Changes under lib/ (source):
- iemre_fetch_worker: replace `if transient_failure?/1` boolean predicate
+ `if/else` with a classifier that pattern-matches the error reason
directly, returning `:transient | :permanent`, and dispatch via
`case`. Three-clause head is clearer than the boolean predicate.
- scores_file.extract_points and nexrad_client.extract_box: force `//1`
step on the row/col comprehensions so an image box whose centre
lands outside the raster collapses to an empty iteration instead
of firing Elixir 1.19's ambiguous-range warning. Adds a regression
test for the right-edge box.
Test coverage added:
- Feature wrappers in Backtest.Features (theta_e_jump, shear_at_top,
duct_thickness, best_duct_freq, duct_usable_for_band,
distance_to_front / parallel_to_front stubs, all_features/0).
- NotifyListener handle_info tolerance for malformed payloads +
unknown messages, plus the PubSub broadcast side effect.
- Viewshed.effective_reach_km across every verdict / diffraction
tier / ducting-score tier combination.
- SnmpClient parse_af60_output unit conversions + unknown-column
handling; parse_snmpget_output OID normalisation and junk-line
tolerance.
- HrrrNativeClient native_level_count, native_variables,
native_messages shape, duct_messages / duct_byte_ranges.
- Changeset coverage for GeomagneticObservation, SolarFluxObservation,
SolarXrayObservation, Ionosphere.Observation, HrrrClimatology, and
Metar5minObservation — lifted each from ~50% / 0% to 100%.
- Property tests: GefsClient.dewpoint_from_rh invariants (Td ≤ T,
monotonic in RH, finite across the operating envelope) + idempotent
nearest_run. NexradClient.pixel_to_dbz monotonicity + bounded
output; latlon_to_pixel round-trip for every grid cell.
Also cleared several unrelated compiler/linter warnings:
- Three private test helpers (create_contact, insert_contact,
current_hour) had `\\ %{}` / `\\ 0` defaults that no caller used.
- profiles_file_test bound `dir` in a pattern match without using it.
Suite: 2,359 tests + 146 properties pass (was 2,300 / 139); coverage
70.38% → 70.89%; credo strict clean.
Telemetry puts nexrad_decode_png at 1.76 s/call × 37,847 calls/h
— ~18.5 h of CPU across the cluster every real hour, the single
biggest CPU consumer in the system. The map-click path
(fetch_rain_cells) already cached decoded frames by 5-min
bucket, but the per-contact CommonVolumeRadarWorker path
(fetch_decoded_frame) went straight to network + decode on every
call. Backfill means many contacts share a 5-min window, so the
same 66 MB frame was being decoded dozens of times.
Wire fetch_decoded_frame through NexradCache keyed on the
rounded timestamp. Add a 20-entry size cap in NexradCache so
backfill processing contacts in random timestamp order can't
grow the ETS table to hundreds of GB. Each frame is ~66 MB, so
20 = ~1.3 GB worst case, well under typical pod memory.
Expected impact: cuts sustained decode load by an order of
magnitude depending on backfill temporal locality; map-click
path is unchanged.
Previously the CommonVolumeRadarWorker ran silently — no URL logged,
no sign in the logs that it was doing any work. Added info-level
fetch/ok/error logs in NexradClient (same shape as WeatherFetchWorker
RAOB logs) plus start-of-work + ingestion lines in the worker itself.
Unchanged: the existing "no frame" warning and all control flow.
Adds Microwaveprop.Propagation.AsosNudge: a pure IDW bias-field module
that takes ASOS observations + HRRR profiles and returns re-scored grid
rows for every cell within 250km of a reporting station. Upper-air
fields (min_refractivity_gradient, pwat_mm, hpbl_m, profile, duct
metadata) pass through unchanged so HRRR's signal isn't clobbered.
The old AsosAdjustmentWorker was unwired and buggy — nil'd out ~22% of
the scoring weight and wrote orphan timestamps. Replaced with a slim
worker that queries the latest HRRR valid_time, fetches live ASOS
currents, calls AsosNudge.compute/3, and upserts onto
(lat, lon, valid_time, band_mhz) so nudged values overwrite the HRRR
hour cleanly instead of polluting available_valid_times. After each
upsert it warms ScoreCache and broadcasts propagation:updated so live
/map clients refresh.
Cron hooked up every 10 minutes in config.exs and dev.exs. Also cleaned
up the stale "dev has propagation disabled" note in CLAUDE.md.
13 new AsosNudge unit tests cover: residual computation (co-located,
out-of-grid, nil fields), IDW weighting (single station, far station,
two equidistant stations, nil component handling), upper-air
preservation, and the compute/3 entry point's shape and radius filter.
Drive-by Styler formatting touched a handful of unrelated files from
`mix format`.
- 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
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.
