emmm

.gitignore

@@ -1,7 +1,7 @@
 .DS_Store
 graph
-wos-data-new
-wos-data-casual
+wos-data*
+user*
 *.svg
 __pycache__
 .vscode/

calc_dnc_players.py

@@ -4,17 +4,12 @@ from island.match import Match
 from island.matches import Matches
 import numpy as np
 
-matches = Matches('wos-data-new')
+matches = Matches('wos-data-compete')
 max_round = 15
 
 total_players = 0
 dnc_players = 0
 
-survivals = {}
-with open('survivals.json', 'r') as f:
-    survivals = json.load(f)
-
-
 for j in range(len(matches.data)):
     players = set()
     for r in matches.data[j].query('player', 'join').raw_data:

calc_participants.py

@@ -2,18 +2,24 @@
 import json
 from pathlib import Path
 from island.match import Match
-
-
+from island.matches import Matches
 
 result = 0
+count = 0
 
-for file in Path('wos-data-new').iterdir():
-    p = Path(file)
-    if p.suffix == '.json':
-        name = p.stem
-        if int(name[1:]) >= 254:
-            m = Match.read_from_json(str(file))
-            result += len(m.query('player', 'join').select('pid').raw_data)
+# ms = Matches.from_profile('CCCN')
+ms = Matches.from_profile_expr(lambda r: 'LAB' in r and 'SURVIVE' in r and 'COMM' in r)
+for m in ms.data:
+    result += len(m.query('player', 'join').where(lambda x: 'bot' not in x or x['bot'] == False).select('pid').raw_data)
+    count += 1
 
 print(result)
+print("avg:", result / count)
 # 146 users
+# casual: 324
+# new(254-354, 全国复杂网络大会): 205
+# new-2(375-421, 无交流): 320
+# new-3(426-440, 有交流): 203
+# new-4(443-472, 经典模式，无交流): 230
+# new-5(474-，经典模式，有交流): 159
+# total: 1117

calc_reward.py

@@ -0,0 +1,50 @@
+import json
+import csv
+from pathlib import Path
+from island.match import Match
+from island.matches import Matches
+
+result = {}
+userdata = {}
+with open('user.data', 'r') as c:
+    for row in csv.reader(c):
+        userdata[int(row[0])] = {
+            'uid': row[0],
+            'name': row[1],
+            'email': row[2]
+        }
+ms = Matches.from_profile_expr(lambda r: 'LAB' in r and 'CLASSIC' in r)
+for m in ms.data:
+    for r in m.query('user', 'fitness').raw_data:
+        if r['user'] in result:
+            result[r['user']]['rewards'] += float(r['fitness']) - 0.0001
+            result[r['user']]['participate'] += 1
+        else:
+            result[r['user']] = {
+                'rewards': float(r['fitness']) - 0.0001,
+                'participate': 1
+            }
+ms = Matches.from_profile_expr(lambda r: 'LAB' in r and 'SURVIVE' in r)
+for m in ms.data:
+    for r in m.query('player', 'join').raw_data:
+        if r['uid'] in result:
+            result[r['uid']]['rewards'] += 5
+            result[r['uid']]['participate'] += 1
+        else:
+            result[r['uid']] = {
+                'rewards': 5.0,
+                'participate': 1
+            }
+    for r in m.query('user', 'fitness').raw_data:
+        result[r['user']]['rewards'] += float(r['fitness']) * 5
+
+total = 0.0
+with open('user.reward.csv', 'w') as out:
+    writer = csv.writer(out)
+    writer.writerow(['uid', 'name', 'email', 'reward', 'participates'])
+    for k,v in result.items():
+        writer.writerow([k, userdata[k]['name'], userdata[k]
+                         ['email'], round(v['rewards'], 2), v['participate']])
+        total += v['rewards']
+
+print("total: %f" % (total))

calc_survivals.py

@@ -4,7 +4,7 @@ from island.match import Match
 
 result = {}
 
-for file in Path('wos-data-new').iterdir():
+for file in Path('wos-data-compete').iterdir():
     p = Path(file)
     if p.suffix == '.json':
         name = p.stem

coopr_per_match.py

@@ -8,7 +8,7 @@ from island.matches import Matches
 def error(f,x,y):
     return sp.sum((f(x)-y)**2)
 
-matches = Matches('wos-data-new')
+matches = Matches('wos-data-new-2')
 max_round = 17
 
 coopr = []

coopr_per_round.py

@@ -4,7 +4,7 @@ from island.match import Match
 from island.matches import Matches
 import numpy as np
 
