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On main I re-built the environment from scratch following instructions in CONTRIBUTING.md and can reproduce this bug locally:
FAILED causalpy/tests/test_pymc_experiments.py::test_inverse_prop - ValueError: autodetected range of [nan, nan] is not finite
This was fixed by adding in the rand_seed code to the PropensityScore.fit method which overrides the ModelBuilder.fit method. So the method should now be:
deffit(self, X, t, coords):
"""Draw samples from posterior, prior predictive, and posterior predictive distributions. We overwrite the base method because the base method assumes a variable y and we use t to indicate the treatment variable here. """# Ensure random_seed is used in sample_prior_predictive() and# sample_posterior_predictive() if provided in sample_kwargs.random_seed=self.sample_kwargs.get("random_seed", None)
self.build_model(X, t, coords)
withself:
self.idata=pm.sample(**self.sample_kwargs)
self.idata.extend(pm.sample_prior_predictive(random_seed=random_seed))
self.idata.extend(
pm.sample_posterior_predictive(
self.idata, progressbar=False, random_seed=random_seed
)
)
returnself.idata
Though it's worth double checking the details of the test and error message which I didn't do 🤷🏻♂️😜
The text was updated successfully, but these errors were encountered:
Slightly strange because all tests passed for #311. But we have a failing remote test for https://github.com/pymc-labs/CausalPy/actions/runs/8974649334/job/24647471387
On
main
I re-built the environment from scratch following instructions inCONTRIBUTING.md
and can reproduce this bug locally:This was fixed by adding in the
rand_seed
code to thePropensityScore.fit
method which overrides theModelBuilder.fit
method. So the method should now be:Though it's worth double checking the details of the test and error message which I didn't do 🤷🏻♂️😜
The text was updated successfully, but these errors were encountered: