--- a/kaks_analysis_barplot.R	Wed Mar 08 14:07:30 2017 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,115 +0,0 @@
-#!/usr/bin/env Rscript
-
-suppressPackageStartupMessages(library("optparse"))
-
-option_list <- list(
-    make_option(c("-c", "--components_input"), action="store", dest="components_input", help="Ks significant components input dataset"),
-    make_option(c("-k", "--kaks_input"), action="store", dest="kaks_input", help="KaKs analysis input dataset"),
-    make_option(c("-o", "--output"), action="store", dest="output", help="Output dataset")
-)
-
-parser <- OptionParser(usage="%prog [options] file", option_list=option_list)
-args <- parse_args(parser, positional_arguments=TRUE)
-opt <- args$options
-
-
-get_num_components = function(components_data)
-{
-    # Get the max of the number_comp column.
-    number_comp = components_data[, 3]
-    num_components <- max(number_comp, na.rm=TRUE);
-    num_components
-}
-
-get_pi_mu_var = function(components_data, num_components)
-{
-    # FixMe: enhance this to generically handle any integer value for num_components.
-    if (num_components == 1)
-    {
-        pi <- c(components_data[1, 9]);
-        mu <- c(components_data[1, 7]);
-        var <- c(components_data[1, 8]);
-    }
-    else if (num_components == 2)
-    {
-        pi <- c(components_data[2, 9], components_data[3, 9]);
-        mu <- c(components_data[2, 7], components_data[3, 7]);
-        var <- c(components_data[2, 8], components_data[3, 8]);
-    }
-    else if (num_components == 3)
-    {
-        pi <- c(components_data[4, 9], components_data[5, 9], components_data[6, 9]);
-        mu <- c(components_data[4, 7], components_data[5, 7], components_data[6, 7]);
-        var <- c(components_data[4, 8], components_data[5, 8], components_data[6, 8]);
-    }
-    else if (num_components == 4)
-    {
-        pi <- c(components_data[7, 9], components_data[8, 9], components_data[9, 9], components_data[10, 9]);
-        mu <- c(components_data[7, 7], components_data[8, 7], components_data[9, 7], components_data[10, 7]);
-        var <- c(components_data[7, 8], components_data[8, 8], components_data[9, 8], components_data[10, 8]);
-    }
-    return = c(pi, mu, var)
-    return
-}
-
-plot_ks<-function(kaks_input, output, pi, mu, var)
-{
-    # Start PDF device driver to save charts to output.
-    pdf(file=output, bg="white")
-    # Change bin width
-    bin <- 0.05 * seq(0, 40);
-    kaks <- read.table(file=kaks_input, header=T);
-    kaks <- kaks[kaks$Ks<2,];
-    h.kst <- hist(kaks$Ks, breaks=bin, plot=F);
-    nc <- h.kst$counts;
-    vx <- h.kst$mids;
-    ntot <- sum(nc);
-    # Set margin for plot bottom, left top, right.
-    par(mai=c(0.5, 0.5, 0, 0));
-    # Plot dimension in inches.
-    par(pin=c(2.5, 2.5));
-    g <- calculate_fitted_density(pi, mu, var);
-    h <- ntot * 2.5 / sum(g);
-    vx <- seq(1, 100) * 0.02;
-    ymax <- max(nc) + 5;
-    barplot(nc, space=0.25, offset=0, width=0.04, xlim=c(0,2), ylim=c(0, ymax));
-    # Add x-axis.
-    axis(1);
-    color <- c('green', 'blue', 'black', 'red');
-    for (i in 1:length(mu))
-    {
-       lines(vx, g[,i] * h, lwd=2, col=color[i]);
-    }
-};
-
-calculate_fitted_density <- function(pi, mu, var)
-{
-    comp <- length(pi);
-    var <- var/mu^2;
-    mu <- log(mu);
-    #calculate lognormal density
-    vx <- seq(1, 100) * 0.02;
-    fx <- matrix(0, 100, comp);
-    for (i in 1:100)
-    {
-        for (j in 1:comp)
-        {
-           fx[i, j] <- pi[j] * dlnorm(vx[i], meanlog=mu[j], sdlog=(sqrt(var[j])));
-        };
-     };
-    fx;
-}
-
-# Read in the components data.
-components_data <- read.delim(opt$components_input, header=TRUE);
-# Get the number of components.
-num_components <- get_num_components(components_data)
-
-# Set pi, mu, var.
-items <- get_pi_mu_var(components_data, num_components);
-pi <- items[1];
-mu <- items[2];
-var <- items[3];
-
-# Plot the output.
-plot_ks(opt$kaks_input, opt$output, pi, mu, var);