the fact that -Inf and Inf will get mapped to the extremes of the position scales without extending them to place it in the bottom left corner. hjust and vjust are needed to make the reference point the lower left corner of your text. [using jlhoward's mock data.]
set.seed(1)
df <- data.frame(x=rnorm(100),y=rnorm(100))
ggplot(df, aes(x,y)) +geom_point()+
annotate("text",x=-Inf,y=-Inf,hjust=0,vjust=0,label="Text annotation")

Is this what you're looking for??
set.seed(1)
df <- data.frame(x=rnorm(100),y=rnorm(100))
ggplot(df, aes(x,y)) +geom_point()+
annotate("text",x=min(df$x),y=min(df$y),hjust=.2,label="Text annotation")
There will probably be a bit of experimentation with hjust=... needed to get this exactly at the bottom left.

The "Inf" solution has problems when you want multi-line text. In addition, it there is no margin between the text and the panel edge, which is ugly. The other solution requires explicit mention of the data which is not good either.
The desired effect can be achieved nicely with annotation_custom (or in my example, the proto Geom directly). You have configurable margin, text and box justification.
The added bonus in the following code is that you can specify which facet to annotate with something like facets=data.frame(cat1='blue', cat2='tall').
library("ggplot2")
annotate_textp <- function(label, x, y, facets=NULL, hjust=0, vjust=0, color='black', alpha=NA,
family=thm$text$family, size=thm$text$size, fontface=1, lineheight=1.0,
box_just=ifelse(c(x,y)<0.5,0,1), margin=unit(size/2, 'pt'), thm=theme_get()) {
x <- scales::squish_infinite(x)
y <- scales::squish_infinite(y)
data <- if (is.null(facets)) data.frame(x=NA) else data.frame(x=NA, facets)
tg <- grid::textGrob(
label, x=0, y=0, hjust=hjust, vjust=vjust,
gp=grid::gpar(col=alpha(color, alpha), fontsize=size, fontfamily=family, fontface=fontface, lineheight=lineheight)
)
ts <- grid::unit.c(grid::grobWidth(tg), grid::grobHeight(tg))
vp <- grid::viewport(x=x, y=y, width=ts[1], height=ts[2], just=box_just)
tg <- grid::editGrob(tg, x=ts[1]*hjust, y=ts[2]*vjust, vp=vp)
inner <- grid::grobTree(tg, vp=grid::viewport(width=unit(1, 'npc')-margin*2, height=unit(1, 'npc')-margin*2))
layer(
data = NULL,
stat = StatIdentity,
position = PositionIdentity,
geom = GeomCustomAnn,
inherit.aes = TRUE,
params = list(
grob=grid::grobTree(inner),
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=Inf
)
)
}
qplot(1:10,1:10) + annotate_text2('some long text\nx = 1', x=0.5, y=0.5, hjust=1)

Related

Insert rectangle outside of ggplot to visualize plot segments

I hope you can help me. I have the idea of visualizing segments within a plot with a rectangle that can be placed next to the y or x-axis which means that it would be outside of the plot area. It should look similar as in the image below:
I tried to reach the mentioned output by trying two different approaches:
I created two viewports with the grid package and put the plot in one viewport that I placed at the bottom and one viewport on top of that. The big problem here is that I need the coordinates from where the grey background panel of the ggplot starts so I can place the top viewport exactly there, so that the segments conincide with the x-axis length. My code looked like following:
container_viewport <- viewport(x=0,y=0,height=1,width=1,just = c("left","bottom"))
pushViewport(container_viewport)
grid.draw(rectGrob())
popViewport()
section_viewport <- viewport(x=0.055,y=0.99,height=0.085,width=0.935,just=c("left","top"))
pushViewport(section_viewport)
plot_obj <- ggplot_build(testplot)
plot_data <- plot_obj$data[[1]]
grid.draw(rectGrob(gp = gpar(col = "red")))
popViewport()
plot_viewport <- viewport(x=0,y=0,height=0.9,width=1,just=c("left","bottom"))
pushViewport(plot_viewport)
grid.draw(ggplotGrob(testplot))
popViewport()
This looks fine but I had to hardcode the coordinates of the viewport at the top.
I used grid.arrange() to arrange to stack the plots vertically (instead of a grob for the rectangle like in the other approach I create a ggplot instead for that). Here, basically the same problem exists, since I somehow need to put the plot representing the rectangle at the top in the right position on the x-axis. My code looked like following:
p1 <- plot_data %>%
ggplot()+
geom_rect(aes(xmin=-Inf,xmax=Inf,ymin=-Inf,ymax=Inf))
p2 <- testplot
test_plot <- grid.arrange(p1,p2,heights=c(1,10))
This approach does not work that good.
Since I would like to create a solution that can be applied generally, trial and error with the coordinates of the viewport is no option since the length of the y-axis label or tick labels can vary and therefore the length and coordinates of the background panel. When this step is done the segmentation of the rectangle should be no problem anymore.
Maybe this is just not possible but if then I would appreciate any help.
Thank you!
I would probably use patchwork here. Let's start by replicating your plot:
library(ggplot2)
library(patchwork)
p <- ggplot(iris, aes(Sepal.Length, Sepal.Width)) +
geom_point(color = "red") +
labs(x = "test", y = "test")
p
That looks very similar. Now we define (in our own co-ordinates) where we want the section split to occur on the x axis.
section_split <- 5.25
Using just this number, we add rectangles and text annotations that cover a copy of our original plot, and remove its axis annotations using theme_void:
p2 <- p +
annotate("rect", xmin = c(-Inf, section_split), ymin = c(-Inf, -Inf),
xmax = c(section_split, Inf), ymax = c(Inf, Inf),
fill = c("#00a2e8", "#ff7f27")) +
annotate("text", label = c("Section A", "Section B"), size = 6,
y = rep(mean(layer_scales(p)$y$range$range), 2),
x = c((min(layer_scales(p)$x$range$range) + section_split)/2,
(max(layer_scales(p)$x$range$range) + section_split)/2)) +
theme_void()
Now we just draw this second plot above our first, adjusting the relative heights to about 1:10
p2/p + plot_layout(heights = c(1, 10))
The benefit of doing it this way is that, since we copied the original plot, the positional mapping of the x axis is identical between the two plots, and patchwork will automatically line up the panels.
Created on 2023-02-04 with reprex v2.0.2

