[Numpy-discussion] dot function or dot notation, matrices, arrays?

[Dag Sverre Seljebotn]

Christopher Barker wrote:
> Dag Sverre Seljebotn wrote:
>> I recently got motivated to get better linear algebra for Python;
> 
> wonderful!
> 
>> To me that seems like the ideal way to split up code -- let NumPy/SciPy 
>> deal with the array-oriented world and Sage the closer-to-mathematics 
>> notation.
> 
> well, maybe -- but there is a lot of call for pure-computational linear 
> algebra. I do hope you'll consider building the computational portion of 
> it in a way that might be included in numpy or scipy by itself in the 
> future.
> 
> Have you read this lengthy thread?
> 
> 
> 
> and these summary wikipages:
> 
> http://scipy.org/NewMatrixSpec
> http://www.scipy.org/MatrixIndexing
> 
> 
> Though it sounds a bit like you are going your own way with it anyway.

Yes, I'm going my own way with it -- the SciPy matrix discussion tends 
to focus on cosmetics IMO, and I just tend to fundamentally disagree 
with the direction these discussions take on the SciPy/NumPy lists.
What I'm after is not just some cosmetics for avoiding a call to dot.

I'm after something which will allow me to structure my programs better 
-- something which e.g. allows my sampling routines to not care (by 
default, rather than as a workaround) about whether the specified 
covariance matrix is sparse or dense when trying to Cholesky decompose 
it, or something which allows one to set the best iterative solver to 
use for a given matrix at an outer level in the program, but do the 
actual solving somewhere else, without all the boilerplate and all the 
variable passing and callbacks.

-- 
Dag Sverre