54 lines
1.3 KiB
R
54 lines
1.3 KiB
R
# read the RDS above, to save as .csv file.
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# source('GetReady.R')
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fun.CMFD.RDS2csv <- function(xfg){
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source('AutoSHUD/Rfunction/LDAS_UnitConvert.R')
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years = xfg$years
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fns = file.path(xfg$dir$predata, paste0('CMFD_',years, '.RDS'))
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fns
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cns = c("Prec", "Temp", "SHum", "SRad", "Wind", "Pres")
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forcnames = c( "Prcp_mm.d", "Temp_C", "RH_%", "Wind_m.s", "RN_w.m2" )
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nf=length(fns)
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for(i in 1:nf){
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x=readRDS(fns[i])
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message(i,'/', nf, '\t', basename(fns[i]))
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y=x[,cns,]
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if(i==1){
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dat = y
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}else{
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dat=abind::abind(dat, y, along=3)
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}
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}
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dn = dimnames(dat)
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nd = dim(dat)
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xl = list()
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time = as.POSIXct(dimnames(dat)[[3]], tz='UTC')
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for(i in 1:nd[1]){
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message(i,'/', nd[1], '\t', dn[[1]][i] )
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x = t( dat[i,,] )
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y=unitConvert.CMFD(x)
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xl[[i]]=as.xts(y, order.by=time)
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}
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nx=length(xl)
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sitename = dn[[1]]
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sitename
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fns=paste0(sitename, '.csv')
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for(i in 1:nx){
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fn=fns[i]
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message(i,'/', nx, '\t', fn)
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write.tsd(xl[[i]], file.path(xfg$dir$forc, fn))
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if(i==1){
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xmean = xl[[i]]
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}else{
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xmean = xmean + xl[[i]]
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}
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}
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png(fn=file.path(xfg$dir$fig, paste0(xfg$prefix, '_Rawdata','_CMFD_TS.png') ), type='cairo',
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height=6, width=7, res=200, units = 'in')
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plot.zoo(xmean/nx, main='CMFD')
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dev.off()
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} |