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library(ggplot2)
head(diamonds,10)
colList <- c("cut", "clarity") #list of columns to replace. Can also be column numbers.
rowstoReplace <- 1:10 
lapply(colList, function(colname){gsub("I", ".", diamonds[rowstoReplace, colname])}) 
#lapply gives it one column name at a time...
#Use a comma instead of rowstoReplace if you want all rows changed.

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# RING of R-Rows C-cols in the center of width w cells
seedCenterRing <- function(r, c, wide){
  for(x in as.integer((areaW-c)/2): as.integer((areaW + c)/2)){
    for(y in as.integer((areaH-r)/2): as.integer((areaH + r)/2)){
      area_df[x,y] <<- 1         
    }
  }
  #scoop out the inner ring
  for(x in as.integer((areaW-c)/2 + wide): as.integer((areaW + c)/2 - wide)){
    for(y in as.integer((areaH-r)/2+wide): as.integer((areaH + r)/2- wide )){

Ram-N

# R-Rows C-cols in the center
seedAreaCenter <- function(r, c){
  for(x in as.integer((areaW-c)/2): as.integer((areaW + c)/2)){
    for(y in as.integer((areaH-r)/2): as.integer((areaH + r)/2)){
      area_df[x,y] <<- 1         
      }
    }
}

#Seed a central area and let it grow

Ram-N

# w-cols to the R and L of center column
seedColumns <- function(c, w){
  startLCol = as.integer( (areaW-c) / 2 )
  startRCol = as.integer( (areaW+c) / 2 )
  
  for(y in 1:areaH) {
    clist = c((startLCol-w):startLCol, startRCol:(startRCol+w))
    lapply(clist, function(x) area_df[x,y] <<- 1)
  }
}

Ram-N

# Original Code by Matt Asher for statisticsblog.com
# Feel free to modify and redistribute, but please keep this notice 

#Modifications by Ram Narasimhan
# @ramnarasimhan

source("~/RStats/simFunctions.R")
library(ggplot2)
library(plyr)

Ram-N

store_iteration_stats<- function(kNumSettlers, found.home, max.look.around) {
  #how many settlers found homes
  print(c(found.home," settled out of ", kNumSettlers, (found.home/kNumSettlers)*100, "%" ) )   
  #avg # of steps per new settler
  print(c("num of look arounds max'ed:", max.look.around))  
}

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# Are any of the 4 direct N E W S adjacent cells occupied?
isAnyOfNEWSCellsOccupied <- function(m,n) {
  canOccupy <- FALSE
  NEWSdir = c(2,4,5,7)
  #traverse the vector of 4 elements
  for(k in 1:4) {
    xCheck = m + adjacells[NEWSdir[k],1]
    yCheck = n + adjacells[NEWSdir[k],2]
    if(!(outOfBounds(xCheck, yCheck))) {      
      if(area_df[xCheck, yCheck] > 0) {

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# Are any of the 4 diagonally adjacent cells occupied?
isAnyDiagNeighboringCellOccupied <- function(m,n) {
  canOccupy <- FALSE
  diag.dir = c(1,3,6,8)
  #traverse the vector of 4 elements
  for(k in 1:4) {
    xCheck = m + adjacells[diag.dir[k],1]
    yCheck = n + adjacells[diag.dir[k],2]
    if(!(outOfBounds(xCheck, yCheck))) {

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# Make multiple runs (Replication of simulation) and take the average of stats
st <- data.frame()
st_row<- vector()
for(i in 1:kNumReplications) {
  area_df <- resetIteration()

  seedAreaWithPioneers(numPioneers,seeding.opt)
  simstats <- accommodateSettlers(kNumSettlers, settling.option)
  
  found.home <- simstats[1]

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store_iteration_stats<- function(iter, kNumSettlers, found.home, max.look.around) {
  #how many settlers found homes
  perSet <- (found.home/kNumSettlers) * 100
  print(c(found.home," settled out of ", kNumSettlers, perSet, "%" ) )   
  #avg # of steps per new settler
  print(c("num of Settlers who hit max look around:", max.look.around))  
  return(c(iter, found.home, kNumSettlers, perSet))
}