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Allow LinearSolve v3 #153
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Allow LinearSolve v3 #153
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Codecov ReportAll modified and coverable lines are covered by tests ✅
❗ Your organization needs to install the Codecov GitHub app to enable full functionality. Additional details and impacted files@@ Coverage Diff @@
## main #153 +/- ##
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Coverage 97.92% 97.92%
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Files 7 7
Lines 1641 1641
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Hits 1607 1607
Misses 34 34 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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This is ready for a review. Regular CI is passing. For the Downgrade test I'll see if I can debug this in another PR. |
To clarify, this PR is also only kind of a hotfix as in general we should be able to solve sparse problems with |
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Thanks for all the work!
We need to discuss this - the docs fail because of this (https://github.com/SKopecz/PositiveIntegrators.jl/actions/runs/14036192931/job/39294690579?pr=153#step:7:27) |
Downgrade still broken
There are more and more errors, when we try to keep support of LinearSolve.jl v2, see https://github.com/SKopecz/PositiveIntegrators.jl/actions/runs/14127496106/job/39579796614?pr=153#step:8:425 for the option, where we require LinearSolve v2.39.1 as suggested by @ChrisRackauckas. I don't understand where the error comes from, but also don't want to spend the time to debug this. So let's just drop support for LinearSolve.jl v2. |
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Thanks a lot!
I just switched toKLUFactorization()
instead ofLUFactorization()
. Let's see if CI passes. Do we generally preferLUFactorization()
overKLUFactorization()
? So should we continue to search for a fix forLUFactorization()
or should we change the default toKLUFactorization()
at least for now to let the tests pass again (would be breaking though)?Using
KLUFactorization()
instead ofLUFactorization
for sparse matrices fixes thepattern of the matrix changed
error from LinearSolve.jl v3.Closes #131, closes #135, closes #136, closes #137, closes #150, closes #151, closes #152.