rdwd (version 1.2.0)

readDWD.asc: read dwd gridded radolan asc data

Description

read grid-interpolated radolan asc data. Intended to be called via readDWD. All layers (following selection if given) in all .tar.gz files are combined into a raster stack with raster::stack. To project the data, use projectRasterDWD

Usage

readDWD.asc(file, exdir = NULL, dividebyten = TRUE, selection = NULL,
  progbar = TRUE, ...)

Arguments

file

Name of file on harddrive, like e.g. DWDdata/grids_germany/hourly/radolan/historical/asc/ 2018_RW-201809.tar. Must have been downloaded with mode="wb"!

exdir

Directory to unzip into. Unpacked files existing therein will not be untarred again, saving up to 15 secs per file. DEFAULT: NULL (subfolder of tempdir())

dividebyten

Divide numerical values by 10? If dividebyten=FALSE and exdir left at NULL (tempdir), save the result on disc with raster::writeRaster. Accessing out-of-memory raster objects won't work if exdir is removed! -> Error in .local(.Object, ...) DEFAULT: TRUE

selection

Optionally read only a subset of the ~24*31=744 files. Called as f[selection]. DEFAULT: NULL (ignored)

progbar

Show messages and progress bars? readDWD will keep progbar=TRUE for asc files, even if length(file)==1. DEFAULT: TRUE

…

Further arguments passed to raster::raster

Value

data.frame

See Also

readDWD

Examples

# NOT RUN {
 # Excluded from CRAN checks, but run in localtests

# File selection and download:
datadir <- localtestdir()
radbase <- paste0(gridbase,"/hourly/radolan/historical/asc/")
radfile <- "2018/RW-201809.tar" # 25 MB to download
file <- dataDWD(radfile, base=radbase, joinbf=TRUE, dir=datadir,
                dfargs=list(mode="wb"), read=FALSE) # download with mode=wb!!!
                
#asc <- readDWD(file) # 4 GB in mem. ~ 20 secs unzip, 30 secs read, 10 min divide
asc <- readDWD(file, selection=1:5, dividebyten=TRUE)
asc <- projectRasterDWD(asc)

raster::plot(asc[[1]], main=names(asc)[1])
addBorders()

rng <- range(raster::cellStats(asc, "range"))
nframes <- 3 # raster::nlayers(asc) for all (time intensive!)
viddir <- paste0(tempdir(),"/RadolanVideo")
dir.create(viddir)
png(paste0(viddir,"/Radolan_%03d.png"), width=7, height=5, units="in", res=300)
dummy <- pbsapply(1:nframes, function(i) 
         raster::plot(asc[[i]], main=names(asc)[i], zlim=rng)) # 3 secs per layer
dev.off()
berryFunctions::openFile(paste0(viddir,"/Radolan_001.png"))

# Time series of a given point in space:
plot(as.vector(asc[800,800,]), type="l", xlab="Time [hours]")

# if dividebyten=FALSE, raster stores things out of memory in the exdir.
# by default, this is in tempdir, hence you would need to save asc manually:
# raster::writeRaster(asc, paste0(datadir,"/RW2018-09"), overwrite=TRUE) 
# }

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