Timeline for Developping PDE with Python symbolically and numericaly
Current License: CC BY-SA 3.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jan 11, 2018 at 11:41 | comment | added | Matt | @Bjoern Dahlgren Thank you very much for help offered! I therefore will be contacting you if I have some troubles running what I need to. :) | |
| Jan 9, 2018 at 22:31 | comment | added | Bjoern Dahlgren | @Matt I'm the author of pyodesys, let me know on github if you run into any trouble. The current design is not optimized for discretized PDEs (though a smaller number of variables should still work of course). You could also try to extend it by subclassing (I'd be happy to answer questions too if you go down that road). For performance you can either generate C++ or have SymEngine jit-compile expressions. | |
| Jan 4, 2018 at 19:16 | comment | added | Chris Rackauckas | Not my library, but spreading the word because it is pretty awesome. | |
| Jan 4, 2018 at 18:45 | comment | added | Matt | Wah, cheers mate, the library seems impressive, I'm gonna try that too. For the time being, I'm not sure I will spend too much time on optimization, since I mainly have to compute each curve once. | |
| Jan 4, 2018 at 17:03 | history | answered | Chris Rackauckas | CC BY-SA 3.0 |