127 lines
4.2 KiB
Python
127 lines
4.2 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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from scipy.stats import pearsonr
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mode = 'CLASSIC'
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matches = Matches.from_profile_expr(lambda r: mode in r)
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k = np.arange(5, 11)
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succ = np.zeros(10)
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total = np.zeros(10)
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survivals = {}
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with open('survivals.json', 'r') as f:
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survivals = json.load(f)
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neighbors = {}
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for i in range(len(matches.data)):
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m = matches.data[i]
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n = {}
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for r in m.query('neighbor', 'create').raw_data:
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if r['a'] in n:
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n[r['a']].append(r['b'])
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else:
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n[r['a']] = [r['b']]
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if r['b'] in n:
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n[r['b']].append(r['a'])
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else:
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n[r['b']] = [r['a']]
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neighbors[matches.names[i]] = n
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for m_i in range(len(matches.data)):
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m = matches.data[m_i]
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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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for p in m.query('player', 'join').raw_data:
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pid = p['pid']
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for i in range(2, game_end_at):
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neighborhood = []
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if pid not in neighbors[matches.names[m_i]]:
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break
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for j in neighbors[matches.names[m_i]][pid]:
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if j in survivals[matches.names[m_i]][str(i-1)]:
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neighborhood.append(j)
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if len(neighborhood) < 2:
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break
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previous_round_partner = []
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for r in m.query('action', 'done').where(lambda x: x['rno']==i-1 and (x['a']==pid or x['b']==pid)).raw_data:
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if r['a'] == pid:
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previous_round_partner.append(r['b'])
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else:
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previous_round_partner.append(r['a'])
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new_partner_request = 0
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for r in m.query('action', 'request').where(lambda x: x['rno']==i and (x['from']==pid or x['to']==pid)).raw_data:
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if r['from'] == pid:
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if r['to'] not in previous_round_partner:
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new_partner_request += 1
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else:
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if r['from'] not in previous_round_partner:
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new_partner_request += 1
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if new_partner_request == 0:
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continue
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new_partner_succ = 0
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for r in m.query('action', 'done').where(lambda x: x['rno']==i and (x['a']==pid or x['b']==pid)).raw_data:
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if r['a'] == pid:
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if r['b'] not in previous_round_partner:
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new_partner_succ += 1
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else:
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if r['a'] not in previous_round_partner:
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new_partner_succ += 1
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try:
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succ[len(neighborhood) - 2] += new_partner_succ
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total[len(neighborhood) - 2] += new_partner_request
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except:
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print("N!: %d" % len(neighborhood))
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print(succ,total)
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# for classic
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succ = succ[4:]
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total = total[4:]
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# for survival
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# succ = succ[:-1]
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# total = total[:-1]
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red = '#d63031'
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fig = plt.figure(figsize=(6.4, 4))
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ax = fig.gca()
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bar_width = 0.35
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opacity = 1
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error_config = {'ecolor': '0.3', 'capsize': 4}
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rects1 = ax.bar(k, succ, bar_width,
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alpha=opacity, color='#00b894',
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# yerr=c_req_suc_std, error_kw=error_config,
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label='Success')
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rects3 = ax.bar(k + bar_width, total, bar_width,
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alpha=opacity, color='#fdcb6e',
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# yerr=d_req_suc_mean, error_kw=error_config,
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label='Requests')
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ax.set_xlabel('k')
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ax.set_ylabel('Count')
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# ax.set_title('Scores by group and gender')
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ax.set_xticks(k + bar_width / 2)
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ax.set_xticklabels(k)
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ax.legend()
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ax2 = ax.twinx()
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ax2.plot(k, succ/total,linewidth=2,color=red, ls='--')
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ax2.set_ylabel("Frequency of new partners", family='sans-serif', color=red)
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ax2.tick_params(axis='y', labelcolor=red)
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ax2.set_ylim(0,1)
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fig.tight_layout()
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# plt.show()
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plt.savefig("graph/k_and_new_partner_%s.eps" % mode)
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print("[succ vs k]pearson: %f, p-value: %f" % pearsonr(succ, k))
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print("[total vs k]pearson: %f, p-value: %f" % pearsonr(total, k))
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print("[rate vs k]pearson: %f, p-value: %f" % pearsonr(succ/total, k))
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print(np.average(succ/total))
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