world map - map halves of countries to different colors

Question

I am using the example here for discussion: ggplot map with l

library(rgdal)
library(ggplot2)
library(maptools)

# Data from http://thematicmapping.org/downl         


        

Answer 1

This is a solution without ggplot that relies on the plot function instead. It also requires the rgeos package in addition to the code in the OP:

EDIT Now with 10% less visual pain

EDIT 2 Now with centroids for east and west halves

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)

Perhaps someone can come up with a good solution using ggplot2. However, based on this answer to a question about multiple fill scales for a single graph ("You can't"), a ggplot2 solution seems unlikely without faceting (which might be a good approach, as suggested in the comments above).

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EDIT re: mapping centroids of the halves to something: The centroids for the east ("left") halves can be obtained by

coordinates(lSPDF)

Those for the west ("right") halves can be obtained by creating an rSPDF object in a similar way:

# 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)

Then information could be plotted on the map according to the centroids of lSPDF or rSPDF:

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