[SciPy-user] Sparse factorisation

[Ondrej Certik]

On Thu, Apr 30, 2009 at 6:56 AM, Gael Varoquaux
<gael.varoquaux at normalesup.org> wrote:
> Hi there,
>
> This is a rather general question about sparse factorisation and Scipy. I
> no nothing about sparse linear algebra, but I happen to need to do a
> sparse Cholesky.
>
> By sparse Cholesky, I don't mean a sparse implementation of Cholesky, my
> matrices are small, I don't actually care about sparse linear algebra,
> but I mean finding P, permutation matrix, and L, lower-only matrix, such
> that the sparse positive definite matrix A can be written:
>        A = P L L' P',
> where P is a reordering of the rows and column of A used to maximise the
> sparsity of L.
>
> What is really of interest to me is P. P can be computed using the colamd
> routine, present in UMFPACK. Scipy sparse does make use of the colamd
> routine (by setting the permc_spec argument of scipy.sparse.splu to 3).
> However, I cannot figure out a way of extracting P.
>
> I have been looking around in the sparse code source, as well as the
> scikits.umfpack code source, and I must admit I am a bit at loss to what
> is the best way to achieve my goals. The umfpack.py module, both in the
> scipy code base and in the scikit, is broken. Scipy seems to hint that it

Is umfpack in scipy really broken? That is very disappointing. I was
planning to use umfpack through scipy. I hope it will not be difficult
for me to fix it.

Ondrej