sage vs enthought for sci computing

Ken Starks straton at lampsacos.demon.co.uk
Wed Jul 9 13:36:06 EDT 2008


sturlamolden wrote:
> On 7 Jul, 22:35, jadamwils... at gmail.com wrote:
>> Hello,
>> I have recently become interested in using python for scientific
>> computing, and came across both sage and enthought. I am curious if
>> anyone can tell me what the differences are between the two, since
>> there seems to be a lot of overlap (from what I have seen). If my goal
>> is to replace matlab (we do signal processing and stats on
>> physiological data, with a lot of visualization), would sage or
>> enthought get me going quicker? I realize that this is a pretty vague
>> question, and I can probably accomplish the same with either, but what
>> would lead me to choose one over the other?
>> Thanks!
> 
> I work in neuroscience, and use Python of signal processing. I've used
> Matlab before. Python is just better.
> 
> I do not use either Sage or Enthought. Instead I have istalled a
> vanilla Python and the libraries I need. The most important parts are:
> 
> - Python 2.5.2
> - NumPy
> - SciPy
> - Matplotlib
> - wxPython
> - pywin32
> - PIL
> - Cython
> - PyOpenGL
> - mpi4py
> - processing module
> - gfortran and gcc (not a Python library, but I need a C and Fortran
> compiler)
> 
> Less important stuff I also have installed:
> 
> - Twisted
> - PyGame
> - MySQL and mysqldb
> - Python for .NET (http://pythonnet.sourceforge.net)
> - VideoCapture
> 
> 

I would add RPy for luck!
The Rproject stats package seems to have attracted a lot of medical 
users, and this is a python interface.

I'm not entirely sure what is the advantage of a python wrapper
over R, (compared with the stand-alone Rproject language), but 
presumably it would be to combine its functionality with that of
some of the python libraries above.

Anyway, you get lots of graphics for exploratory data analysis, high
quality stats, the ability to write scripts.

The RPy is on sourceforge:
   http://rpy.sourceforge.net/

the Rproject itself is at:
   http://www.r-project.org/
and there is a whole CRAN (Comprehensive R archive network)




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