(This article was first published on

While preparing for the new teaching semester I have created an implementation of NetLogo GenDrift P local in GNU R.**R snippets**, and kindly contributed to R-bloggers)The model works as follows. Initially a square grid having side size is randomly populated with n types of agents (denoted by colors).

Each agent randomly changes type (color) to one of its eight neighbors colors. In long run only one agent type remains due to random selection process (although it can take a long time if we set

side to a large value).

Here is the simulation code:

We can select if we want to see the animation on the screen or save it to file via animate option.`library(lattice)`

library(animation)`# initialize simulation`

# side - square grid size

# n - number of agent types (from 2 to 6)

init <- function(side, n) {

matrix(sample.int(n, side * side, TRUE), side)

}

# plot simulation state

# s - simulation state

# n - initial number of agent types

do.plot <- function(s, n) {

print(levelplot(s, at = (0:n) + 0.5,

col.regions = 1 + (1:n),

scales = list(draw = F), xlab = "", ylab = "",

colorkey = list(tick.number = n)))

}`# perform one step of simulation`

# state - simulation state

sim.step <- function(state) {

updated <- FALSE

side <- dim(state)[1]

moves_x <- rep(-1:1, 3)[-5]

moves_y <- rep(-1:1, each = 3)[-5]

sequence <- sample.int(length(state))

for (i in sequence) {

x <- 1 + (i - 1)%%side

y <- 1 + (i - 1)%/%side

ref <- sample.int(8, 1)

ref.x <- 1 + (x + moves_x[ref] - 1)%%side

ref.y <- 1 + (y + moves_y[ref] - 1)%%side

if (state[x, y] != state[ref.x, ref.y]) {

state[x, y] <- state[ref.x, ref.y]

updated <- TRUE

}

}

list(state, updated)

}

go <- function(size, n) {

s <- init(size, n)

updated <- TRUE

for (i in 1:4) {

do.plot(s, n)

}

i <- 0

while (updated) {

i <- i + 1

do.plot(s, n)

out <- sim.step(s)

s <- out[[1]]

updated <- out[[2]]

do.plot(s, n)

}

print(i)

for (i in 1:4) {

do.plot(s, n)

}

}

set.seed(1)

animate <- FALSE # do we want to save animation?

side <- 15 # simulation grid will be side x side

n <- 5 # initial number of agent types

if (animate) {

ani.options(interval = 0.2)

saveGIF(go(side, n))

} else {

go(side, n)

}

The animation the code generates is presented below:

To

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