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General k=2, r=2 rules
General k=2, r=2 rules
In[]:=
ltk2r2=;
This is reduced in counts by canonical reduction of genotypes
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ListLogPlot[Length/@GroupBy[Normal[ltk2r2],Last->First],PlotRange->All]
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In[]:=
Lengthltk2r2=
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2651
lifetimes (simple)
lifetimes (simple)
In[]:=
ltk2r2=;
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BinaryMutationDistance[{r1_,m1_},{r2_,m2_},resample_:Identity]:=DigitCount[resample[BitAnd[BitAnd[BitXor[r1,r2],m1],m2]],2,1]
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AbsoluteTiming[Apply[BinaryMutationDistance,RandomSample[Keys[ltk2r2],2]]][[1]]*Length[ltk2r2]^2
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3837.18
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AbsoluteTiming[g0=NearestNeighborGraph[Keys[ltk2r2],DistanceFunction->Function[BinaryMutationDistance[#1,#2]]];]
Out[]=
{171.866,Null}
need to figure out times
need to figure out times
In[]:=
AbsoluteTiming[res1=EvolutionaryMultiwayGraph[ltk2r2,GraphLayout->"LayeredDigraphEmbedding","DistanceFunction"->Function[BinaryMutationDistance[#1,#2]],AspectRatio->1];VertexCount@%]
Out[]=
{169.156,VertexCount[Null]}
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#[res1]&/@{VertexCount,EdgeCount}
Out[]=
{2052,3226}
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WeaklyConnectedGraphComponents[res1]
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addVertexFigures[#,ltk2r2,VertexSize->1/3,EdgeStyle->Gray]&/@Drop,2
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To do
To do
Start with null graph and try to grow to the full k=2, r=2 multway graph
Consider the symmetry k=3, r=1 case
Questions
Questions
What are the rules unreachable from the null rule by single point mutations? [These need the system to preserve “non winners”, and perhaps go through nonfinite lifetime cases]
[If we did enough mutations at the same time we can obviously get anywhere]
[If we did enough mutations at the same time we can obviously get anywhere]
Lifetime tagging
Lifetime tagging
Note : there are a lot of dead ends.
To do: make width-lifetime rectangles for each node
To do: make width-lifetime rectangles for each node
Question: what is the distribution of lifetimes after adaptive evolution?
Question: what is the distribution of lifetimes after adaptive evolution?
Full (99%?) graph
Full (99%?) graph
Number of phenotypes per vertex:
Ones that (can) take the most intermediate steps to reach:
COMPARE WITH:
These are also the cases where there are the largest number of phenotypes per vertex ... presumably because with more phenotypes there’s more catchment
Map of common ancestry:
Which parts of the graph are made inaccessible by what edges being cut?
AKA what are the most important nodes/“highways” on the graph?
Which parts of the graph are made inaccessible by what edges being cut?
AKA what are the most important nodes/“highways” on the graph?
AKA what are the most important nodes/“highways” on the graph?