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for paper v1.4

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wJsJwr 2018-08-19 23:26:08 +08:00
parent 7b673d11e7
commit c1abe1cab6
11 changed files with 258 additions and 138 deletions
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2
break_tie.py
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@ -3,7 +3,7 @@ from matplotlib import pyplot as plt
from island.match import Match from island.match import Match
from island.matches import Matches from island.matches import Matches
mode = 'CLASSIC' mode = 'SURVIVE'
matches = Matches.from_profile_expr(lambda r: mode in r) matches = Matches.from_profile_expr(lambda r: mode in r)
labels = ['Stay Connected', 'Break Tie'] labels = ['Stay Connected', 'Break Tie']

36
break_tie_bar.py
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@ -4,18 +4,23 @@ from matplotlib import pyplot as plt
''' '''
survive survive
'''
break_tie = [13.717872086072923, 86.26126126126125] break_tie = [13.717872086072923, 86.26126126126125]
stay_connected = [86.28212791392707, 13.738738738738737] stay_connected = [86.28212791392707, 13.738738738738737]
'''
classic classic
break_tie = [8.331150117893634, 42.07858048162231]
stay_connected = [91.66884988210636, 57.9214195183777]
''' '''
# break_tie = [8.331150117893634, 42.07858048162231]
# stay_connected = [91.66884988210636, 57.9214195183777]
mode = 'SURVIVE' """
NEW VERSION
"""
bt_s = [13.717872086072923, 86.26126126126125]
bt_c = [8.331150117893634, 42.07858048162231]
fig = plt.figure(figsize=(3, 3)) fig = plt.figure(figsize=(4, 4))
ax = fig.gca() ax = fig.gca()
index = np.arange(2) index = np.arange(2)
@ -24,21 +29,22 @@ bar_width = 0.35
opacity = 1 opacity = 1
error_config = {'ecolor': '0.3'} error_config = {'ecolor': '0.3'}
rects1 = ax.bar(index, break_tie, bar_width, rects1 = ax.bar(index, bt_s, bar_width,
alpha=opacity, color='#fdcb6e', alpha=opacity, color='#d63031',
label='Break Tie') label='Dissipative')
rects2 = ax.bar(index + bar_width, stay_connected, bar_width, rects2 = ax.bar(index + bar_width, bt_c, bar_width,
alpha=opacity, color='#00b894', alpha=opacity, color='#00b894',
label='Stay Connected') label='Classic')
ax.set_ylabel('Frequency of Behavior') ax.set_ylabel('Frequency of Breaking Ties')
ax.set_title('Behavior after Moves') # ax.set_title('Behavior after Moves')
ax.set_xticks(index + bar_width / 2) ax.set_xticks(index + bar_width / 2)
ax.set_xticklabels(('C', 'D')) ax.set_xticklabels(('C', 'D'))
ax.set_xlabel('Previous Move')
ax.set_ylim(0,100) ax.set_ylim(0,100)
fig.legend(loc='lower center') ax.legend(loc='upper left')
fig.tight_layout() fig.tight_layout()
# plt.show() # plt.show()
plt.savefig("graph/break_tie_bar_%s.eps" % (mode)) plt.savefig("graph/break_tie_bar.eps")

6
break_tie_chi2.py
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@ -1,15 +1,15 @@
from scipy.stats import chi2_contingency as chi2 from scipy.stats import chi2_contingency as chi2
import numpy as np import numpy as np
obs = np.array([[2887.0, 459.0], [61.0, 383.0]]) obs = np.array([[2887.0, 61.0], [459.0, 383.0]])
chi,p,dof,expected = chi2(obs) chi,p,dof,expected = chi2(obs)
print("%f, %e, %f" % (chi, p, dof)) print("%f, %e, %f" % (chi, p, dof))
''' '''
survive: survive:
chi = 1189.53, p = 1.149752e-260 chi = 1189.5306, p = 1.149752e-260
classic: classic:
chi = 611.59, p = 5.031232e-135 chi = 600.7032, p = 1.177183e-132
''' '''

