On 19-Oct-05, at 5:01 PM, David Boddie wrote: > You can still learn about efficiency in Python. The result just > might not > be as fast as you would like. :-)
Coding in Python and using external libraries is pretty damn fast. I know of one government physics lab that uses Python wrappers around their Fortran libraries, for instance. > In the end, I went from RLaB to Python precisely because Python is > a more > general purpose and extensible language. For anything that required > intensive computation, I used C with the help of the Numerical > Recipes book > and processed the results with Python. In an ideal world, I'd have > used > an ODE solver from Python. I don't know if it includes an ODE solver (since I don't know what that is), but have you checked out Matplotlib (http:// matplotlib.sourceforge.net/), which aims to reproduce at least some of the functionality of a Matlab/Mathematica/Maple? It is also part of the larger SciPy project (http://www.scipy.org/About/) which appears to be even closer to your "ideal world." HTH --Dethe "And you think you're so clever and classless and free" — John Lennon on prototype-based programming _______________________________________________ Edu-sig mailing list [email protected] http://mail.python.org/mailman/listinfo/edu-sig
