80 lines
2.5 KiB
Python
80 lines
2.5 KiB
Python
"""
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sb策略和真人收益对比，其中分别比较sb0,sb0.2,所有人平均，获胜者平均，获胜者最高，统计10-15共6组
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"""
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import json
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import numpy as np
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import math
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from matplotlib import pyplot as plt
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from island.matches import Matches
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from island.match import Match
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human_avg = np.zeros(6)
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human_count = np.zeros(6)
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winner_avg = np.zeros(6)
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winner_count = np.zeros(6)
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winner_max = np.zeros(6)
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"""
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omega = np.ceil(5/(3-(x*2.6)))
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fb0 = 5-omega*(3-(x*2.6+(1-x)*4.5))
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fb = fb0 - (15-omega)*(3-2.6)
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y = fb/2
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"""
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r = np.arange(10, 16)
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x = 0.1924
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sb0 = (8 - 0.4 * (r - 2)) / 2
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o = math.ceil(5 / (3 - (x * 2.6)))
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sb1 = (5 - o * (3 - (x * 2.6 + (1 - x) * 4.5)) - 0.4 * (r - o)) / 2
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for m in Matches.from_profile('SURVIVE').data:
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info = m.query('game', 'created').select('info').first()['info']
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conf = json.loads(info['config'])
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game_end_at = int(info['game_end_at'])
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foods = {}
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for p in m.query('player', 'join').select('pid').raw_data:
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foods[p['pid']] = conf['start_resource']
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for i in range(1, game_end_at + 1):
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for a in m.query('action', 'done').where(lambda x: x['rno'] == i).raw_data:
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foods[a['a']] += conf['payoffs']["%s%s" % (a['act_a'], a['act_b'])][0] * a['tr'] / 1440.0
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foods[a['b']] += conf['payoffs']["%s%s" % (a['act_a'], a['act_b'])][1] * a['tr'] / 1440.0
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for j in foods.keys():
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foods[j] -= conf['rounds']['consumption']
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human_count += len(foods)
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for j in foods.keys():
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if foods[j] > 0:
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winner_avg[game_end_at - 10] += foods[j]
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human_avg[game_end_at - 10] += foods[j]
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winner_count += 1
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if foods[j] > winner_max[game_end_at - 10]:
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winner_max[game_end_at - 10] = foods[j]
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if foods[j] > 3:
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print(m.name, j, foods[j])
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human_avg /= human_count
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winner_avg /= winner_count
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idx = np.arange(6)
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bw = 0.15
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fig = plt.figure(figsize=(5,3))
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ax = fig.gca()
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ax.bar(idx-2*bw, sb0, bw, color='tomato', label='Sacrifice(n=4)')
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ax.bar(idx-bw, sb1, bw, color='limegreen', label='Sacrifice Max(n=4)')
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ax.bar(idx, human_avg, bw, color='blueviolet', label='Human Average')
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ax.bar(idx+bw, winner_avg, bw, color='gold', label='Winner Average')
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# ax.bar(idx+2*bw, winner_max, bw, color='deepskyblue', label='Winner Max')
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ax.set_ylabel('Average Reward')
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ax.set_ylim(0,3.5)
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ax.set_xlabel('Match Ends At')
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ax.set_xticks(idx + bw / 2)
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ax.set_xticklabels(('10', '11', '12', '13', '14', '15'))
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ax.legend(ncol=2)
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fig.tight_layout()
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# plt.show()
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plt.savefig("graph/sb_vs_human.eps")
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