163
fail_reason.py
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@ -2,62 +2,127 @@ import json
from matplotlib import pyplot as plt from matplotlib import pyplot as plt
from island.match import Match from island.match import Match
from island.matches import Matches from island.matches import Matches
import numpy as np
from scipy.stats import pearsonr
mode = 'SURVIVE' class Solution:
matches = Matches.from_profile_expr(lambda r: mode in r) def __init__(self, mode):
self.mode = mode
self.matches = Matches.from_profile_expr(lambda r: mode in r)
self.survivals = {}
with open('survivals.json', 'r') as f:
self.survivals = json.load(f)
self.neighbors = {}
self.read_neighbor()
self.suff = 0
self.insuff = 0
self.detail_suff = [0]*2
self.detail_insuff = [0]*2
percents = [0.0, 0.0] def read_neighbor(self):
for i, m in enumerate(self.matches.data):
n = {}
for r in m.query('neighbor', 'create').raw_data:
if r['a'] in n:
n[r['a']].append(r['b'])
else:
n[r['a']] = [r['b']]
op = 'D' if r['b'] in n:
n[r['b']].append(r['a'])
else:
n[r['b']] = [r['a']]
self.neighbors[self.matches.names[i]] = n
def get_reason(m, i, target): def get_reason(self, m, i, target, ttr):
r = m.query('action', 'request').where(lambda x: x['rno'] == i+1 and x['from'] == target).raw_data tr = 1440
rs = m.query('action', 'approve').where(lambda x: x['rno'] == i+1 and x['to'] == target).raw_data for k in m.query('action', 'request').where(lambda x: x['rno'] == i and x['from'] == target).raw_data:
rsn = [n['from'] for n in rs] tr -= k['tr']
for j in r: for k in m.query('action', 'cancel').where(lambda x: x['rno'] == i and x['from'] == target).raw_data:
if j['to'] not in rsn: tr += m.query('action', 'request').where(lambda x: x['rno'] == i and x['from'] == target and x['to'] == k['to'] and x['log_id'] < k['log_id']).orderby('log_id').raw_data[-1]['tr']
tr = 1440 for k in m.query('action', 'deny').where(lambda x: x['rno'] == i and x['to'] == target).raw_data:
for k in m.query('action', 'request').where(lambda x: x['rno'] == i+1 and x['from'] == j['to']).raw_data: tr += m.query('action', 'request').where(lambda x: x['rno'] == i and x['from'] == target and x['to'] == k['from'] and x['log_id'] < k['log_id']).orderby('log_id').raw_data[-1]['tr']
tr -= k['tr'] for k in m.query('action', 'approve').where(lambda x: x['rno'] == i and x['from'] == target).raw_data:
for k in m.query('action', 'cancel').where(lambda x: x['rno'] == i+1 and x['from'] == j['to']).raw_data: tr -= k['tr']
tr += m.query('action', 'request').where(lambda x: x['rno'] == i+1 and x['from'] == j['to'] and x['to'] == k['to'] and x['log_id'] < k['log_id']).orderby('log_id').raw_data[-1]['tr'] return tr >= ttr
for k in m.query('action', 'deny').where(lambda x: x['rno'] == i+1 and x['to'] == j['to']).raw_data:
tr += m.query('action', 'request').where(lambda x: x['rno'] == i+1 and x['from'] == j['to'] and x['to'] == k['from'] and x['log_id'] < k['log_id']).orderby('log_id').raw_data[-1]['tr']
for k in m.query('action', 'approve').where(lambda x: x['rno'] == i+1 and x['from'] == j['to']).raw_data:
tr -= k['tr']
# print(tr)
if tr >= j['tr']:
percents[1] += 1
else:
percents[0] += 1
for m in matches.data: def new_partner_reason(self):
info = m.query('game', 'created').select('info').first()['info'] re_after = [0] * 2 # [c,d]
conf = json.loads(info['config']) su_after = [0] * 2
game_end_at = int(info['game_end_at']) for m in self.matches.data:
