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 >
