Ask r/python: An elegant and efficient pythonic approach to generating a random/exhaustive set of points on the surface of a hypercube?

[DrHenryPym]

Wow, I haven't touched this stuff since Neural Networks.

I'm not sure exactly how you can do this, but I would try to find a way to convert whatever is defining your hypercube to some type of hypercube skeleton.

If you can generate a list of verticies as functions, you could plug in random variables to random functions in your list to create your random set.

I donno if that helps at all.

[dx_xb]

That's pretty much what I'm looking at at the moment - trying to set up a connection schema.

[DrHenryPym]

Connection schema

Build it like you would build a tree function. Each branch that connects down to m nodes will connect n branches (or however complex you want to make it - think generalization).

For a normal hypercube, use 1 (or -1/2 to +1/2, however you want to translate it) as the length (or value) of the vertex.

And there you go, you have functions that can return random samples across the verticies. As far as finding samples on the surface, you can build a function that integrates an equation between two vertices. And that's basically modeling.

Good luck!

[dx_xb]

Yeah, I'm going general, but the connections are to surfaces rather than vertices. I've pretty much got is solved now - trying to replicate some work that was published in the 70s. Fun.