[Numpy-discussion] dot function or dot notation, matrices, arrays?
Dag Sverre Seljebotn
dagss@student.matnat.uio...
Mon Dec 21 15:31:04 CST 2009
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
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