{"id":4203,"date":"2016-03-26T12:17:18","date_gmt":"2016-03-26T17:17:18","guid":{"rendered":"http:\/\/rud.is\/b\/?p=4203"},"modified":"2018-03-07T16:42:45","modified_gmt":"2018-03-07T21:42:45","slug":"nuclear-animations-in-r","status":"publish","type":"post","link":"https:\/\/rud.is\/b\/2016\/03\/26\/nuclear-animations-in-r\/","title":{"rendered":"Nuclear Animations in R"},"content":{"rendered":"

> UPDATE: For #rstats<\/a> folks interested in what this might look like in D3, [take a gander](https:\/\/rud.is\/b\/2016\/03\/27\/nuclear-animations-in-d3\/)<\/p>\n

@jsvine (Data Editor at BuzzFeed) cleaned up and posted a [data sets of historical nuclear explosions](https:\/\/github.com\/data-is-plural\/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!<\/p>\n

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.<\/p>\n

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.<\/p>\n

https:\/\/rud.is\/b\/wp-content\/uploads\/2016\/03\/booms.mp4<\/a><\/video><\/div>\n
library(purrr)\r\nlibrary(dplyr)\r\nlibrary(tidyr)\r\nlibrary(sp)\r\nlibrary(maptools)\r\nlibrary(maps)\r\nlibrary(grid)\r\nlibrary(scales)\r\nlibrary(ggplot2)   # devtools::install_github("hadley\/ggplot2")\r\nlibrary(ggthemes)\r\nlibrary(gridExtra)\r\nlibrary(ggalt)\r\n\r\n# read and munge the data, being kind to github's servers\r\nURL <- "https:\/\/raw.githubusercontent.com\/data-is-plural\/nuclear-explosions\/master\/data\/sipri-report-explosions.csv"\r\nfil <- basename(URL)\r\nif (!file.exists(fil)) download.file(URL, fil)\r\n\r\nread.csv(fil, stringsAsFactors=FALSE) %>%\r\n  tbl_df() %>%\r\n  mutate(date=as.Date(as.character(date_long), format="%Y%m%d"),\r\n         year=as.character(year),\r\n         yr=as.Date(sprintf("%s-01-01", year)),\r\n         country=sub("^PAKIST$", "PAKISTAN", country)) -> dat\r\n\r\n# doing this so we can order things by most irresponsible country to least\r\ncount(dat, country) %>%\r\n  arrange(desc(n)) %>%\r\n  mutate(country=factor(country, levels=unique(country))) -> booms\r\n\r\n# Intercourse Antarctica\r\nworld_map <- filter(map_data("world"), region!="Antarctica")\r\n\r\nscary <- "#2b2b2b" # a.k.a "slate black"\r\nlight <- "#bfbfbf" # a.k.a "off white"\r\n\r\nproj <- "+proj=kav7" # Winkel-Tripel is *so* 2015\r\n\r\n# In the original code I was using to play around with various themeing\r\n# and display options this encapsulated theme_ function really helped alot\r\n# but to do the grid.arrange with the bars it only ended up saving a teensy\r\n# bit of typing.\r\n#\r\n# Also, Tungsten is ridiculously expensive but I have access via corporate\r\n# subscriptions, so I'd suggest going with Arial Narrow vs draining your\r\n# bank account since I really like the detailed kerning pairs but also think\r\n# that it's just a tad too narrow. It seemed fitting for this vis, tho.\r\n\r\ntheme_scary_world_map <- function(scary="#2b2b2b", light="#8f8f8f") {\r\n  theme_map() +\r\n    theme(text=element_text(family="Tungsten-Light"),\r\n          title=element_text(family="Tungsten-Semibold"),\r\n          plot.background=element_rect(fill=scary, color=scary),\r\n          panel.background=element_rect(fill=scary, color=scary),\r\n          legend.background=element_rect(fill=scary),\r\n          legend.key=element_rect(fill=scary, color=scary),\r\n          legend.text=element_text(color=light, size=10),\r\n          legend.title=element_text(color=light),\r\n          axis.title=element_text(color=light),\r\n          