mirror of
https://github.com/dcs-liberation/dcs_liberation.git
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0a416ab758
This improves the AI behavior by choosing the stances non-randomly: * Breakthrough will be used if the base is expected to be capturable and the coalition outnumbers the enemy by 20%. * Elimination will be used if the coalition has at least as many units as the enemy. * Defensive will be used if the coalition has at least half as many units as the enemy. * Retreat will be used if the coalition is significantly outnumbers. This also exposes the option to the player.
117 lines
3.9 KiB
Python
117 lines
3.9 KiB
Python
from dataclasses import dataclass, field
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from datetime import timedelta
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from enum import Enum, unique
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from typing import Dict, Optional, Any
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from dcs.forcedoptions import ForcedOptions
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@unique
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class AutoAtoBehavior(Enum):
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Disabled = "Disabled"
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Never = "Never assign player pilots"
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Default = "No preference"
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Prefer = "Prefer player pilots"
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@dataclass
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class Settings:
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# Difficulty settings
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player_skill: str = "Good"
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enemy_skill: str = "Average"
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ai_pilot_levelling: bool = True
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enemy_vehicle_skill: str = "Average"
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map_coalition_visibility: ForcedOptions.Views = ForcedOptions.Views.All
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labels: str = "Full"
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only_player_takeoff: bool = True # Legacy parameter do not use
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night_disabled: bool = False
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external_views_allowed: bool = True
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supercarrier: bool = False
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generate_marks: bool = True
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manpads: bool = True
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version: Optional[str] = None
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player_income_multiplier: float = 1.0
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enemy_income_multiplier: float = 1.0
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#: Feature flag for squadron limits.
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enable_squadron_pilot_limits: bool = False
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#: The maximum number of pilots a squadron can have at one time. Changing this after
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#: the campaign has started will have no immediate effect; pilots already in the
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#: squadron will not be removed if the limit is lowered and pilots will not be
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#: immediately created if the limit is raised.
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squadron_pilot_limit: int = 12
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#: The number of pilots a squadron can replace per turn.
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squadron_replenishment_rate: int = 4
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default_start_type: str = "Cold"
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# Mission specific
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desired_player_mission_duration: timedelta = timedelta(minutes=60)
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# Campaign management
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automate_runway_repair: bool = False
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automate_front_line_reinforcements: bool = False
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automate_aircraft_reinforcements: bool = False
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automate_front_line_stance: bool = True
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restrict_weapons_by_date: bool = False
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disable_legacy_aewc: bool = True
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disable_legacy_tanker: bool = True
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generate_dark_kneeboard: bool = False
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invulnerable_player_pilots: bool = True
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auto_ato_behavior: AutoAtoBehavior = AutoAtoBehavior.Default
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auto_ato_player_missions_asap: bool = True
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# Performance oriented
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perf_red_alert_state: bool = True
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perf_smoke_gen: bool = True
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perf_smoke_spacing = 1600
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perf_artillery: bool = True
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perf_moving_units: bool = True
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perf_infantry: bool = True
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perf_destroyed_units: bool = True
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reserves_procurement_target: int = 10
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# Performance culling
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perf_culling: bool = False
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perf_culling_distance: int = 100
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perf_do_not_cull_carrier = True
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# LUA Plugins system
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plugins: Dict[str, bool] = field(default_factory=dict)
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# Cheating
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show_red_ato: bool = False
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enable_frontline_cheats: bool = False
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enable_base_capture_cheat: bool = False
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never_delay_player_flights: bool = False
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@staticmethod
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def plugin_settings_key(identifier: str) -> str:
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return f"plugins.{identifier}"
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def initialize_plugin_option(self, identifier: str, default_value: bool) -> None:
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try:
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self.plugin_option(identifier)
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except KeyError:
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self.set_plugin_option(identifier, default_value)
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def plugin_option(self, identifier: str) -> bool:
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return self.plugins[self.plugin_settings_key(identifier)]
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def set_plugin_option(self, identifier: str, enabled: bool) -> None:
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self.plugins[self.plugin_settings_key(identifier)] = enabled
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def __setstate__(self, state: dict[str, Any]) -> None:
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# __setstate__ is called with the dict of the object being unpickled. We
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# can provide save compatibility for new settings options (which
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# normally would not be present in the unpickled object) by creating a
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# new settings object, updating it with the unpickled state, and
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# updating our dict with that.
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new_state = Settings().__dict__
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new_state.update(state)
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self.__dict__.update(new_state)
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