I think this is what i'm looking for. Thanks
On Sunday, July 10, 2016 at 8:14:18 PM UTC-7, Andreas Noack wrote: > > The for Cholesky and sparse LDLt there are methods for reusing an existing > symbolic factorization. They are cholfact!/ldltfact!(Factorization,Matrix) > so you can e.g. do > > ``` > > julia> A = sprandn(100,100,0.1) + 10I; > > > julia> F = cholfact(Symmetric(A)); > > > julia> cholfact!(F, Symmetric(A - I)); > > ``` > > > See > https://github.com/JuliaLang/julia/blob/f8d67f7521287d9325e91fd2142dad5f222e6eaf/base/sparse/cholmod.jl#L1260-L1272 > . > > > > > On Friday, July 8, 2016 at 4:40:45 AM UTC-4, Gabriel Goh wrote: >> >> Hey, >> >> I have a sequence of sparse matrix factorizations I need to do, each one >> a different matrix but with the same sparsity structure. Is there a way I >> can save the AMD (or any other) ordering that sparsesuite returns, it does >> not need to be recomputed each time? >> >> Thanks a lot for the help! >> >> Gabe >> >
