[SciPy-User] Large banded matrix least squares solution

[J. David Lee]

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.

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.

Thank you for your help,

David Lee