Nuclear Animations in R

[This article was first published on R –, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

@jsvine (Data Editor at BuzzFeed) cleaned up and posted a data sets of historical nuclear explosions earlier this week. I used it to show a few plotting examples in class, but it’s also a really fun data set to play around with: categorial countries; time series; lat/long pairs; and, of course, nuclear explosions!

My previous machinations with the data set were all static, so I though it’d be fun to make a WarGames-esque world map animation to show who boomed where and how many booms each ended up making. The code is below (after the video). It’s commented and there are some ggplot2 tricks in there that those new to R might be interested in.

As I say in the code, I ended up tweaking ffmpeg parameters to get this video working on Twitter (the video file ended up being much, much smaller than the animated gif I originally toyed with making). Using convert from ImageMagick will quickly make a nice, local animated gif, or you can explore how to incorporate the ggplot2 frames into the animation package.

library(ggplot2)   # devtools::install_github("hadley/ggplot2")
# read and munge the data, being kind to github's servers
URL <- ""
fil <- basename(URL)
if (!file.exists(fil)) download.file(URL, fil)
dat <- read.csv(fil, stringsAsFactors=FALSE)
dat$date <- as.Date(as.character(dat$date_long), format="%Y%m%d")
dat$year <- as.character(dat$year)
dat$yr <- as.Date(sprintf("%s-01-01", dat$year))
dat$country <- sub("^PAKIST$", "PAKISTAN", dat$country)
# doing this so we can order things by most irresponsible country to least
booms <- arrange(count(dat, country), desc(n))
booms$country <- factor(booms$country, levels=unique(booms$country))
dat$country <- factor(dat$country, levels=unique(booms$country))
# Intercourse Antarctica
world_map <- filter(map_data("world"), region!="Antarctica")
scary <- "#2b2b2b" # a.k.a "slate black"
light <- "#bfbfbf" # a.k.a "off white"
proj <- "+proj=kav7" # Winkel-Tripel is *so* 2015
# In the original code I was using to play around with various themeing
# and display options this encapsulated theme_ function really helped alot
# but to do the grid.arrange with the bars it only ended up saving a teensy
# bit of typing.
# Also, Tungsten is ridiculously expensive but I have access via corporate
# subscriptions, so I'd suggest going with Arial Narrow vs draining your
# bank account since I really like the detailed kerning pairs but also think
# that it's just a tad too narrow. It seemed fitting for this vis, tho.
theme_scary_world_map <- function(scary="#2b2b2b", light="#8f8f8f") {
  theme_map() +
          plot.background=element_rect(fill=scary, color=scary),
          panel.background=element_rect(fill=scary, color=scary),
          legend.key=element_rect(fill=scary, color=scary),
          legend.text=element_text(color=light, size=10),
          axis.title.x=element_text(color=light, family="Tungsten-Book", size=14),
          plot.title=element_text(color=light, face="bold", size=16),
          plot.subtitle=element_text(color=light, family="Tungsten-Light",
                                     size=13, margin=margin(b=14)),
          plot.caption=element_text(color=light, family="Tungsten-ExtraLight",
                                    size=9, margin=margin(t=10)),
          plot.margin=margin(0, 0, 0, 0),
# I wanted to see booms by unique coords
dat_agg <- count(dat, year, country, latitude, longitude)
dat_agg$country <- factor(dat_agg$country, levels=unique(booms$country))
years <- as.character(seq(1945, 1998, 1))
# place to hold the pngs
dir.create("booms", FALSE)
# I ended up lovingly hand-crafting ffmpeg parameters to get the animation to
# work with Twitter's posting guidelines. A plain 'old ImageMagick "convert"
# from multiple png's to animated gif will work fine for a local viewing
for (i in 1:length(years)) {
