Python advocacy in scientific computation

[val bykoski]

sturlamolden wrote:
> Robert Kern wrote:
> 
>> 1. Write grant proposals.
>> 
>> 2. Advise and teach students.
> 
> 
> Sorry I forgot the part about writing grant applications. As for 
> teaching students, I have thankfully not been bothered with that too 
> much.
> 
>> Yes, and this is why you will keep saying, "My simulation is
>> running too slowly," and "My simulation is running out of memory."
>> All the vectorization you do won't make a quadratic algorithm run
>> in O(n log(n)) time. Knowing the right algorithm and the right data
>> structures to use will save you programming time and execution
>> time. Time is money, remember, and every hour you spend tweaking 
>> Matlab code to get an extra 5% of speed is just so much grant money
>> down the drain.
> 
> 
> Yes, and that is why I use C (that is ISO C99, not ANSI C98) instead
> of Matlab for everything except trivial tasks. The design of Matlab's
>  language is fundamentally flawed. I once wrote a tutorial on how to 
> implement things like lists and trees in Matlab (using functional 
> programming, e.g. using functions to represent list nodes), but it's 
> just a toy. And as Matlab's run-time does reference counting insted
> of proper garbage collection, any datastructure more complex than
> arrays are sure to leak memory (I believe Python also suffered from
> this as some point). Matlab is not useful for anything except
> plotting data quickly. And as for the expensive license, I am not
> sure its worth it. I have been considering a move to Scilab for some
> time, but it too carries the burden of working with a flawed
> language.
> 

A quick addition to Robert's very reasonable response to you.  My point 
is that to *trust* a simulation *results* (no matter how fast/slow/etc 
you obtained it) you have to explore and manage the "physics" or 
"biology" of your code.  That's where Python's readability, flexibility, 
and dynamism (including on-the-fly model building/testing/correction) as 
well as model introspecting and exploration capabilities are of critical 
importance and sometimes the indication to a missing link.  It does not 
hurt to remember that the original idea (by S.Ulam) of a computer was 
the idea of an *experimentation environment* (including sampling).  It 
does not look like the Matlab's strongest point is the feedback-driven 
experimentation.  Or i'm missing smth about ISO C99?
  Val Bykoski