Generate random seeds in dataset for reproducible stochastic simulations#202
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MaxGhenis wants to merge 1 commit into
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Generate random seeds in dataset for reproducible stochastic simulations#202MaxGhenis wants to merge 1 commit into
MaxGhenis wants to merge 1 commit into
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This change moves random number generation from policyengine-uk into the dataset generation, following the pattern established in policyengine-us-data. Changes: - Add random seed generation in FRS dataset for person, benunit, and household entities - Update SPI dataset to use seeded generator for age assignment - Update income imputation to use seeded generator for age assignment - Update capital gains imputation to use seeded generator for quantile sampling - Update childcare assumptions to use seeded generator All random generation now uses np.random.default_rng(seed=100) for full reproducibility across dataset builds. This replaces the previous approach of calculating random variables directly during simulation and instead stores random seeds in the dataset that can be used by variables in policyengine-uk. Related: policyengine-uk PR (must be merged after this)
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Summary
This PR moves random number generation from policyengine-uk into the dataset generation, following the pattern established in policyengine-us-data.
Changes
All random generation now uses
np.random.default_rng(seed=100)for full reproducibility across dataset builds.This replaces the previous approach of calculating random variables directly during simulation and instead stores random seeds in the dataset that can be used by variables in policyengine-uk.
Related PRs
Test Plan
🤖 Generated with Claude Code
Co-Authored-By: Claude noreply@anthropic.com