prysm VS pymae

My current concept is to just combine zernike polynomials with a random factor and calculate the PSF from that, which can be somewhat easily be done with the prysm library. These PSFs can then be convolved with circular and gaussian kernels for modelling additional defocus and accounting for other stuff like the AA filter. Then I'd add chromatic aberration by offseting/scaling the PSFs for each channel. Some generated kernels already look pretty good when comparing them to stars in astrophotography images, but others not so much.

https://github.com/brandondube/prysm (caveat emptor: mine)

You can trace about 1 billion raysurfaces per second in pure python with CuPy, or a few million raysurfaces per second on CPU.

New paper from /u/BDube_Lensman using prysm to model NASA's Roman Coronagraph

This free book is what this free code is based on

Prysm Originally for diffraction type optics but seems to able to handle...everything? Performance as a priamary concern, GPU acceleration, proven JPL heritage :) Raytracing is however still experimental and without docs, generally whilst the library looks excellent if you're an optics person already I think I lack a bit of the base fundamental knowledge to really use it powerfully from just the API reference. I can see BDube has some raytracing example code in some of the issues I could probably adapt and muddle my way through at least. No guis is mildly annoying for a noob like myself, but I can work my way around matplotlib-ing just fine instead i'm sure.

You may want to steal my shim set since it lets you hot swap Numpy<-->cupy at runtime

I do computational diffraction with large manycore servers and GPUs at a FFRDC. The difference between MKL and not MKL is the difference between hitting enter and getting a result in an hour or two vs tomorrow.

I wrote a book about Python for Mechanical and Aerospace Engineering. Website is here, Github is here, and I send a free pdf copy to students. It is in dirty imperial units, though.

Just gonna drop this: https://github.com/alexkenan/pymae/ GitHub repo with (basic) examples for using Python in mechanical and aerospace engineering

In addition to what the others mentioned (I like Automate the Boring Stuff the most), I wrote a book about the very thing! Python for Mechanical and Aerospace Engineering. Website here, github here, and I send a free copy to students!

Sorry to toot my own horn, but I wrote a book specifically for Python for mech/aero engineering. Website is here, and the github repo is here. Did you have any coding classes in school? Usually there are a few.

Check out Python for Mechanical and Aerospace Engineering if you're in mech or aero. I send free copies to students!

Python or Matlab. I'm incredibly biased, and I think Python is better. I wrote a book about it, and I send free copies to students.

You can also take a look through my Github repo for a book that I wrote about Python for mechanical and aerospace engineering. It's not quite related to what you'd be looking for, but it's probably a little closer to how you could use Python in oil & gas than "here's how you can automate report entry" (which still could be useful).

I have some basic mechanical and aerospace engineering examples here. Not sure if that counts as "physics" though. I think anything involving kinematics, energy, and/or forces are fair game!

For anybody reading this thread, I wrote a book about Python for mechanical and aerospace engineering since there was nothing out there. The website link is here and the GitHub repo with all of the finished programs is here.

Please let me know if you end up getting Python integrated into your work. The reason I was invited to speak to NLR is because I wrote a book about Python for mech/aero engineering (website here, github here, but it's really aimed at learning the language. I'm considering trying to get materials together to make a follow-up book that addresses "Great, I've learned the language. Now what?"