axis.title.x=element_text(color=light, family="Tungsten-Book", size=14),\r\n          axis.title.y=element_blank(),\r\n          plot.title=element_text(color=light, face="bold", size=16),\r\n          plot.subtitle=element_text(color=light, family="Tungsten-Light",\r\n                                     size=13, margin=margin(b=14)),\r\n          plot.caption=element_text(color=light, family="Tungsten-ExtraLight",\r\n                                    size=9, margin=margin(t=10)),\r\n          plot.margin=margin(0, 0, 0, 0),\r\n          legend.position="bottom")\r\n}\r\n\r\n# I wanted to see booms by unique coords\r\ncount(dat, year, country, latitude, longitude) %>%\r\n  ungroup() %>%\r\n  mutate(country=factor(country, levels=unique(booms$country))) -> dat_agg\r\n\r\nyears <- as.character(seq(1945, 1998, 1))\r\n\r\n# place to hold the pngs\r\ndir.create("booms", FALSE)\r\n\r\n# I ended up lovingly hand-crafting ffmpeg parameters to get the animation to\r\n# work with Twitter's posting guidelines. A plain 'old ImageMagick "convert"\r\n# from multiple png's to animated gif will work fine for a local viewing\r\n\r\ntil <- length(years)\r\npb <- progress_estimated(til)\r\nsuppressWarnings(walk(1:til, function(i) {\r\n\r\n  pb$tick()$print()\r\n  \r\n  # data for map\r\n  tmp_dat <- filter(dat_agg, year<=years[i])\r\n\r\n  # data for bars\r\n  count(tmp_dat, country, wt=n) %>%\r\n    arrange(desc(nn)) %>%\r\n    mutate(country=factor(country, levels=unique(country))) %>%\r\n    complete(country, fill=list(nn=0)) -> boom2 # this gets us all the countries on the barplot x-axis even if the had no booms yet\r\n\r\n  gg <- ggplot()\r\n  gg <- gg + geom_map(data=world_map, map=world_map,\r\n                      aes(x=long, y=lat, map_id=region),\r\n                      color=light, size=0.1, fill=scary)\r\n  gg <- gg + geom_point(data=tmp_dat,\r\n                        aes(x=longitude, y=latitude, size=n, color=country),\r\n                        shape=21, stroke=0.3)\r\n\r\n  # the "trick" here is to force the # of labeled breaks so ggplot2 doesn't\r\n  # truncate the range on us (it's nice that way and that feature is usually helpful)\r\n  gg <- gg + scale_radius(name="", range=c(2, 8), limits=c(1, 50),\r\n                          breaks=c(5, 10, 25, 50),\r\n                          labels=c("1-4", "5-9", "10-24", "25-50"))\r\n\r\n  gg <- gg + scale_color_brewer(name="", palette="Set1", drop=FALSE)\r\n  gg <- gg + coord_proj(proj)\r\n  gg <- gg + labs(x=years[i], y=NULL, title="Nuclear Explosions, 1945\u20131998",\r\n                  subtitle="Stockholm International Peace Research Institute (SIPRI) and Sweden's Defence Research Establishment",\r\n                  caption=NULL)\r\n\r\n  # order doesn't actually work but it will after I get a PR into ggplot2\r\n  # the tweaks here let us make the legends look like we want vs just mapped\r\n  # to the aesthetics\r\n  gg <- gg + guides(size=guide_legend(override.aes=list(color=light, stroke=0.5)),\r\n                    color=guide_legend(override.aes=list(alpha=1, shape=16, size=3), nrow=1))\r\n\r\n  gg <- gg + theme_scary_world_map(scary, light)\r\n  gg <- gg + theme(plot.margin=margin(t=6, b=-1.5, l=4, r=4))\r\n  gg_map <- gg\r\n  \r\n  gg\r\n\r\n  gg <- ggplot(boom2, aes(x=country, y=nn))\r\n  gg <- gg + geom_bar(stat="identity", aes(fill=country), width=0.5, color=light, size=0.05)\r\n  gg <- gg + scale_x_discrete(expand=c(0,0))\r\n  gg <- gg + scale_y_continuous(expand=c(0,0), limits=c(0, 