ggplot: place image in corner of panel

I'm trying to find a way to insert an image into the corner of a ggplot panel, without specifying the coordinates manually each time.
In this instance, I'm attempting to place a graphic in the top right.
library(magick)
library(ggplot2)
library(datasets)
homer <- magick::image_read("http://icons.iconarchive.com/icons/jonathan-rey/simpsons/128/Homer-Simpson-04-Happy-icon.png")
g <- ggplot(mpg, aes(class)) +
geom_bar() +
labs(
title = "Count of Auto by Class",
subtitle = "Text to Create More Space")
g + annotation_custom(rasterGrob(homer, interpolate = TRUE),
xmax = Inf, ymax = Inf) +
coord_cartesian(clip = "off")
I have found some examples that come close to solving this:
Inserting an image to ggplot outside the chart area
Corner Labels in ggplot2
But neither quite get there. Specifying the exact location at which to place the image seems to require quite a bit of trial-and-error on each plot created, especially when x is categorical.
I would also like to maintain the size of my original image; the code I've used above seems to stretch it across the plot.
Thanks in advance...much appreciated.
try this
library(grid)
a <- rasterGrob(homer, interpolate = TRUE,
width=unit(1,'cm'),
x = unit(1,"npc"), y = unit(1,"npc"),
hjust = 1, vjust=1)
g + annotation_custom(grob = a)

autoplot - How to adjust loading labels?

I would like to be able to adjust the positions of the loading labels, so that they do not fall atop the the arrows. However, I do not know where the adjustments need to be made. The geom_text can be used to adjust the position of the site positions, but I cannot find where the vectors are stored in str(g).
library(ggplot2)
library(ggfortify)
df <- data.frame(replicate(10,sample(-10:10,10,rep=TRUE)))
names(df) <- c('up','down','left','right','circle','square','triangle','x','r1','l1')
rownames(df) <- paste('Dummy Site', seq(0,9,1))
g <- autoplot(prcomp(df[,-11], scale=TRUE), data=df,
loadings.label=TRUE, loadings=TRUE,
loadings.label.size=8, loadings.colour='blue',
label.size=5) +
geom_text(vjust=-1, label=rownames(df)) +
theme(plot.background=element_blank(),
panel.background=element_rect(fill='transparent',color='black',size=1),
legend.text=element_text(hjust=1),
legend.key=element_blank())
g
I've looked in ggplot2::theme and I've examined the help docs for autoplot, but can't find any mention of the adjusting label position. Bonus points if it can adjust based on the vector of the arrow, but a static adjustment would be acceptable.
Currently, here is what the plot looks like:
You can get the coordinates by layer_data(g, 2). But autoplot(prcomp.obj) passes other arguments to ggbiplot(), so you can change label and loadings.label position using arguments of ggbiplot(), such as loadings.label.hjust (see ?ggbiplot).
example code:
arrow_ends <- layer_data(g, 2)[,c(2,4)]
autoplot(prcomp(df[,-11], scale=TRUE), data=df,
loadings.label=TRUE, loadings=TRUE,
loadings.label.size=8, loadings.colour='blue',
label.size=5, loadings.label.vjust = 1.2) + # change loadings.label position
geom_point(data = arrow_ends, aes(xend, yend), size = 3) + # the coordinates from layer_data(...)
geom_text(vjust=-1, label=rownames(df)) +
theme(plot.background=element_blank(),
panel.background=element_rect(fill='transparent',color='black',size=1),
legend.text=element_text(hjust=1),
legend.key=element_blank())

