How to resolve the algorithm One-dimensional cellular automata step by step in the R programming language
Published on 12 May 2024 09:40 PM
How to resolve the algorithm One-dimensional cellular automata step by step in the R programming language
Table of Contents
Problem Statement
Assume an array of cells with an initial distribution of live and dead cells, and imaginary cells off the end of the array having fixed values. Cells in the next generation of the array are calculated based on the value of the cell and its left and right nearest neighbours in the current generation. If, in the following table, a live cell is represented by 1 and a dead cell by 0 then to generate the value of the cell at a particular index in the array of cellular values you use the following table:
Let's start with the solution:
Step by Step solution about How to resolve the algorithm One-dimensional cellular automata step by step in the R programming language
Source code in the r programming language
set.seed(15797, kind="Mersenne-Twister")
maxgenerations = 10
cellcount = 20
offendvalue = FALSE
## Cells are alive if TRUE, dead if FALSE
universe <- c(offendvalue,
sample( c(TRUE, FALSE), cellcount, replace=TRUE),
offendvalue)
## List of patterns in which the cell stays alive
stayingAlive <- lapply(list(c(1,1,0),
c(1,0,1),
c(0,1,0)), as.logical)
## x : length 3 logical vector
## map: list of length 3 logical vectors that map to patterns
## in which x stays alive
deadOrAlive <- function(x, map) list(x) %in% map
cellularAutomata <- function(x, map) {
c(x[1], apply(embed(x, 3), 1, deadOrAlive, map=map), x[length(x)])
}
deadOrAlive2string <- function(x) {
paste(ifelse(x, '#', '_'), collapse="")
}
for (i in 1:maxgenerations) {
universe <- cellularAutomata(universe, stayingAlive)
cat(format(i, width=3), deadOrAlive2string(universe), "\n")
}
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