On Thu, Feb 17, 2011 at 9:11 PM, rjf <fate...@gmail.com> wrote: > > > On Feb 17, 4:49 pm, Matt Goodman <meawo...@gmail.com> wrote: >> MATLAB isn't a tool used outside of academia very often. > > I think you are wrong here. I don't have any data to point to though. > Do you have any data on this?
No data versus no data. >> Its licensing makes it hard to redistribute code (like to a third party), >> or even run it on a couple different workstations in a HPC sense. > > Huh? How so? You write a program, you own it, you can give it to > someone else. > Did they make that hard to do somehow? Each copy of MATLAB costs (a lot of) money. Python is free. (It's simply amazing to me that you don't realize that this is what he is talking about! How is it even possible?) >> I >> would guess the matlab base is about 2x the scientific python community, but >> the science python people are only 5%-10% of Python users. The same foes >> for LabView etc. > > I think you are way off, and the Matlab community is many times the > scientific > python community, but again I have no data. The TIOBE index also illustrates is that whatever the real data is, it is probably constantly changing, and in some cases changing very quickly. See, e.g., the history of Objective-C in TIOBE -- 3 years ago it was a very unpopular language, and now it is very popular (probably because of Apple's iOS programming). > I suspect that the > serious scientific computing community is almost all non-python, and > that > it consists of C/Fortran/Matlab. I suspect that was a true statement at some point in time. >> >> Its easy to forget that science Python is a serious _minority_ in the Python >> community. I attend the Enthought monthly Python meetup here in Austin, and >> of 50 people, maybe 3-5 are science Python programmers. > > I am not surprised that there is a relatively small overlap between > scientific > computing and Python programming. Most scientific computing tasks are > sensitive > to efficiency of resulting code. This is just FUD, suggesting that one can't use Python for scientific computing due to it being too slow. Most people doing scientific also use C/Fortran-based libraries such as numpy and scipy, and quite a few use Cython as well. These tools allow you to write code that is as fast as code one produces in Matlab or Fortran. -- William > > -- > To post to this group, send an email to sage-devel@googlegroups.com > To unsubscribe from this group, send an email to > sage-devel+unsubscr...@googlegroups.com > For more options, visit this group at > http://groups.google.com/group/sage-devel > URL: http://www.sagemath.org > -- William Stein Professor of Mathematics University of Washington http://wstein.org -- To post to this group, send an email to sage-devel@googlegroups.com To unsubscribe from this group, send an email to sage-devel+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/sage-devel URL: http://www.sagemath.org