Whisker plots to compare mean and variance between clusters [duplicate]

I am trying to recreate a figure from a GGplot2 seminar http://dl.dropbox.com/u/42707925/ggplot2/ggplot2slides.pdf.
In this case, I am trying to generate Example 5, with jittered data points subject to a dodge. When I run the code, the points are centered around the correct line, but have no jitter.
Here is the code directly from the presentation.
set.seed(12345)
hillest<-c(rep(1.1,100*4*3)+rnorm(100*4*3,sd=0.2),
rep(1.9,100*4*3)+rnorm(100*4*3,sd=0.2))
rep<-rep(1:100,4*3*2)
process<-rep(rep(c("Process 1","Process 2","Process 3","Process 4"),each=100),3*2)
memorypar<-rep(rep(c("0.1","0.2","0.3"),each=4*100),2)
tailindex<-rep(c("1.1","1.9"),each=3*4*100)
ex5<-data.frame(hillest=hillest,rep=rep,process=process,memorypar=memorypar, tailindex=tailindex)
stat_sum_df <- function(fun, geom="crossbar", ...) {stat_summary(fun.data=fun, geom=geom, ...) }
dodge <- position_dodge(width=0.9)
p<- ggplot(ex5,aes(x=tailindex ,y=hillest,color=memorypar))
p<- p + facet_wrap(~process,nrow=2) + geom_jitter(position=dodge) +geom_boxplot(position=dodge)
p
In ggplot2 version 1.0.0 there is new position named position_jitterdodge() that is made for such situation. This postion should be used inside the geom_point() and there should be fill= used inside the aes() to show by which variable to dodge your data. To control the width of dodging argument dodge.width= should be used.
ggplot(ex5, aes(x=tailindex, y=hillest, color=memorypar, fill=memorypar)) +
facet_wrap(~process, nrow=2) +
geom_point(position=position_jitterdodge(dodge.width=0.9)) +
geom_boxplot(fill="white", outlier.colour=NA, position=position_dodge(width=0.9))
EDIT: There is a better solution with ggplot2 version 1.0.0 using position_jitterdodge. See #Didzis Elferts' answer. Note that dodge.width controls the width of the dodging and jitter.width controls the width of the jittering.
I'm not sure how the code produced the graph in the pdf.
But does something like this get you close to what you're after?
I convert tailindex and memorypar to numeric; add them together; and the result is the x coordinate for the geom_jitter layer. There's probably a more effective way to do it. Also, I'd like to see how dodging geom_boxplot and geom_jitter, and with no jittering, will produce the graph in the pdf.
library(ggplot2)
dodge <- position_dodge(width = 0.9)
ex5$memorypar2 <- as.numeric(ex5$tailindex) +
3 * (as.numeric(as.character(ex5$memorypar)) - 0.2)
p <- ggplot(ex5,aes(x=tailindex , y=hillest)) +
scale_x_discrete() +
geom_jitter(aes(colour = memorypar, x = memorypar2),
position = position_jitter(width = .05), alpha = 0.5) +
geom_boxplot(aes(colour = memorypar), outlier.colour = NA, position = dodge) +
facet_wrap(~ process, nrow = 2)
p

How to smartly place text labels beside points of different sizes in ggplot2?

