examples: ERA LTE Tier-1 integration script (#110)#112
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Runnable bridge from the ERA LTEs dataset to the toolkit: reads ERA's shipped unique_ltes.csv registry and runs analyze_climate_statistics with auto season detection per LTE site-period, emitting a tidy per-season climate table. No R needed for this tier. --dry-run / --limit for safe testing. Verified against the real ERA CSV (parses/dedups to 358 site-periods) and ruff clean.
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Adds the ERA LTE Tier-1 integration as a runnable, reviewable file (
examples/era_lte_tier1.py) instead of living only in the issue discussion. Relates to #110.What it does
Bridges the ERA LTEs dataset (ERAgriculture/LTEs) to this toolkit with no R required:
data/unique_ltes.csvregistry (LTE.ID, Site.ID, Year.start, Year.end, Latitude, Longitude).analyze_climate_statisticswith auto season detection per site and flattensseason_statisticsinto a tidy per-season climate table (rainfall total, rainy/dry days, mean temp, NDWS, WRSI).--dry-run(list sites, no fetch) and--limit Nfor safe testing.Verification
ruffclean.--dry-runagainst the real ERAunique_ltes.csv: parses/dedups to 358 unique site-periods and lists them correctly. (A full run fetches Earth Engine data per site, so--limitis provided for validation first.)Scope
This is Tier 1 (the pure-Python pass). Tier 2 — the yield comparison — needs a short R export of ERA's season windows + crop/yield from the
industrious_elephant.RDatatables, then feeds the adapter documented on #110. That stays as a workflow step; this PR just lands the runnable Tier-1 entry point underexamples/.