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JuliaDiff / SparseDiffTools.jl

Fast jacobian computation through sparsity exploitation and matrix coloring
MIT License
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(Kind-of) Type Stability Fixes for No Chunksize Specified #271

Closed avik-pal closed 8 months ago

codecov[bot] commented 8 months ago

Codecov Report

Attention: 2 lines in your changes are missing coverage. Please review.

Comparison is base (9d68481) 87.34% compared to head (41033f4) 87.32%. Report is 1 commits behind head on master.

Additional details and impacted files ```diff @@ Coverage Diff @@ ## master #271 +/- ## ========================================== - Coverage 87.34% 87.32% -0.03% ========================================== Files 21 21 Lines 1241 1254 +13 ========================================== + Hits 1084 1095 +11 - Misses 157 159 +2 ``` | [Files](https://app.codecov.io/gh/JuliaDiff/SparseDiffTools.jl/pull/271?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=JuliaDiff) | Coverage Δ | | |---|---|---| | [ext/SparseDiffToolsSymbolicsExt.jl](https://app.codecov.io/gh/JuliaDiff/SparseDiffTools.jl/pull/271?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=JuliaDiff#diff-ZXh0L1NwYXJzZURpZmZUb29sc1N5bWJvbGljc0V4dC5qbA==) | `100.00% <ø> (ø)` | | | [ext/SparseDiffToolsZygoteExt.jl](https://app.codecov.io/gh/JuliaDiff/SparseDiffTools.jl/pull/271?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=JuliaDiff#diff-ZXh0L1NwYXJzZURpZmZUb29sc1p5Z290ZUV4dC5qbA==) | `97.36% <ø> (ø)` | | | [src/coloring/acyclic\_coloring.jl](https://app.codecov.io/gh/JuliaDiff/SparseDiffTools.jl/pull/271?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=JuliaDiff#diff-c3JjL2NvbG9yaW5nL2FjeWNsaWNfY29sb3Jpbmcuamw=) | `98.57% <ø> (ø)` | | | [src/coloring/backtracking\_coloring.jl](https://app.codecov.io/gh/JuliaDiff/SparseDiffTools.jl/pull/271?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=JuliaDiff#diff-c3JjL2NvbG9yaW5nL2JhY2t0cmFja2luZ19jb2xvcmluZy5qbA==) | `0.00% <ø> (ø)` | | | [src/coloring/high\_level.jl](https://app.codecov.io/gh/JuliaDiff/SparseDiffTools.jl/pull/271?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=JuliaDiff#diff-c3JjL2NvbG9yaW5nL2hpZ2hfbGV2ZWwuamw=) | `100.00% <ø> (ø)` | | | [src/coloring/matrix2graph.jl](https://app.codecov.io/gh/JuliaDiff/SparseDiffTools.jl/pull/271?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=JuliaDiff#diff-c3JjL2NvbG9yaW5nL21hdHJpeDJncmFwaC5qbA==) | `100.00% <ø> (ø)` | | | [src/differentiation/compute\_hessian\_ad.jl](https://app.codecov.io/gh/JuliaDiff/SparseDiffTools.jl/pull/271?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=JuliaDiff#diff-c3JjL2RpZmZlcmVudGlhdGlvbi9jb21wdXRlX2hlc3NpYW5fYWQuamw=) | `100.00% <100.00%> (ø)` | | | [src/differentiation/compute\_jacobian\_ad.jl](https://app.codecov.io/gh/JuliaDiff/SparseDiffTools.jl/pull/271?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=JuliaDiff#diff-c3JjL2RpZmZlcmVudGlhdGlvbi9jb21wdXRlX2phY29iaWFuX2FkLmps) | `91.80% <ø> (ø)` | | | [src/differentiation/jaches\_products.jl](https://app.codecov.io/gh/JuliaDiff/SparseDiffTools.jl/pull/271?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=JuliaDiff#diff-c3JjL2RpZmZlcmVudGlhdGlvbi9qYWNoZXNfcHJvZHVjdHMuamw=) | `95.53% <ø> (ø)` | | | [src/differentiation/vecjac\_products.jl](https://app.codecov.io/gh/JuliaDiff/SparseDiffTools.jl/pull/271?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=JuliaDiff#diff-c3JjL2RpZmZlcmVudGlhdGlvbi92ZWNqYWNfcHJvZHVjdHMuamw=) | `93.75% <ø> (ø)` | | | ... and [5 more](https://app.codecov.io/gh/JuliaDiff/SparseDiffTools.jl/pull/271?src=pr&el=tree-more&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=JuliaDiff) | |

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avik-pal commented 8 months ago

The ordinarydiffeq test failure is just some internet problem most likely. the nonlinearsolve ones will be handled by https://github.com/SciML/NonlinearSolve.jl/pull/265. Once the tests on that PR pass we can merge this

avik-pal commented 8 months ago

@ChrisRackauckas this should be good to go