Lsst products - #62
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LSST DC2 selection-function products + curve bright cuts + Roman survey docs
lsst/dc2): truth-anchored maglim maps (g/r, nside=1024, median r = 26.52), two-curve photometric errors (sample/catalog + afterburner), stellarclassification_detection_effcurve (S/N>5 counted exactly once), and a compact-galaxy misclassification curve — with generatorsscripts/lsst/create_streamobs_files_lsst_dc2.pyandbuild_lsst_dc2_galaxy_misclass.py, plus a tracked validation notebook.cut_brightafterburner rule; the injector's saturation handling governs brighter magnitudes.delta_mag = mag − maglimsign and themissclassification_effcolumn the loader expects (was inverted / misnamed; previously unconsumed so no behavior change).gal_misclassificationinto the DC2/HLWAS survey configs (loader now handles multi-line CSV provenance headers); DC2-backed misclass tests now pass.surveys/Roman.mdpage matching the LSST convention, with new efficiency/error figures and an all-sky HLWAS-all depth map.lsst_yr1–5use the DC2-derived efficiency / misclassification / two-curve photo-error tables (symlinked byscripts/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.pyarrow(hard dep),skyproj(plotting extra), andpytest-cov(dev extra;pytest.iniaddopts use--cov).bin/build_data_archive.pynow includes the lsst_dc2 runtime products;data.ziprebuilt (74 files, ~33 MB) and validated.Follow-ups (separate PRs): upload
data.zipto Zenodo and bumpBASE_DATA_URLinbin/download_data.py.