1100))\r\n  gg <- gg + scale_fill_brewer(name="", palette="Set1", drop=FALSE)\r\n  gg <- gg + labs(x=NULL, y=NULL, title=NULL, subtitle=NULL,\r\n                  caption="Data from https:\/\/github.com\/data-is-plural\/nuclear-explosions")\r\n  gg <- gg + theme_scary_world_map(scary, light)\r\n  gg <- gg + theme(axis.text=element_text(color=light))\r\n  gg <- gg + theme(axis.text.x=element_text(color=light, size=11, margin=margin(t=2)))\r\n  gg <- gg + theme(axis.text.y=element_text(color=light, size=6, margin=margin(r=5)))\r\n  gg <- gg + theme(axis.title.x=element_blank())\r\n  gg <- gg + theme(plot.margin=margin(l=20, r=20, t=-1.5, b=5))\r\n  gg <- gg + theme(panel.grid=element_line(color=light, size=0.15))\r\n  gg <- gg + theme(panel.margin=margin(0, 0, 0, 0))\r\n  gg <- gg + theme(panel.grid.major.x=element_blank())\r\n  gg <- gg + theme(panel.grid.major.y=element_line(color=light, size=0.05))\r\n  gg <- gg + theme(panel.grid.minor=element_blank())\r\n  gg <- gg + theme(panel.grid.minor.x=element_blank())\r\n  gg <- gg + theme(panel.grid.minor.y=element_blank())\r\n  gg <- gg + theme(axis.line=element_line(color=light, size=0.1))\r\n  gg <- gg + theme(axis.line.x=element_line(color=light, size=0.1))\r\n  gg <- gg + theme(axis.line.y=element_blank())\r\n  gg <- gg + theme(legend.position="none")\r\n  gg_bars <- gg\r\n\r\n  # dimensions arrived at via trial and error\r\n\r\n  png(sprintf(".\/booms\/frame_%03d.png", i), width=639.5*2, height=544*2, res=144, bg=scary)\r\n  grid.arrange(gg_map, gg_bars, ncol=1, heights=c(0.85, 0.15), padding=unit(0, "null"), clip="on")\r\n  dev.off()\r\n\r\n}))<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"
> UPDATE: For #rstats folks interested in what this might look like in D3, [take a gander](https:\/\/rud.is\/b\/2016\/03\/27\/nuclear-animations-in-d3\/) @jsvine (Data Editor at BuzzFeed) cleaned up and posted a [data sets of historical nuclear explosions](https:\/\/github.com\/data-is-plural\/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 […]<\/p>\n","protected":false},"author":1,"featured_media":4215,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":true,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"activitypub_content_warning":"","activitypub_content_visibility":"","activitypub_max_image_attachments":3,"activitypub_interaction_policy_quote":"anyone","activitypub_status":"","footnotes":""},"categories":[24,678,673,674,753,91],"tags":[810],"class_list":["post-4203","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-charts-graphs","category-data-visualization","category-datavis-2","category-dataviz","category-ggplot","category-r","tag-post"],"yoast_head":"\nNuclear Animations in R - rud.is<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/rud.is\/b\/2016\/03\/26\/nuclear-animations-in-r\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Nuclear Animations in R - rud.is\" \/>\n<meta property=\"og:description\" content=\"> UPDATE: For #rstats folks interested in what this might look like in D3, [take a gander](https:\/\/rud.is\/b\/2016\/03\/27\/nuclear-animations-in-d3\/) @jsvine (Data Editor at BuzzFeed) cleaned up and posted a [data sets of historical nuclear explosions](https:\/\/github.com\/data-is-plural\/nuclear-explosions) earlier this week. 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So much so that I made a D3 version that's similar to the R version I made the other day. 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