info = m.query('game', 'created').select('info').first()['info']
game_end_at = int(info['game_end_at'])
for i in range(1, game_end_at): for p in m.query('player', 'join').raw_data:
calced = set() pid = p['pid']
for row in m.query('action', 'done').where(lambda x: (x['act_a'] == op or x['act_b'] == op) and x['rno'] == i).raw_data: for i in range(2, game_end_at):
if row['act_a'] == op and row['a'] not in calced: previous_round_partner = []
get_reason(m, i, row['a']) c, t = 0, 0
calced.add(row['a']) for r in m.query('action', 'done').where(lambda x: x['rno'] == i - 1 and (x['a'] == pid or x['b'] == pid)).raw_data:
if row['act_b'] == op and row['b'] not in calced: if r['a'] == pid:
get_reason(m, i, row['b']) previous_round_partner.append(r['b'])
calced.add(row['b']) if r['act_a'] == 'C':
c += 1
else:
previous_round_partner.append(r['a'])
if r['act_b'] == 'C':
c += 1
t += 1
is_coop = 0 if c * 2 >= t else 1
print(percents) new_partner_requester = {}
_all = sum(percents) / 100 for r in m.query('action', 'request').where(lambda x: x['rno'] == i and (x['from'] == pid or x['to'] == pid)).raw_data:
percents[0] /= _all if r['from'] == pid:
percents[1] /= _all if r['to'] not in previous_round_partner:
# new_partner_request += 1
new_partner_requester[r['to']] = r['tr']
else:
if r['from'] not in previous_round_partner:
# new_partner_request += 1
new_partner_requester[r['from']] = r['tr']
if not new_partner_requester:
continue
re_after[is_coop] += len(new_partner_requester)
new_partner_succ = 0
new_partner = []
for r in m.query('action', 'done').where(lambda x: x['rno'] == i and (x['a'] == pid or x['b'] == pid)).raw_data:
if r['a'] == pid:
if r['b'] not in previous_round_partner:
new_partner_succ += 1
new_partner.append(r['b'])
else:
if r['a'] not in previous_round_partner:
new_partner_succ += 1
new_partner.append(r['a'])
su_after[is_coop] += new_partner_succ
for npr, ntr in new_partner_requester.items():
if npr not in new_partner:
if self.get_reason(m, i, npr, ntr):
self.suff += 1
self.detail_suff[is_coop] += 1
else:
self.insuff += 1
self.detail_insuff[is_coop] += 1
for i, _ in enumerate(su_after):
print(su_after[i], re_after[i], su_after[i] / re_after[i])
su_after[i] /= re_after[i]
return su_after
labels = ['Insufficient Time Resource', 'Sufficient Time Resource'] if __name__ == '__main__':
print('CLASSIC')
plt.figure() sc = Solution('CLASSIC')
plt.pie(percents, labels=labels, autopct="%1.2f%%", pctdistance=1.1, labeldistance=2,startangle=90, colors=['#00b894', '#fdcb6e']) npc_after = sc.new_partner_reason()
plt.legend() print("reason: ", sc.suff, sc.insuff, sc.insuff / (sc.suff + sc.insuff))
plt.axis('equal') # Equal aspect ratio ensures that pie is drawn as a circle. print("reason(c): ", sc.detail_suff[0], sc.detail_insuff[0], sc.detail_insuff[0] / (sc.detail_suff[0] + sc.detail_insuff[0]))
# plt.show() print("reason(d): ", sc.detail_suff[1], sc.detail_insuff[1], sc.detail_insuff[1] / (sc.detail_suff[1] + sc.detail_insuff[1]))
plt.savefig("graph/fail_reason_%s_%s.eps"%(op, mode)) print('SURVIVE')
ss = Solution('SURVIVE')
nps_after = ss.new_partner_reason()
print("reason: ", ss.suff, ss.insuff, ss.insuff / (ss.suff + ss.insuff))
print("reason(c): ", ss.detail_suff[0], ss.detail_insuff[0], ss.detail_insuff[0] / (ss.detail_suff[0] + ss.detail_insuff[0]))
print("reason(d): ", ss.detail_suff[1], ss.detail_insuff[1], ss.detail_insuff[1] / (ss.detail_suff[1] + ss.detail_insuff[1]))

