feat(rover): end-to-end Calculate pipeline

This commit is contained in:
Graham McIntire 2026-04-25 16:15:31 -05:00
parent d80ca24e2e
commit 2e462b0697
No known key found for this signature in database
GPG key ID: F4ABF488E6029E59
2 changed files with 272 additions and 0 deletions

View file

@ -0,0 +1,172 @@
defmodule Microwaveprop.Rover.Compute do
@moduledoc """
End-to-end Calculate pipeline for the rover planner.
Given a home QTH, a list of selected fixed stations, a band/time/mode,
and drive/elevation constraints, returns the per-cell quality scores
plus the top 5 candidate parking spots.
"""
alias Microwaveprop.Propagation
alias Microwaveprop.Radio.Maidenhead
alias Microwaveprop.Rover.Aggregator
alias Microwaveprop.Rover.DriveTime
alias Microwaveprop.Rover.Elevation
alias Microwaveprop.Rover.LinkMargin
@avg_speed_kmh 65.0
@drive_penalty_db_per_hour 2.0
@elev_bonus_db_per_100m 1.0
@elev_bonus_cap_db 5.0
@top_n 5
@tier_excellent 10.0
@tier_good 3.0
@tier_marginal 0.0
@color_excellent "#16a34a"
@color_good "#eab308"
@color_marginal "#f97316"
@type run_args :: %{
home: %{lat: float(), lon: float(), elev_m: integer() | nil},
stations: [%{callsign: String.t(), lat: float(), lon: float(), selected: boolean()}],
band_mhz: non_neg_integer(),
valid_time: DateTime.t(),
mode: atom(),
max_drive_min: integer(),
min_elev_gain: integer()
}
@spec run(run_args(), keyword()) :: %{cells: [map()], top_candidates: [map()]}
def run(args, deps \\ []) do
scores_at = Keyword.get(deps, :scores_at, &Propagation.scores_at/3)
elev_lookup = Keyword.get(deps, :elev_lookup, &Elevation.lookup_many/1)
%{
home: home,
stations: stations,
band_mhz: band_mhz,
valid_time: valid_time,
mode: mode,
max_drive_min: max_drive_min,
min_elev_gain: min_elev_gain
} = args
selected_stations = Enum.filter(stations, & &1.selected)
radius_km = max_drive_min * @avg_speed_kmh / 60.0
bbox = bbox_around(home, radius_km)
raw_cells = scores_at.(band_mhz, valid_time, bbox)
# First filter: drive radius
in_radius =
Enum.filter(raw_cells, fn cell ->
DriveTime.haversine_km({home.lat, home.lon}, {cell.lat, cell.lon}) <= radius_km
end)
# Bulk elevation lookup for surviving cells
points = Enum.map(in_radius, &{&1.lat, &1.lon})
elev_map = elev_lookup.(points)
home_elev = home.elev_m || 0
cells =
in_radius
|> Enum.map(fn cell -> annotate_cell(cell, elev_map, home, home_elev, mode, selected_stations) end)
|> Enum.filter(&keep_cell?(&1, home_elev, min_elev_gain))
top_candidates =
cells |> Enum.sort_by(& &1.score, :desc) |> Enum.take(@top_n) |> Enum.map(&candidate_payload(&1, home))
%{cells: cells, top_candidates: top_candidates}
end
defp keep_cell?(nil, _home_elev, _min_gain), do: false
defp keep_cell?(%{elev_m: elev_m, score: score}, home_elev, min_gain) when is_integer(elev_m) do
elev_m - home_elev >= min_gain and score >= 0
end
defp keep_cell?(_, _, _), do: false
defp annotate_cell(cell, elev_map, home, home_elev, mode, stations) do
elev_m = Map.get(elev_map, {cell.lat, cell.lon})
case elev_m do
nil ->
nil
_ ->
margins = Enum.map(stations, fn _s -> LinkMargin.link_margin_from_score(cell.score, mode) end)
agg = Aggregator.cell_margin_db(margins)
case agg do
nil ->
nil
agg_db ->
dist_km = DriveTime.haversine_km({home.lat, home.lon}, {cell.lat, cell.lon})
elev_bonus = elev_bonus(elev_m, home_elev)
drive_penalty = drive_penalty(dist_km)
score = agg_db + elev_bonus - drive_penalty
%{
lat: cell.lat,
lon: cell.lon,
elev_m: elev_m,
score: score,
distance_km: dist_km,
tier_color: tier_color(score)
}
end
end
end
defp candidate_payload(cell, home) do
drive_min = DriveTime.drive_min(cell.distance_km)
bearing = DriveTime.bearing_compass({home.lat, home.lon}, {cell.lat, cell.lon})
grid = Maidenhead.from_latlon(cell.lat, cell.lon, 6)
%{
grid: grid,
lat: cell.lat,
lon: cell.lon,
elev_m: cell.elev_m,
drive_min: drive_min,
score: cell.score,
tier_color: cell.tier_color,
distance_km: cell.distance_km,
bearing_compass: bearing,
name: "#{grid}#{round(cell.distance_km)} km #{bearing} of home"
}
end
defp elev_bonus(elev_c, elev_home) do
diff = (elev_c - elev_home) / 100.0 * @elev_bonus_db_per_100m
diff |> max(0.0) |> min(@elev_bonus_cap_db)
end
defp drive_penalty(dist_km), do: dist_km / @avg_speed_kmh * @drive_penalty_db_per_hour
defp tier_color(score) do
cond do
score >= @tier_excellent -> @color_excellent
score >= @tier_good -> @color_good
score >= @tier_marginal -> @color_marginal
true -> @color_marginal
end
end
# Approximate bounding box. 1 deg lat ≈ 111 km; 1 deg lon ≈ 111·cos(lat) km.
defp bbox_around(%{lat: lat, lon: lon}, radius_km) do
dlat = radius_km / 111.0
dlon = radius_km / (111.0 * max(:math.cos(lat * :math.pi() / 180.0), 0.1))
%{
"south" => lat - dlat,
"north" => lat + dlat,
"west" => lon - dlon,
"east" => lon + dlon
}
end
end

