u/superfluidvortex

47 post karma · 27 comment karma · joined Aug 2020

superfluidvortex

it hurts, but you have to manage your expectations, that's a generous v4 at best, devalues your future achievements to pretend otherwise. Great effort though!

superfluidvortex

Assuming you're generating your hulls from sets of points, can't you just combine all of the points and generate the convex hull of that? Making sure to check for overlap before including then?

superfluidvortex

I’m one of those researchers. I’d love an expert pair of eyes to help me understand/debug/improve a broken CUDA fortran code of mine to simulate the Nonlinear Schrodinger equation. Send me a message if this interests you :)

superfluidvortex

Some dude posted it here, thanks!

superfluidvortex

Whilst I thank you, my battery curses you

superfluidvortex

I did, but thanks anyway

superfluidvortex

Excellent, thank you sir!

superfluidvortex

Amazing, thank you! I wish these settings weren't so buried

superfluidvortex

It's mainly just for during workouts, but indeed, RIP

superfluidvortex

Of course! I was inspired by this:

https://www.bonappetit.com/recipe/miso-pesto-with-ramen-noodles?intcid=inline_amp

The butter in the recipe is unnecessary, and I didn't replace it with an alternative, the sauce is rich enough as it is. I also didn't use salt (miso adds enough for me)

I changed the thinner noodles out for the udon as I prefer the texture and added birds eye chilli for heat (2-3 birds eye blended into the sauce in addition to the topping)

Enjoy!

superfluidvortex

SimCopter

superfluidvortex

Spooky action at a distance

superfluidvortex

Chris Hemsworth isn't looking his best here

superfluidvortex

I'm terribly sorry for the late response on this. Let me also start by saying thank you for such a thoughtful, eloquent and helpful response!

What you suggest is great and actually works as a simpler implementation of the Laplacian for testing inside fortran then I previously had so thank you very much :)

Unfortunately though, you are right, that transformation was chosen for a reason. Performing spectral derivatives is far more accurate than any central difference methods and for my use-case is somewhat essential.

In any case, thank you, kind sir :)

superfluidvortex

There is an actual tutorial in the documentation: here

Edit: simply x=a\b would suffice since this uses LU decomposition behind the scenes

superfluidvortex

Can someone remove this moron's spam?

superfluidvortex

Thanks for the copy, look forward to working through it!