New_CA_Simulation.m

% the size of our array of cells
latticeSize=149;
% neighborhood radius
radius = 1;
% rule size
ruleSize=3;
% number of time steps
max=320;

a=zeros(1,latticeSize);
newa=zeros(1,latticeSize);

% the ruleset data object
ruleSet = CARuleset;

% patterns 
ruleSet.patterns = flipud(combn([0 1],ruleSize));
                
% transformation rules for each pattern 
% this is wolfram rule 90 --> http://mathworld.wolfram.com/Rule90.html
%ruleSet.transformations = [0, 1, 0, 1, 1, 0, 1, 0];
% this is wolfram rule 110 --> http://mathworld.wolfram.com/Rule110.html
ruleSet.transformations = [0, 1, 1, 0, 1, 1, 1, 0];

%randomize initial configuration
a = randint(1, latticeSize, [0 1]);
%a(50) = 1;

%assign initial configuration to the grid
GRID(1,:)=a;

% initialize the grid except 1st row (initial configuration)
for i=2:max,
    GRID(i,:)=zeros(1,latticeSize);
end

%spit out first frame
spy(GRID)
M(1) = getframe;

%brace yourself - this is the main loop
g=1;
while (g<max), 
    
  %run the chosen rule foreach cell for a given time step g
  %this example includes a circular lattice simulation
  for i=1:latticeSize,  
    % retrieve pattern in the local 'hood 
    localPattern = circularSubarray(a, i-radius, i+radius);
    % find the transformation rule for the given local pattern
    for c=1:2^ruleSize,
        if(isequal(ruleSet.patterns(c, :, :), localPattern))
            newa(i) = ruleSet.transformations(c);
            break
        end
    end
  end
  
  % assign new states
  g=g+1;
  a=newa;
  GRID(g,:)=a;
  
  %push a snapshot to a frame
  spy(GRID)
  M(g) = getframe;
end

%last frame - final state of the matrix
spy(GRID)
M(max) = getframe;

%playback
movie(M,0)