View file

@ -0,0 +1,100 @@
defmodule Microwaveprop.Rover.ComputeTest do
use ExUnit.Case, async: true
alias Microwaveprop.Rover.Compute
defp build_grid(home_lat, home_lon) do
# 3x3 grid of cells around home spaced 0.1 deg apart
for dlat <- [-0.1, 0.0, 0.1], dlon <- [-0.1, 0.0, 0.1] do
%{
lat: Float.round(home_lat + dlat, 4),
lon: Float.round(home_lon + dlon, 4),
score: 80
}
end
end
test "returns top_candidates ordered by score desc with required fields" do
home = %{lat: 33.0, lon: -96.0, elev_m: 200}
stations = [%{callsign: "W5LUA", lat: 33.10, lon: -96.625, selected: true}]
grid = build_grid(home.lat, home.lon)
scores_at = fn _band, _t, _bbox -> grid end
elev_lookup = fn points -> Map.new(points, fn p -> {p, 250} end) end
args = %{
home: home,
stations: stations,
band_mhz: 10_000,
valid_time: ~U[2026-04-25 12:00:00Z],
mode: :ssb,
max_drive_min: 60,
min_elev_gain: 0
}
result = Compute.run(args, scores_at: scores_at, elev_lookup: elev_lookup)
assert is_map(result)
assert Map.has_key?(result, :cells)
assert Map.has_key?(result, :top_candidates)
assert is_list(result.cells)
assert length(result.top_candidates) <= 5
assert length(result.top_candidates) > 0
# Sorted by score desc.
scores = Enum.map(result.top_candidates, & &1.score)
assert scores == Enum.sort(scores, :desc)
# Required candidate fields.
cand = hd(result.top_candidates)
for key <- [
:grid,
:lat,
:lon,
:elev_m,
:drive_min,
:score,
:tier_color,
:distance_km,
:bearing_compass,
:name
] do
assert Map.has_key?(cand, key), "expected candidate to have key #{inspect(key)}"
end
assert is_binary(cand.grid)
assert is_binary(cand.tier_color)
assert is_binary(cand.bearing_compass)
assert is_binary(cand.name)
end
test "filters cells failing min_elev_gain" do
home = %{lat: 33.0, lon: -96.0, elev_m: 500}
stations = [%{callsign: "W5LUA", lat: 33.1, lon: -96.6, selected: true}]
grid = build_grid(home.lat, home.lon)
# All elevations below home — nothing should pass min_elev_gain=200.
scores_at = fn _band, _t, _bbox -> grid end
elev_lookup = fn points -> Map.new(points, fn p -> {p, 100} end) end
result =
Compute.run(
%{
home: home,
stations: stations,
band_mhz: 10_000,
valid_time: ~U[2026-04-25 12:00:00Z],
mode: :ssb,
max_drive_min: 60,
min_elev_gain: 200
},
scores_at: scores_at,
elev_lookup: elev_lookup
)
assert result.cells == []
assert result.top_candidates == []
end
end