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 _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
