出于复制目的，请考虑以下数据：
library(rgdal)
library(ggplot2)
library(rgeos)
download.file("http://spatialanalysis.co.uk/wp-content/uploads/2010/09/London_Sport.zip",
destfile = "London_Sport.zip")
unzip("London_Sport.zip")
projection="+proj=merc"
london_shape = readOGR("./", layer="london_sport")
# Create random points
set.seed(1)
points = data.frame(long=rnorm(10000, mean=-0.1, sd=0.1), lat=rnorm(10000, mean=51.5, sd=0.1))
points = SpatialPoints(points, proj4string=CRS("+proj=latlon"))
# Transform data to our projection
london = spTransform(london_shape, CRS(projection))
points = spTransform(points, CRS(projection))
# Keeps only points inside London
intersection = gIntersects(points, london, byid = T)
outside = apply(intersection == FALSE, MARGIN = 2, all)
points = points[which(!outside), ]
# Blank theme
new_theme_empty <- theme_bw()
new_theme_empty$line <- element_blank()
new_theme_empty$rect <- element_blank()
new_theme_empty$strip.text <- element_blank()
new_theme_empty$axis.text <- element_blank()
new_theme_empty$plot.title <- element_blank()
new_theme_empty$axis.title <- element_blank()
new_theme_empty$plot.margin <- structure(c(0, 0, -1, -1), unit = "lines", valid.unit = 3L, class = "unit")
# Prepare data to ggplot
london = fortify(london)
points = as.data.frame(points)
我想绘制点的密度图。我可以通过使用来做到这一点stat_bin2d:
ggplot() +
geom_polygon(data=london, aes(x=long,y=lat,group=group), fill="black") +
stat_bin2d(data=points, aes(x=long,y=lat), bins=40) +
geom_path(data=london, aes(x=long,y=lat,group=id), colour='white') +
coord_equal() +
new_theme_empty
但这会导致密度方块的某些部分被绘制在伦敦以外的地方：
如何仅绘制伦敦内部的密度图？
我通过获取伦敦边界框与伦敦本身之间的差异的多边形找到了答案（使用gDifference）并将其绘制在所有内容之上的白色。我认为这种方法的缺点是：1）如果某些正方形仍然出现在多边形后面，则必须手动增加多边形的大小。 2）不能使用背景复杂的绘图主题。因此，如果有人有更好的答案，我将暂时保留这个问题。
这是代码：
library(rgdal)
library(ggplot2)
library(rgeos)
projection="+proj=merc"
#London boroughs polygons
download.file("http://spatialanalysis.co.uk/wp-content/uploads/2010/09/London_Sport.zip", destfile = "London_Sport.zip")
unzip("London_Sport.zip")
london = readOGR("./", layer="london_sport")
london = spTransform(london, CRS(projection))
# Generate random points
set.seed(1)
points = data.frame(long=rnorm(10000, mean=-0.1, sd=0.1), lat=rnorm(10000, mean=51.5, sd=0.1))
points = SpatialPoints(points, proj4string=CRS("+proj=latlon"))
points = spTransform(points, CRS(projection))
# Keep only points inside London
intersection = gIntersects(points, london, byid = TRUE)
inside = apply(intersection == TRUE, MARGIN = 2, any)
points = points[which(inside), ]
# Create a bounding box 10% bigger than the bounding box of London
x_excess = (london@bbox['x','max'] - london@bbox['x','min'])*0.1
y_excess = (london@bbox['y','max'] - london@bbox['y','min'])*0.1
x_min = london@bbox['x','min'] - x_excess
x_max = london@bbox['x','max'] + x_excess
y_min = london@bbox['y','min'] - y_excess
y_max = london@bbox['y','max'] + y_excess
bbox = matrix(c(x_min,x_max,x_max,x_min,x_min,
y_min,y_min,y_max,y_max,y_min),
nrow = 5, ncol =2)
bbox = Polygon(bbox, hole=FALSE)
bbox = Polygons(list(bbox), "bbox")
bbox = SpatialPolygons(Srl=list(bbox), pO=1:1, proj4string=london@proj4string)
# Get the Polygon that is the difference between the bounding box and London
outside = gDifference(bbox,london)
# Blank theme
new_theme_empty <- theme_bw()
new_theme_empty$line <- element_blank()
new_theme_empty$rect <- element_blank()
new_theme_empty$strip.text <- element_blank()
new_theme_empty$axis.text <- element_blank()
new_theme_empty$plot.title <- element_blank()
new_theme_empty$axis.title <- element_blank()
new_theme_empty$plot.margin <- structure(c(0, 0, -1, -1), unit = "lines", valid.unit = 3L, class = "unit")
# Prepare data for ggplot
london = fortify(london)
points = as.data.frame(points)
outside = fortify(outside)
# Plot!
ggplot() +
geom_polygon(data=london, aes(x=long,y=lat,group=group), fill="black") +
stat_bin2d(data=points, aes(x=long,y=lat), bins=40) +
geom_path(data=london, aes(x=long,y=lat,group=id), colour='white') +
geom_polygon(data=outside, aes(x=long,y=lat), fill='white') +
coord_equal() +
new_theme_empty
