Add example for regional frequency distribution
Change-Id: I5cc2f31baae86ccba1eb73a4b0bb76d0fbfaba1c
diff --git a/examples/geo/regional.R b/examples/geo/regional.R
new file mode 100644
index 0000000..59e7e7f
--- /dev/null
+++ b/examples/geo/regional.R
@@ -0,0 +1,80 @@
+#!/usr/bin/Rscript
+library(RKorAPClient)
+library(ggplot2)
+library(raster)
+library(broom)
+
+mapfile <- "examples/geo/data/cache/map.rds"
+
+fetchAndPrepareMap <- function(map, pick) {
+ cat("Downloading GADM map data for ", map, "\n")
+ sp <- readRDS(url(sprintf("https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_%s_sp.rds", map)))
+ if (pick > 0) {
+ sp@polygons <- sp@polygons[pick]
+ sp@data <- sp@data[pick,]
+ }
+ sp
+}
+
+fetchMaps <- function(maps, picks) {
+ if (file.exists(mapfile)) {
+ df <- readRDS(mapfile)
+ } else {
+ cat("Downloading and caching GADM map data.\nPlease note that the GADM map data is licensed for academic use and other non-commercial use, only.\nSee https://gadm.org/license.html\n")
+ df <- broom::tidy(Reduce(bind, mapply(fetchAndPrepareMap, maps, picks)))
+ dir.create(dirname(mapfile), recursive = TRUE, showWarnings = FALSE)
+ saveRDS(df, mapfile)
+ }
+ df$grp <- floor(as.numeric(as.character(df$group)))
+ df
+}
+
+map <- fetchMaps(c("DEU_1", "AUT_1", "CHE_1", "LUX_0", "BEL_3", "ITA_1"), c(0,0,0,0,34,17))
+
+geoDistrib <- function(query, kco = new("KorAPConnection", verbose=TRUE)) {
+ regions <- readRDS("examples/geo/data/regions.rds")
+ regions$freq <- NA
+ plot <- NULL
+ vc <- ""
+ for (i in 1:nrow(regions)) {
+ if (!is.na(regions[i,]$query)) {
+ cat(as.character(regions[i,]$land), "\n")
+ regions[i,]$total <- corpusStats(kco, vc=paste0(vc, regions[i,]$query))@tokens
+ if (regions[i,]$total == 0) {
+ regions[i,]$afreq <- 0
+ regions[i,]$freq <- NA
+ } else {
+ regions[i,]$afreq <- corpusQuery(kco, query, vc=paste0(vc, regions[i,]$query))@totalResults
+ regions[i,]$freq <- regions[i,]$afreq / regions[i,]$total
+ }
+ cat(regions[i,]$afreq, regions[i,]$total, regions[i,]$freq, "\n")
+ plot <- updatePlot(query, plot, map, regions)
+ cat("\n\n")
+ }
+ }
+}
+
+updatePlot <- function(query, regionsPlot, map, laender) {
+ map$ipm <- sapply(map$grp, function(grp) laender$freq[grp] * 10^6)
+ regionsPlot <- ggplot(map) +
+ geom_polygon(aes(x=long, y=lat, group=group, fill=ipm), colour= "black", size=.1) +
+ theme(axis.line.x = element_blank(),
+ axis.line.y = element_blank(),
+ panel.grid.major = element_blank(),
+ panel.grid.minor = element_blank(),
+ panel.border = element_blank(),
+ panel.background = element_blank(),
+ axis.line=element_blank(),axis.text.x=element_blank(),
+ axis.text.y=element_blank(),axis.ticks=element_blank(),
+ axis.title.x=element_blank(),
+ axis.title.y=element_blank()) +
+ coord_equal(ratio=1.5) +
+ labs(title = sprintf("Regional distribution of “%s”", query))
+ print(regionsPlot)
+ regionsPlot
+}
+
+#geoDistrib("wegen dem [tt/p=NN]")
+geoDistrib("heuer")
+#geoDistrib("Sonnabend")
+#geoDistrib("eh")