How to resolve the algorithm One-dimensional cellular automata step by step in the Raku programming language

Published on 12 May 2024 09:40 PM
#Raku

How to resolve the algorithm One-dimensional cellular automata step by step in the Raku 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 Raku programming language

Source code in the raku programming language

class Automaton {
    has $.rule;
    has @.cells;
    has @.code = $!rule.fmt('%08b').flip.comb».Int;
 
    method gist { "|{ @!cells.map({+$_ ?? '#' !! ' '}).join }|" }
 
    method succ {
        self.new: :$!rule, :@!code, :cells( 
            @!code[
                    4 «*« @!cells.rotate(-1)
                »+« 2 «*« @!cells
                »+«       @!cells.rotate(1)
            ]
        )
    }
}

#  The rule proposed for this task is rule 0b01101000 = 104

my @padding = 0 xx 5;
my Automaton $a .= new:
    rule  => 104,
    cells => flat @padding, '111011010101'.comb, @padding
;
say $a++ for ^10;


# Rule 104 is not particularly interesting so here is [[wp:Rule 90|Rule 90]], 
# which shows a [[wp:Sierpinski Triangle|Sierpinski Triangle]].

say '';
@padding = 0 xx 25;
$a = Automaton.new: :rule(90), :cells(flat @padding, 1, @padding);
 
say $a++ for ^20;

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