On Jun 2, 2013, at 9:20 AM, Dima Pasechnik wrote: > On 2013-06-01, Volker Braun <vbraun.n...@gmail.com> wrote: > [...] >> >> On a related note, sparse matrices in Sage suck (dictionary of keys). >> Sparse matrices in LELA only suck slightly less (list of lists). For fast >> computation one should implement compressed sparse row/column, I think. > > IMHO one needs to create a framework where one can choose a backend for > sparse matrices, rather than aim for a complete from scratch > implementation.
I don't know what kind of interface do these package exhibit to access/modify/compute with a sparse matrix.... (eg. Linbox VS numerical-stuff) There is a presumably standard sparse-blas API : http://math.nist.gov/spblas/ > E.g. there is a kind of standard, in numerics world, implementation of sparse > matrices, which comes with a lot of extra goodies (including such > important things like sparse Cholesky factorization, etc): > http://www.cise.ufl.edu/research/sparse/SuiteSparse/ > A part of it, complete with a Python interface, is already in Sage, > in CVXOPT. And part of this is accessible already through SciPy (for floating-point matrices) : http://docs.scipy.org/doc/scipy/reference/sparse.linalg.html#module-scipy.sparse.linalg http://docs.scipy.org/doc/scipy/reference/sparse.linalg.html --- Charles -- You received this message because you are subscribed to the Google Groups "sage-devel" group. To unsubscribe from this group and stop receiving emails from it, send an email to sage-devel+unsubscr...@googlegroups.com. To post to this group, send email to sage-devel@googlegroups.com. Visit this group at http://groups.google.com/group/sage-devel?hl=en. For more options, visit https://groups.google.com/groups/opt_out.
