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analytic_gaussian: assert finite EP evidence and no ep_mean_field RuntimeWarning (PyAutoFit#1713) - #116
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…timeWarning (PyAutoFit#1713) Seed-0 legs A and B now run their EP columns under warnings capture and assert no RuntimeWarning from ep_mean_field.py and a finite final log_evidence. A new seed-25 leg B under the mode projection (EP only, ~3 s) reproduces the +inf scatter-sigma evidence term and asserts it is named in the log and in ep_diagnostics.results (or that the evidence is finite). Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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Summary
Regression for PyAutoFit#1713. The seed-0 EP columns (legs A and B) now run under
warnings.catch_warnings(record=True)and assert noRuntimeWarningfromep_mean_field.pyplus a finite finallog_evidence(leg A 62.44, leg B 167.05). A new seed-25 leg B under the default mode projection (EP only, ~3 s) reproduces the ensemble's +inf scatter-sigma evidence term (first at step 39) and asserts the library names it in both the log andep_diagnostics.results, or that the evidence is finite (mode-projection outcomes depend on process history, as the script's docstring notes). Header docstring section and runtime note updated.Scripts Changed
scripts/graphical/analytic_gaussian.py— warnings capture + finite-evidence checks on the seed-0 EP columns; new seed-25 mode-projection leg with the named-term check; docstring section and CI-cap noteUpstream PR
PyAutoLabs/PyAutoFit#1714
Test Plan
PARITY: PASS (53/53), column runtime 122 s, wall 2m05s (< 300 s cap)Generated by the PyAutoLabs agent workflow.
🤖 Generated with Claude Code