Aliases: add module aliases for 9 nested module references
Apply: replace apply/3 with direct module attribute calls
Line length: break 1 long spec line
Refactoring: extract helpers to reduce complexity and nesting
in show.ex, radio.ex, weather workers, terrain, duct detection,
backfill dashboard, contact map, and mix tasks
- Replace %Struct{} with Struct.t() in all @spec annotations
- Replace length(x) > 0 with x != [] in test assertions
- Fix multi-line spec struct references in weather.ex
- Revert enrichment status cards from daisyUI stat to plain containers
(tabular status rows don't fit the stat component's layout)
- Add overflow-hidden to DB stat cards for large numbers
- Fix select text centering with display:flex + align-items:center
- Add belongs_to :user on Beacon schema, preload in get_beacon!/1
- Show "Submitted by {callsign}" on beacon detail page
- Add NTMS donation link on the about page
- Change grid preference text to 8 characters (e.g. EM12kp37)
Parse ADIF tagged-data format with fuzzy frequency-to-band matching
(nearest microwave band for any freq >= 900 MHz). Supports STATION_CALLSIGN,
OPERATOR, CALL, GRIDSQUARE, MY_GRIDSQUARE, FREQ, BAND, QSO_DATE, TIME_ON.
Same dedup and preview/commit flow as CSV upload.
Also fix select dropdown text alignment in daisyUI.
Backfill page now sums child partition stats for partitioned tables
like hrrr_profiles (relkind 'p') which were excluded by the relkind
'r' filter. Contacts map defers Leaflet init to requestAnimationFrame
so the flex container has dimensions before map initialization.
SRTM profiles no longer abort on missing tiles — water/ocean areas
return 0m elevation instead of failing the entire profile and falling
back to the rate-limited API. Elevation client and viewshed now pass
download: true to auto-fetch missing tiles from S3. NFS mount changed
to writable so downloaded tiles persist across pods.
Replace the JS-built Leaflet control panel with a server-side
sidebar (desktop) and mobile floating controls. Band checkboxes,
callsign filter, and nav links now match the main propagation map
layout. Filter state managed by LiveView, pushed to JS via events.
Registered users can suggest edits to any contact's core fields
(callsigns, grids, band, mode, timestamp). Edits enter an admin
approval queue with field-by-field diff view. On approve, changes
are applied and enrichment re-enqueued if grids/band changed.
Users receive email notification on approve or reject.
Also updates dependabot.yml for mix ecosystem.
- Callsign input filters contacts where either station matches
(case-insensitive substring match, debounced 300ms)
- Band checkboxes now show per-band count of visible contacts
- All/None buttons for quick band selection
- Header count updates dynamically with filters
- Complete rewrite: rebuilds map on any filter change instead of
toggling individual layers (simpler, handles cross-filter correctly)
The sidebar and mobile floating controls overlay the dark map tiles
but inherited light theme colors, making dropdowns, inputs, and
menus invisible (white-on-white). Adding data-theme="dark" forces
all daisyUI components within these containers to use dark variants
regardless of the page's theme setting.
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.
Terrain elevations now include the earth bulge correction, so the
profile visually humps up in the middle relative to the straight
LOS beam — showing how the curved earth rises into the signal path.
Uses actual k-factor from HRRR refractivity when available, otherwise
standard 4/3. For a 300 km path at k=4/3, the midpoint bulge is
~2,650 m (8,700 ft).
When clicking a grid point with ducting, the panel now shows each
duct layer with base-top height in feet, thickness in meters, and
minimum trapped frequency. Data flows from Duct.analyze through
the scoring factors as a ducts array.
- Replace stale April 2026 manual weights with recalibrated values
- Document native hybrid-sigma data in data flow section
- Note refractivity factor now uses native 10-50m resolution
- Add hourly grid integration section to Part 12
- Expose duct_info (count, freq, thickness) in scoring factors for UI
The PropagationGridWorker now fetches native hybrid-sigma levels
(TMP, SPFH, HGT, PRES × 50 levels) alongside the standard surface
and pressure products. Native data provides 10-50m vertical spacing
vs 250m from pressure levels, detecting thin surface ducts invisible
to the standard product.
Key design: cell-by-cell reducer in Wgrib2.extract_grid_from_file_mapped
processes each of the 95k CONUS cells through a duct analysis function
inline, keeping only scalar metrics per cell. Peak memory ~86 MB
instead of ~1.8 GB for the full grid map.
Per-cell output: native_min_gradient, best_duct_freq_ghz,
max_duct_thickness_m, duct_count. The scorer prefers the native
gradient over the pressure-level gradient when available.
Native fetch is optional — if it fails, scoring continues with
pressure-level data only.
