75 lines
2.3 KiB
Python
75 lines
2.3 KiB
Python
import json
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from matplotlib import pyplot as plt
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from island.match import Match
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from island.matches import Matches
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import numpy as np
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matches = Matches('wos-data-new')
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max_round = 15
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alive = []
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yerr = []
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x = []
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al_al = []
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d = []
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d_sem = []
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survivals = {}
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with open('winner.json','r') as f:
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survivals = json.load(f)
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for i in range(max_round):
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defects = []
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count = []
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for j in range(len(matches.data)):
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defector = set()
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for row in matches.data[j].query('action', 'done').where(lambda x: x['rno']==i+1 and (x['act_a']=='D' or x['act_b']=='D')).raw_data:
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if row['act_a']=='D':
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defector.add(row['a'])
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if row['act_b'] == 'D':
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defector.add(row['b'])
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if defector:
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# print("[%d,%d] %s" % (i,j,str(defector)))
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incr = 0
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for k in survivals[matches.names[j]]:
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if k in defector:
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incr += 1
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# print(k)
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defects.append(float(incr) / float(len(defector)))
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count.append(len(defector))
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print(i)
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print(defects)
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print(count)
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if defects:
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defects = np.array(defects)
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al_al.append(defects)
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alive.append(np.average(defects))
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yerr.append(np.std(defects))
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count = np.array(count)
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d.append(np.average(count))
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d_sem.append(np.std(count))
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else:
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al_al.append([])
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alive.append(0)
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yerr.append(0)
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d.append(0)
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d_sem.append(0)
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x.append(i+1)
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fig = plt.figure(figsize=(6.4, 4))
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flier_marker = dict(markerfacecolor='w', marker='o', markersize=3, markeredgewidth=0.5)
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mean_marker = dict(markerfacecolor='w', marker='s', markeredgecolor='#0984e3', markersize=3, markeredgewidth=1)
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ax1 = fig.gca()
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# plt.errorbar(x, alive, yerr=[yerr_min, yerr_max], fmt='o', capsize=4)
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ax1.boxplot(al_al, showmeans=True, meanprops=mean_marker, flierprops=flier_marker)
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plt.xlabel('Round')
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plt.ylabel('Frequency of Defection Survivals')
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# ax2 = ax1.twinx()
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# ax2.errorbar(list(range(1, max_round+1)), d, yerr=d_sem, fmt='o-', capsize=2, color='#00b894', alpha=0.5, linewidth=1, zorder=-1)
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# ax2.errorbar(x, alive, yerr=yerr, fmt='o-', capsize=2, color='#00b894', alpha=0.5, linewidth=1, zorder=-1)
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# ax2.tick_params(axis='y', labelcolor='#00b894')
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plt.tight_layout()
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plt.show()
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# plt.savefig('graph/survive_after_defect.png') |