Just for fun, sometimes when I share R graphics via Twitter or on other social media platforms, I switch to a dramatic BLACK background.
For instance, here's a recent tweet in which I describe how to fix the root state for both traits in Pagel's (1994) binary correlated character evolution model:
Today's response to #phytools user #Rstats question - how to fix (i.e., fossilize) the state at the global root in fitPagel: https://t.co/3yCNQb1ock. pic.twitter.com/lw4p3CgBdf
— Liam Revell (@phytools_liam) August 5, 2020
Normally, however, in the blog posts themselves I stick with the standard transparent background, which will usually appear white on the web.
Working with R base graphics, though, it's really easy to change the background of your plot - and this applies equally to a scatterplot as to a plotted phylogenetic tree.
This is normally done using the function par - which is used to query or (in our case) set
graphical parameters for the active plotting device.
The most useful par arguments we're going to see are bg (background color) and fg (foreground
color); however, we also may need to use col.lab, col.axis, or col.main, depending on the type
of plot we're trying to create.
Let's see a couple of examples.
For this, we'll use some data from phytools. (Note, that you make have to update phytools from GitHub to get these datasets.)
library(phytools)
data(mammal.data)
mammal.data
## bodyMass homeRange
## U._maritimus 265.00 115.600
## U._arctos 251.30 82.800
## U._americanus 93.40 56.800
## N._narica 4.40 1.050
## P._lotor 7.00 1.140
## M._mephitis 2.50 2.500
## M._meles 11.60 0.870
## C._lupus 35.30 202.800
## C._latrans 13.30 45.000
## L._pictus 20.00 160.000
## C._aureus 8.80 9.100
## U._cinereoargenteus 3.70 1.100
## V._fulva 4.80 3.870
## H._hyaena 26.80 152.800
## C._crocuta 52.00 25.000
## A._jubatus 58.80 62.100
## P._pardus 52.40 23.200
## P._tigris 161.00 69.600
## P._leo 155.80 236.000
## T._bairdii 250.00 2.000
## C._simum 2000.00 6.650
## D._bicornis 1200.00 15.600
## E._hemionus 200.00 35.000
## E._caballus 350.00 22.500
## E._burchelli 235.00 165.000
## L._guanicoe 95.00 0.500
## C._dromedarius 550.00 100.000
## G._camelopardalis 1075.00 84.600
## S._caffer 6210.00 138.000
## B._bison 865.00 133.000
## T._oryx 511.00 87.500
## G._granti 62.50 20.000
## G._thomsonii 20.50 5.300
## A._cervicapra 37.50 6.500
## M._kirki 5.00 0.043
## O._americanus 113.50 22.750
## O._canadensis 85.00 14.330
## H._equinus 226.50 80.000
## A._melampus 53.25 3.800
## C._taurinus 216.00 75.000
## D._lunatus 130.00 2.200
## A._buselaphus 136.00 5.000
## A._americana 50.00 10.000
## C._canadensis 300.00 12.930
## D._dama 55.00 1.300
## A._alces 384.00 16.100
## R._tarandus 100.00 30.000
## O._virginianus 57.00 1.960
## O._hemionus 74.00 2.850
par(mar=c(5.1,5.1,3.1,1.1))
options(scipen=100)
plot(mammal.data,log="xy",bty="n",pch=19,
cex=1.5,xlab="body mass (kg)",
ylab=expression(paste("range size (km"^"2",
")")),cex.axis=0.8)
There are some plotting tricks in this chode chunk. For instance, I put an exponent (for km2)
in my axis label using expression; and I forced R to not use scientific notation in my axis labels
by setting options(scipen=100) (any positive value for scipen would have done the trick, in fact).
OK, now why don't we flip our background & foreground colors? To do this, I'm going to use par(bg),
and par(fg), but also par(col.lab) and par(col.main).
par(mar=c(5.1,5.1,3.1,1.1),
bg="black",
fg="white",
col.lab="white",
col.axis="white")
plot(mammal.data,log="xy",bty="n",pch=19,
cex=1.5,xlab="body mass (kg)",
ylab=expression(paste("range size (km"^"2",
")")),cex.axis=0.8)
Nice.
OK, now let's do the same thing with a plotted tree. This time, I'll use a dark slate background instead
of a solid background. For this example, I only need to set par(fg) and par(bg).
data(mammal.tree)
lnHomeRange<-setNames(log(mammal.data$homeRange),
rownames(mammal.data))
homeRange.fit<-edge.widthMap(mammal.tree,lnHomeRange)
homeRange.fit
## Object of class "edge.widthMap" containing:
## (1) Phylogenetic tree with 49 tips and 48 internal nodes.
## (2) Vector of node values for a mapped quantitative
## trait.
par(fg="white",bg="#696969")
plot(homeRange.fit,
border="white",max.width=0.8,lwd=2,
color=palette()[4],
legend="log(home range size)")
Of course, we mustn't forget that unless we reset them or close our active plotting device (using dev.off
or by closing the graphical device in our Rgui) our next plot will also inherit the values of par that
we set - whether we wanted that or not!
That's all for now folks.
