111 lines
3.7 KiB
R
111 lines
3.7 KiB
R
# read the orginal fldas data and save to .RDS file.
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#install.packages('ncdf4')
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require(ncdf4)
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# library(rSHUD)
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# source('GetReady.R')
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# =========Forcing Coverage===========================
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# sp0 = readOGR(xfg$fsp.forc)
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# ========= Get the GRID===========================
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# spx = readOGR(xfg$pd.gcs$meteoCov)
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# fl=spx@data
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fun.GLDAS.nc2RDS <- function(xfg, res=0.25){
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buf.g = readOGR(xfg$pd.gcs$wbd.buf)
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ext = extent(buf.g)
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dir.years = file.path(xfg$dir.ldas, xfg$years)
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ndir = length(dir.years)
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xfg$dir.ldas
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writelog(msg=paste0('forcing dir:', xfg$dir.ldas), caller = caller)
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fns=list.files(file.path(xfg$dir.ldas, '2002/100'), pattern=glob2rx('*.nc4'), recursive = T, full.names = T)[1]
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# cmd = paste('find',xfg$dir.lddas, ' -name "*.nc4" > filelist.txt')
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# system(cmd)
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# fns=readLines(file.path(xfg$dir.ldas, 'filelist.txt'))
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fid=nc_open(fns[1]) #打开一个NC文件
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nc.all = rSHUD::readnc(fid, varid = 2)
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nc.sub = rSHUD::readnc(fid, varid = 2, ext = ext)
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nc_close(fid)
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r = xyz2Raster(x = nc.all)
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r.sub = xyz2Raster(x = nc.sub, res=res)
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# plot(r.sub);
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# plot(add=T, buf.g)
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vns = names(fid$var)
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vns = vns[! grepl('time', tolower(vns))] # don't need the time_bnds
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# =========PLOT===========================
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go.plot <- function(prefix){
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png(file.path(xfg$dir$fig, paste0(prefix, '_LDAS_location.png')), height=8, width=15, units = 'in', res=200)
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plot(r * 0, col='gray', legend=FALSE)
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plot(r.sub * 0, col='red', legend=FALSE, add=TRUE)
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plot(buf.g, add=T)
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grid();
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mtext(side=3, 'GLDAS coverage (0.25 deg)')
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dev.off()
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}; go.plot(xfg$prefix)
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# =========Get the data===========================
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xfg$res = 0.25
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yx = expand.grid(nc.sub$y, nc.sub$x)
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rn = paste0('X', yx[, 2], 'Y',yx[,1])
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ext.fn = c(range(yx[, 2]), range(yx[, 1]) ) + c(-1, 1, -1, 1) *0.5 * xfg$res
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ext.fn
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sp.forc = fishnet(xx=seq(ext.fn[1], ext.fn[2], xfg$res ),
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yy=seq(ext.fn[3], ext.fn[4], xfg$res), crs=xfg$crs.gcs)
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go.plot <- function(prefix){
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png(file.path(xfg$dir$fig, paste0(prefix, '_LDAS_Coverage.png')), height=8, width=8, units = 'in', res=200)
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plot(sp.forc, axes=TRUE);
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plot(buf.g, border='red', add=T); grid()
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text(yx[, 2], yx[, 1]+xfg$res/5, paste0('X', yx[, 2]))
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text(yx[, 2], yx[, 1]-xfg$res/5, paste0('Y', yx[, 1]))
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mtext(side=3, 'GLDAS coverage (0.25 deg)')
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dev.off()
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}; go.plot(xfg$prefix)
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sp0.gcs = spTransform(sp.forc, xfg$crs.gcs)
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sp0.pcs = spTransform(sp.forc, xfg$crs.pcs)
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writeshape(sp0.gcs, file = xfg$pd.gcs$meteoCov)
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writeshape(sp0.pcs, file = xfg$pd.pcs$meteoCov)
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ns = length(rn)
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nv=length(vns)
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# library(foreach)
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# library(doMC)
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# library(doParallel)
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# registerDoMC(12)
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# foreach (idd = 1:ndir) %dopar%{
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for (idd in 1:ndir) {
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cdir <- dir.years[idd]
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message(idd, '/', ndir, '\t', basename(cdir))
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fn.rds = file.path(xfg$dir$predata, paste0(xfg$prjname,'-', basename(cdir), '.RDS'))
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if(!file.exists(fn.rds)){
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fns = list.files(cdir, pattern=glob2rx('*.nc4'), recursive = T, full.names = T)
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nf = length(fns)
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x.t= character(nf)
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for(j in 1:nf){ # files in each year
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fn=fns[j]
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message('\t', j, '/', nf, '\t', basename(fn))
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ncid = nc_open(fn)
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# debug(readnc)
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x.nc = readnc(ncid, varid=vns, ext=ext)
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nc_close(ncid)
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if(j == 1){
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d3 = dim(x.nc$arr)
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x.arr = array(0, dim=c(d3[1] * d3[2], nv, nf) )
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}
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x.t[j] = strftime(x.nc$time, usetz = FALSE, tz='UTC')
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x.arr[ , , j] = matrix(x.nc$arr, ncol=nv)
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}
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dimnames(x.arr) = list(rn, vns, x.t)
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saveRDS(x.arr, file=fn.rds)
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}else{
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}
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}
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}
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# xfg = CV$xfg
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# xfg$prefix = 'AutoSHUD_S2'
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# fun.GLDAS.nc2RDS(xfg)
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# fun.GLDAS.RDS2csv(xfg) |