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import numpy as np |
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from dataclasses import dataclass |
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import param_ |
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from settings import Settings |
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from drone import Drone |
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@dataclass |
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class Playground: |
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""" |
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This is a cylindrical 3D-env where blue drones defend a central zone from the attack of red drones |
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the playground manages also the interactions between foe-drones such as the firing |
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""" |
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perimeter = Settings.perimeter |
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perimeter_z = Settings.perimeter_z |
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groundzone = Settings.groundzone |
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env: object |
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blue_drones: [Drone] |
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red_drones: [Drone] |
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def __post_init__(self): |
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self.blues_have_fired_reds = np.zeros(shape=(len(self.blue_drones), |
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len(self.red_drones)), dtype=int) |
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self.reds_have_fired_blues = np.zeros(shape=(len(self.red_drones), |
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len(self.blue_drones)), dtype=int) |
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self.blue_shots_to_kill = param_.DRONE_MODELS[param_.DRONE_MODEL[True]]['duration_to_neutralisation'] |
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self.red_shots_to_kill = param_.DRONE_MODELS[param_.DRONE_MODEL[False]]['duration_to_neutralisation'] |
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self.blue_shots_to_kill //= param_.STEP |
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self.red_shots_to_kill //= param_.STEP |
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self.distance_blue_shot = param_.DRONE_MODELS[param_.DRONE_MODEL[True]]['distance_to_neutralisation'] |
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self.distance_red_shot = param_.DRONE_MODELS[param_.DRONE_MODEL[False]]['distance_to_neutralisation'] |
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def reset(self): |
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self.blues_have_fired_reds[...] = 0 |
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self.reds_have_fired_blues[...] = 0 |
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def get_observation(self): |
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return self.blues_have_fired_reds / self.blue_shots_to_kill, \ |
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self.reds_have_fired_blues / self.red_shots_to_kill |
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def step(self): |
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""" |
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determines who has fired who, and who is dead in the end |
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:return: Tuple with list of Blue and Reds dead. (if a blue or a red is dead, the sequence is over) |
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""" |
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blues_fire_reds = np.array([[blue.fires_(red) for red in self.red_drones] for blue in self.blue_drones]) |
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reds_fire_blues = np.array([[red.fires_(blue) for blue in self.blue_drones] for red in self.red_drones]) |
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self.blues_have_fired_reds *= blues_fire_reds |
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self.reds_have_fired_blues *= reds_fire_blues |
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self.blues_have_fired_reds += blues_fire_reds |
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self.reds_have_fired_blues += reds_fire_blues |
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red_deads = np.unique(np.argwhere(self.blues_have_fired_reds >= self.blue_shots_to_kill).T[1]) |
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blue_deads = np.unique(np.argwhere(self.reds_have_fired_blues >= self.red_shots_to_kill).T[1]) |
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for drone_id in blue_deads: |
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self.blue_drones[drone_id].is_killed(is_blue=True) |
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for drone_id in red_deads: |
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self.red_drones[drone_id].is_killed(is_blue=False) |
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blue_drones = [drone for drone in self.blue_drones if drone.is_alive] |
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red_drones = [drone for drone in self.red_drones if drone.is_alive] |
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bf_obs, rf_obs = self.get_observation() |
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bf_reward = rf_reward = 0 |
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remaining_blues, remaining_reds = len(blue_drones), len(red_drones), |
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blue_shots, red_shots = len(blue_deads), len(red_deads) |
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if blue_shots + red_shots > 0: |
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print('someone is killed: {0} blues and {1} reds'.format(blue_shots, red_shots)) |
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return bf_obs, bf_reward, remaining_blues, blue_shots, rf_obs, rf_reward, remaining_reds, red_shots |
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