8000 [TST] Upcoming dependency test failures · Issue #24060 · matplotlib/matplotlib · GitHub
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[TST] Upcoming dependency test failures #24060

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github-actions bot opened this issue Oct 1, 2022 · 3 comments · Fixed by #24266
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[TST] Upcoming dependency test failures #24060

github-actions bot opened this issue Oct 1, 2022 · 3 comments · Fixed by #24266
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v3.6.2

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github-actions bot commented Oct 1, 2022

The weekly build with nightly wheels from numpy and pandas
has failed. Check the logs for any updates that need to be
made in matplotlib.
https://github.com/matplotlib/matplotlib/actions/runs/3163174215
@tacaswell
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This does look real:

>       assert cb.ax.get_ylim() == (1e-4, 1e6)
190
E       assert (9.9999999999...05, 1000000.0) == (0.0001, 1000000.0)
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E         At index 0 diff: 9.999999999999999e-05 != 0.0001
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E         Full diff:
193
E         - (0.0001, 1000000.0)
194
E         + (9.999999999999999e-05, 1000000.0)

@timhoffm
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timhoffm commented Oct 6, 2022

Is this something we should investigate for 3.6.1? The change becomes user-facing in existing versions of matplotlib when a new version of the responsible dependency gets released. If we need to fix this on our side, it is desirable to have a fixed version already out there to minimize user-impact.

@jklymak jklymak added this to the v3.6.2 milestone Oct 6, 2022
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jklymak commented Oct 6, 2022

Add some floating point tolerances to these tests so they don't fail is probably OK.

This was referenced Oct 8, 2022
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This was referenced Oct 22, 2022
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jklymak pushed a commit that referenced this issue Oct 25, 2022
@QuLogic
TST: Increase fp tolerance on more tests for new NumPy
6a5b7e5 
This is similar to #22132 in that NumPy has added more code paths that
now take advantage of AVX512 optimizations and causes slight variations
in results.

Fixes #24060
melissawm pushed a commit to melissawm/matplotlib that referenced this issue Dec 19, 2022
@QuLogic @melissawm
TST: Increase fp tolerance on more tests for new NumPy
ae9105f 
This is similar to matplotlib#22132 in that NumPy has added more code paths that
now take advantage of AVX512 optimizations and causes slight variations
in results.

Fixes matplotlib#24060
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TST: Increase fp tolerance on more tests for new NumPy QuLogic/matplotlib
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@tacaswell @jklymak @timhoffm
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