Multi dimensional integrator

[JacobHass8]

I made a small function to integrate in higher dimensions by recursively integrating in 1D. It gets slower and less accurate as the dimension increases. I only wrote test for 2 and 3 dimensions and 3 dimensions was already getting slow.

However, this could be useful for low dimensional integrals that don't require high precision. When I researched higher dimensional integrals, most answers online suggested repeated 1D integration. From my understanding, this is actually how scipy implements their arbitrary dimensional integrator nquad. This could work as a quick solution before implementing sparse grids.

There's still a few more changes that I need to make, but the rough draft is here.

[NAThompson]

I'm not 100% sure of the utility of this. IMO Claude will be able to 1-shot repeated 1D integration for anyone who wants it-but it's an anti-pattern in general.

These would be better in low d: https://nines.cs.kuleuven.be/research/ecf/, https://link.springer.com/article/10.1007/s002110050358

And I don't think sparse grids are beyond your talents! I think you could get them working.

[JacobHass8]

I'm not 100% sure of the utility of this. IMO Claude will be able to 1-shot repeated 1D integration for anyone who wants it-but it's an anti-pattern in general.

Thanks for taking a look! I'll go ahead and close this then.

These would be better in low d: https://nines.cs.kuleuven.be/research/ecf/, https://link.springer.com/article/10.1007/s002110050358

The first link looks promising but I can't access any of the tables. Even if I did, is this something I could use under the boost copyright?

I was looking at implementing this first https://www.researchgate.net/publication/225149450_Padua2DM_Fast_interpolation_and_cubature_at_the_Padua_points_in_MatlabOctave

[NAThompson]

@JacobHass8 : Padua points would be an awesome first step!