75 lines
2.5 KiB
Python
75 lines
2.5 KiB
Python
import numpy as np
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import matplotlib.pyplot as plt
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from game import Game
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from tqdm import tqdm
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from os import environ
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environ['PYGAME_HIDE_SUPPORT_PROMPT'] = '1'
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if __name__ == '__main__':
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n_episodes = 1000
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game_len = 10000
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figure_file = 'plots/score.png'
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best_score = 0
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avg_score = 0
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game = Game()
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agent_list = []
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exp_points_list = []
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score_history = np.zeros(
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shape=(len(game.level.player_sprites), n_episodes, ))
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best_score = np.zeros(len(game.level.player_sprites))
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avg_score = np.zeros(len(game.level.player_sprites))
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for i in tqdm(range(n_episodes)):
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# TODO: Make game.level.reset_map() so we don't __init__ everything all the time (such a waste)
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if i != 0:
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game.level.__init__(reset=True)
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# TODO: Make game.level.reset_map() so we don't pull out and load the agent every time (There is -definitevly- a better way)
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for player in game.level.player_sprites:
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for agent in agent_list:
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player.agent = agent_list[player.player_id]
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player.stats.exp = score_history[player.player_id][i-1]
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agent_list = []
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for j in range(game_len):
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if not game.level.done:
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game.run()
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game.calc_score()
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if (j == game_len-1 or game.level.done) and game.level.enemy_sprites != []:
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for player in game.level.player_sprites:
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for enemy in game.level.enemy_sprites:
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player.stats.exp *= .95
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else:
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break
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for player in game.level.player_sprites:
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agent_list.append(player.agent)
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exp_points = player.stats.exp
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score_history[player.player_id][i] = exp_points
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avg_score[player.player_id] = np.mean(
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score_history[player.player_id])
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if avg_score[player.player_id] >= best_score[player.player_id]:
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player.agent.save_models()
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best_score[player.player_id] = avg_score[player.player_id]
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print(
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f"\nCumulative score for player {player.player_id}:\
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{score_history[0][i]}\
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\nAverage score for player {player.player_id}:\
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{avg_score[player.player_id]}\
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\nBest score for player {player.player_id}:\
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{best_score[player.player_id]}")
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plt.plot(score_history[0])
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game.quit()
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plt.show()
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