fix: correct biased pymc HMC sampling (target_accept)#1908
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The hmc parametrizations of test_c2st_pymc_sampler_on_Gaussian were failing in CD (c2st ~0.62). Root cause is PyMC's HamiltonianMC default target_accept=0.65, which mixes poorly on this peaked target regardless of seed, warmup, or number of draws (NUTS is unaffected). Expose seed and target_accept on PyMCSampler and set target_accept=0.95 (c2st ~0.51-0.54 across seeds and chain counts) plus a fixed seed in the test for reproducibility.
MCMCPosterior._pymc_mcmc left PyMC's HamiltonianMC at its default target_accept=0.65, which produces biased hmc_pymc posteriors (c2st ~0.62 on a Gaussian). Default it to 0.9 for the HMC step, leaving nuts_pymc and slice_pymc unchanged. hmc_pymc now samples accurately (c2st ~0.51).
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## main #1908 +/- ##
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+ Coverage 87.81% 87.89% +0.07%
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dgedon
reviewed
Jul 14, 2026
| step = steps[mcmc_method] | ||
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| if target_accept is None and step == "hmc": | ||
| target_accept = 0.9 |
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We should probably add a CHANGELOG for this. Currently it's a silent change of default values
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| a higher value (e.g. 0.9-0.95) gives markedly less biased samples. | ||
| Ignored for the `"slice"` step. |
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We should probably mention our new default of 0.9 here explicitly
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Follow-up to #1894 because CD is failing again. Once the lockfile fix let the pymc tests run again in CD,
test_c2st_pymc_sampler_on_Gaussianfailed on thehmcparametrizations with c2st around 0.62.However, it's not flaky: pymc's
HamiltonianMCdefaults totarget_accept=0.65, which mixes poorly on this peaked Gaussian and biases the samples, regardless of seed, warmup, or number of draws. NUTS works fine.To fix this:
seedandtarget_acceptonPyMCSamplertarget_accept=0.9for thehmc_pymcstep inMCMCPosteriorto get accurate HMC posteriors (c2st ~0.51 vs ~0.62);nuts_pymc/slice_pymcunchangedtarget_accept=0.95in the c2st test for reproducible samplingslicedoes not taketarget_accept, so it is only applied to hmc/nuts.Note: the c2st test is marked
slow, I will run the CD on this branch via workflow dispatch.