After the last two R posts, here's something a bit more useful.

Creating animations in R was hard. Then Yihui Xie wrote the

animation package.

animation lets you plot individual frames, then record them.

I've been working on a little R package called

anim.plots which adds some syntactic sugar to this. It provides a few commands, similar to the standard R graphics, to create animated plots. Here's a quick demo. (The speed is quite slow: this is because I converted the files to animated GIFs. The original animations go reasonably fast.)

library(anim.plots)

anim.plot(1:5, 1:5, col="green")

To control what gets plotted when, use the times parameter.

x <- rep(1:100/10, 20)

times <- rep(1:20, each=100) # twenty frames with 100 points each

y <- sin(x*times/4)

waves <- anim.plot(x,y,times, type="l", col="orange", lwd=2, speed=2)

You can make incremental animations using the window parameter. Here's a printout of the first 20 plot symbols:

anim.plot(rep(1:10,2), rep(2:1, each=10), window=1:t, pch=1:20, ylim=c(0,3),cex=2, col=1:5, xlab=paste("Plot symbols", 1:20))

The above code also shows how parameters get recycled where appropriate, either to the number of points, or to the number of frames. For more complex parameters, you might have to use a matrix. Here we zoom in on a distribution of points by changing the xlim and ylim parameters.

x <- rnorm(4000)

y <- rnorm(4000)

x <- rep(x, 40)

y <- rep(y, 40)

xlims <- 4*2^(-(1:40/10))

ylims <- xlims <- rbind(xlims, -xlims)

anim.plot(x, y, times=40, speed=5, xlim=xlims, ylim=ylims,

col=rgb(0,0,0,.3), pch=19, bg="white")

The window argument is quite powerful. You can use it to create moving plots over time.

## discoveries 1860-1959

xlim <- rbind(1860:1959,1870:1969)

anim.plot(1860:1959, discoveries, times=1:100, xlim=xlim, col="red", xaxp=rbind(xlim, 10), window=t:(t+10), type="h", lwd=8, speed=5)

There's also a formula interface. Here's a plot of some chicks being fed one of four different diets:

data(ChickWeight)

ChickWeight$chn <- as.numeric(as.factor(ChickWeight$Chick))

tmp <- anim.plot(weight ~ chn + Time, data=ChickWeight, col=as.numeric(Diet), pch=as.numeric(Diet), speed=3)

Sometimes you need to run extra plotting commands after each frame. You can do this using the replay command:

replay(tmp, after=legend("topleft", legend=paste("Diet", 1:4), pch=1:4, col=1:4))

You aren't limited to the standard plot function. Here's a histogram with increasingly fine bins:

anim.hist(rep(rnorm(5000), 7), times=rep(1:7, each=5000), breaks=c(5,10,20,50,100,200, 500, 1000))

And here's how to animate a plot of a mathematical expression:

anim.curve(x^t, times=10:50/10, n=20)

You can animate contour plots. Here's the map of the Maunga Whau volcano in Auckland, emerging from a sphere. (Well, I had to come up with something!)

data(volcano)

# create a circle:

tmp <- volcano

tmp[] <- 200 - ((row(tmp) - 43)^2 + (col(tmp) - 30)^2)/20

# an animated contour needs a 3D array:

cplot <- array(NA, dim=c(87,61,20))

cplot[,,1] <- tmp

cplot[,,20] <- volcano

# morph the volcano into a circle:

cplot <- apply(cplot, 1:2, function(x) seq(x[1], x[20], length.out=20))

cplot <- aperm(cplot, c(2,3,1))

anim.contour(z=cplot, times=1:20, speed=3, levels=80 + 1:12*10, lty=c(1,2,2))

Finally, here are last week's earthquakes on the world map.

eq = read.table(

file="http://earthquake.usgs.gov/earthquakes/catalogs/eqs7day-M1.txt",

fill=TRUE, sep=",", header=T)

eq$time <- as.numeric(strptime(eq$Datetime, "%A, %B %d, %Y %X UTC"))

eq <- eq[-1,]

library(maps)

map('world')

tmp <- anim.points(Lat ~ Lon + time, data=eq, cex=Magnitude, col=rgb(

1-Depth/200, 0, Depth/200,.7), pch=19, speed=3600*12, show=FALSE)

replay(tmp, before=map('world', fill=TRUE, col="wheat"))

install_github("hughjonesd/anim.plots")