-matches = Matches('wos-data-new')
+matches = Matches('wos-data-new-3')
 max_round = 15
 
 coopr = []
@@ -37,6 +37,8 @@ for i in range(max_round):
         yerr_min.append(coopr[-1] - min(co))
         yerr_max.append(max(co) - coopr[-1])
         print("%f, %f, %f"%(yerr_min[-1], yerr_max[-1], coopr[-1]))
+    else:
+        coopr.append(0)
 
 
 plt.figure()

dist_of_k.py

@@ -6,21 +6,21 @@ from numpy import mean, std
 import numpy as np
 
 
-matches = Matches('wos-data-new')
+matches = Matches('wos-data-new-2')
 max_round = 15
 
 
 
 fig = plt.figure(figsize=(6.4, 3.6))
 ax = fig.gca()
-index = np.arange(11)
+index = np.arange(13)
 ax.set_xlabel('k')
 ax.set_ylabel('p(k)')
 
 c = ['#00b894','#00cec9','#0984e3','#6c5ce7','#e84393','#d63031','#e17055','#fdcb6e','#2d3436','#6ab04c','#30336b','#ED4C67']
 
 for i in range(len(matches.data)):
-    k = np.zeros(11)
+    k = np.zeros(13)
     m = matches.data[i]
     n = {}
     for r in m.query('neighbor', 'create').raw_data:
@@ -34,10 +34,12 @@ for i in range(len(matches.data)):
         else:
             n[r['b']] = [r['a']]
     for j in n.keys():
+        print(n[j], len(n[j]))
         k[len(n[j])] += 1
     pk = k / np.sum(k)
     print(i)
-    ax.scatter(index, pk, color=c[i])
+    # ax.scatter(index, pk, color=c[i])
+    ax.scatter(index, pk)
 
 # ax.set_title('Scores by group and gender')
 fig.tight_layout()

draw_game_history.py

@@ -351,9 +351,9 @@ def draw_picture(fin,fout):
 
 
 if __name__ == '__main__':
-    # for file in Path('wos-data-new').iterdir():
-    #     p = Path(file)
-    #     if p.suffix == '.json':
-    #         name = p.stem
-    #         draw_picture(str(p), str(p.parent.parent / 'graph' / ("%s.eps"%name)))
-    draw_picture("wos-data-new/G285.json", "graph/G285.eps")
+    for file in Path('wos-data-compete').iterdir():
+        p = Path(file)
+        if p.suffix == '.json':
+            name = p.stem
+            draw_picture(str(p), str(p.parent.parent / 'graph' / ("%s.eps"%name)))
+    # draw_picture("wos-data-new/G285.json", "graph/G285.eps")

interactions_per_round.py

@@ -4,7 +4,7 @@ from island.match import Match
 from island.matches import Matches
 import numpy as np
 
-matches = Matches('wos-data-new')
+matches = Matches('wos-data-new-2')
 max_round = 14
 
 coopr = []
@@ -16,7 +16,7 @@ y = np.zeros((5, max_round))
 sy = np.zeros(max_round)
 
 survivals = {}
-with open('survivals.json', 'r') as f:
+with open('survivals-2.json', 'r') as f:
     survivals = json.load(f)
 
 

island/matches.py

@@ -1,13 +1,37 @@
 from pathlib import Path
 from .match import Match
+import json
+import csv
 
 
 class Matches:
-    def __init__(self, logdir):
+    def __init__(self, source, from_list=False):
         self.data = []
         self.names = []
-        for file in Path(logdir).iterdir():
-            if Path(file).suffix == '.json':
-                self.data.append(Match.read_from_json(str(file)))
-                self.names.append(Path(file).stem)
+        if from_list:
+            for l in source:
+                self.data.append(Match.read_from_json(l))
+                self.names.append(Path(l).stem)
+        else:
+            for f in Path(source).iterdir():
+                if Path(f).suffix == '.json':
+                    self.data.append(Match.read_from_json(str(f)))
+                    self.names.append(Path(f).stem)
 
+    @staticmethod
+    def from_profile(pname, ppos='profile.csv'):
+        source = []
+        with open(ppos, 'r', encoding='utf-8') as f:
+            for row in csv.reader(f):
+                if pname in row:
+                    source.append(row[0])
+        return Matches(source, True)
+
+    @staticmethod
+    def from_profile_expr(expr, ppos='profile.csv'):
+        source = []
+        with open(ppos, 'r', encoding='utf-8') as f:
+            for row in csv.reader(f):
+                if expr(row):
+                    source.append(row[0])
+        return Matches(source, True)

k_and_new_partner.py

@@ -6,14 +6,14 @@ import numpy as np
 from scipy.stats import pearsonr
 
 
-matches = Matches('wos-data-new')
+matches = Matches('wos-data-new-2')
 
