Probability and statistics blog

If you are used to object oriented programing in a different language, the way R does things can seem a little strange and backwards. “proto” to the rescue. With this library you can simulate “normal” OOP. I found the examples for proto not so helpful, so to figure out how the package works I sent one lonely red ant on a drunken walk. Here’s my code:

 
library("proto")

# Everybody likes ants
ant <- proto(
	# Default values for the class variables
	xPos = 0,            
	yPos = 0,
	name = character(),      
)

# What do ants do? They move
ant$move <-function(.,xDisp=0, yDisp=0) {
	.$xPos = .$xPos + xDisp
	.$yPos = .$yPos + yDisp
}

# See the little red ant move
ant$plot <- function(.) {
	points(.$xPos, .$yPos, pch=20, col="red")
}

# Instantiate the class. 
myAnt = ant
myAnt$name = "George"


plot(myAnt$xPos, myAnt$yPos, xlim=c(-10,10), ylim=c(-10,10), pch=20, col="red")
for(i in 1:40) {

	# The ant is drunk on Kool Aid
	myAnt$move(rnorm(1),rnorm(1))
	
	# The ant is lazy and will rest for a moment
	Sys.sleep(.5)
	
	# Plot the new location
	ant$plot()
	
}

cat("The ant named", myAnt$name, "is now located at (", myAnt$xPos, myAnt$yPos, ")\n")

Tags: drunken walk, oop, r, random walk

This entry was posted on Thursday, May 20th, 2010 at 6:12 pm and is filed under feature, r. You can follow any comments to this entry through the RSS 2.0 feed. Both comments and pings are currently closed.