2
fail_reason_chi2.py
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@ -1,7 +1,7 @@
from scipy.stats import chi2_contingency as chi2 from scipy.stats import chi2_contingency as chi2
import numpy as np import numpy as np
obs = np.array([[203.0, 49.0], [279.0, 78.0]]) obs = np.array([[290.0, 1023.0], [30.0, 321.0]])
chi,p,dof,expected = chi2(obs) chi,p,dof,expected = chi2(obs)
print("%f, %e, %f" % (chi, p, dof)) print("%f, %e, %f" % (chi, p, dof))

55
food_loss.py
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@ -1,5 +1,6 @@
import json import json
from matplotlib import pyplot as plt from matplotlib import pyplot as plt
from matplotlib import patches as pch
from island.match import Match from island.match import Match
from island.matches import Matches from island.matches import Matches
import numpy as np import numpy as np
@ -12,6 +13,9 @@ class Solution:
self.matches = Matches.from_profile_expr(lambda r: mode in r) self.matches = Matches.from_profile_expr(lambda r: mode in r)
def food_loss(self): def food_loss(self):
survivals = {}
with open('survivals.json', 'r') as f:
survivals = json.load(f)
fl = [[],[]] fl = [[],[]]
payoff = { payoff = {
'C': { 'C': {
@ -30,46 +34,57 @@ class Solution:
for p in m.query('player', 'join').raw_data: for p in m.query('player', 'join').raw_data:
pid = p['pid'] pid = p['pid']
for i in range(2, game_end_at): for i in range(2, game_end_at):
if pid not in survivals[m.name][str(i)]: break
c, t = 0, 0 c, t = 0, 0
for r in m.query('action', 'done').where(lambda x: x['rno'] == i - 1 and (x['a'] == pid or x['b'] == pid)).raw_data: for r in m.query('action', 'done').where(lambda x: x['rno'] == i - 1 and (x['a'] == pid or x['b'] == pid)).raw_data:
if r['act_a' if r['a'] == pid else 'act_b'] == 'C': if r['act_a' if r['a'] == pid else 'act_b'] == 'C':
c += 1 c += 1
t += 1 t += 1
is_coop = 0 if c * 2 >= t else 1 is_coop = 0 if c * 2 >= t else 1
f = -3.0 f = -3.0 if self.mode == 'SURVIVE' else 0
for r in m.query('action', 'done').where(lambda x: x['rno'] == i and (x['a'] == pid or x['b'] == pid)).raw_data: for r in m.query('action', 'done').where(lambda x: x['rno'] == i and (x['a'] == pid or x['b'] == pid)).raw_data:
if r['a'] == pid: if r['a'] == pid:
f += payoff[r['act_a']][r['act_b']] * r['tr'] / 1440.0 f += payoff[r['act_a']][r['act_b']] * r['tr'] / 1440.0
else: else:
f += payoff[r['act_b']][r['act_a']] * r['tr'] / 1440.0 f += payoff[r['act_b']][r['act_a']] * r['tr'] / 1440.0
fl[is_coop].append(f) fl[is_coop].append(-f)
print(len(fl[0]), len(fl[1]))
print(sum(fl[0]) / len(fl[0]), sum(fl[1]) / len(fl[1]))
return fl return fl
if __name__ == '__main__': if __name__ == '__main__':
mode = 'SURVIVE' sc = Solution('CLASSIC')
s = Solution(mode) fc = sc.food_loss()
f = s.food_loss() ss = Solution('SURVIVE')
fs = ss.food_loss()
blue = '#0984e3' blue = '#0984e3'
red = '#d63031' red = '#d63031'
green = '#00b894'
c = [blue, red] c = [blue, red]
labels = ['C', 'D'] labels = ['Dissipative', 'Classic']
fig = plt.figure(figsize=(3, 3)) fig = plt.figure(figsize=(8, 6))
ax = fig.gca() ax = fig.gca()
error_config = {'ecolor': '0.3', 'capsize': 4} index = np.arange(2)
bplot = ax.boxplot(f, widths = 0.3
vert=True, # vertical box alignment
patch_artist=True, # fill with color
notch=True, # notch shape
labels=labels) # will be used to label x-ticks
for patch, color in zip(bplot['boxes'], c): vp1 = ax.violinplot(fs, positions=index-widths/2, widths=widths, showmeans=True, showmedians=True)
patch.set_facecolor(color) vp2 = ax.violinplot(fc, positions=index+widths/2, widths=widths, showmeans=True, showmedians=True)
ax.set_ylabel('Frequency') hdl1 = pch.Patch(facecolor=vp1['bodies'][0].get_facecolor()[0])
hdl2 = pch.Patch(facecolor=vp2['bodies'][0].get_facecolor()[0])
vp1['cmeans'].set_edgecolor(green)
vp1['cmeans'].set_linestyle(':')
vp2['cmeans'].set_edgecolor(green)
vp2['cmeans'].set_linestyle(':')
ax.set_ylabel('Food Loss')
ax.yaxis.grid(True, linestyle='--')
# ax.set_title('Scores by group and gender') # ax.set_title('Scores by group and gender')
ax.set_xticks(index)
ax.legend() ax.set_xticklabels(['C', 'D'])
ax.set_ylim(-6, 4)
ax.set_xlabel("Previous Move")
ax.legend([hdl1, hdl2], labels)
fig.tight_layout() fig.tight_layout()
plt.show() # plt.show()
# plt.savefig("graph/new_partner_bar_%s.eps" % mode) plt.savefig("graph/FoodLoss.svg")

