@Theodore Mollano I see your article exploring the graph tilings, and the constrained network systems. It almost makes me want to use Graph3D
, to separate different evolution paths in 3D space.
Graph[GraphUnion @@ generateSimpleTemplate[{3}, 6],
VertexStyle -> RandomColor[RGBColor[1, 0.51, 0.2]],
EdgeStyle -> RGBColor[0.331, 0.4884, 0.7223]]
With @James Boyd this is easy. There's an old Ruliad proverb that whenever you're working with big graphs, when you're dancing with the Ruliad you should bitmap.
![Generate Simple Template](https://community.wolfram.com//c/portal/getImageAttachment?filename=GenerateSimpleTemplate.png&userId=2553367)
Because graph tilings have important relations to Combinatorics, Graph Theory, and Computer science, and this article was Space & Time
.
With[{graphstwo =
Select[DeleteDuplicates[
Graph[VertexList@#, #,
VertexStyle -> {RandomColor[], EdgeForm[Black],
AbsolutePointSize[15]},
EdgeStyle -> {RandomColor[], AbsoluteThickness[2.5]}] & /@
Subsets[EdgeList[
GraphUnion[CompleteGraph[5],
Graph[{1 \[UndirectedEdge] 1, 2 \[UndirectedEdge] 2,
3 \[UndirectedEdge] 3, 4 \[UndirectedEdge] 4,
5 \[UndirectedEdge] 5}]]]], IsomorphicGraphQ],
ConnectedGraphQ]},
Grid[Partition[graphstwo, 50], Frame -> None,
ItemSize -> {1.5, 1.5}]]
Offer us a glimpse into statistical and algorithmic connections, and we have got the template tiling.
![graphstwo](https://community.wolfram.com//c/portal/getImageAttachment?filename=graphstwo.png&userId=2553367)
These are illustrative examples of the k-valent tilings.
Grid[Partition[
Flatten[Map[Map[NeighborhoodGraph[#, 1, 1] &, #] &,
Map[{doubleEdge[#], tripleEdge[#], tripleEdge[doubleEdge[#]]} &,
graphstwo], {2}]], 50], Frame -> None, ItemSize -> {1.5, 1.5}]
And the @Stephen Wolfram future problem determines the largest graph that can be formed using a simple set of templates.
![Neighborhood Graph](https://community.wolfram.com//c/portal/getImageAttachment?filename=NeighborhoodGraph.png&userId=2553367)
This is such a good framework for project culmination.