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fix: DynestyDynamic OverflowError when run without an output path - #1658
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…tput path With `NullPaths` (a search created without a `name`), `iterations_from` returned `int(1e99)` as the "unbounded" per-chunk budget. dynesty's dynamic sampler computes `maxcall - ncall` with a numpy int64 `ncall`, and a 99-digit Python int cannot be converted to a C long, raising `OverflowError: Python int too large to convert to C long`. The static sampler only compares against `maxcall`, so it was unaffected. Use `sys.maxsize`, which is the sentinel dynesty itself uses for `maxcall=None`. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…C long Regression test for the OverflowError raised by dynesty's dynamic sampler when a search is run without an output path. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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Summary
Discussion: https://github.com/orgs/PyAutoLabs/discussions/28
DynestyDynamiccrashed withOverflowError: Python int too large to convert to C longwhenever the search had no output path (NullPaths, i.e. created without aname).AbstractDynesty.iterations_fromreturnedint(1e99)as the "unbounded" per-chunkmaxcallbudget in that case. dynesty's dynamic sampler computesmaxcall - ncallwith a numpy int64ncall, which cannot handle a 99-digit Python int. The static sampler only compares againstmaxcallin pure Python, so it was unaffected.This PR returns
sys.maxsizeinstead, the same sentinel dynesty substitutes formaxcall=None. The branch wheremaxcallis set is unchanged. A comment at the site records why the value matters.API Changes
iterations_fromis internal and theNullPathsreturn value changes fromint(1e99)tosys.maxsize. Both mean "no limit". No downstream code reads this value.Test Plan
test__null_paths_iteration_budget_fits_c_long, parametrised overDynestyStaticandDynestyDynamic: asserts the budget issys.maxsize, that subtracting anp.int64from it works, and that an explicitmaxcallis still returned unchanged. Fails red onmain(int(1e99) != sys.maxsize).DynestyDynamic) now runs to completion, with and withoutn_effective. Fitting with a named search before and after the change gives the same sample counts and effective sample sizes.test_autofit/non_linear/search/nest/: 40 passed, 13 skipped, on macOS / Python 3.13.7 / dynesty 2.1.5. Run with the conftest'sset_start_methodstubbed because of the macOS import-time bug fixed separately in fix: do not fix the multiprocessing start method at import time on macOS #1657.🤖 Generated with Claude Code