1
island/match.py
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@ -10,6 +10,7 @@ class Match:
""" """
:param json_string: string represents data in json format :param json_string: string represents data in json format
""" """
self.name = ''
if dtype == 'json': if dtype == 'json':
self.raw_data = json.loads(raw) self.raw_data = json.loads(raw)
self.dtype = 'json' self.dtype = 'json'

2
island/matches.py
View File

@ -11,11 +11,13 @@ class Matches:
if from_list: if from_list:
for l in source: for l in source:
self.data.append(Match.read_from_json(l)) self.data.append(Match.read_from_json(l))
self.data[-1].name = Path(l).stem
self.names.append(Path(l).stem) self.names.append(Path(l).stem)
else: else:
for f in Path(source).iterdir(): for f in Path(source).iterdir():
if Path(f).suffix == '.json': if Path(f).suffix == '.json':
self.data.append(Match.read_from_json(str(f))) self.data.append(Match.read_from_json(str(f)))
self.data[-1].name = Path(f).stem
self.names.append(Path(f).stem) self.names.append(Path(f).stem)
@staticmethod @staticmethod

27
new_partner_bar.py
View File

@ -75,14 +75,16 @@ class Solution:
new_partner_succ += 1 new_partner_succ += 1
su_after[is_coop] += new_partner_succ su_after[is_coop] += new_partner_succ
for i, _ in enumerate(su_after): for i, _ in enumerate(su_after):
print(su_after[i], re_after[i], su_after[i] / re_after[i])
su_after[i] /= re_after[i] su_after[i] /= re_after[i]
return su_after return su_after
if __name__ == '__main__': if __name__ == '__main__':
mode = 'CLASSIC' sc = Solution('CLASSIC')
s = Solution(mode) npc_after = sc.new_partner_after()
su_after = s.new_partner_after() ss = Solution('SURVIVE')
nps_after = ss.new_partner_after()
index = np.arange(2) index = np.arange(2)
blue = '#0984e3' blue = '#0984e3'
@ -90,20 +92,23 @@ if __name__ == '__main__':
fig = plt.figure(figsize=(3, 3)) fig = plt.figure(figsize=(3, 3))
ax = fig.gca() ax = fig.gca()
bar_width = 0.5 bar_width = 0.35
opacity = 1 opacity = 1
error_config = {'ecolor': '0.3', 'capsize': 4} error_config = {'ecolor': '0.3', 'capsize': 4}
rects1 = ax.bar(index, su_after, bar_width, rects1 = ax.bar(index, nps_after, bar_width,
color=red, label='New Patner') color=red, label='Dissipative')
rects2 = ax.bar(index + bar_width, npc_after, bar_width,
alpha=opacity, color='#00b894',
label='Classic')
ax.set_ylabel('Frequency') ax.set_ylabel('Rate')
# ax.set_title('Scores by group and gender') # ax.set_title('Rate of Successfully Making New Partner')
ax.set_xticks(index) ax.set_xlabel('Previous Move')
ax.set_xticks(index + bar_width / 2)
ax.set_xticklabels(['C', 'D']) ax.set_xticklabels(['C', 'D'])
ax.set_ylim(0,1) ax.set_ylim(0,1)
ax.set_xlim(-0.5,1.5)
ax.legend() ax.legend()
fig.tight_layout() fig.tight_layout()
# plt.show() # plt.show()
plt.savefig("graph/new_partner_bar_%s.eps" % mode) # plt.savefig("graph/new_partner_bar.eps")

