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Add weather satellite auto-scheduler, polar plot, ground track map, and rtlamr Docker support
- Fix SDR device stuck claimed on capture failure via on_complete callback - Improve SatDump output parsing to emit all lines (throttled 2s) for real-time feedback - Extract shared pass prediction into utils/weather_sat_predict.py with trajectory/ground track support - Add auto-scheduler (utils/weather_sat_scheduler.py) using threading.Timer for unattended captures - Add scheduler API endpoints (enable/disable/status/passes/skip) with SSE event notifications - Add countdown timer (D/H/M/S) with imminent/active glow states - Add 24h timeline bar with colored pass markers and current-time cursor - Add canvas polar plot showing az/el trajectory arc with cardinal directions - Add Leaflet ground track map with satellite path and observer marker - Restructure to 3-column layout (passes | polar+map | gallery) with responsive stacking - Add auto-schedule toggle in strip bar and sidebar - Add rtlamr (Go utility meter decoder) to Dockerfile Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Mitch Ross
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"""Weather satellite pass prediction utility.
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Shared prediction logic used by both the API endpoint and the auto-scheduler.
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"""
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from __future__ import annotations
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import datetime
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from typing import Any
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from utils.logging import get_logger
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from utils.weather_sat import WEATHER_SATELLITES
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logger = get_logger('intercept.weather_sat_predict')
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def predict_passes(
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lat: float,
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lon: float,
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hours: int = 24,
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min_elevation: float = 15.0,
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include_trajectory: bool = False,
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include_ground_track: bool = False,
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) -> list[dict[str, Any]]:
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"""Predict upcoming weather satellite passes for an observer location.
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Args:
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lat: Observer latitude (-90 to 90)
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lon: Observer longitude (-180 to 180)
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hours: Hours ahead to predict (1-72)
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min_elevation: Minimum max elevation in degrees (0-90)
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include_trajectory: Include az/el trajectory points (30 points)
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include_ground_track: Include lat/lon ground track points (60 points)
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Returns:
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List of pass dicts sorted by start time.
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Raises:
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ImportError: If skyfield is not installed.
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"""
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from skyfield.api import load, wgs84, EarthSatellite
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from skyfield.almanac import find_discrete
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from data.satellites import TLE_SATELLITES
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ts = load.timescale()
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observer = wgs84.latlon(lat, lon)
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t0 = ts.now()
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t1 = ts.utc(t0.utc_datetime() + datetime.timedelta(hours=hours))
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all_passes: list[dict[str, Any]] = []
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for sat_key, sat_info in WEATHER_SATELLITES.items():
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if not sat_info['active']:
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continue
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tle_data = TLE_SATELLITES.get(sat_info['tle_key'])
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if not tle_data:
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continue
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satellite = EarthSatellite(tle_data[1], tle_data[2], tle_data[0], ts)
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def above_horizon(t, _sat=satellite):
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diff = _sat - observer
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topocentric = diff.at(t)
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alt, _, _ = topocentric.altaz()
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return alt.degrees > 0
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above_horizon.step_days = 1 / 720
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try:
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times, events = find_discrete(t0, t1, above_horizon)
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except Exception:
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continue
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i = 0
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while i < len(times):
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if i < len(events) and events[i]: # Rising
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rise_time = times[i]
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set_time = None
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for j in range(i + 1, len(times)):
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if not events[j]: # Setting
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set_time = times[j]
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i = j
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break
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else:
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i += 1
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continue
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if set_time is None:
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i += 1
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continue
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duration_seconds = (
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set_time.utc_datetime() - rise_time.utc_datetime()
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).total_seconds()
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duration_minutes = round(duration_seconds / 60, 1)
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# Calculate max elevation and trajectory
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max_el = 0.0
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max_el_az = 0.0
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trajectory: list[dict[str, float]] = []
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num_traj_points = 30
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for k in range(num_traj_points):
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frac = k / (num_traj_points - 1)
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t_point = ts.utc(
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rise_time.utc_datetime()
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+ datetime.timedelta(seconds=duration_seconds * frac)
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)
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diff = satellite - observer
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topocentric = diff.at(t_point)
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alt, az, _ = topocentric.altaz()
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if alt.degrees > max_el:
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max_el = alt.degrees
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max_el_az = az.degrees
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if include_trajectory:
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trajectory.append({
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'el': float(max(0, alt.degrees)),
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'az': float(az.degrees),
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})
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if max_el < min_elevation:
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i += 1
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continue
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# Rise/set azimuths
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rise_topo = (satellite - observer).at(rise_time)
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_, rise_az, _ = rise_topo.altaz()
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set_topo = (satellite - observer).at(set_time)
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_, set_az, _ = set_topo.altaz()
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pass_data: dict[str, Any] = {
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'id': f"{sat_key}_{rise_time.utc_datetime().strftime('%Y%m%d%H%M')}",
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'satellite': sat_key,
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'name': sat_info['name'],
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'frequency': sat_info['frequency'],
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'mode': sat_info['mode'],
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'startTime': rise_time.utc_datetime().strftime('%Y-%m-%d %H:%M UTC'),
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'startTimeISO': rise_time.utc_datetime().isoformat(),
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'endTimeISO': set_time.utc_datetime().isoformat(),
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'maxEl': round(max_el, 1),
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'maxElAz': round(max_el_az, 1),
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'riseAz': round(rise_az.degrees, 1),
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'setAz': round(set_az.degrees, 1),
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'duration': duration_minutes,
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'quality': (
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'excellent' if max_el >= 60
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else 'good' if max_el >= 30
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else 'fair'
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),
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}
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if include_trajectory:
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pass_data['trajectory'] = trajectory
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if include_ground_track:
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ground_track: list[dict[str, float]] = []
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for k in range(60):
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frac = k / 59
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t_point = ts.utc(
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rise_time.utc_datetime()
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+ datetime.timedelta(seconds=duration_seconds * frac)
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)
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geocentric = satellite.at(t_point)
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subpoint = wgs84.subpoint(geocentric)
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ground_track.append({
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'lat': float(subpoint.latitude.degrees),
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'lon': float(subpoint.longitude.degrees),
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})
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pass_data['groundTrack'] = ground_track
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all_passes.append(pass_data)
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i += 1
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all_passes.sort(key=lambda p: p['startTimeISO'])
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return all_passes
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