Backtest on 11,431 native profiles (2026-04-11):
- Drop duct_usable_10/24/47ghz (always 1.0, no discrimination)
- Drop bulk_richardson (near-identical QSO vs baseline means)
- Document all feature results with signal strength assessment
- theta_e_jump is strongest native discriminator (44% lift)
- best_duct_freq and duct_thickness show clear physical signal
- Round grid-derived lat/lon in maybe_fill_latlon changeset step
- Format lat/lon to 6 decimal places on index table
- Migrate existing beacon data to 6 decimal precision
- Add comma separators to EIRP mW display (e.g. 10,000 mW)
- Extract shared add_commas helper for format_freq and format_mw
Height in feet doesn't need decimal precision. Migrates the DB
column, updates schema type, and strips trailing .0 from form
input so the integer cast succeeds.
- Add CommaNumber JS hook for live comma formatting while typing
frequency MHz in the beacon form
- Strip commas server-side before changeset validation
- Order beacon list by most recently added (desc inserted_at)
- Round lat/lon to 6 decimal places in changeset and display
- Round height_ft to integer in changeset and display
- Display coords at 6 decimal places on show page
Without -s, wgrib2 -lon only outputs msg:offset:lon=X,lat=Y,val=Z
with no variable name or level. The -s flag adds the short inventory
(d=DATE:VAR:LEVEL:...) so the parser can identify which variable
each value belongs to.
Points spread coast-to-coast created a ~476k cell bounding grid
(350 messages × 476k cells × 4 bytes ≈ 665 MB), causing OOM.
Switch to -lon which extracts values at specific lat/lon points
with text output. One wgrib2 call, one file scan, negligible
BEAM memory regardless of point geographic spread.
- Stream profile storage and score upsert instead of materializing
full 20k+ item lists (propagation_grid_worker, propagation.ex)
- GC between forecast hours and store/compute phases to reclaim
~400 MB of grid data between steps
- Single-pass field extraction in scorer.ex path_integrated_conditions
instead of 6 separate Enum traversals
- Eliminate intermediate merged map in fetch_grid by combining
merge + profile build into one pipe
- Fix UUID bug: bingenerate → generate in native grid worker
(same issue previously fixed in nexrad_worker)
The parallel download was holding all ~530MB of range responses in
memory before writing to disk. Now each range is fetched and written
one at a time, so only one chunk is in memory at a time.
Instead of holding ~530MB GRIB binary in BEAM memory, download
ranges directly to a temp file and run wgrib2 on it. Peak memory
drops from ~530MB to just HTTP chunk buffers.
Release.backtest_all, climatology, native_derive now enqueue an
AdminTaskWorker job on the new :admin queue and return immediately.
Progress visible in Oban Web at /admin/oban.
- Add `mix backtest --all` for consolidated pass/fail table across all features
- Add Backtest.consolidated_report/2 and to_consolidated_markdown/1
- Add Features.all_features/0 to auto-discover backtestable features
- Add `mix import_contest_logs` for bulk ARRL contest CSV import with dedup
- Fix hrrr_climatology to batch by (month, hour) to avoid query timeout
- Fix Repo.query! result pattern (Postgrex.Result, not tuple)
- Backtest reports for all Phase 1-6 features
Mix tasks that call app.start were also booting Oban's cron scheduler,
causing PropagationGridWorker and other cron jobs to fire during
backfills. Add Oban.pause_all_queues(Oban) immediately after app.start
in every mix task that only needs Repo access.
FrontalAnalysis module (Weather.FrontalAnalysis):
- detect_fronts/3 computes the Thermal Front Parameter (TFP) from
2D grids of surface temperature and pressure using Nx vectorized
ops. TFP = -nabla|nabla(theta)| . nabla(theta)/|nabla(theta)|.
Most negative values mark cold fronts.
- central_gradient/1 for 2D finite differences with edge handling
- nearest_front/3 finds closest front point with distance and bearing
- path_front_angle/2 computes angle between a QSO path and the
front (0 = parallel = good, 90 = crosses = dead)
Backtest feature stubs for distance_to_front and parallel_to_front
(return nil until the pipeline caches per-cell frontal features from
the hourly HRRR grid run). The FrontalAnalysis module itself is
tested and ready for integration.
NEXRAD spike docs also included in this commit.
NCEI ASOS 5-minute data client (Weather.NceiMetarClient):
- fetch/3 pulls per-station monthly .dat files from NCEI C00418
- parse/1 decodes the fixed-width METAR format including precise
T-group temperatures (T02110094 → 21.1/9.4°C)
- metar_5min_observations table: schema-identical to
surface_observations, separate table to avoid mixing cadences
Weather.recent_surface_obs/3 prefers 5-min data when available,
falls back to the hourly surface_observations table.
Data URL: https://www.ncei.noaa.gov/data/automated-surface-observing-system-five-minute/access/YYYY/MM/asos-5min-KXXX-YYYYMM.dat
Available back to 1996.
