[SciPy-Dev] Allow specification of matrix permutation method in scipy.sparse.linalg.eigs()

[Paul Nation]

In my case, I am looking to set the ordering used in splu to reduce the 
fill-in in the LU factors.  I do not think that this can be accomplished 
using the M matrix.  However, using such a feature may be too 
specialized to justify inclusion into SciPy.

Paul

On 03/06/2015 04:21 AM, Pauli Virtanen wrote:
> 05.03.2015, 04:40, Paul Nation kirjoitti:
>> As of SciPy 0.15, there are now a few matrix reordering methods in the scipy.sparse.csgraph module.  Some reorderings, such as the reverse_cuthill_mckee ordering are similarity transforms (symmetric permutations), and can be used when solving the generalized eigenvalue problem using eigs() or eigsh().  In some cases, the reduced bandwidth and profile can lead to a considerable reduction in fill-in compared to other methods, such as the default COLAMD.  However, as it stands now, these functions do not allow one to specify the matrix ordering, and always default to COLAMD as the sparse LU inverse routine simply calls:
>>
>> self.M_lu = splu(M)
>>
>> I am writing to see if a pull request that will allow for the user to set
>> the reordering used in eigs() and eigsh() via the permc_spec kwarg in splu
>> is something that people are interested in.
> The interface to splu contains also other tunable things. I'm not sure
> if it makes sense to expose these, since you can pass in a custom M and
> Minv object, which can be used in more complicated cases.
>
>
> _______________________________________________
> SciPy-Dev mailing list
> SciPy-Dev at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-dev