--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ks_distribution.R	Mon May 01 13:47:20 2017 -0400
@@ -0,0 +1,115 @@
+#!/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);