149 lines
4.2 KiB
Python
149 lines
4.2 KiB
Python
from collections.abc import Iterable
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from dataclasses import dataclass
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from datetime import timedelta
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from functools import total_ordering
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from io import StringIO
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import logging
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from math import nan
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from pathlib import Path
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from typing import Self
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import pandas
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import requests_cache
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from xdg_base_dirs import xdg_config_home
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FREQUENCY_COLUMNS = ["uplink", "downlink", "beacon"]
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DEFAULT_QTH = "Home.qth"
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# TODO: check this on windows
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GPREDICT_CONFIG_DIR = xdg_config_home() / "Gpredict"
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GPREDICT_MODULE_DEST = GPREDICT_CONFIG_DIR / "modules"
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def is_2m(freq):
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return (144 <= freq) & (freq <= 148)
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def is_70cm(freq):
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return (420 <= freq) & (freq <= 450)
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def is_vu(freq):
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return is_2m(freq) | is_70cm(freq)
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@dataclass(frozen=True)
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class FrequencyRange:
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start: float
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stop: float
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# Custom comparison operators for if the range is inside a frequency band
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def __le__(self, freq: float):
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return self.start <= freq and self.stop <= freq
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def __ge__(self, freq: float):
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return self.start >= freq and self.stop >= freq
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def active_frequency(cell) -> float | FrequencyRange:
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cell = str(cell)
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if "-" in cell:
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# Frequency range (e.g. SSB transponder?)
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a, _sep, b = cell.partition("-")
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try:
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return FrequencyRange(float(a), float(b))
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except ValueError:
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logging.warning("Unable to parse frequency: %r, ignoring", cell)
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return nan
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options = str(cell).split("/")
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if len(options) == 1:
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selection = options[0].removesuffix("*")
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else:
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selection = next((o.removesuffix("*") for o in options if o.endswith("*")), nan)
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try:
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return float(selection)
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except ValueError:
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logging.warning("Unable to parse frequency: %r, ignoring", selection)
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return nan
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def get_active_satellites() -> pandas.DataFrame:
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session = requests_cache.CachedSession(
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expire_after=timedelta(days=1),
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)
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session.headers["User-Agent"] = (
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"make_configs (adam@gaussian.dev;https://github.com/K9API/logbook)"
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)
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amsat_csv = session.get(
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"https://raw.githubusercontent.com/palewire/amateur-satellite-database/refs/heads/main/data/amsat-all-frequencies.csv"
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)
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amsat_csv.raise_for_status()
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amsat_db = pandas.read_csv(StringIO(amsat_csv.text))
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for c in FREQUENCY_COLUMNS:
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amsat_db[c] = amsat_db[c].map(active_frequency)
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satnogs_csv = session.get(
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"https://raw.githubusercontent.com/palewire/amateur-satellite-database/refs/heads/main/data/satnogs.csv"
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)
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satnogs_csv.raise_for_status()
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satnogs_db = pandas.read_csv(StringIO(satnogs_csv.text))
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satnogs_alive_ids = set(satnogs_db.sat_id.where(satnogs_db.status == "alive"))
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any_frequency_listed = amsat_db[FREQUENCY_COLUMNS].notna().any(axis="columns")
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return amsat_db[
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amsat_db.status.isin(["active", "operational"])
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& amsat_db.satnogs_id.isin(satnogs_alive_ids)
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& any_frequency_listed
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]
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def make_gpredict_module(satellite_ids: Iterable) -> str:
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satellites = ";".join(str(int(i)) for i in satellite_ids)
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return f"""[GLOBAL]\nSATELLITES={satellites}\nQTHFILE={DEFAULT_QTH}\n"""
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def save_gpredict_module(name: str, dest_dir: Path, satellite_ids: Iterable):
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with (dest_dir / f"{name}.mod").open("w+") as f:
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f.write(make_gpredict_module(satellite_ids))
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def main():
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logging.basicConfig(level=logging.INFO)
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pandas.set_option("future.no_silent_downcasting", True)
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active_db = get_active_satellites()
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all_beacons = active_db[is_vu(active_db.beacon)]
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save_gpredict_module(
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"AMSAT_All_Beacons",
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GPREDICT_MODULE_DEST,
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all_beacons.norad_id.drop_duplicates().dropna(),
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)
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all_fm = active_db[active_db["mode"].str.contains("FM").fillna(False)]
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save_gpredict_module(
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"AMSAT_All_Repeaters",
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GPREDICT_MODULE_DEST,
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all_fm.norad_id.drop_duplicates().dropna(),
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)
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all_digi = active_db[
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active_db["mode"].str.contains("APRS").fillna(False)
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| active_db["mode"].str.contains("Digipeater").fillna(False)
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]
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save_gpredict_module(
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"AMSAT_All_Digi",
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GPREDICT_MODULE_DEST,
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all_digi.norad_id.drop_duplicates().dropna(),
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)
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if __name__ == "__main__":
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main()
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