Fix handling of AbstractSparseMatrixCSC #525
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* `SciMLBase.init` did check only for `SparseMatrixCSC`, thus leading to dispatches for AbstractSparseMatrixCSC with awful timings. * Now, if A (resp. b) is an `AbstractSparseMatrixCSC`, instead of making a `copy` (or even `deepcopy`), a `SparseMatrixCSC` is constructed using `size`, `getcolptr`, `rowvals` and `nonzeros`.
ChrisRackauckas
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Aug 18, 2024
j-fu
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Aug 19, 2024
Both are subtypes of AbstractFactorization. This allows to set default_alias_A=true for sparse factorizations (which just cannot overwrite A anyway). This allows to create the cache parametrized with the original matrix type and we can use `reinit!(cache;A)` or `cache.A=A` if `A` is an AbstractSparseMatrixCSC, like with Krylov solvers. Before, due to SciML#525, these methods would require a SparseMatrixCSC, even if the Problem was created with a AbstractSparseMatrixCSC.
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SciMLBase.initdid check only forSparseMatrixCSC, thus leading to dispatches for AbstractSparseMatrixCSC with awful timings.AbstractSparseMatrixCSC, instead of making acopy(or evendeepcopy), aSparseMatrixCSCis constructed usingsize,getcolptr,rowvalsandnonzeros.Checklist
contributor guidelines, in particular the SciML Style Guide and
COLPRAC.
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