library("GO.db") 
library('GOstats')
library("Rgraphviz")
library('grDevices')

# main directory to search for postprocessing data
#mainDir <- '../MF/norm_vs_tumor'
#mainDir <- '../MF/tumor_vs_metas'
#mainDir <- '../BP/norm_vs_tumor'
mainDir <- '../BP/tumor_vs_metas'

# prefix for graph picture
#picNamePref <- 'MF_norm_vs_tumor_'
#picNamePref <- 'MF_tumor_vs_metas_'
#picNamePref <- 'BP_norm_vs_tumor_'
picNamePref <- 'BP_tumor_vs_metas_'

# domain type for graph
#graphType <- GOMFPARENTS
graphType <- GOBPPARENTS


plotSelected <- function (g, selectednodes , r = NULL, add.counts = TRUE, max.nchar = 20,
                     node.colors = c(selected = "green", not = "white"),
                     node.shape = "plaintext",
                     dotfilename = 'plot-dot.txt', ...)
{
    if (!require("Rgraphviz", quietly = TRUE)) 
        stop("The Rgraphviz package is required for this feature")
    n <- nodes(g)
    termLab <- if ("term" %in% names(nodeDataDefaults(g))) {
        unlist(nodeData(g, attr = "term"))
    }
    else n
    if (!is.null(max.nchar)) 
        termLab <- sapply(termLab, substr, 1L, max.nchar, USE.NAMES = FALSE)
    ncolors <- rep(node.colors["not"], length(n))
    ncolors[g@nodes %in% selectednodes] <- node.colors["selected"]
  
    
    if (!is.null(r) && add.counts) {
        if (is.null(names(node.colors))) 
            stop(paste("invalid node.colors arg:", "must have named elements 'sig' and 'not'"))
        resultTerms <- names(pvalues(r))
        ncolors <- ifelse(n %in% sigCategories(r), node.colors["sig"], 
            node.colors["not"])
        counts <- sapply(n, function(x) {
            if (x %in% resultTerms) {
                paste(geneCounts(r)[x], "/", universeCounts(r)[x], 
                  sep = "")
            }
            else {
                "0/??"
            }
        })
        nlab <- paste(termLab, counts)
    }
    else {
        nlab <- termLab
    }
    nattr <- makeNodeAttrs(g, label = nlab, shape = node.shape, 
        fillcolor = ncolors, fixedsize = TRUE)
    plot(g, ..., nodeAttrs = nattr)
}



# find postprocessing data

pdp_pp <- list.files(mainDir, '*_disk_data')
pdpPath <- paste(mainDir, pdp_pp, 'postprocessing_results', sep='/')

# find all SIZE_ABOVE_stats there
stats <- list.files(pdpPath, 'SIZE_ABOVE_stats_mu')

for (stat in stats) {
    # resolve full path
    statPath <- paste(pdpPath, stat, sep='/')
    # resolve name
    mergeSuffix <- unlist(strsplit(stat, '.txt'))
    # resolve graph picture name
    picName <- paste(picNamePref, mergeSuffix, sep='')

    # load content and extract nodes
    statContent <- read.table(statPath, sep=',', header=T)
    results.nodes <- as.vector(statContent[[1]])

    # create graph
    graph <- GOGraph(results.nodes, graphType)

    picNameEx = paste(picName, '.pdf', sep='')
    dotNameEx = paste(picName, '.dot.txt', sep='')

    # create device instance
    pdf(file = picNameEx,
	width=20, height=20, bg='white', pointsize=1,
        onefile=FALSE, useDingbats=FALSE
    )
    cat(names(dev.cur()), 'device initialized with size', dev.size('px'), 'px', '\n')

#    toDot(g, dotfilename, nodeAttrs=nattr)
#    cat(dotNameEx, 'written\n')

    cat('On', picNameEx, 'plotting', length(nodes(graph)), 'nodes,', length(results.nodes), 'selected\n')

    gc(verbose=FALSE)

    tryCatch(plotSelected(graph, results.nodes,
        r = NULL, add.counts = FALSE,
        max.nchar = 20,
        node.shape="circle",
        dotfilename = dotNameEx
        ), error = function(e) cat('Error!\n'))
    dev.off()

}