54
rewiring_rate.py
View File

@ -18,7 +18,7 @@ def p1(x, rewires, tau, postfix, show):
ax2 = ax.twinx() ax2 = ax.twinx()
ax2.plot(x, tau, color=red, linewidth=3) ax2.plot(x, tau, color=red, linewidth=3)
ax2.set_ylim(0, 1440) ax2.set_ylim(0, 1440)
ax.set_xlim(1, 14) ax.set_xlim(2, 15)
ax.set_xlabel("Rounds") ax.set_xlabel("Rounds")
ax.set_ylabel("Rewiring Rate", color=green) ax.set_ylabel("Rewiring Rate", color=green)
ax.tick_params(axis='y', labelcolor=green) ax.tick_params(axis='y', labelcolor=green)
@ -31,11 +31,31 @@ def p1(x, rewires, tau, postfix, show):
else: else:
plt.savefig("graph/tau_p_rewire_plot_%s.eps" % postfix) plt.savefig("graph/tau_p_rewire_plot_%s.eps" % postfix)
def p2c(tau, rewires, show):
# # p2散点图
fig = plt.figure(figsize=(4, 3))
ax = fig.gca()
plt.scatter(tau, rewires, color=green, linewidths=2, zorder=100)
ax.set_xlabel('$\\tau_{p}$', family='sans-serif')
ax.set_ylabel('Rewiring Rate')
ax.set_xlim(0, 1440)
ax.set_xticks(sp.linspace(0, 1440, 7))
ax.set_ylim(0, 0.6)
plt.tight_layout()
if show:
plt.show()
else:
plt.savefig("graph/tau_p_rewire_sca_c.eps")
# 皮尔逊相关系数
print("pearson: %f, p-value: %f" % pearsonr(tau, rewires))
def p2(tau, rewires, postfix, show): def p2(tau, rewires, postfix, show):
# # p2散点图 # # p2散点图
fig = plt.figure(figsize=(6.4, 3.6)) fig = plt.figure(figsize=(4, 3))
ax = fig.gca() ax = fig.gca()
# ax.set_ylim(0.5, 1)
fp1,residuals,rank,sv,rcond = sp.polyfit(tau, rewires, 1, full=True) fp1,residuals,rank,sv,rcond = sp.polyfit(tau, rewires, 1, full=True)
print("残差：",residuals) print("残差：",residuals)
print('Model parameter:',fp1) print('Model parameter:',fp1)
@ -51,7 +71,7 @@ def p2(tau, rewires, postfix, show):
ax.set_xlabel('$\\tau_{p}$', family='sans-serif') ax.set_xlabel('$\\tau_{p}$', family='sans-serif')
ax.set_ylabel('Rewiring Rate') ax.set_ylabel('Rewiring Rate')
ax.set_xlim(0, 1440) ax.set_xlim(0, 1440)
ax.set_xticks(sp.linspace(0, 1440, 13)) ax.set_xticks(sp.linspace(0, 1440, 7))
ax.set_ylim(0, 0.6) ax.set_ylim(0, 0.6)
plt.tight_layout() plt.tight_layout()
if show: if show:
@ -64,7 +84,7 @@ def p2(tau, rewires, postfix, show):
if __name__ == '__main__': if __name__ == '__main__':
mode = 'CLASSIC' mode = 'SURVIVE'
matches = Matches.from_profile_expr(lambda r: mode in r) matches = Matches.from_profile_expr(lambda r: mode in r)
max_round = 15 max_round = 15
@ -74,7 +94,7 @@ if __name__ == '__main__':
neighbors = {} neighbors = {}
rewires = [] rewires = []
x = np.arange(1, max_round) x = np.arange(2, max_round+1)
mwRe = {} # Match-wise frequency of rewiring mwRe = {} # Match-wise frequency of rewiring
mwTau = {} # Match-wise Tau mwTau = {} # Match-wise Tau
tau = [] tau = []
@ -94,7 +114,7 @@ if __name__ == '__main__':
n[r['b']] = [r['a']] n[r['b']] = [r['a']]
neighbors[matches.names[i]] = n neighbors[matches.names[i]] = n
for i in range(max_round-1): for i in range(1, max_round):
re = [] re = []
for j in range(len(matches.data)): for j in range(len(matches.data)):
rewire = 0 rewire = 0
@ -110,7 +130,7 @@ if __name__ == '__main__':
rewires.append(np.average(re)) rewires.append(np.average(re))
for i in range(max_round-1): for i in range(1, max_round):
tp = [] tp = []
for j in range(len(matches.data)): for j in range(len(matches.data)):
if i == 0: if i == 0:
@ -148,8 +168,10 @@ if __name__ == '__main__':
red = '#d63031' red = '#d63031'
# p1折线图 # p1折线图
# p1(x, rewires, tau, mode, False) # p1(x, rewires, tau, mode, True)
p2(tau, rewires, mode, False) # p2c(tau, rewires, False)
p2(tau[:12], rewires[:12], mode, False)
''' '''
classic classic
@ -157,12 +179,12 @@ classic
Model parameter: [ 9.81549075e-04 -9.87729952e-01] Model parameter: [ 9.81549075e-04 -9.87729952e-01]
error= 0.058738 error= 0.058738
Other parameters: rank=2, sv=[ 1.41291267 0.06064473], rcond=3.10862446895e-15 Other parameters: rank=2, sv=[ 1.41291267 0.06064473], rcond=3.10862446895e-15
pearson: 0.823000, p-value: 0.000300 pearson: -0.507660, p-value: 0.063859
survive survive
残差： [ 0.05788203] 残差： [ 0.00293523]
Model parameter: [ 0.00033232 -0.06283898] Model parameter: [ 0.00016483 -0.02259405]
error= 0.057882 error= 0.002935
Other parameters: rank=2, sv=[ 1.3284034 0.48512309], rcond=3.10862446895e-15 Other parameters: rank=2, sv=[ 1.33437859 0.46843758], rcond=2.6645352591e-15
pearson: 0.893237, p-value: 0.000017 pearson: 0.947167, p-value: 0.000003
''' '''

