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aa328d3ef7
* Implements #1399 * Reverting accidental change in generate_landmap.py * Changelog update * Import beacon data for Marianas. Co-authored-by: Dan Albert <dan@gingerhq.net>
89 lines
2.4 KiB
Python
89 lines
2.4 KiB
Python
from __future__ import annotations
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import json
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import argparse
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from pathlib import Path
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from typing import List, Tuple, Union, Dict
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from dcs.terrain import (
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Caucasus,
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PersianGulf,
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Syria,
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Nevada,
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Normandy,
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TheChannel,
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MarianaIslands,
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)
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from dcs import Mission
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Terrain = Union[
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Caucasus, PersianGulf, Syria, Nevada, Normandy, TheChannel, MarianaIslands
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]
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SAVE_PATH = Path("resources/frontlines")
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def validate_miz(file_path: Path) -> bool:
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return bool(file_path.suffix == ".miz" and file_path.exists())
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def validate_airports(airports: Tuple[int], terrain: Terrain):
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for airport in airports:
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if terrain.airport_by_id(airport) is None:
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print(f"Cannot load airport for invalid id {airport}")
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def load_files(files) -> List[Mission]:
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missions = []
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for file in files:
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if validate_miz(file):
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mission = Mission()
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mission.load_file(file)
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missions.append(mission)
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else:
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print(f"Error: {file} doesn't look like a valid mission file.")
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return missions
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def create_frontline_dict(mission: Mission) -> Dict[str, Dict]:
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frontline_dict = {}
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for group in mission.country("USA").vehicle_group:
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groupname = str(group.name).replace(group.name.id, "").replace(":", "")
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control_points = groupname.split("|")
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frontline_dict[groupname] = {
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"points": [(i.position.x, i.position.y) for i in group.points],
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"start_cp": int(control_points[0]),
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}
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return frontline_dict
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def process_missions(missions: List[Mission]) -> None:
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for mission in missions:
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frontline_dict = create_frontline_dict(mission)
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write_json(frontline_dict, mission.terrain.name.lower())
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def write_json(frontline_dict: Dict[str, Dict], terrain_name: str) -> None:
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with open(SAVE_PATH.joinpath(terrain_name + ".json"), "w") as file:
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json.dump(frontline_dict, file)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="Process a miz file to create json descriptions of multi-segment frontlines"
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)
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parser.add_argument(
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"files",
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metavar="N",
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type=Path,
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nargs="+",
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help="A list of space separated .miz files to extract frontlines from",
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)
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args = parser.parse_args()
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missions = load_files(args.files)
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process_missions(missions)
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# frontline_dict = create_frontline_dict(missions[0])
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print("Done")
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