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In[]:=
Nearest[Values[changeFitness[{2,2},$LifetimeData[2,2,"Symmetric"],Function[Divide@@Dimensions[DeleteCases[#,{0...}]]]]]]
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NearestFunction
Data points: 77
Input: scalar
In[]:=
%65/@Range[.6,1.2,.1]
Out[]=
3
5
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3
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8
11
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8
11
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8
11
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8
11
,
4
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,
4
5
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4
5
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4
5
,
4
5
,
4
5
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4
5
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26
29
,{1,1,1,1,1,1,1,1,1,1,1},
10
9
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10
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23
19
In[]:=
First/@%
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3
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8
11
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4
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26
29
,1,
10
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23
19
In[]:=
(1-ColorData["SunsetColors"][#])&[.5]
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1-
In[]:=
gensMarkovWeights
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In[]:=
Histogram[Flatten[Log[1+gensMarkovWeights]],Automatic,{"Log","Count"}]
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In[]:=
rulesMarkovMatrix=N[MarkovWeights/Total/@MarkovWeights];
In[]:=
MatrixPlot[rulesMarkovMatrix,FrameTicks->None]
Out[]=

Morphospace

In[]:=
Take[dimensionReductionFull,5]
Out[]=
0{3.9752,1.53238},20{3.61602,4.98802},272{5.4246,2.37197},276{3.91832,5.04402},16788{3.81199,5.15403}
In[]:=
Take[$LifetimeData[2,2,"All"],10]
Out[]=
{0,65815}0,{20,16847199}1,{272,16847199}1,{276,285295007}1,{16788,285299167}2,{1048868,156317055}2,{1049892,3507586495}2,{268452116,285299167}2,{1082788,3507590655}3,{135274788,156317055}3
In[]:=
Take[heightPhenotypesFull,5]
Out[]=
{{0,65815},{276,285295007},{1049892,3507586495},{269484468,424769023},{1343260068,3646010879}}
ListPlot[Lookup[dimensionReductionFull,heightPhenotypesFull[[All,1]]],Axes->False,AspectRatio->1/GoldenRatio]
In[]:=
ListPlot[MapThread[Style[#1,Blend[{Blue,Blue,Red},(#2/309.)^.2]]&,{Lookup[dimensionReductionFull,heightPhenotypesFull[[All,1]]],Lookup[$LifetimeData[2,2,"All"],heightPhenotypesFull]}],Axes->False,AspectRatio->1/GoldenRatio,Frame->True,FrameStyle->Gray,FrameTicks->None]
Out[]=
In[]:=
ListPlot[MapThread[Style[#1,Blend[{Blue,Blue,Red},(#2/309.)^.2]]&,{Lookup[dimensionReductionFull,widthPhenotypesFull[[All,1]]],Lookup[changeFitness[{2,2},$LifetimeData[2,2,"All"],Length@*First],widthPhenotypesFull]}],Axes->False,AspectRatio->1/GoldenRatio,Frame->True,FrameStyle->Gray,FrameTicks->None]
Out[]=
In[]:=
Histogram[Values[$LifetimeData[2,2,"All"]]]
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