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Two negating pins for dependencies - libnetcdf and numpy #5274
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I can't be 100% sure if the below was originally written accounting for broken NumPy behaviour that has now been fixed. Anyone care to weigh in? iris/lib/iris/analysis/cartography.py Lines 559 to 569 in 1afae0d
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Codecov ReportPatch and project coverage have no change.
Additional details and impacted files@@ Coverage Diff @@
## main #5274 +/- ##
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Coverage 89.32% 89.32%
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Files 89 89
Lines 22390 22390
Branches 5374 5374
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Hits 20000 20000
Misses 1640 1640
Partials 750 750 Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here. ☔ View full report in Codecov by Sentry. |
Although this would be rather odd, since NumPy's change is only for masked arrays, and if we had to put some sort of masked-vs-not type check in here that would seem like evidence that the problem is in NumPy and not in Iris. |
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@trexfeathers Just to confirm, from the PR description, are you saying that the lockfiles are generating issues with the new dependencies?
No, sorry for lack of clarity.
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@trexfeathers We can watch |
Thanks @bjlittle 🙂 |
* upstream/main: Two negating pins for dependencies - libnetcdf and numpy (SciTools#5274) [pre-commit.ci] pre-commit autoupdate (SciTools#5275) updated installing instructions to use pip (SciTools#5273) remove sphinx-panel config as now longer needed (SciTools#5272)
* upstream/main: Adopt sphinx-apidoc and retire complex sphinxext (SciTools#5264) Two negating pins for dependencies - libnetcdf and numpy (SciTools#5274) [pre-commit.ci] pre-commit autoupdate (SciTools#5275)
🚀 Pull Request
libnetcdf !=4.9.1
Closes #5245, closes #5187. Thanks very much @zklaus for sorting this out in conda-forge/libnetcdf-feedstock#175 🌟. I've tested locally and
stdout
is no longer polluted with numerous HDF5 errors.numpy !=1.24.3
Updating the lock files introduced errors in
iris.tests.test_analysis.TestLatitudeWeightGeneration
:test_cosine_latitude_weights_2d
test_cosine_latitude_weights_2d_latitude_first
test_cosine_latitude_weights_2d_latitude_last
Breadcrumb trail starts with numpy/numpy#23651. This relates to ordering in masked arrays, and having looked at the way the tests are constructed, I don't believe they are asserting for the wrong answer.
Consult Iris pull request check list