Prior predictions constant data #5723
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Codecov Report
@@ Coverage Diff @@
## main #5723 +/- ##
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- Coverage 88.92% 88.90% -0.03%
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Files 75 75
Lines 13739 13738 -1
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- Hits 12218 12214 -4
- Misses 1521 1524 +3
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I don't know why the test is failing on windows. The failing test |
OriolAbril
reviewed
Apr 22, 2022
pymc/backends/arviz.py
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| @@ -464,7 +468,7 @@ def observed_data_to_xarray(self): | |||
| default_dims=[], | |||
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| @requires(["trace", "predictions"]) | |||
| @requires(["trace", "predictions", "prior_predictions"]) | |||
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I think this prior predictions attribute is not needed, generating the constant data group here should be enough. IIUC, removing this line completely and leaving everything else untouched should be enough
pymc/tests/test_sampling.py
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| @@ -1042,6 +1042,28 @@ def point_list_arg_bug_fixture() -> Tuple[pm.Model, pm.backends.base.MultiTrace] | |||
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| class TestSamplePriorPredictive(SeededTest): | |||
| def test_idata_output(self): | |||
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I think this test should be in idata_conversion. And I would try to avoid having a new test but instead checking for constant data in existing tests where it is currently missing
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Yes, you are right. Thank you for the review. I pushed the changes. |
OriolAbril
approved these changes
Apr 22, 2022
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Thanks @TimOliverMaier ! |
fonnesbeck
added a commit
that referenced
this pull request
May 6, 2022
* Refactor get_tau_sigma to handle lists * Fixed syntax error * Black formatted * Change assertions to ValueError raises * Prior predictions constant data (#5723) * support return constant_data with prior pred * pre-commit format * added test * code review * Fix issue probably-meant-fstring found at https://codereview.doctor (#5726) * Add coords argument to pymc.set_data (#5588) Co-authored-by: Oriol (ZBook) <[email protected]> * remove MultinomialRV override * ⬆️ UPGRADE: Autoupdate pre-commit config * Group GaussianRandomWalk tests in single class * Infer steps from shape in GaussianRandomWalk * Unpin upper limit on numpydoc Closes #5401 * ⬆️ UPGRADE: Autoupdate pre-commit config * Standardize docstrings of input dists arguments and add warning about cloning * Remove unnecessary tag in Simulator logp * Replace deprecated tag.ignore_logprob * Group compile_pymc tests in own class * Remove remaining uses of default_updates in codebase * Remove redundant/wrong docstrings from GaussianRandomWalk logp * Add moment to GaussianRandomWalk and fix mu/sigma broadcasting bug * Do not create temporary SymbolicDistribution just to retrieve number of RNGs needed Reordered methods for consistency * Move SymbolicDistribution docstring to body of class * Refactor AR distribution * Deprecates AR1 distribution * Implements random and moment methods * Batching works on the left as with other distributions * Rename `pandas_to_array` to `convert_observed_data` * Obtain step information from dims and observed * Make AR steps extend shape beyond initial_dist This is consistent with the meaning of steps in the GaussianRandomWalk and translates directly to the number of scan steps taken Co-authored-by: TimOliverMaier <[email protected]> Co-authored-by: code-review-doctor <[email protected]> Co-authored-by: Somasree Majumder <[email protected]> Co-authored-by: Oriol (ZBook) <[email protected]> Co-authored-by: danhphan <[email protected]> Co-authored-by: twiecki <[email protected]> Co-authored-by: Ricardo <[email protected]> Co-authored-by: Ravin Kumar <[email protected]> Co-authored-by: Michael Osthege <[email protected]>
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This is my suggestion for issue #5722
With this minor changes, pm.sample_prior_predictive() returns an InferenceData object, that
contains the
constant_datagroup, useful for e.g. plotting purposes of prior predictions before sampling.