[SciPy-User] Large banded matrix least squares solution

[Charles R Harris]

On Wed, Mar 16, 2011 at 1:53 PM, J. David Lee <johnl at cs.wisc.edu> wrote:

> Hello.
>
> I'm trying to find a least squares solution to a system Ax=b, where A is
> a lower diagonal, banded matrix. The entries of A on a given diagonal
> are all identical, with about 300 unique values, and A can be quite
> large, on the order of 1e6 rows and columns.
>
>
So this is sort of a convolution? Do you need exact, or will somewhat
approximate do? I think you can probably do something useful with an fft.

scipy.sparse.linalg.lsqr works on smaller examples, up to a few thousand
> rows and columns, but not much larger. It is also very time consuming to
> construct A, though I'm sure there must be a fast way to do that.
>
> Given the amount of symmetry in the problem, I suspect there is a fast
> way to calculate the result, or perhaps another way to solve the problem
> entirely.
>
>
Chuck
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.scipy.org/pipermail/scipy-user/attachments/20110316/4329e887/attachment.html>