R 世界地图-将一半国家映射为不同颜色

我在这里用这个例子进行讨论：

库（rgdal）
图书馆（GG2）
图书馆（地图工具）
#数据来自http://thematicmapping.org/downloads/world_borders.php.
#直接链接：http://thematicmapping.org/downloads/TM_WORLD_BORDERS_SIMPL-0.3.zip
#解包并将文件放入目录“数据”
gpclibPermit（）
world.map这是一个没有
ggplot
的解决方案，它依赖于
plot
函数。除了OP中的代码外，它还需要
rgeos
包：

编辑现在视觉疼痛减轻10%

编辑2现在东半部和西半部具有质心

library(rgeos)
library(RColorBrewer)

# Get centroids of countries
theCents <- coordinates(world.map)

# extract the polygons objects
pl <- slot(world.map, "polygons")

# Create square polygons that cover the east (left) half of each country's bbox
lpolys <- lapply(seq_along(pl), function(x) {
  lbox <- bbox(pl[[x]])
  lbox[1, 2] <- theCents[x, 1]
  Polygon(expand.grid(lbox[1,], lbox[2,])[c(1,3,4,2,1),])
})

# Slightly different data handling
wmRN <- row.names(world.map)

n <- nrow(world.map@data)
world.map@data[, c("growth", "category")] <- list(growth = 4*runif(n),
                 category = factor(sample(1:5, n, replace=TRUE)))

# Determine the intersection of each country with the respective "left polygon"
lPolys <- lapply(seq_along(lpolys), function(x) {
  curLPol <- SpatialPolygons(list(Polygons(lpolys[x], wmRN[x])),
    proj4string=CRS(proj4string(world.map)))
  curPl <- SpatialPolygons(pl[x], proj4string=CRS(proj4string(world.map)))
  theInt <- gIntersection(curLPol, curPl, id = wmRN[x])
  theInt
})

# Create a SpatialPolygonDataFrame of the intersections
lSPDF <- SpatialPolygonsDataFrame(SpatialPolygons(unlist(lapply(lPolys,
  slot, "polygons")), proj4string = CRS(proj4string(world.map))),
  world.map@data)

##########
## EDIT ##
##########
# Create a slightly less harsh color set
s_growth <- scale(world.map@data$growth,
  center = min(world.map@data$growth), scale = max(world.map@data$growth))
growthRGB <- colorRamp(c("red", "blue"))(s_growth)
growthCols <- apply(growthRGB, 1, function(x) rgb(x[1], x[2], x[3],
  maxColorValue = 255))
catCols <- brewer.pal(nlevels(lSPDF@data$category), "Pastel2")

# and plot
plot(world.map, col = growthCols, bg = "grey90")

plot(lSPDF, col = catCols[lSPDF@data$category], add = TRUE)

可通过以类似方式创建
rSPDF
对象来获得西半部（“右”）的对象：

# Create square polygons that cover west (right) half of each country's bbox
rpolys <- lapply(seq_along(pl), function(x) {
  rbox <- bbox(pl[[x]])
  rbox[1, 1] <- theCents[x, 1]
  Polygon(expand.grid(rbox[1,], rbox[2,])[c(1,3,4,2,1),])
})

# Determine the intersection of each country with the respective "right polygon"
rPolys <- lapply(seq_along(rpolys), function(x) {
  curRPol <- SpatialPolygons(list(Polygons(rpolys[x], wmRN[x])),
    proj4string=CRS(proj4string(world.map)))
  curPl <- SpatialPolygons(pl[x], proj4string=CRS(proj4string(world.map)))
  theInt <- gIntersection(curRPol, curPl, id = wmRN[x])
  theInt
})

# Create a SpatialPolygonDataFrame of the western (right) intersections
rSPDF <- SpatialPolygonsDataFrame(SpatialPolygons(unlist(lapply(rPolys,
  slot, "polygons")), proj4string = CRS(proj4string(world.map))),
  world.map@data)

你可能会考虑并列两张地图。可能比这个国家分裂更直观。@Marcinebox谢谢你的建议。谢谢你的回答（和更新）。如果我遵循以下网站上的建议，这是否允许我结合您所做的工作（除了ggplot2）@XuWang，您应该能够使用链接的说明绘制
lSPDF
和
rSPDF
形状文件，但是如果您希望每个半部分都有不同的
fill
映射，那么您可能会遇到问题。
coordinates(lSPDF)

# Create square polygons that cover west (right) half of each country's bbox
rpolys <- lapply(seq_along(pl), function(x) {
  rbox <- bbox(pl[[x]])
  rbox[1, 1] <- theCents[x, 1]
  Polygon(expand.grid(rbox[1,], rbox[2,])[c(1,3,4,2,1),])
})

# Determine the intersection of each country with the respective "right polygon"
rPolys <- lapply(seq_along(rpolys), function(x) {
  curRPol <- SpatialPolygons(list(Polygons(rpolys[x], wmRN[x])),
    proj4string=CRS(proj4string(world.map)))
  curPl <- SpatialPolygons(pl[x], proj4string=CRS(proj4string(world.map)))
  theInt <- gIntersection(curRPol, curPl, id = wmRN[x])
  theInt
})

# Create a SpatialPolygonDataFrame of the western (right) intersections
rSPDF <- SpatialPolygonsDataFrame(SpatialPolygons(unlist(lapply(rPolys,
  slot, "polygons")), proj4string = CRS(proj4string(world.map))),
  world.map@data)

points(coordinates(rSPDF), col = factor(rSPDF@data$REGION))
# or
text(coordinates(lSPDF), labels = lSPDF@data$FIPS, cex = .7)