diff ks_distribution.R @ 1:56f42cc1dd58 draft

Uploaded

--- a/ks_distribution.R	Thu Jun 08 12:55:49 2017 -0400
+++ b/ks_distribution.R	Wed Jun 28 11:20:17 2017 -0400
@@ -5,67 +5,86 @@
 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")
+    make_option(c("-n", "--number_comp"), action="store", dest="number_comp", type="integer", help="Number of significant components in the Ks distribution"),
+    make_option(c("-o", "--output"), action="store", dest="output", help="Output dataset"),
+    make_option(c("-s", "--specified_colors"), action="store", dest="specified_colors", default=NULL, help="List of component colors")
 )
 
 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)
-    return(num_components)
+set_component_colors = function(colors, number_comp) {
+    # Handle colors for components.
+    if (is.null(colors)) {
+        # Randomly specify colors for components.
+        component_colors <- c("red", "yellow", "green", "black", "blue", "darkorange")
+    } else {
+        # Handle selected colors for components.
+        component_colors <- c()
+        colors <- as.character(colors) 
+        items <- strsplit(colors, ",") 
+        for (item in items) { 
+            component_colors <- c(component_colors, item)
+        }
+        num_colors_specified <- length(component_colors)
+        if (num_colors_specified < number_comp) {
+            # The number of selected colors is less than the number of
+            # components, so we'll add random colors that were not
+            # selected to the set of component colors until we have a
+            # color for each component.
+            loop_count <- number_comp - num_colors_specified
+            for (i in 1:loop_count) {
+                if (!(is.element("red", component_colors))) {
+                    component_colors <- c(component_colors, "red")
+                } else if (!(is.element("yellow", component_colors))) {
+                    component_colors <- c(component_colors, "yellow")
+                } else if (!(is.element("green", component_colors))) {
+                    component_colors <- c(component_colors, "green")
+                } else if (!(is.element("black", component_colors))) {
+                    component_colors <- c(component_colors, "black")
+                } else if (!(is.element("blue", component_colors))) {
+                    component_colors <- c(component_colors, "blue")
+                } else if (!(is.element("darkorange", component_colors))) {
+                    component_colors <- c(component_colors, "darkorange")
+                }
+            }
+        }
+    }
+    return(component_colors)
 }
 
-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)
-    {
+get_pi_mu_var = function(components_data, number_comp) {
+    if (number_comp == 1) {
         pi <- c(components_data[1, 9])
         mu <- c(components_data[1, 7])
         var <- c(components_data[1, 8])
-    }
-    else if (num_components == 2)
-    {
+    } else if (number_comp == 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)
-    {
+    } else if (number_comp == 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)
-    {
+    } else if (number_comp == 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])
-    }
-    else if (num_components == 5)
-    {
+    } else if (number_comp == 5) {
         pi <- c(components_data[11, 9], components_data[12, 9], components_data[13, 9], components_data[14, 9], components_data[15, 9])
         mu <- c(components_data[11, 7], components_data[12, 7], components_data[13, 7], components_data[14, 7], components_data[15, 7])
         var <- c(components_data[11, 8], components_data[12, 8], components_data[13, 8], components_data[14, 8], components_data[15, 8])
-    }
-    else if (num_components == 6)
-    {
+    } else if (number_comp == 6) {
         pi <- c(components_data[16, 9], components_data[17, 9], components_data[18, 9], components_data[19, 9], components_data[20, 9], components_data[21, 9])
         mu <- c(components_data[16, 7], components_data[17, 7], components_data[18, 7], components_data[19, 7], components_data[20, 7], components_data[21, 7])
         var <- c(components_data[16, 8], components_data[17, 8], components_data[18, 8], components_data[19, 8], components_data[20, 8], components_data[21, 8])
     }
-    results = c(pi, mu, var)
+    results <- c(pi, mu, var)
     return(results)
 }
 
-plot_ks<-function(kaks_input, output, pi, mu, var)
-{
+plot_ks<-function(kaks_input, component_colors, output, pi, mu, var) {
     # Start PDF device driver to save charts to output.
     pdf(file=output, bg="white")
     kaks <- read.table(file=kaks_input, header=T)
@@ -89,27 +108,24 @@
     barplot(nc, space=0.25, offset=0, width=0.04, xlim=c(0, max_ks), ylim=c(0, ymax), col="lightpink1", border="lightpink3")
     # Add x-axis.
     axis(1)
-    color <- c('red', 'yellow','green','black','blue', 'darkorange' )
-    for (i in 1:length(mu))
-    {
-       lines(vx, g[,i] * h, lwd=2, col=color[i])
+    for (i in 1:length(mu)) {
+       lines(vx, g[,i] * h, lwd=2, col=component_colors[i])
     }
 }
 
-calculate_fitted_density <- function(pi, mu, var, max_ks)
-{
+calculate_fitted_density <- function(pi, mu, var, max_ks) {
     comp <- length(pi)
     var <- var/mu^2
     mu <- log(mu)
     # Calculate lognormal density.
     vx <- seq(1, 100) * (max_ks / 100)
     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])))
-           if (is.nan(fx[i,j])) fx[i,j]<-0
+    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])))
+            if (is.nan(fx[i,j])) {
+                fx[i,j]<-0
+            }
         }
      }
     return(fx)
@@ -117,47 +133,42 @@
 
 # Read in the components data.
 components_data <- read.delim(opt$components_input, header=TRUE)
-# Get the number of components.
-num_components <- get_num_components(components_data)
+number_comp <- as.integer(opt$number_comp)
+if (number_comp == 0) {
+    # Default to 1 component to allow functional testing.
+    number_comp <- 1
+}
+
+# Set component colors.
+component_colors <- set_component_colors(opt$specified_colors, number_comp)
 
 # Set pi, mu, var.
-items <- get_pi_mu_var(components_data, num_components)
-if (num_components == 1)
-{
-	pi <- items[1]
-	mu <- items[2]
-	var <- items[3]
-}
-if (num_components == 2)
-{
-	pi <- items[1:2]
-	mu <- items[3:4]
-	var <- items[5:6]
-}
-if (num_components == 3)
-{
-	pi <- items[1:3]
-	mu <- items[4:6]
-	var <- items[7:9]
-}
-if (num_components == 4)
-{
-	pi <- items[1:4]
-	mu <- items[5:8]
-	var <- items[9:12]
-}
-if (num_components == 5)
-{
-	pi <- items[1:5]
-	mu <- items[6:10]
-	var <- items[11:15]
-}
-if (num_components == 6)
-{
-	pi <- items[1:6]
-	mu <- items[7:12]
-	var <- items[13:18]
+items <- get_pi_mu_var(components_data, number_comp)
+if (number_comp == 1) {
+    pi <- items[1]
+    mu <- items[2]
+    var <- items[3]
+} else if (number_comp == 2) {
+    pi <- items[1:2]
+    mu <- items[3:4]
+    var <- items[5:6]
+} else if (number_comp == 3) {
+    pi <- items[1:3]
+    mu <- items[4:6]
+    var <- items[7:9]
+} else if (number_comp == 4) {
+    pi <- items[1:4]
+    mu <- items[5:8]
+    var <- items[9:12]
+} else if (number_comp == 5) {
+    pi <- items[1:5]
+    mu <- items[6:10]
+    var <- items[11:15]
+} else if (number_comp == 6) {
+    pi <- items[1:6]
+    mu <- items[7:12]
+    var <- items[13:18]
 }
 
 # Plot the output.
-plot_ks(opt$kaks_input, opt$output, pi, mu, var)
+plot_ks(opt$kaks_input, component_colors, opt$output, pi, mu, var)