3 commits

Author	SHA1	Message	Date
Graham McIntire	250709a1b2	Add more caching to make the map feel instant ... - ScoreCache stores {band, valid_time} as %{{lat, lon} => score} map so point lookups are O(1); adds fetch_point/4 and valid_times/1 - available_valid_times/1 reads directly from ScoreCache when warm, falls back to DB on cold start - point_forecast/3 iterates cached valid_times and uses fetch_point/4 instead of hitting the DB per click - NexradCache: node-local ETS cache of decoded n0q PNG pixel buffers keyed by 5-minute rounded timestamp; skips ~1-5s HTTP+decode on concurrent/repeat clicks within the same window - MapLive: start_async the rain_scatter fetch so point_detail renders immediately with a pending marker; push rain_scatter_update when NEXRAD resolves - MapLive: preload all 18 remaining forecast hours for the current viewport after mount/band change/propagation_updated; client caches them and renders timeline scrubs instantly without a server roundtrip. Adds set_selected_time event for fast-path state sync. - Propagation map JS: forecastCache map + drawScatterMarkers helper, timeline click uses preloaded cache when available	2026-04-12 12:26:25 -05:00
Graham McIntire	e8ae407be9	Add rain scatter prediction to map detail panel ... When clicking a grid point, fetches the latest NEXRAD composite reflectivity and identifies rain cells within 300 km that could enable rain scatter contacts. Shows: - Scatter classification (excellent/good/marginal/none) - Top 3 cells with dBZ, distance, bearing, and relative signal - Colored circle markers on the map at rain cell locations - Markers sized by reflectivity, colored by intensity Uses simplified bistatic radar equation accounting for reflectivity, frequency-dependent scattering (Rayleigh/Mie), and R^4 path loss. NEXRAD cells sampled every ~5 km within bounding box for efficiency.	2026-04-11 15:19:19 -05:00
Graham McIntire	e7a7ae073d	Phase 9.3, 9.4, and Phase 3 NEXRAD pipeline ... Task 9.3 - Weight recalibration via gradient descent: - Recalibrator module fits logistic regression weights using Nx - Trains on QSO positives vs random baseline negatives - Cross-validates by month, normalizes weights to sum to 1.0 - Mix task: mix recalibrate_scorer --sample 5000 --epochs 2000 Task 9.4 - Side-by-side scorer comparison: - ScorerDiff.compare/3 re-scores grid with old vs new weights - Reports mean diff, regressions, improvements, per-band breakdown - Mix task: mix scorer_diff --new-weights '{...}' Phase 3 - NEXRAD ingestion pipeline: - NexradClient fetches IEM n0q composite PNGs, extracts per-point box statistics (mean/max dBZ, texture variance) - NexradObservation schema with unique (lat, lon, observed_at) - NexradWorker on :nexrad queue for background processing - nexrad_texture backtest feature in Features module - mix nexrad_backfill --limit 200 All tasks added to AdminTaskWorker and Release for production use. 1116 tests, 0 failures.	2026-04-10 12:48:36 -05:00