  cat(".") # a poor data scientist's progress bar
  # data for map
  tmp_dat <- filter(dat_agg, year<=years[i])
  # data for bars
  boom2 <- arrange(count(tmp_dat, country, wt=n), desc(n))
  boom2$country <- factor(boom2$country, levels=unique(booms$country))
  # this gets us all the countries on the barplot x-axis even if the had no booms yet
  boom2 <- complete(boom2, country, fill=list(n=0))
  gg <- ggplot()
  gg <- gg + geom_map(data=world_map, map=world_map,
                      aes(x=long, y=lat, map_id=region),
                      color=light, size=0.1, fill=scary)
  gg <- gg + geom_point(data=tmp_dat,
                        aes(x=longitude, y=latitude, size=n, color=country),
                        shape=21, stroke=0.3)
  # the "trick" here is to force the # of labeled breaks so ggplot2 doesn't
  # truncate the range on us (it's nice that way and that feature is usually helpful)
  gg <- gg + scale_radius(name="", range=c(2, 8), limits=c(1, 50),
                          breaks=c(5, 10, 25, 50),
                          labels=c("1-4", "5-9", "10-24", "25-50"))
  gg <- gg + scale_color_brewer(name="", palette="Set1", drop=FALSE)
  gg <- gg + coord_proj(proj)
  gg <- gg + labs(x=years[i], y=NULL, title="Nuclear Explosions, 1945–1998",
                  subtitle="Stockholm International Peace Research Institute (SIPRI) and Sweden's Defence Research Establishment",
  # order doesn't actually work but it will after I get a PR into ggplot2
  # the tweaks here let us make the legends look like we want vs just mapped
  # to the aesthetics
  gg <- gg + guides(size=guide_legend(override.aes=list(color=light, stroke=0.5)),
                    color=guide_legend(override.aes=list(alpha=1, shape=16, size=3), nrow=1))
  gg <- gg + theme_scary_world_map(scary, light)
  gg <- gg + theme(plot.margin=margin(t=6, b=-1.5, l=4, r=4))
  gg_map <- gg
  gg <- ggplot(boom2, aes(x=country, y=n))
  gg <- gg + geom_bar(stat="identity", aes(fill=country), width=0.5, color=light, size=0.05)
  gg <- gg + scale_x_discrete(expand=c(0,0))
  gg <- gg + scale_y_continuous(expand=c(0,0), limits=c(0, 1100))
  gg <- gg + scale_fill_brewer(name="", palette="Set1", drop=FALSE)
  gg <- gg + labs(x=NULL, y=NULL, title=NULL, subtitle=NULL,
                  caption="Data from")
  gg <- gg + theme_scary_world_map(scary, light)
  gg <- gg + theme(axis.text=element_text(color=light))
  gg <- gg + theme(axis.text.x=element_text(color=light, size=11, margin=margin(t=2)))
  gg <- gg + theme(axis.text.y=element_text(color=light, size=6, margin=margin(r=5)))
  gg <- gg + theme(axis.title.x=element_blank())
  gg <- gg + theme(plot.margin=margin(l=20, r=20, t=-1.5, b=5))
  gg <- gg + theme(panel.grid=element_line(color=light, size=0.15))
  gg <- gg + theme(panel.margin=margin(0, 0, 0, 0))
  gg <- gg + theme(panel.grid.major.x=element_blank())
  gg <- gg + theme(panel.grid.major.y=element_line(color=light, size=0.05))
  gg <- gg + theme(panel.grid.minor=element_blank())
  gg <- gg + theme(panel.grid.minor.x=element_blank())
  gg <- gg + theme(panel.grid.minor.y=element_blank())
  gg <- gg + theme(axis.line=element_line(color=light, size=0.1))
  gg <- gg + theme(axis.line.x=element_line(color=light, size=0.1))
  gg <- gg + theme(axis.line.y=element_blank())
  gg <- gg + theme(legend.position="none")
  gg_bars <- gg
  # dimensions arrived at via trial and error
  png(sprintf("./booms/frame_%03d.png", i), width=639.5*2, height=544*2, res=144, bg=scary)
  grid.arrange(gg_map, gg_bars, ncol=1, heights=c(0.85, 0.15), padding=unit(0, "null"), clip="on")

To leave a comment for the author, please follow the link and comment on their blog: R – offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)