prop/lib/microwaveprop/rover/compute.ex

201 lines
6.1 KiB
Elixir

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()],
warnings: [String.t()]
}
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))
warnings = build_warnings(raw_cells, in_radius, elev_map, cells)
%{cells: cells, top_candidates: top_candidates, warnings: warnings}
end
defp build_warnings(raw_cells, in_radius, elev_map, cells) do
[]
|> add_warning_if(raw_cells == [], "No HRRR score grid available for this band/time.")
|> add_warning_if(in_radius == [], "No score grid cells within the drive radius.")
|> add_warning_if(
in_radius != [] and elev_map_all_nil?(elev_map),
"Elevation tiles unavailable (SRTM not mounted); ranking ignores elevation."
)
|> add_warning_if(
in_radius != [] and cells == [],
"All cells filtered out by score/elevation thresholds."
)
end
defp add_warning_if(list, true, msg), do: list ++ [msg]
defp add_warning_if(list, false, _msg), do: list
defp elev_map_all_nil?(elev_map) do
elev_map != %{} and Enum.all?(elev_map, fn {_k, v} -> is_nil(v) end)
end
defp keep_cell?(nil, _home_elev, _min_gain), do: false
defp keep_cell?(%{score: score, elev_m: elev_m}, home_elev, min_gain) do
# Cells with unknown elevation (no SRTM tile) are kept; elev gain
# filter only applies when we actually know the cell elevation.
elev_ok? = is_nil(elev_m) or elev_m - home_elev >= min_gain
elev_ok? 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})
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
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, 10)
%{
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(nil, _elev_home), do: 0.0
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