I am trying to make a labeled bubble plot with ggplot2 in R. Here is the simplified scenario:
I have a data frame with 4 variables: 3 quantitative variables, x, y, and z, and another variable that labels the points, lab.
I want to make a scatter plot, where the position is determined by x and y, and the size of the points is determined by z. I then want to place text labels beside the points (say, to the right of the point) without overlapping the text on top of the point.
If the points did not vary in size, I could try to simply modify the aesthetic of the geom_text layer by adding a scaling constant (e.g. aes(x=x+1, y=y+1)). However, even in this simple case, I am having a problem with positioning the text correctly because the points do not scale with the output dimensions of the plot. In other words, the size of the points remains constant in a 500x500 plot and a 1000x1000 plot - they do not scale up with the dimensions of the outputted plot.
Therefore, I think I have to scale the position of the label by the size (e.g. dimensions) of the output plot, or I have to get the radius of the points from ggplot somehow and shift my text labels. Is there a way to do this in ggplot2?
Here is some code:
# Stupid data
df <- data.frame(x=c(1,2,3),
y=c(1,2,3),
z=c(1,2,1),
lab=c("a","b","c"), stringsAsFactors=FALSE)
# Plot with bad label placement
ggplot(aes(x=x, y=y), data=df) +
geom_point(aes(size=z)) +
geom_text(aes(label=lab),
colour="red") +
scale_size_continuous(range=c(5, 50), guide="none")
EDIT: I should mention, I tried hjust and vjust inside of geom_text, but it does not produce the desired effect.
# Trying hjust and vjust, but it doesn't look nice
ggplot(aes(x=x, y=y), data=df) +
geom_point(aes(size=z)) +
geom_text(aes(label=lab), hjust=0, vjust=0.5,
colour="red") +
scale_size_continuous(range=c(5, 50), guide="none")
EDIT: I managed to get something that works for now, thanks to Henrik and shujaa. I will leave the question open just in case someone shares a more general solution.
Just a blurb of what I am using this for: I am plotting a map, and indicating the amount of precipitation at certain stations with a point that is sized proportionally to the amount of precipitation observed. I wanted to add a station label beside each point in an aesthetically pleasing manner. I will be making more of these plots for different regions, and my output plot may have a different resolution or scale (e.g. due to different projections) for each plot, so a general solution is desired. I might try my hand at creating a custom position_jitter, like baptiste suggested, if I have time during the weekend.
It appears that position_*** don't have access to the scales used by other layers, so it's a no go. You could make a clone of GeomText that shifts the labels according to the size mapped,
but it's a lot of effort for a very kludgy and fragile solution,
geom_shiftedtext <- function (mapping = NULL, data = NULL, stat = "identity",
position = "identity",
parse = FALSE, ...) {
GeomShiftedtext$new(mapping = mapping, data = data, stat = stat, position = position,
parse = parse, ...)
}
require(proto)
GeomShiftedtext <- proto(ggplot2:::GeomText, {
objname <- "shiftedtext"
draw <- function(., data, scales, coordinates, ..., parse = FALSE, na.rm = FALSE) {
data <- remove_missing(data, na.rm,
c("x", "y", "label"), name = "geom_shiftedtext")
lab <- data$label
if (parse) {
lab <- parse(text = lab)
}
with(coord_transform(coordinates, data, scales),
textGrob(lab, unit(x, "native") + unit(0.375* size, "mm"),
unit(y, "native"),
hjust=hjust, vjust=vjust, rot=angle,
gp = gpar(col = alpha(colour, alpha),
fontfamily = family, fontface = fontface, lineheight = lineheight))
)
}
})
df <- data.frame(x=c(1,2,3),
y=c(1,2,3),
z=c(1.2,2,1),
lab=c("a","b","c"), stringsAsFactors=FALSE)
ggplot(aes(x=x, y=y), data=df) +
geom_point(aes(size=z), shape=1) +
geom_shiftedtext(aes(label=lab, size=z),
hjust=0, colour="red") +
scale_size_continuous(range=c(5, 100), guide="none")
This isn't a very general solution, because you'll need to tweak it every time, but you should be able to add to the x value for the text some value that's linear depending on z.
I had luck with
ggplot(aes(x=x, y=y), data=df) +
geom_point(aes(size=z)) +
geom_text(aes(label=lab, x = x + .06 + .14 * (z - min(z))),
colour="red") +
scale_size_continuous(range=c(5, 50), guide="none")
but, as the font size depends on your window size, you would need to decide on your output size and tweak accordingly. I started with x = x + .05 + 0 * (z-min(z)) and calibrated the intercept based on the smallest point, then when I was happy with that I adjusted the linear term for the biggest point.
Another alternative. Looks OK with your test data, but you need to check how general it is.
dodge <- abs(scale(df$z))/4
ggplot(data = df, aes(x = x, y = y)) +
geom_point(aes(size = z)) +
geom_text(aes(x = x + dodge), label = df$lab, colour = "red") +
scale_size_continuous(range = c(5, 50), guide = "none")
Update
Just tried position_jitter, but the width argument only takes one value, so right now I am not sure how useful that function would be. But I would be happy to find that I am wrong. Example with another small data set:
df3 <- mtcars[1:10, ]
ggplot(data = df3, aes(x = wt, y = mpg)) +
geom_point(aes(size = qsec), alpha = 0.1) +
geom_text(label = df3$carb, position = position_jitter(width = 0.1, height = 0)) +
scale_size_continuous(range = c(5, 50), guide = "none")

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