Subtle hint appears in top-right corner (desktop only) when the
detail panel is open. Fades in when panel shows, fades out on ESC.
Hidden on mobile where the X button is more appropriate.
Extract GridSquare class and updateGridOverlay from propagation_map_hook
into shared maidenhead_grid.js module. Rover map now shows the same
zoom-adaptive Maidenhead grid overlay as the main /map page — red
rectangles with labels that switch between field (2-char) and square
(4-char) based on zoom level. Updates on pan/zoom.
Toggle button hides/shows the grid overlay.
- Toggle button for Maidenhead grid overlay (on by default)
- Coverage candidates now at 0.25° resolution (~28 km) instead of
2°×1° Maidenhead grids, matching HRRR propagation grid density
- Coverage rectangles render as 0.25° cells for finer detail
- Grid overlay is separate from coverage coloring
Rewrites rover planner to automatically color the map after stations
are entered. No manual stop selection needed — the system evaluates
every Maidenhead grid in range and scores them by:
- SRTM terrain analysis to each station (diffraction loss, LOS verdict)
- HRRR propagation forecast (ducting, refractivity, atmospheric conditions)
- Distance to stations vs band range limits
- Propagation boost: good conditions (score 80+) make blocked paths
viable through ducting, matching the app's core beyond-LOS prediction
Coverage score formula: boosted path quality 30% + propagation 30%
+ distance 20% + station count 20%. Colored grid squares on the map
show best (green) to worst (red) operating positions.
Sidebar shows top 10 grids ranked with: workable station count,
propagation score, best operating hour, 18-hour forecast sparkline.
Click a grid for per-station detail: distance, terrain verdict,
diffraction loss.
URL stores stations + band for sharing: /rover?stations=W5ISP,K5TR&band=10000
Switch from getCurrentPosition (which looped via push_patch) to
watchPosition with a 60-second throttle. Break the server-side
request_gps loop by skipping re-request when coords already exist.
Interactive map-based tool for planning rover operating positions.
Rovers enter stationary stations they want to work, then click the
map to evaluate candidate operating grids.
Features:
- Add stationary stations by callsign or grid square
- Click map to add operating positions (snaps to Maidenhead grid)
- Async SRTM terrain analysis: each stop computes terrain profile
to every station, shows CLEAR/BLOCKED verdict + diffraction loss
- Terrain lines on map: green=workable, red=blocked, dashed=marginal
- Propagation score and 18-hour forecast sparkline per stop
- Route summary: driving distance, unique grid-station pairs
- Band selector affects range limits and propagation scores
- Numbered waypoint markers with score-colored backgrounds
New files:
- Geo module (shared haversine/bearing, used by PathLive too)
- RoverLive with fullscreen map + sidebar
- RoverMap JS hook with grid overlay, station/stop markers, route line
- Nav links in header and map control panel
- "My Location" button with text label (was just an icon)
- Two share buttons after results:
- "Copy Link" — fixed coordinates, exact result
- "Copy Link (use viewer's GPS)" — source=gps, dynamic per viewer
- CopyLink JS hook copies full URL to clipboard with "Copied!" feedback
Bookmarking /path?source=gps&destination=K5TR&band=10000 will use
the viewer's device GPS to resolve the source location on load.
The LocateMe hook handles both button clicks and server-pushed
request_gps events. Once coords are resolved, the URL is updated
with actual lat,lon and calculation runs automatically.
- TX/RX height in feet (converted to meters for terrain analysis)
- TX power in dBm with mW equivalent display
- TX gain and RX gain (dBi) inputs
- Power budget: TX power + TX gain - feed loss = EIRP - path loss
+ RX gain = RX power vs CW sensitivity = margin
- Loss budget: FSPL + gaseous (O2+H2O) + diffraction + rain
with per-km gas rate detail
- GPS "Locate Me" button using browser geolocation API
- Lat,lon coordinate pairs accepted as input
- Weather displayed in F with C below
- LiveStash preserves form inputs across page reloads
- Terrain cross-section with beam line and Fresnel zone
Collapsible control panel with hamburger toggle, detail panel as
bottom sheet, compact legend moved to top-right, and scaled timeline
buttons for narrow viewports.
Without a distance limit, the BFS would expand across the entire grid
when conditions were broadly favorable, producing a polygon covering
most of CONUS.
