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Lsst products - #62

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psferguson wants to merge 6 commits into
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lsst_products
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Lsst products#62
psferguson wants to merge 6 commits into
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LSST DC2 selection-function products + curve bright cuts + Roman survey docs

  • New LSST DC2 product suite (lsst/dc2): truth-anchored maglim maps (g/r, nside=1024, median r = 26.52), two-curve photometric errors (sample/catalog + afterburner), stellar classification_detection_eff curve (S/N>5 counted exactly once), and a compact-galaxy misclassification curve — with generators scripts/lsst/create_streamobs_files_lsst_dc2.py and build_lsst_dc2_galaxy_misclass.py, plus a tracked validation notebook.
  • Bright cuts on all curve products: LSST rows with Δmag < −11 and Roman rows with Δmag < −8.7 (saturation jump in the F158 scatter curve) are dropped, via a new config-driven cut_bright afterburner rule; the injector's saturation handling governs brighter magnitudes.
  • Roman misclass product fix: CSV now uses the standard delta_mag = mag − maglim sign and the missclassification_eff column the loader expects (was inverted / misnamed; previously unconsumed so no behavior change).
  • Wire gal_misclassification into the DC2/HLWAS survey configs (loader now handles multi-line CSV provenance headers); DC2-backed misclass tests now pass.
  • Docs: full surveys/Roman.md page matching the LSST convention, with new efficiency/error figures and an all-sky HLWAS-all depth map.
  • LSST year releases now depend on DC2: lsst_yr1–5 use the DC2-derived efficiency / misclassification / two-curve photo-error tables (symlinked by scripts/lsst/link_lsst_yr_products.py) and differ only in their RubinSim depth maps — same convention as the Roman HLWAS tiers. Test registry carries the matching DC2-model threshold overrides; the match-filter integration test now asserts both red-cap modes explicitly.
  • Packaging: declare pyarrow (hard dep), skyproj (plotting extra), and pytest-cov (dev extra; pytest.ini addopts use --cov).
  • Data archive: bin/build_data_archive.py now includes the lsst_dc2 runtime products; data.zip rebuilt (74 files, ~33 MB) and validated.

Follow-ups (separate PRs): upload data.zip to Zenodo and bump BASE_DATA_URL in bin/download_data.py.

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