- Nx, Axon, EXLA, Polaris deps restricted to only: [:dev, :test]
- model.ex and training mix tasks moved to lib_ml/ (compiled via
elixirc_paths in dev/test only)
- load_ml_model uses Code.ensure_loaded? + apply/3 to avoid
compile-time references to ML modules in production
- Verified: MIX_ENV=prod compiles clean with no ML warnings
ML Integration:
- Load trained model at app startup, cache compiled predict fn in persistent_term
- Grid worker uses batched ML prediction (10K chunks) when model loaded,
falls back to algorithm scorer when not
- ML score replaces composite, algorithm factor scores preserved for detail view
- Fix process explosion: single EXLA call per chunk instead of per-grid-point
QSO Features:
- Callsign search (ILIKE on station1/station2) with trigram indexes
- Reciprocal QSO grouping (same pair, same band, same hour)
- Wider layout (max-w-7xl) for data table pages
- QSO Training Data link on map page
Infrastructure:
- Re-enable hourly propagation grid worker in dev
- Track ML model weights in git for Docker builds
- Add btree indexes on qsos (timestamp, band, distance_km)
- Remove nav icons from layout header
Add SFI, Kp max (solar), K-index, lifted index (sounding stability),
and ducting_detected (HRRR) as model features. Training now joins to
solar_indices and nearest sounding (within 6 hours) for both phases.
Model can learn solar/geomagnetic effects if they exist in the data.
- 15 features: add surface_refractivity and latitude
- Bigger network: 128→64→32 (3 hidden layers)
- Phase 1: pretrain on 500K stratified algorithm scores (all seasons/locations)
- Phase 2: fine-tune on 57K real QSO-HRRR matched data (percentile target)
- Lower LR (0.0003) for fine-tuning to preserve pretrained knowledge
- Model.train accepts :initial_state option for transfer learning
- 3 hidden layers instead of 2 for better feature interaction learning
- Target is within-band distance percentile (0-1) instead of raw
normalized distance — reduces noise from operator/equipment variation
Raw features had vastly different scales (pressure ~1013, sin/cos ~[-1,1])
causing gradient explosion. Normalize all atmospheric features to ~[0,1]
using known physical bounds. Add Polaris dep for optimizer.
Solar time (longitude/15) replaces fixed CDT/CST offset for time-of-day
scoring. Correlation analysis shows dramatic improvement at higher
frequencies: 24 GHz rho jumps from 0.056 (UTC) to 0.188 (solar), and
75 GHz corrects from spurious -0.39 to physically correct +0.24.
Score time-of-day per grid point using longitude/15 solar offset instead of
hardcoded CST/CDT. Add PWAT as 10th scoring factor. Refine pressure thresholds.
Update ML model and training pipeline to use local solar time.
Previous thresholds (-500 to -60) were calibrated for radiosonde data.
HRRR profiles have coarser vertical resolution, with gradients clustering
between -40 and -130 N/km (median -70). Nearly all grid points were
falling through to the default score of 42, wasting the refractivity
factor. New thresholds (-200 to -40) spread across HRRR percentiles.
- Add enqueue_for_qso/1 to directly enqueue weather/HRRR/terrain/IEMRE
jobs for a single user-submitted QSO (no cron, no bulk processing)
- Submit flow calls enqueue_for_qso instead of generic enqueue worker
- Add enrichment queues to prod config for on-demand processing
- Guard against HRRR fill values in store_hrrr_profiles (fixes badarith)
- Filter QSOs without pos2 in build_terrain_jobs
Replaces the one-shot startup Task with a GenServer that checks every
5 minutes whether propagation scores are older than 2 hours. If stale,
enqueues a PropagationGridWorker job (with dedup check to avoid double
queuing). Disabled in test env to avoid SQL Sandbox conflicts.
Replace circle markers with a canvas tile layer that renders smooth,
flowing colored regions using bilinear interpolation between grid
points. Colors interpolate between tiers for gradients. ~95k grid
points at 0.125 degree resolution with wgrib2 extraction.
Add Wgrib2 module that shells out to wgrib2 binary for fast GRIB2
grid extraction using -lola (nearest-neighbor to regular lat-lon grid).
Falls back to pure-Elixir decoder if wgrib2 is not installed.
Also: parallel GRIB2 range downloads, merge adjacent byte ranges,
skip corrupt messages instead of failing, pressure fetch is optional.
95k points at 0.125 degree resolution caused the GRIB2 extraction to
take too long. 0.5 degree (~55 km) resolution gives 6k points which
completes in under a minute. Can increase resolution later once the
extraction is optimized.
Define 0.125-degree CONUS grid (25-50N, 125-66W) for propagation
scoring and create propagation_scores table with composite unique
index on lat/lon/valid_time/band_mhz for upsert support.
Single source of truth for all scoring parameters: weights, thresholds,
seasonal tables, and per-band coefficients for 8 microwave bands
(10G through 241G). Includes ITU-R P.838-3 rain attenuation
coefficients, humidity effects, refractivity scoring thresholds,
and sunrise/tier definitions.
