Recalibrator and FrontalAnalysis use Nx for tensor math, but Nx is
declared `only: [:dev, :test]` in mix.exs because neither module has a
prod entry point — Recalibrator is invoked by hand from IEx and
FrontalAnalysis is research scaffolding. The prod compile would emit
"Nx.to_number/1 is undefined" warnings on every Nx call. Add a
`@compile {:no_warn_undefined, Nx}` directive to both modules so the
prod build is clean without dragging Nx/Axon/EXLA (~hundreds of MB) into
the runtime image.
The /path calculator showed "0 / 9 HRRR points" in production despite
the on-disk profile store being current. Root cause: profile_from_cell/2
treated the cell's :profile key as a wrapper sub-map and called
Map.put_new on it — but the :profile key actually holds the vertical
pressure-level LIST. Every point sample crashed with BadMapError, the
crash propagated as {:exit, _} through Task.async_stream, and the
consumer silently dropped all 9 results.
Fix: stop wrapping. Cells are already flat HrrrProfile-shaped maps;
just stamp lat/lon (from the caller, since cells don't carry their
own coords — those are the map key) and valid_time onto the cell.
Audit + log every other async error path so the next silent failure
isn't invisible:
- PathLive HRRR point lookup
- Propagation.point_forecast per-hour reads
- Viewshed ray crashes
- IemClient ASOS network fetches
- RtmaClient range-download tasks
- Recalibrator factor-vector batches (positive + negative samples)
- MapLive forecast preload tasks
- RoverLive station resolution
LiveViews already had handle_async/3 exit clauses with logging. The
gap was always in Task.async_stream consumers that wrote {:exit, _} -> []
without surfacing the reason.
Add the rule to CLAUDE.md and project memory so this never repeats.
Also fix a pre-existing skewt_svg.ex compiler warning where
@critical_label_min_dy was used before being defined.
Wrap a Task.Supervisor in a PartitionSupervisor (one partition per
scheduler) and route the four sustained async_stream callers through
`{:via, PartitionSupervisor, {Microwaveprop.TaskSupervisor, self()}}`.
Concurrent work — the hourly PropagationGridWorker pulling f00-f18
HRRR range downloads, the GEFS worker scoring its grid, and the
Recalibrator's 20-way positive/negative fan-out — no longer funnels
through a single supervisor PID.
Light/one-shot Task.async + Task.start sites (hrrr_client surface/
pressure fan-out, application boot warmup, weather fire-and-forget)
are left alone; partitioning only helps under sustained concurrency.
Path calculator conditions map was missing :latitude and
:best_duct_band_ghz. Scorer read them with bracket-notation so the
behaviour was defensively correct but we were leaving signal on the
floor:
- latitude: midpoint of src/dst so `score_season` picks up the right
latitude-based seasonal shift for northern vs southern paths
- best_duct_band_ghz: queried via new Weather.nearest_native_duct_ghz/3
at the midpoint so score_refractivity/4 applies the 1.15× boost
when a native-resolution duct supports the target band
Recalibrator.fit/1 was serialising ~10k per-contact HRRR lookups
(5000 positives + 5000 negatives, one Weather.find_nearest_hrrr each).
Parallelised both sides with Task.async_stream at 20 concurrency —
well under the prod db pool of 30. Cuts a band recalibration from
~minutes of query round-trips to seconds.
Ran recalibrate_algo.py against the full local prop_dev (81,994 contacts,
18.6M HRRR rows) and derived per-band composite weights for the nine
bands with >=200 matched contacts. Moisture (dewpoint/PWAT/surface N)
is consistently beneficial through 5.76 GHz, reverses at 24 GHz; rain
scales sqrt(rain_k) not linearly so 24 GHz gets 0.215 rain weight
instead of the linear-ratio 0.95. 10 GHz stays as the reference band
(defaults); 47+ GHz inherits defaults (n<200).
- BandConfig.weights/1 returns per-band override or default fallback
- @band_configs carries :weights on 222/432/902/1296/2304/3400/5760/24G
- Recalibrator.compute_factors/3 + fit(band_mhz:) band-aware fitting
- Scorer + ContactLive.Show pass band_config to weights/1
- algo.md Part 2d documents the 2026-04-18 analysis + derivation rule
- scripts/derive_band_weights.py turns correlations into weight maps
- report preserved at docs/algo-reports/2026-04-18-recalibration.md
57,186 prod contacts stored pos1/pos2 with 'lng'; 1,133 used 'lon'.
Every Elixir caller carried a `pos["lon"] || pos["lng"]` fallback
— which just caused a SQL widget to silently miscount 98% of contacts
(count_narr_done used `pos1->>'lon'` directly, no fallback, so every
lng-keyed row returned NULL and failed the coverage check).
- Migration rewrites every pos1/pos2 JSONB in place, renaming 'lng' to
'lon' and dropping 'lng'.
- Removes all 20+ `|| pos["lng"]` fallbacks across lib/, workers,
scorer, weather, radio.ex, contact show view, and recalibrator.
- lib_ml/propagation_analyze.ex SQL now reads pos1->>'lon' directly
(was reading 'lng' only, which would have broken after migration).
- priv/repo/import_contacts.exs one-time seed script now emits 'lon'
with string keys, matching production shape.
- Test fixtures in 4 test files normalized to 'lon'.
- Two lng-characterization tests deleted — nonsensical post-normalize.
- Updated notebook + old import_weather script to match.
- JS hook contact_map_hook.ts TypeScript type narrowed to 'lon'.
