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plot.R
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plot.R
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##' @importFrom ggplot2 ggplot
##' @importFrom ggplot2 aes_
##' @importFrom ggplot2 theme_minimal
##' @importFrom ggplot2 xlab
##' @importFrom ggplot2 ylab
##' @importFrom ggplot2 labs
##' @importFrom ggplot2 coord_sf
##' @importFrom ggplot2 geom_sf
##' @importFrom ggplot2 geom_sf_text
plot_city <- function(x, region, chinamap,
continuous_scale=TRUE, label=TRUE, date, palette = "Reds",
font.size = 3.8, font.family = "") {
map <- tibble::as_tibble(chinamap)
if (x$lang == "zh") {
load(system.file("ncovEnv.rda", package="nCov2019"))
ncovEnv <- get("ncovEnv")
setup_city <- get("setup_city", envir = ncovEnv)
map$NAME <- setup_city(map$NAME)
}
map <- do.call('rbind', lapply(region, function(r) {
stats <- get_city_data(x, r, date)
code <- sub("(\\d{2}).*", "\\1",
map$ADMINCODE[which(map$NAME == stats[1,1])])
map[grep(paste0("^", code), map$ADMINCODE),]
}))
stats <- get_city_data(x, region, date)
map2 <- dplyr::left_join(map, stats, by='NAME')
p <- ggplot(map2, aes_(geometry=~geometry)) +
theme_minimal() + xlab(NULL) + ylab(NULL) +
labs(title = '2019nCov',
subtitle = paste('confirmed cases:', sum(stats$confirm)),
caption=paste("accessed date:", time(x))) +
coord_sf()
if (continuous_scale) {
p <- p + geom_sf(aes_(fill=~confirm)) +
fill_scale_continuous(palette)
} else {
map2$confirm2 <- cut(map2$confirm2, discrete_breaks,
include.lowest = T, right=F)
p <- p + geom_sf(aes_(fill=~confirm2)) +
fill_scale_discrete(palette)
}
if (label) p <- p + geom_sf_text(aes_(label=~NAME), size=font.size, family=font.family)
return(p)
}
##' @importFrom ggplot2 map_data
##' @importFrom ggplot2 coord_equal
plot_world <- function(x, continuous_scale=TRUE, palette = "Reds") {
d <- x['global', ]
if (x$lang == "zh") {
nn <- readRDS(system.file("country_translate.rds", package="nCov2019"))
d$name <- nn[as.character(d$name)]
}
d$name <- sub("United\\sStates.*", "USA", d$name)
world <- map_data('world')
world <- world[world$region != "Antarctica", ]
w <- merge(world, d, by.x='region', by.y='name', all.x=T)
w <- w[order(w$order),]
p <- ggplot(w, aes_(~long, ~lat)) +
coord_equal() +
theme_minimal(base_size = 14) +
xlab(NULL) + ylab(NULL) +
labs(title = '2019nCov',
subtitle = paste('confirmed cases:', sum(d$confirm)),
caption=paste("accessed date:", time(x)))
if (continuous_scale) {
p1 <- p +
geom_map(aes_(~long, ~lat, map_id = ~region, group=~group, fill=~confirm),
map=w, data=w, colour='grey') +
fill_scale_continuous(palette)
} else {
w$confirm2 = cut(w$confirm, discrete_breaks,
include.lowest = T, right=F)
p1 <- p +
geom_map(aes_(~long, ~lat, map_id=~region, group=~group, fill=~confirm2),
map=w, data=w, colour='grey') +
fill_scale_discrete(palette)
}
return(p1)
}
##' @importFrom ggplot2 coord_map
plot_china <- function(x, chinamap, continuous_scale = TRUE, date, palette = "Reds") {
if (!missing(date)) {
tt <- date
} else {
tt <- time(x)
}
if (is(x, "nCov2019")) {
total <- x$chinaTotal$confirm
} else if (is(x, "nCov2019History")) {
total <- sum(extract_history(x, date = date)$confirm)
} else {
stop("object not supported...")
}
p <- ggplot() + coord_map() +
theme_minimal() +
xlab(NULL) + ylab(NULL) +
labs(title = '2019nCov',
subtitle = paste('confirmed cases:', total),
caption=paste("accessed date:", tt))
p + layer_chinamap(x, chinamap, continuous_scale, add_scale=TRUE, date=date, palette = palette)
}
##' @importFrom ggplot2 geom_map
layer_chinamap <- function(x, chinamap, continuous_scale = TRUE,
add_scale=TRUE, date, palette = "Reds") {
if (is(x, "nCov2019")) {
df <- x[]
} else if (is(x, "nCov2019History")) {
df <- extract_history(x, date = date)
} else {
stop("object not supported...")
}
cn <- chinamap
if (x$lang == "zh") {
load(system.file("ncovEnv.rda", package="nCov2019"))
ncovEnv <- get("ncovEnv")
setup_province <- get("setup_province", envir = ncovEnv)
cn$province <- setup_province(cn$province)
}
cn2 <- merge(cn, df, by.x='province', by.y='name', all.x=TRUE)
cn2 <- cn2[order(cn2$order),]
if (continuous_scale) {
ly <- list(geom_map(aes_(x=~long, y=~lat, map_id=~id, group=~group, fill=~confirm),
map=cn2, data=cn2, colour='grey'),
fill_scale_continuous(palette)
)
} else {
cn2$confirm2 <- cut(cn2$confirm, discrete_breaks,
include.lowest = T, right=F)
ly <- list(
geom_map(aes_(~long, ~lat, map_id=~id, group=~group,
fill=~confirm2),
map=cn2, data=cn2, colour='grey'),
fill_scale_discrete(palette)
)
}
if (!add_scale) ly[[2]] = NULL
return(ly)
}
##' @importFrom methods is
##' @importFrom ggplot2 geom_text
##' @method plot nCov2019
##' @export
plot.nCov2019 <- function(x, region="world", chinamap,
continuous_scale = TRUE, label = TRUE,
font.size = 3.8, font.family = "", palette = "Reds", ...) {
if ("world" %in% region) {
p <- plot_world(x, continuous_scale = continuous_scale, palette = palette)
if (missing(chinamap)) {
return(p)
} else {
p <- p + layer_chinamap(x, chinamap, continuous_scale, palette = palette, add_scale=FALSE)
}
return(p)
}
if ("china" %in% region) {
p <- plot_china(x, chinamap, continuous_scale, palette = palette, ...)
if (label) {
prov.df <- readRDS(system.file("prov_location.rds", package="nCov2019"))
if (x$lang == "en") {
prov.df$name <- trans_province(prov.df$name)
}
p <- p + geom_text(aes_(~long, ~lat, label=~name), data=prov.df, size=font.size, family=font.family)
}
return(p)
}
plot_city(x, region = region, chinamap = chinamap,
continuous_scale = continuous_scale,
label = label, palette = palette, ...)
}
##' @method plot nCov2019History
##' @export
plot.nCov2019History <- plot.nCov2019