Add elsim.studies API and migrate Monte Carlo examples (#10)#52
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Add elsim.studies API and migrate Monte Carlo examples (#10)#52endolith wants to merge 3 commits into
elsim.studies API and migrate Monte Carlo examples (#10)#52endolith wants to merge 3 commits into
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Introduce parameter expansion helpers (expand_product, expand_zip, expand_rows), serial and Joblib backends with map_repeat and map_each, run_batched and merge_counters, and Merrill-style Condorcet-efficiency tallies. Refactor three examples to use the new helpers, document the module in Sphinx, add tests, and include joblib in the test extra for CI. Co-authored-by: endolith <endolith@gmail.com>
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elsim.studies API for Monte Carlo example scripts (closes #10)elsim.studies API for Monte Carlo example scripts (#10)
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Add social_utility helpers for Merrill/Weber-style utility totals. Refactor every batch-style example to use JoblibBackend (or studies metrics) instead of raw joblib, document the Hypothesis script as out of scope, and restore tabulate/elapsed output where tooling had stripped it. Co-authored-by: endolith <endolith@gmail.com>
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elsim.studies API for Monte Carlo example scripts (#10)elsim.studies API and migrate Monte Carlo examples (#10)
Exercise social_utility branches, runner edge cases, parameter helpers, Serial/Joblib backend error paths (including simulated missing joblib), and Merrill Condorcet rated-method tallies. Use Optional[str] for UW tiebreaker annotation for Python 3.8. Co-authored-by: endolith <endolith@gmail.com>
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Summary
This PR addresses issue #10 with a new
elsim.studiessubpackage and refactors all Monte Carlo–style examples to use it.elsim.studies(building blocks)expand_product,expand_zip,expand_rows— explicit Cartesian vs zipped vs fixed scenario rows.SerialBackend/JoblibBackendwithmap_repeatandmap_each(forfunctools.partialjob lists).run_batched,merge_counters.merrill_1984_comparison_methods,tally_condorcet_agreement.spatial_random_reference_utility_updates,random_society_utility_updates,ranked_rated_utility_updates— shared per-election float totals for Merrill / Weber scripts.hypothesis_election_finder.pyis documented as Hypothesis-based search, not batched Monte Carlo, so it intentionally does not importstudies.weber_1977_expressions.pystays analytical only.Examples
Parallel examples now use
JoblibBackendinstead ofjoblib.Parallel/delayeddirectly. Merrill / Weber loops use the tallies above where they match prior logic (includingutility_winner(utilities)without tiebreaker for Weber effectiveness / Merrill Table 3 UW).Tests
tests/test_studies.pycovers expansion, backends, batching, Condorcet tallies, and the new social-utility helpers.Other
joblibadded to thetestoptional extra so CI exercisesJoblibBackend.elsim.studies.