On Thursday 20 October 2005 06:19, Dethe Elza wrote: > 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.
Sure, but then you're learning about efficiency with Fortran. :-) > > 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. Just to add an explanation: Wikipedia appears to have a fair amount of material on ordinary differential equations (ODEs). I suppose the following page would be a fairly good place to start reading about them: http://en.wikipedia.org/wiki/Ordinary_differential_equation > 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." I don't do this sort of thing much any more. I think it doesn't really need to be said but, if I was to repeat the university experience, I'd use Python a lot more. :-) At this point, I don't even know whether the original poster is still reading, or whether he's already resigned himself to teaching programming with Matlab. David _______________________________________________ Edu-sig mailing list [email protected] http://mail.python.org/mailman/listinfo/edu-sig
