plot_heatmap.R

# Reusing this R script from an earlier project.
# R script to plot a heatmap of the l2-normed weight vector
#
# Input: 
# Input filename, output folder (path), rank of the weight vector, 
# and the oligomer length for ODH
#
# Output: Weight vector l2-norm matrix heatmap
#
# Author: snikumbh@mpi-inf.mpg.de

args <- commandArgs(TRUE)
# send inputFilename outputFolder rank and oligoLen
inputFilename <- args[1]
outputFolder <- args[2]
rank <- args[3]
oligoLen <- as.numeric(args[4])
# this project, we only use the heatmap functionality
plot_heatmap <- TRUE

if(plot_heatmap == TRUE){
    library(lattice)
    pdfname <- paste0(outputFolder, "/norms_mat_rank", rank, "_oligolen", oligoLen, ".pdf")
    names <- seq(1,4^oligoLen, by=1)
    x <- expand.grid(rep(list(c('A', 'C', 'G', 'T')), 2))
    names <- do.call(paste0, rev(x))
    new.palette <- colorRampPalette(c("white","blue"),space="rgb")
    fname <- inputFilename
    mat_data <- as.matrix(read.csv(fname, header = FALSE))
    rownames(mat_data) <- names
    colnames(mat_data) <- names
    pdf(pdfname)
    p <- levelplot(mat_data, col.regions=new.palette(20), scales=list(x=list(cex=.5, rot= 90),y=list(cex=.5)), xlab=list(label=paste0(oligoLen, "-mers"), cex=.9), ylab=list(label=paste0(oligoLen, "-mers"), cex=.9), region = TRUE, main="", title = paste0("_heatmaps"))
    print(p)
    dev.off()
}else{
    pdf("barplot_max_weight_subvector.pdf")
    weights <- as.matrix(read.table("max_weight_subvector.lsv", sep = ",", header = FALSE), ncol = 1)
    barplot(weights[,1], main="", ylim = c(-0.1, 0.6), ylab="discriminant weights", cex.lab = 1.0)
    text(50.0, -0.05, "Distances", cex=1.0, pos=4, col="black")
    box()
    dev.off()
}