- Mark duct closest to endpoint elevations as likely signal path
- Likely duct drawn with solid borders, bold label, stronger fill
- Other ducts shown dimmed with dashed borders
- Fix path info layout: table columns prevent El wrapping
- Surface observations as compact table, limited to 5 nearest stations
- Use all HRRR profiles along path (start, mid, end) for duct detection
- Fall back to sounding ducts when HRRR too coarse to detect layers
- Merge overlapping ducts, show top 3 strongest with source labels
- Limit surface observations to 5 closest stations along path
- Compact solar conditions as inline row
- Compact band/mode/distance info line
- Fix button text to "Flag as Invalid"
- Overlay HRRR duct layers on elevation profile chart (green bands)
- Add flagged_invalid field to contacts with toggle button on detail page
- Fix prune_old_grid_profiles to only delete 0.125° grid profiles,
preserving QSO-linked HRRR data at arbitrary positions
- Auto-enqueue HRRR fetch when viewing contact without HRRR data (<48h)
- Compact solar conditions and contact details layout
- Add band/mode/distance info line to elevation profile section
- Leaflet map on contact detail pages showing both station locations
- SRTM elevation profile with Chart.js: terrain, LOS, Fresnel zone
- Path info: distance, azimuth, elevation angle in both directions
- Compact 4-column grid layout for contact details
- Contact map page with all contacts plotted
- Rename QSOs to Contacts in page header
- Wrap algo page in standard layout
- All menus and UI text now say Contacts instead of QSOs
- Add 68, 122, 134, 241 GHz bands to submit form and validation
- Add info box on submit page explaining why contacts matter
- Larger submit button with icon
- Make HRRR partition migration idempotent for partial re-runs
The ML model undervalues conditions outside Aug/Sep training data
(e.g. April with excellent factors scored 37/100). Algorithm's
physics-based factors handle unseen seasons correctly.
- Algorithm is primary scorer, ML infrastructure kept for iteration
- Remove unused ML grid worker code path
- Add client-side propagation reach: BFS flood-fill from clicked point
through contiguous cells with score >= 50, drawn as convex hull polygon
- point_detail response includes forecast array (score per valid_time)
- SVG sparkline shows score trend across all forecast hours
- Trend indicator: Improving/Declining/Steady based on first vs last score
- Add covering index (band_mhz, lat, lon, valid_time) INCLUDE (score) for
point_forecast queries
- HrrrClient.hrrr_url accepts forecast_hour param (wrfsfcfHH.grib2)
- PropagationGridWorker fetches all 19 forecast hours per run
- Propagation.scores_at/3 queries scores at specific valid_time
- Propagation.available_valid_times/1 returns all forecast times for timeline
- Pruning keeps scores with valid_time >= now - 2h (forecast-aware)
- MapLive: select_time event, timeline data pushed to JS
- JS: forecast timeline bar at bottom of map with clickable hour buttons
- PubSub broadcast sends list of valid_times instead of single time
- Add phx-update="ignore" to detail-panel so LiveView patches don't wipe it
- Re-request point_detail after scores update to refresh with new data
- Range circles persist across updates since they're on a separate layer
- Viewshed uses propagation score to set max range (ducting/NLOS distance)
- Terrain checked within radio horizon; clear paths get full atmospheric range
- Detail panel moves from map popup to sidebar for better visibility
- Panel shows instantly on click with loading state
- Dark opaque background for readability over map
- Factor analysis section explains each score with contextual descriptions
Replace generic range circles with actual LOS coverage polygon computed
from SRTM elevation data. Casts 180 rays (every 2 degrees) from the
clicked point, runs Fresnel/diffraction analysis on each, and renders
the reachable area as a Leaflet polygon.
- Viewshed module with haversine forward, terrain sweep, async compute
- Antenna height control (default 8 ft) in map panel
- LiveView start_async/handle_async for non-blocking computation
- Remove signal icon from band selector
- Remove factors from heatmap scores, fetch on-demand via point_detail
- Pre-encode initial scores JSON once instead of per-render
- Don't store scores in socket assigns (reduce memory)
- Pre-calculate RGBA color lookup table for canvas rendering
- Batch fillStyle changes, hoist math out of inner loop
- Show topbar immediately on data requests (no 300ms delay)
- Port grid square rendering from gridmap-web with toggle control
- Consolidate band selector, grid toggle, data timestamp, and links
into unified control panel
- Add "How this works" (/algo) and "Submit a QSO" (/submit) links
- Add back-to-map link on algo page
- Darken range circles for visibility over propagation overlay
- Fix popup blocking double-click zoom with pointer-events passthrough
- Prevent control panel from intercepting map click/scroll events
- Scores now include factors and valid_time in the viewport query,
eliminating the server round-trip for popups
- Click shows two range circles: solid inner (typical range) and
dashed outer (max estimated range), colored by score tier
- Circles disappear when popup closes
- Band info pushed to client on band switch for accurate range estimates
Click anywhere on the propagation map to see a detailed popup with:
- Overall score and tier label with color
- Estimated range for the selected band (CW mode)
- All 9 scoring factors with visual bar charts, individual scores,
and weight percentages
- Grid point coordinates and data timestamp
Factors are displayed in weight order so users can immediately see
which atmospheric conditions are driving the prediction.
