[SciPy-user] Pros and Cons of Python verses other array environments

[John Hassler]

I went back to the beginning of the thread, to find out what I was 
actually talking about.  I interpreted the question to mean using Python 
vs Matlab the way Matlab is commonly used by students.  I now see that 
this is too restrictive, but still, I think it's representative of a 
large class of users.

So what, exactly, is the question?  What sort of user do we mean?  
Somebody who has used other "array environments" would have no 
difficulty switching to Python.  Someone who is completely new to 
computer computation would seem to me to be unlikely to use any advanced 
features of the language.   Matlab has some specialized (as in 
"expensive") toolboxes for special problems; do we mean these?  I'm 
familiar with the controls toolbox, and by omission, with the 
optimization toolbox.  Neither has anything that an undergraduate 
student would use that isn't also in SciPy.  I don't know anything about 
any of the other toolboxes.

As an aside, I use Python with Jedit.  It serves as a perfectly usable 
combination, at least as convenient as Matlab with its built-in editor.  
(I've used Scite and PSPad, too, but I personally like Jedit better.)  
I've got it set up so that I save and hit F5 to run ... as in Matlab.

john

Travis Oliphant wrote:
> Hi all,
>
> I've started a possibly controversial but hopefully informative page 
> that tries to list some of the advantages of using 
> Python+NumPy+Scipy+Matplotlib+IPython (I'm calling that combination 
> PyLab) versus other array environments.
>
> The purpose is not to go into detail about semantic differences, but 
> document higher-level differences that might help somebody decide 
> whether or not they could use NumPy instead of some other environment.  
> I've started with a comparison to MATLAB, based on an email response I 
> sent to a friend earlier today. 
>
> Additions and corrections welcome.
>
> -Travis O.
>
>
>
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