pneuma-pygame/main.py

import numpy as np
import matplotlib.pyplot as plt

from game import Game
from tqdm import tqdm

from os import environ
environ['PYGAME_HIDE_SUPPORT_PROMPT'] = '1'


if __name__ == '__main__':

    n_episodes = 1000
    game_len = 10000

    figure_file = 'plots/score.png'
    best_score = 0
    avg_score = 0

    game = Game()

    agent_list = []
    exp_points_list = []
    score_history = np.zeros(
        shape=(len(game.level.player_sprites), n_episodes, ))
    best_score = np.zeros(len(game.level.player_sprites))
    avg_score = np.zeros(len(game.level.player_sprites))
    for i in tqdm(range(n_episodes)):
        # TODO: Make game.level.reset_map() so we don't __init__ everything all the time (such a waste)
        if i != 0:
            game.level.__init__(reset=True)
        # TODO: Make game.level.reset_map() so we don't pull out and load the agent every time (There is -definitevly- a better way)
            for player in game.level.player_sprites:
                for agent in agent_list:
                    player.agent = agent_list[player.player_id]
                    player.stats.exp = score_history[player.player_id][i-1]

        agent_list = []

        for j in range(game_len):
            if not game.level.done:

                game.run()
                game.calc_score()

                if (j == game_len-1 or game.level.done) and game.level.enemy_sprites != []:
                    for player in game.level.player_sprites:
                        for enemy in game.level.enemy_sprites:
                            player.stats.exp *= .95
            else:
                break

        for player in game.level.player_sprites:
            agent_list.append(player.agent)
            exp_points = player.stats.exp
            score_history[player.player_id][i] = exp_points
            avg_score[player.player_id] = np.mean(
                score_history[player.player_id])
            if avg_score[player.player_id] >= best_score[player.player_id]:
                player.agent.save_models()
                best_score[player.player_id] = avg_score[player.player_id]

            print(
                f"\nCumulative score for player {player.player_id}:\
                    {score_history[0][i]}\
                    \nAverage score for player {player.player_id}:\
                    {avg_score[player.player_id]}\
                    \nBest score for player {player.player_id}:\
                    {best_score[player.player_id]}")

    plt.plot(score_history[0])

    game.quit()

    plt.show()