Am Dienstag, 3. Juli 2012 22:00:41 UTC+2 schrieb Ondřej Čertík: > There is a difference between calling matplotlib, numpy or scipy, > and having a working fortran or C compiler working at your machine. > > In particular, in scipy ODE, you can provide a simple Python function > to get the ODE integrated. I am pretty sure that our approach 1) > will be quite faster than high level eval_to_numpy(). > > Having to require a working C/Fortran compiler to do any plotting > or ODE solving is an overkill in my opinion and it will make > things more complicated for the end user. > > (Allowing to also use C/Fortran is of course great for advanced > users.) >
We already have sympy/utilities/compilef.py for compiling C code. It's a bit of a hack, but it only depends on libtcc (LGPL), which is quite small. Last time I tried, it was a bit faster than numpy for evaluation of complicated functions (including the overhead of compiling the C code). The ugly part is that you have to get a development version (maybe it works with the current stable, it did not back then) of TCC and compile libtcc. (We could however provide the binary.) Vinzent -- You received this message because you are subscribed to the Google Groups "sympy" group. To view this discussion on the web visit https://groups.google.com/d/msg/sympy/-/OPrnkk0YC6sJ. To post to this group, send email to sympy@googlegroups.com. To unsubscribe from this group, send email to sympy+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/sympy?hl=en.
