gmt.map.variables.core = function( id=NULL, U, params, variables, plottimes, basedir, conversions, delta, db ) {
varnames = colnames(U)
# the first index is a list that is passed from the calling prog: in this case "ssplt" (if parallel)
if (params$do.parallel) {
id = as.numeric(id)
if (exists( "libs", p)) RLibrary( p$libs )
} else {
id = c(1:length(variables) )
}
for (i in id) {
plotvar = variables[i]
if (! (plotvar %in% varnames) ) next ()
for (ti in plottimes) {
u = recode.time(U, ti, delta ) # delta is for running averages
u[,plotvar] = variable.recode( u[,plotvar], plotvar, "forward", db=db) # check if log transform is needed
u = u[, c("yr", "lon", "lat", plotvar, "sa")]
u = u[is.finite(u[,plotvar] *u[,"lon"]*u[,"lat"] ),]
params$outdir = file.path(basedir, ti, plotvar)
params = gmt.define.colours (params, variable=plotvar)
params = gmt.colourscale(params, u[,plotvar], plotvar, NSTD=3 ) # NSTD is no of stdev
dir.create ( params$outdir, recursive=T, showWarnings=F )
for (j in sort(unique(u$yr)) ) {
oo = which(u$yr==j & is.finite( u[,1] + u[,2] + u[,3]+u[,4] ) )
if (length(oo) > 10 ) {
toplot = u[ oo, c("lon", "lat", plotvar, "sa") ]
params$outfile.basename = file.path(params$outdir, paste(plotvar, j, sep="."))
# print( params$outfile.basename )
gmt.map( params, toplot, year=j, vname=plotvar, conversions=conversions )
}
}
}}
return ()
}
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