[SciPy-User] cholesky of sparse symmetric banded matrix
Wed Aug 22 09:19:25 CDT 2012
On Wed, Aug 22, 2012 at 12:16 AM, <email@example.com> wrote:
> I would like to get a cholesky decomposition of a symmetric banded matrix
> and multiply it with a dense array
> I found
> and this
> 1) is there a way to do linear algebra (dot multiplication) directly in the
> "upper diagonal ordered form"?
> 2) is there an efficient way to go from the "upper diagonal ordered form" to
> a sparse diagonal matrix (or both ways)?
> Is there code that uses this and that I can look at for the pattern?
> my problem is standard linear least squares, where I have an explicit banded
> form for the (nobs, nobs) weighting matrix
> X'WX and X'Wy
> and I need a transformation X2 = W^(0.5) X and y2 = W^(0.5) y
> so I get X2'X2 and X2'y2
> (nobs: number of observations, prime is transpose)
> My first example only has one upper and one lower off-diagonal, so working
> with dense is wasteful.
If you only have one off-diagonal, then you may be best off using
CHOLMOD on the CSC representation:
Of course this uses GPLed code.
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