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Sharrow compatibility for v15.3.1 #2
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Sharrow compatibility for v15.3.1 #2
jpn--
wants to merge
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commits into
wsp-sag:sync_production_v15.3.1
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driftlesslabs:sync_production_v15.3.1
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i-am-sijia
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Nov 11, 2025
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@jpn-- Looks good, thanks! If I merge this, PR ActivitySim#39 becomes a duplicate of PR ActivitySim#37. I have no particular preference on which one we want to keep. |
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This pull request introduces new scripts and configuration files to support running the SANDAG ABM3 example model at different scales and with different settings, including sharrow and multiprocessing options. It also updates dependency requirements and makes minor corrections to configuration and sample files to improve consistency and avoid variable conflicts. The most important changes are grouped below.
New scripts and workflow enhancements
run-small-sharrow.py,run-large-sharrow.py,run-large-legacy.py,run-large-sharrow-mp.sh,run-large-legacy-mp.sh) to enable running the model with different configurations (small/test, large/full-scale, sharrow enabled/disabled, multiprocessing) and improved reproducibility via embedded metadata for dependency management. [1] [2] [3] [4] [5]scripts/fulldata.pyto handle downloading and verifying the full-scale dataset, including checksum validation and extraction, ensuring large datasets are managed efficiently and securely.scripts/README.mdexplaining the purpose and usage of each script for easier onboarding and clarity.Configuration updates for sharrow and multiprocessing
settings_mp_sharrow.yamlto support running the model with sharrow and multiprocessing, including settings for process count, fail-fast behavior, and model steps.Dependency and compatibility improvements
activitysimversion inpyproject.tomlfrom1.4to>=1.5to ensure compatibility with newer features and bug fixes.Data and configuration corrections
trip_destination_sample.csvandtrip_destination_annotate_trips_preprocessor.csvto avoid conflicts and ensure proper evaluation of expressions. [1] [2]data/maz_maz_bike.csvfromUnnamed: 0toNothingfor clarity.Testing adjustments
rtol) in the model test checkpoint comparison to reduce false negatives in cross-platform testing.