On 09/05/2008, Ron Johnson <[EMAIL PROTECTED]> wrote: > Then write your apps in FORTRAN. (But then, you aren't the OP...)
Sometimes I do, as a matter of fact, but I feel more comfortable with C++. > > You're not going to convince a numericist to give up compiled > > languages. :-) Give it up. > > > I'm not going to try. Well, not much... Since all the functions > are already written in a compiled language, what you're really doing > is using Python as "stitching". Like I said before, Python and Octave are interpreted languages with a good numerical slant, but you really get a slowdown from the interpreter itself. Tricks like vectorisation can sometimes work around the slowdown, but sometimes code just isn't easily lent to vectorisation. This is why Octave also provides its C++ libraries for code that you just can't figure out how to vectorise when the interpreter is slowing you down. The same remarks apply to Numpy. I personally reserve interpreted languages for profiling or quickly testing out ideas, but once I need to actually implement my ideas, it's C++ (or sometimes, Fortran). - Jordi G. H. -- To UNSUBSCRIBE, email to [EMAIL PROTECTED] with a subject of "unsubscribe". Trouble? Contact [EMAIL PROTECTED]
