| #!/usr/bin/Rscript |
| library(RKorAPClient) |
| library(ggplot2) |
| library(raster) |
| library(broom) |
| library(plotly) |
| library(htmlwidgets) |
| |
| devAskNewPage(ask = FALSE) |
| mapfile <- "demo/data/cache/map-v2.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_0", "CHE_0", "LUX_0", "BEL_3", "ITA_1", "LIE_0"), c(0, 0, 0, 0, 34, 17, 0)) |
| |
| geoDistrib <- function(query, kco = new("KorAPConnection", verbose=TRUE)) { |
| regions <- readRDS("demo/data/regions.rds") |
| regions$freq <- NA |
| regions$url <- NA |
| plot <- NULL |
| vc <- "" |
| for (i in 1:nrow(regions)) { |
| if (!is.na(regions[i,]$query)) { |
| cat(as.character(regions[i,]$region), "\n") |
| regions[i,]$total <- corpusStats(kco, vc=paste0(vc, regions[i,]$query))@tokens |
| if (regions[i,]$total == 0) { |
| regions[i,]$afreq <- 0 |
| regions[i,]$freq <- NA |
| } else { |
| kqo <- corpusQuery(kco, query, vc=paste0(vc, regions[i,]$query)) |
| regions[i,]$afreq <- kqo@totalResults |
| regions[i,]$freq <- regions[i,]$afreq / regions[i,]$total |
| regions[i,]$url <- kqo@webUIRequestUrl |
| } |
| cat(regions[i,]$afreq, regions[i,]$total, regions[i,]$freq, "\n") |
| cat("\n\n") |
| } |
| } |
| plot <- updatePlot(query, map, regions) |
| pp <- ggplotly(plot) |
| for (i in 1:nrow(regions)) { |
| j <- grep(paste0(regions$region[i], "\""), pp$x$data, perl=TRUE) |
| pp$x$data[[j]]$customdata <- regions[i,]$url |
| } |
| ppp <- onRender(pp, "function(el, x) { el.on('plotly_click', function(d) { var url=d.points[0].data.customdata; window.open(url, 'korap') })}") |
| print(ppp) |
| pp |
| } |
| |
| updatePlot <- function(query, map, regions) { |
| map$ipm <- sapply(map$grp, function(grp) regions$freq[grp] * 10^6) |
| map$region <- sapply(map$grp, function(grp) regions$region[grp]) |
| map$url <- sapply(map$grp, function(grp) regions$url[grp]) |
| regionsPlot <- ggplot(map) + |
| geom_polygon(aes(x=long, y=lat, group=group, fill=ipm, hack=region), 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 \u201c%s\u201d", query)) |
| print(regionsPlot) |
| regionsPlot |
| } |
| |
| #geoDistrib("wegen dem [tt/p=NN]") |
| geoDistrib("heuer") |
| #geoDistrib("Sonnabend") |
| #geoDistrib("eh") |