#script to make high quality GEDI graph
# input mapCentroid.txt output from GEDI
#	number of rows (GEDI grid size is colXrow)
#	number of cols
#       optional: upper limit of lowest bin, default .10 quantile
#       optional: lower limit of highest bin, default .90 quantile
#	optional: number of bins

args <- commandArgs(trailingOnly = TRUE)
file <- args[1]
numr <- as.numeric(args[2])
numc <- as.numeric(args[3])
if (exists(args[4])) {
   lim1 <- as.numeric(args[4])
}
if (exists(args[5])) {
   lim2 <- as.numeric(args[5])
}
bins = 100 #should be much higher than number of colors
if (exists(args[6])) {
   bins <- as.integer(args[6])
}

data <- read.table(file, sep="\t", header=TRUE, row.names=1)
data <- as.matrix(data)
summary(data)

if (exists(args[4])) {
   lim1=as.numeric(args[4])
}else {
   lim1=quantile(data, c(.10))
}
if (exists(args[5])) {
   lim2=as.numeric(args[5])
}else {
   lim2=quantile(data, c(.90))
}
step = (lim2 - lim1)/bins
breaks = c(seq(lim1,lim2,by=step))
tot=ncol(data)

library(gplots)

#put into numr by numc matrix and print for each graph
for (i in 1:tot) {
   d=matrix(data[,i], nrow=numr, ncol=numc)
   pdf(file=paste0("GEDI",colnames(data)[i],".pdf"))
   heatmap.2(d, Rowv=FALSE, Colv=FALSE, trace="none", scale="none", col=colorRampPalette(c("navyblue","mediumblue","cyan3","cyan","green","yellow","orange","red","brown","brown4")), dendrogram="none",breaks=breaks, labRow=FALSE, labCol=FALSE, density.info="none", key=TRUE)
   dev.off()
}