As mentioned during our last meeting, we won’t be hosting any talks in December, and shall be resuming activity in January 2018. But fear not! We’ve prepared something else instead: a fun & short demo for creating an animation in
R, where random scatterplot points converge dynamically into a legible text message:
How can you do this in
R? By relying on packages:
gganimate, plus a little help from a very clever external tool: WebPlotDigitizer. Let’s start by loading the required
library(tweenr) library(ggplot2) # library(devtools) # install_github("dgrtwo/gganimate") library(gganimate)
# We'll begin with very simple base R plot, and then save it locally. # This will map out the desired locations of points - # locations which we'll later reverse-engineer online: plot( c( 0, 1 ), c( 0, 1 ), ann = F, bty = 'n', type = 'n', xaxt = 'n', yaxt = 'n' ) text( x = 0.45, y = 0.55, paste( "Merry Christmas" ), col = "black", srt = 45, vfont = c( 'script', 'bold' ), cex = 3 ) text( x = 0.52, y = 0.46, paste( "from EdinbR!" ), col = "black", srt = 45, cex = 2 ) # Alternative to manual export: # message <- recordPlot() # Then use png(); print(message); dev.off() to export the 'message' plot as a .png.
What you get is this:
Now upload this very simple plot to WebPlotDigitizer, and let it work its magic. Its author, Ankit Rohatgi offers a very useful video tutorial here (and you can find further information here).
In this case, the job of WebPlotDigitizer is to convert our text to points with specific coordinates - and to do so quite precisely, so we don’t end up with very fuzzy lettering. You can see the interface below:
Once you’re happy with how precisely the points trace / are mapped onto the shape of the letters, you can export their coordinates as a .csv file, and return with it in
# After extracting the point coordinates with WebPlotDigitizer (i.e., the points which make up the text), return here with the outputted .csv file: digitized_points <- read.csv( "/path/to/my/points/MerryChristmasDigitizedPoints.csv", header = F ) # Now create a randomized version of the data (i.e., randomly sort one of the two columns, independently of the other): digitized_points_random <- digitized_points digitized_points_random$V1 <- digitized_points_random$V1[ sample( 1 : nrow( digitized_points_random ), nrow( digitized_points_random ), replace = F ) ] # Further create a list of the various states of the data: random, and legible text message. # NB: The 'legible' data will be sandwiched between two copies of the random data, # to ensure a smooth transition in the animation: digi_data_states <- list( digitized_points_random, digitized_points, digitized_points_random ) tween_message <- tween_states( digi_data_states, tweenlength = 1, statelength = 0.5, ease = "sine-out", nframe = 200 ) p <- ggplot( tween_message, aes( x = V1, y = V2 ) ) + geom_point( aes( frame = .frame ) ) animation::ani.options( interval = 1 / 15 ) gganimate( p, title_frame = FALSE, filename = "/path/to/my/points/MerryChristmas.gif" )
So, what happened above is that
tweenr took as input the various data states, and created the transition between them. Then,
gganimate created an animation for it.
Hope that was fun and perhaps even useful for you - especially since the same idea of animating data transitions is applicable to things like the well-known Anscombe Quartet, or more recently, the Datasaurus Dozen! Comments are welcome below.
Enjoy the winter holidays & see you in January 2018!