r - 使用降雪和sfLapply栅格化R中的多边形

我想将一个非常大的矢量文件光栅化到25m，并且在“cluster”包中取得了一些成功，修改了qu的here和here，这两个包对于特定的数据非常有效。
不过，我现在有一个更大的矢量文件，需要光栅化，并有权访问使用降雪群集。我不习惯集群函数，我只是不知道如何设置sfLapply。当在集群中调用sfLapply时，我始终会得到以下类型的错误：

Error in checkForRemoteErrors(val) :
  one node produced an error: 'quote(96)' is not a function, character or symbol
Calls: sfLapply ... clusterApply -> staticClusterApply -> checkForRemoteErrors

我的完整代码：

library(snowfall)
library(rgeos)
library(maptools)
library(raster)
library(sp)

setwd("/home/dir/")

# Initialise the cluster...
hosts = as.character(read.table(Sys.getenv('PBS_NODEFILE'),header=FALSE)[,1]) # read the nodes to use
sfSetMaxCPUs(length(hosts)) # make sure the maximum allowed number of CPUs matches the number of hosts
sfInit(parallel=TRUE, type="SOCK", socketHosts=hosts, cpus=length(hosts), useRscript=TRUE) # initialise a socket cluster session with the named nodes
sfLibrary(snowfall)

# read in required data

shp <- readShapePoly("my_data.shp")
BNG <- "+proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000 +ellps=airy +datum=OSGB36 +units=m +no_defs"
crs(shp) <- BNG

### rasterize the uniques to 25m and write (GB and clipped) ###
rw <- raster(res=c(25,25), xmn=0, xmx=600000, ymn=0, ymx=1000000, crs=BNG)

# Number of polygons features in SPDF
features <- 1:nrow(shp[,])

# Split features in n parts
n <- 96
parts <- split(features, cut(features, n))

rasFunction = function(X, shape, raster, nparts){
    ras = rasterize(shape[nparts[[X]],], raster, 'CODE')
    return(ras)
}

# Export everything in the workspace onto the cluster...
sfExportAll()

# Distribute calculation across the cluster nodes...
rDis = sfLapply(n, fun=rasFunction,X=n, shape=shp, raster=rw, nparts=parts) # equivalent of sapply
rMerge <- do.call(merge, rDis)

writeRaster(rMerge, filename="my_data_25m",  format="GTiff", overwrite=TRUE)

# Stop the cluster...
sfStop()

我试过很多方法，改变函数和函数，但是我不能让它运行。谢谢

最佳答案

因为我不能在评论中设置格式：

library(maptools)
shp <- readShapePoly("my_data.shp")
BNG <- "+proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000 +ellps=airy +datum=OSGB36 +units=m +no_defs"

shp.2 <- spTransform(shp, BNG)
#Continue as before

覆盖投影！=重新注入数据。