Ram-N

#Given a parent individual, get one of their Alleles in the gamete
  getGamete <- function(indiv) {
    if (indiv == 1) return(1) #AA
    if (indiv == 3) return(0) #aa
   #if Parent is Aa, the gamete is one binomial trial with prob.big.A
    if (indiv == 2) return(rbinom(1, size=1, prob.big.A)) #Aa
  }
  
  #Two parental Gametes combine to form a zygote
  combineGametes <- function(mg,dg) {

Ram-N

getNextGen <- function(x) {
  nextgen <- list()
  for(i in seq(1, kStartPop, by=2)) {
    firstborn <- getOffspring(x[i], x[i+1])
    secondborn <- getOffspring(x[i], x[i+1])
    nextgen[i] <- firstborn
    nextgen[i+1] <- secondborn  
  }
  return(unlist(nextgen))
}

Ram-N

simulationOneTrial <- function(start.pop, knumGenerations, trial.index) {  
  df.allele <- NULL
  df.gen <- NULL
  
  #Keep track of the individuals in each generation
  df.gen <- rbind(df.gen, start.pop)
  
  x <- start.pop
  for ( gen in 1:knumGenerations) {

Ram-N

#Bookkeeping 
calcAllelesInGeneration <- function(x) {
  AA = sum(x==1)
  AB = sum(x==2)
  BB = sum(x==3)
  #print(unlist(x))
  #print(c(AA, AB, BB))
  num.A <- (2 * AA)   + AB
  num.B <- (2 * BB)   + AB
  return(c(num.A, num.B))

Ram-N

rm(list=ls())
library(ggplot2)
library(reshape2)

#Function Definition

#Bookkeeping 
calcAllelesInGeneration <- function(x) {
  AA = sum(x==1)
  AB = sum(x==2)

Ram-N

<?xml version="1.0"?>
<catalog>
   <book id="bk101">
      <author>Gambardella, Matthew</author>
      <title>XML Developer's Guide</title>
      <genre>Computer</genre>
      <price>44.95</price>
      <publish_date>2000-10-01</publish_date>
      <description>An in-depth look at creating applications 
      with XML.</description>

Ram-N

library(XML)
#Recursive Function to visit the XML tree (depth first)
visitNode <- function(node) {
  if (is.null(node)) {
    #leaf node reached. Turn back
    return()
  }
  print(paste("Node: ", xmlName(node)))
  num.children = xmlSize(node)  
  if(num.children == 0 ) {

Ram-N

#set up a coloring scheme using colorRampPalette
red=rgb(1,0,0); green=rgb(0,1,0); blue=rgb(0,0,1); white=rgb(1,1,1)
RtoWrange<-colorRampPalette(c(red, white ) )
WtoGrange<-colorRampPalette(c(white, green) ) 

p <- p + scale_fill_gradient2(low=RtoWrange(100), mid=WtoGrange(100), high="gray")
p

Ram-N

#set up a coloring scheme using colorRampPalette
red=rgb(1,0,0); green=rgb(0,1,0); blue=rgb(0,0,1); white=rgb(1,1,1)
RtoWrange<-colorRampPalette(c(red, white ) )
WtoGrange<-colorRampPalette(c(white, green) ) 

p <- p + scale_fill_gradient2(low=RtoWrange(100), mid=WtoGrange(100), high="gray")

Ram-N

library(ggplot2)
library(reshape2)
data(movies)
movieGenres <- movies[c(18:23)] #subset to 6 genres

cor(movieGenres) # 6x6 cor matrix

#ggplot likes the data 'melted' one value per row
m <-melt(cor(movieGenres)) 
p <- ggplot(data=m, aes(x=Var1, y=Var2, fill=value)) + geom_tile()