Handle Symmetric/Hermitian in PDSparseMat#230
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Packages like NLPModels return Hessians as `Symmetric(L, :L)` where `L`
is a sparse lower-triangular matrix. Previously, `PDSparseMat` only
supported `SparseMatrixCSC` directly.
This also:
- Acknowledges that `CholTypeSparse` is now an abstract type and adds
its concrete type as a parameter to `PDSparseMat`.
- Adds a "coercion cascade" `PDSparseMat{T}(args...)` -> `PDSparseMat{T,
S}(args...)` -> `PDSparseMat{T, S, C}(args...)` to reduce code
duplication. This is sometimes needed when one object of a different
type needs to be converted into some standard type in generic code.
- Moves size checks into the inner constructor, so that it is impossible
to create an invalid `PDSparseMat`.
Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #230 +/- ##
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- Coverage 93.37% 92.60% -0.78%
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Files 11 11
Lines 800 811 +11
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+ Hits 747 751 +4
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Packages like NLPModels return Hessians as
Symmetric(L, :L)whereLis a sparse lower-triangular matrix. Previously,
PDSparseMatonlysupported
SparseMatrixCSCdirectly.This also:
CholTypeSparseis now an abstract type and addsits concrete type as a parameter to
PDSparseMat.PDSparseMat{T}(args...)->PDSparseMat{T, S}(args...)->PDSparseMat{T, S, C}(args...)to force type conversion. This is sometimes needed when one object of a differenttype needs to be converted into some standard type in generic code.
to create an invalid
PDSparseMat.I expect this to pass tests on 1.10 but fail on 1.12 due to JuliaSparse/SparseArrays.jl#662 (UPDATE: fix already merged, queued for backporting). Before going further, it makes some sense to take a step back and acknowledge other caveats:
UnionSparseMatrixCSCfrom the one that was supplied.PDMatandPDSparseMat+ move SparseArrays support to an extension #188 might be a better way forward