source('../../cfneval_lib.R')
source('weightedTau.R')

# set constants
cost.fcn    <- c('pred_pb_mean')
eval.dir    <- '/projects/compbio/experiments/protein-predict/casp7'
target.file <- paste(eval.dir, 'target_list.txt', sep='/')
score.file  <- 'decoys/evaluate.anglevector.rdb'
qual.metric <- 'real_cost'

# read the targets
targets <- read.delim(target.file, header=FALSE, colClasses="character")$V1

# set up data structures to store the decoy information
decoys <- vector("list", length(targets))
names(decoys) <- targets
complete.decoys <- partial.decoys <- decoys

# populate those structures
for(t in targets)
{    decoys[[t]] <- read.rdb(paste(eval.dir, t, score.file, sep='/'))
     decoys[[t]] <- subset(decoys[[t]],
	      decoys[[t]][[qual.metric]] != min(decoys[[t]][[qual.metric]]))
     complete.decoys[[t]] <- subset(decoys[[t]], missing_atoms == 0)
     partial.decoys[[t]] <- subset(decoys[[t]], missing_atoms > 0)
}

for(t in targets)
{   png(paste('plots/', t, '.png', sep=''), height=600, width=800)
    plot(complete.decoys[[t]][[cost.fcn]], complete.decoys[[t]][[qual.metric]],
         xlab=cost.fcn, ylab=qual.metric, main=t)
#    points(complete.decoys[[t]][[cost.fcn]],
#	   complete.decoys[[t]][[qual.metric]],
#	   pch=1)
#    points(partial.decoys[[t]][[cost.fcn]],
#	   partial.decoys[[t]][[qual.metric]],
#	   pch=2)

    n <- length(complete.decoys[[t]][[cost.fcn]])
    r <- vector("numeric", n)
    r[order(complete.decoys[[t]][[cost.fcn]])] <- 0:(n-1)
    w <- vector("numeric", n)
    tau <- vector("numeric", 7)
    tauexp <- vector("list", 7)
    for(a in 1:7)
    {   alpha  <- a - 1
	w      <- exp(-(alpha - 1) * r / n)

	tau[a] <- weightedTau(complete.decoys[[t]][[cost.fcn]],
			      complete.decoys[[t]][[qual.metric]],
			      w)


	tauexp[[a]] <- substitute(tau[alpha] == value,
		                  list(alpha=alpha,
				       value=as.numeric(format(tau[a],
					       		       digits=2))))
    }

    mtext(substitute(list(a,b,c,d,e,f,g),
		     list(a=tauexp[[1]], b=tauexp[[2]],
			  c=tauexp[[3]], d=tauexp[[4]],
			  e=tauexp[[5]], f=tauexp[[6]],
			  g=tauexp[[7]])))

    graphics.off()

}