48
tau_p_co.py
View File

@ -15,20 +15,21 @@ def error(f,x,y):
return sp.sum((f(x)-y)**2) return sp.sum((f(x)-y)**2)
def p1(x, coopr, tau, postfix, show=True): def p1(x, coopr, tau, postfix, show=True):
fig = plt.figure(figsize=(6.4, 3.6)) fig = plt.figure(figsize=(5, 4))
ax = fig.gca() ax = fig.gca()
ax.plot(x, coopr, color=blue, linewidth=3) ax.plot(x, coopr, color=blue, linewidth=2, label="$f_c$")
ax.set_ylim(0.5, 1) ax.set_ylim(0, 1)
ax2 = ax.twinx() ax2 = ax.twinx()
ax2.plot(x, tau, color=red, linewidth=3) ax2.plot(x, tau, color=red, linewidth=2, label=r"$\tau_p$")
ax2.set_ylim(0, 1440) ax2.set_ylim(0, 1440)
ax.set_xlim(1, 14) ax.set_xlim(1, 15)
ax.set_xlabel("Rounds") ax.set_xlabel("Rounds")
ax.set_ylabel("Frequency of Cooperation", color=blue) ax.set_ylabel(r"$f_c$", color=blue)
ax.tick_params(axis='y', labelcolor=blue) ax.tick_params(axis='y', labelcolor=blue)
ax2.set_ylabel("$\\tau_{p}$", family='sans-serif', color=red) ax2.set_ylabel(r"$\tau_{p}$", family='sans-serif', color=red)
ax2.tick_params(axis='y', labelcolor=red) ax2.tick_params(axis='y', labelcolor=red)
fig.legend()
plt.tight_layout() plt.tight_layout()
if show: if show:
plt.show() plt.show()
@ -49,7 +50,7 @@ def p2(tau, coopr, limited, postfix, show=True):
coopr_r.append(coopr[i]) coopr_r.append(coopr[i])
# p2散点图 # p2散点图
fig = plt.figure(figsize=(6.4, 3.6)) fig = plt.figure(figsize=(4, 3))
ax = fig.gca() ax = fig.gca()
# ax.set_ylim(0.5, 1) # ax.set_ylim(0.5, 1)
fp1,residuals,rank,sv,rcond = sp.polyfit(tau2, coopr2, 1, full=True) fp1,residuals,rank,sv,rcond = sp.polyfit(tau2, coopr2, 1, full=True)
@ -63,10 +64,10 @@ def p2(tau, coopr, limited, postfix, show=True):
plt.plot(fx,f1(fx),linewidth=2,color=red, ls='--', zorder=0) plt.plot(fx,f1(fx),linewidth=2,color=red, ls='--', zorder=0)
plt.scatter(tau2, coopr2, color=blue, linewidths=2, zorder=100) plt.scatter(tau2, coopr2, color=blue, linewidths=2, zorder=100)
plt.scatter(tau_r, coopr_r, color='white', edgecolors=blue, linewidths=2, zorder=101) plt.scatter(tau_r, coopr_r, color='white', edgecolors=blue, linewidths=2, zorder=101)
ax.set_xlabel('$\\tau_{p}$', family='sans-serif') ax.set_xlabel(r'$\tau_{p}$', family='sans-serif')
ax.set_ylabel('Frequency of Cooperation') ax.set_ylabel(r'$f_{c}$', family='sans-serif')
