In[]:=
BricksArrayPlot[list_]:=ArrayPlot[MapIndexed[If[EvenQ[First[#2]],Prepend[#,0],Append[#,0]]&,Flatten/@Map[{#,#}&,list,{2}]],AspectRatio->(Divide@@Dimensions[list])]
In[]:=
BricksArrayPlot[CellularAutomaton[{102,2,3/2},{{1},0},5]]
Out[]=
In[]:=
ArrayPlot[BricksArrayPlot[CellularAutomaton[{102,2,3/2},{{1},0},5]]]
Out[]=
In[]:=
lifetimes=Sort[Select[Association[Table[ru->TestLifetime[{ru,2,3/2},{1,1,1,0,1,1,1},30],{ru,0,2^2^4-1,2}]],0<=#<Infinity&]];
In[]:=
Table[ArrayPlot[CellularAutomaton[{n,2,3/2},{{1},0},10]],{n,100,120,2}]
Out[]=

,
,
,
,
,
,
,
,
,
,

In[]:=
BricksArrayPlot[data_]:=Graphics[Rectangle[Reverse[#{-1,1}]-#[[1]]{1/2,0}]&/@Position[data,1]]
In[]:=
Module[​​{deep=5000,cut=50,ru,life,evo,data,init={1,1,1,0,1,1,1}},​​ParallelTable[SeedRandom[426777+i];​​evo=NestList[CompoundExpression[​​ru=RandomRuleMutation[First[#]],​​life=TestLifetime[ru,init,cut],​​If[life>=Last[#],{ru,life},#]​​]&,{{0,2,3/2},1},deep];​​evo=Rest[First/@SplitBy[evo,Last]];​​Map[CompoundExpression[​​data=CellularAutomaton[​​First[#],{init,0},Last[#]+2],​​data=ArrayPad[#,2]&/@data,​​ArrayPlot[data,​​ImageSize->{Automatic,14Sqrt[Length[data]+1]},​​Mesh->True,MeshStyle->Opacity[.1]​​]​​]&,​​evo],{i,{3,2,5,21}}]​​]
In[]:=
Module[​​{deep=5000,cut=50,ru,life,evo,data,init={1,1,1,0,1,1,1}},​​ParallelTable[SeedRandom[426777+i];​​evo=NestList[CompoundExpression[​​ru=RandomRuleMutation[First[#]],​​life=TestLifetime[ru,init,cut],​​If[life>=Last[#],{ru,life},#]​​]&,{{0,2,3/2},1},deep];​​evo=Rest[First/@SplitBy[evo,Last]],{i,{3,2,5,21}}]​​]
Out[]=
8192,2,
3
2
,2,35976,2,
3
2
,3,35496,2,
3
2
,5,43688,2,
3
2
,6,47784,2,
3
2
,7,23208,2,
3
2
,10,520,2,
3
2
,2,49256,2,
3
2
,3,50216,2,
3
2
,4,27688,2,
3
2
,8,28264,2,
3
2
,9,16384,2,
3
2
,2,20512,2,
3
2
,3,22656,2,
3
2
,4,31880,2,
3
2
,5,29832,2,
3
2
,9,30344,2,
3
2
,10,17408,2,
3
2
,2,18048,2,
3
2
,3,50880,2,
3
2
,5,52928,2,
3
2
,6,61120,2,
3
2
,7
In[]:=
CellularAutomaton35496,2,
3
2
,{{1,1,1,0,1,1,1},0},6
Out[]=
{{1,1,1,0,1,1,1},{1,1,0,0,1,1,0},{1,0,0,1,1,0,0},{0,0,1,1,0,0,0},{0,0,1,0,0,0,0},{0,0,0,0,0,0,0},{0,0,0,0,0,0,0}}
In[]:=
BricksArrayPlot[%]
Out[]=
In[]:=
VertexCount

Out[]=
86
In[]:=
Subgraph[$EvolutionData["MutationGraph"],#]&/@$EvolutionData["SubLevels"]
Out[]=
{0,1}
,{1,1}
,{2,1}
,{2,2}
,{2,3}
,{2,4}
,{2,5}
,{2,6}
,{3,1}
,{3,2}
,{3,3}
,{3,4}
,{3,5}
,{3,6}
,{3,7}
,{3,8}
,{3,9}
,{3,10}
,{3,11}
,{3,12}
,{3,13}
,{3,14}
,{3,15}
,{3,16}
,{3,17}
,{3,18}
,{3,19}
,{3,20}
,{3,21}
,{3,22}
,{4,1}
,{4,2}
,{4,3}
,{4,4}
,{4,5}
,{4,6}
,{4,7}
,{4,8}
,{4,9}
,{4,10}
,{4,11}
,{4,12}
,{4,13}
,{4,14}
,{4,15}
,{4,16}
,{4,17}
,{4,18}
,{4,19}
,{4,20}
,{4,21}
,{4,22}
,{4,23}
,{4,24}
,{4,25}
,{4,26}
,{4,27}
,{4,28}
,{4,29}
,{4,30}
,{4,31}
,{5,1}
,{5,2}
,{5,3}
,{5,4}
,{5,5}
,{5,6}
,{5,7}
,{5,8}
,{5,9}
,{5,10}
,{5,11}
,{5,12}
,{5,13}
,{5,14}
,{5,15}
,{5,16}
,{5,17}
,{6,1}
,{6,2}
,{6,3}
,{6,4}
,{6,5}
,{6,6}
,{6,7}
,{6,8}
,{6,9}
,{6,10}
,{6,11}
,{6,12}
,{7,1}
,{7,2}
,{7,3}
,{7,4}
,{8,1}
,{8,2}
,{8,3}
,{10,1}
,{12,1}


k=2, r=2 symmetric

Branchial Graphs

k=2, r=2 symmetric

k=2, r=2

Could indicate actual displayed morphological difference cases.....

k=2, r=1 fitness landscape

Exhaustive Search

Determining Bits that Matter