Fix microsim skill: warn against np.array() and entity-level mismatches#107
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nwoodruff-co merged 1 commit intomainfrom Mar 8, 2026
Merged
Fix microsim skill: warn against np.array() and entity-level mismatches#107nwoodruff-co merged 1 commit intomainfrom
nwoodruff-co merged 1 commit intomainfrom
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Real bug encountered: np.array() on MicroSeries strips entity context, allowing silent mismatches between tax_unit (23K rows) and household (15K rows) arrays. Boolean mask from one entity applied to weights from another gives silently wrong counts (showed 1K losers instead of 719K). Changes: - Expand CRITICAL section to warn against np.array() specifically (not just .values), explaining entity mismatch as the primary danger - Add entity-level matching section with wrong/right examples - Note that household_net_income includes state tax effects and add federal-only pattern using income_tax for scoring federal bills Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Summary
np.array()on MicroSeries, which strips both weights AND entity contexthousehold_net_incomeincludes state tax effects; addincome_taxpattern for federal-only scoringBug this prevents
When analyzing WATCA,
np.array()was used to convert MicroSeries to numpy. A tax_unit-levelincome_taxarray (23K rows) was indexed with a boolean mask, then matched againsthousehold_weight(15K rows). Numpy didn't error — it silently gave wrong counts (1K losers instead of 719K).Test plan
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