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Fix Matplotlib type error for tests #4023
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Check for support for `warn` argument in `matplotlib.use()` call. Drop it if it causes an error.
Codecov Report
@@ Coverage Diff @@
## master #4023 +/- ##
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+ Coverage 81.17% 86.77% +5.59%
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Files 88 88
Lines 14137 14137
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+ Hits 11476 12267 +791
+ Misses 2661 1870 -791
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pymc3/tests/test_examples.py
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from .helpers import SeededTest | |||
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matplotlib.use('Agg', warn=False) | |||
try: |
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Instead of a try except we can check against the matplotlib version, right?
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I think. Was this changed in 3.3.5? I am finding it hard to identify where the change happened.
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If you can tell me, I will change the patch.
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It was changed in 3.3
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Thanks for this quick fix @rpgoldman !
* Update GP NBs to use standard notebook style (pymc-devs#3978) * update gp-latent nb to use arviz * rerun, run black * rerun after fixes from comments * rerun black * rewrite radon notebook using ArviZ and xarray (pymc-devs#3963) * rewrite radon notebook using ArviZ and xarray Roughly half notebook has been updated * add comments on xarray usage * rewrite 2n half of notebook * minor fix * rerun notebook and minor changes * rerun notebook on pymc3.9.2 and ArviZ 0.9.0 * remove unused import * add change to release notes * SMC: refactor, speed-up and run multiple chains in parallel for diagnostics (pymc-devs#3981) * first attempt to vectorize smc kernel * add ess, remove multiprocessing * run multiple chains * remove unused imports * add more info to report * minor fix * test log * fix type_num error * remove unused imports update BF notebook * update notebook with diagnostics * update notebooks * update notebook * update notebook * Honor discard_tuned_samples during KeyboardInterrupt (pymc-devs#3785) * Honor discard_tuned_samples during KeyboardInterrupt * Do not compute convergence checks without samples * Add time values as sampler stats for NUTS (pymc-devs#3986) * Add time values as sampler stats for NUTS * Use float time counters for nuts stats * Add timing sampler stats to release notes * Improve doc of time related sampler stats Co-authored-by: Alexandre ANDORRA <[email protected]> Co-authored-by: Alexandre ANDORRA <[email protected]> * Drop support for py3.6 (pymc-devs#3992) * Drop support for py3.6 * Update RELEASE-NOTES.md Co-authored-by: Colin <[email protected]> Co-authored-by: Colin <[email protected]> * Fix Mixture distribution mode computation and logp dimensions Closes pymc-devs#3994. * Add more info to divergence warnings (pymc-devs#3990) * Add more info to divergence warnings * Add dataclasses as requirement for py3.6 * Fix tests for extra divergence info * Remove py3.6 requirements * follow-up of py36 drop (pymc-devs#3998) * Revert "Drop support for py3.6 (pymc-devs#3992)" This reverts commit 1bf867e. * Update README.rst * Update setup.py * Update requirements.txt * Update requirements.txt Co-authored-by: Adrian Seyboldt <[email protected]> * Show pickling issues in notebook on windows (pymc-devs#3991) * Merge close remote connection * Manually pickle step method in multiprocess sampling * Fix tests for extra divergence info * Add test for remote process crash * Better formatting in test_parallel_sampling Co-authored-by: Junpeng Lao <[email protected]> * Use mp_ctx forkserver on MacOS * Add test for pickle with dill Co-authored-by: Junpeng Lao <[email protected]> * Fix keep_size for arviz structures. (pymc-devs#4006) * Fix posterior pred. sampling keep_size w/ arviz input. Previously posterior predictive sampling functions did not properly handle the `keep_size` keyword argument when getting an xarray Dataset as parameter. Also extended these functions to accept InferenceData object as input. * Reformatting. * Check type errors. Make errors consistent across sample_posterior_predictive and fast_sample_posterior_predictive, and add 2 tests. * Add changelog entry. Co-authored-by: Robert P. Goldman <[email protected]> * SMC-ABC add distance, refactor and update notebook (pymc-devs#3996) * update notebook * move dist functions out of simulator class * fix docstring * add warning and test for automatic selection of sort sum_stat when using wassertein and energy distances * update release notes * fix typo * add sim_data test * update and add tests * update and add tests * add docs for interpretation of length scales in periodic kernel (pymc-devs#3989) * fix the expression of periodic kernel * revert change and add doc * FIXUP: add suggested doc string * FIXUP: revertchanges in .gitignore * Fix Matplotlib type error for tests (pymc-devs#4023) * Fix for issue 4022. Check for support for `warn` argument in `matplotlib.use()` call. Drop it if it causes an error. * Alternative fix. * Switch from pm.DensityDist to pm.Potential to describe the likelihood in MLDA notebooks and script examples. This is done because of the bug described in arviz-devs/arviz#1279. The commit also changes a few parameters in the MLDA .py example to match the ones in the equivalent notebook. * Remove Dirichlet distribution type restrictions (pymc-devs#4000) * Remove Dirichlet distribution type restrictions Closes pymc-devs#3999. * Add missing Dirichlet shape parameters to tests * Remove Dirichlet positive concentration parameter constructor tests This test can't be performed in the constructor if we're allowing Theano-type distribution parameters. * Add a hack to statically infer Dirichlet argument shapes Co-authored-by: Brandon T. Willard <[email protected]> Co-authored-by: Bill Engels <[email protected]> Co-authored-by: Oriol Abril-Pla <[email protected]> Co-authored-by: Osvaldo Martin <[email protected]> Co-authored-by: Adrian Seyboldt <[email protected]> Co-authored-by: Alexandre ANDORRA <[email protected]> Co-authored-by: Colin <[email protected]> Co-authored-by: Brandon T. Willard <[email protected]> Co-authored-by: Junpeng Lao <[email protected]> Co-authored-by: rpgoldman <[email protected]> Co-authored-by: Robert P. Goldman <[email protected]> Co-authored-by: Tirth Patel <[email protected]> Co-authored-by: Brandon T. Willard <[email protected]>
Check for support for
warn
argument inmatplotlib.use()
call. Drop it if it causes an error.Attempted fix for #4022
I don't have the same version of matplotlib, so I am debugging through Travis!