ax.set_xlim(0, 1440) ax.set_xlim(0, 1440)
ax.set_xticks(sp.linspace(0, 1440, 13)) ax.set_xticks(sp.linspace(0, 1440, 7))
ax.set_ylim(0.5, 1) ax.set_ylim(0.5, 1)
plt.tight_layout() plt.tight_layout()
if show: if show:
@ -88,7 +89,7 @@ if __name__ == '__main__':
neighbors = {} neighbors = {}
coopr = [] coopr = []
x = np.arange(1, max_round) x = np.arange(1, max_round+1)
mwCo = {} # Match-wise frequency of cooperation mwCo = {} # Match-wise frequency of cooperation
mwTau = {} # Match-wise Tau mwTau = {} # Match-wise Tau
bx = [] bx = []
@ -109,7 +110,7 @@ if __name__ == '__main__':
n[r['b']] = [r['a']] n[r['b']] = [r['a']]
neighbors[matches.names[i]] = n neighbors[matches.names[i]] = n
for i in range(max_round-1): for i in range(max_round):
co = [] co = []
for j in range(len(matches.data)): for j in range(len(matches.data)):
coop = 0 coop = 0
@ -130,7 +131,7 @@ if __name__ == '__main__':
coopr.append(0) coopr.append(0)
for i in range(max_round-1): for i in range(max_round):
tp = [] tp = []
for j in range(len(matches.data)): for j in range(len(matches.data)):
if i == 0: if i == 0:
@ -168,18 +169,13 @@ if __name__ == '__main__':
red = '#d63031' red = '#d63031'
# p1折线图 # p1折线图
# p1(x, coopr, tau, 'survive', False) # p1(x, coopr, tau, 'classic', False)
p2(tau[:12], coopr[:12], 720, 'survive', False) p2(tau[:12], coopr[:12], 720, 'survive', True)
# p2(tau, coopr, 1440, 'classic', False)
''' '''
classic
残差： [ 0.00317365]
Model parameter: [ -1.24291981e-04 9.70766132e-01]
Other parameters: rank=2, sv=[ 1.41276801 0.06392615], rcond=2.6645352591e-15
error= 0.003174
pearson: -0.607866, p-value: 0.036010
survive survive
残差： [ 0.00548837] 残差： [ 0.00548837]
@ -187,4 +183,12 @@ if __name__ == '__main__':
Other parameters: rank=2, sv=[ 1.36321571 0.37635479], rcond=1.99840144433e-15 Other parameters: rank=2, sv=[ 1.36321571 0.37635479], rcond=1.99840144433e-15
error= 0.005488 error= 0.005488
pearson: -0.829102, p-value: 0.005723 pearson: -0.829102, p-value: 0.005723
classic
残差： [ 0.00489393]
Model parameter: [ -1.38823596e-04 9.82787424e-01]
Other parameters: rank=2, sv=[ 1.41298532 0.05892772], rcond=3.33066907388e-15
error= 0.004894
pearson: -0.582154, p-value: 0.022790
''' '''