 k = np.arange(2, 11)
 succ = np.zeros(9)
 total = np.zeros(9)
 
 survivals = {}
-with open('survivals.json', 'r') as f:
+with open('survivals-2.json', 'r') as f:
     survivals = json.load(f)
 
 neighbors = {}

neighbor_per_round.py

@@ -6,11 +6,11 @@ from numpy import mean, std
 import numpy as np
 
 
-matches = Matches('wos-data-new')
+matches = Matches('wos-data-new-2')
 max_round = 15
 
 survivals = {}
-with open('survivals.json', 'r') as f:
+with open('survivals-2.json', 'r') as f:
     survivals = json.load(f)
 
 neighbors = {}
@@ -123,5 +123,5 @@ ax.set_xticks(index + bar_width / 2)
 ax.set_xticklabels(index+1)
 ax.legend()
 fig.tight_layout()
-# plt.show()
-plt.savefig('graph/neigh_per_round.eps')
+plt.show()
+# plt.savefig('graph/neigh_per_round.eps')

profile.csv

@@ -0,0 +1,75 @@
+wos-data-compete/G254.json,CCCN,,,COMM,SURVIVE,
+wos-data-compete/G272.json,CCCN,,,COMM,SURVIVE,
+wos-data-compete/G285.json,CCCN,,,COMM,SURVIVE,
+wos-data-compete/G295.json,CCCN,,,COMM,SURVIVE,
+wos-data-compete/G299.json,CCCN,,,COMM,SURVIVE,
+wos-data-compete/G302.json,CCCN,,,COMM,SURVIVE,
+wos-data-compete/G307.json,CCCN,,,COMM,SURVIVE,
+wos-data-compete/G318.json,CCCN,,,COMM,SURVIVE,
+wos-data-compete/G337.json,CCCN,,,COMM,SURVIVE,
+wos-data-compete/G341.json,CCCN,,,COMM,SURVIVE,
+wos-data-compete/G349.json,CCCN,,,COMM,SURVIVE,
+wos-data-compete/G354.json,CCCN,,,COMM,SURVIVE,
+wos-data-compete/G375.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G379.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G380.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G385.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G386.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G389.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G390.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G391.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G392.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G393.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G394.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G395.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G396.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G397.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G398.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G399.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G400.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G402.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G403.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G404.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G405.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G406.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G407.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G408.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G409.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G413.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G420.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G421.json,,LAB,NOCOMM,,SURVIVE,
+wos-data-compete/G426.json,,LAB,,COMM,SURVIVE,
+wos-data-compete/G427.json,,LAB,,COMM,SURVIVE,
+wos-data-compete/G428.json,,LAB,,COMM,SURVIVE,
+wos-data-compete/G429.json,,LAB,,COMM,SURVIVE,
+wos-data-compete/G430.json,,LAB,,COMM,SURVIVE,
+wos-data-compete/G431.json,,LAB,,COMM,SURVIVE,
+wos-data-compete/G434.json,,LAB,,COMM,SURVIVE,
+wos-data-compete/G435.json,,LAB,,COMM,SURVIVE,
+wos-data-compete/G436.json,,LAB,,COMM,SURVIVE,
+wos-data-compete/G437.json,,LAB,,COMM,SURVIVE,
+wos-data-compete/G439.json,,LAB,,COMM,SURVIVE,
+wos-data-compete/G440.json,,LAB,,COMM,SURVIVE,
+wos-data-compete/G443.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G447.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G448.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G449.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G450.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G451.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G452.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G467.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G468.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G469.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G470.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G471.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G472.json,,LAB,NOCOMM,,,CLASSIC
+wos-data-compete/G474.json,,LAB,,COMM,,CLASSIC
+wos-data-compete/G475.json,,LAB,,COMM,,CLASSIC
+wos-data-compete/G476.json,,LAB,,COMM,,CLASSIC
+wos-data-compete/G477.json,,LAB,,COMM,,CLASSIC
+wos-data-compete/G478.json,,LAB,,COMM,,CLASSIC
+wos-data-compete/G479.json,,LAB,,COMM,,CLASSIC
+wos-data-compete/G480.json,,LAB,,COMM,,CLASSIC
+wos-data-compete/G481.json,,LAB,,COMM,,CLASSIC
+wos-data-compete/G482.json,,LAB,,COMM,,CLASSIC
+wos-data-compete/G483.json,,LAB,,COMM,,CLASSIC

request_success.py

@@ -6,13 +6,18 @@ from numpy import mean, std
 import numpy as np
 
 
-matches = Matches('wos-data-new')
+matches = Matches('wos-data-new-2')
 max_round = 14
 
-c_req_succ = np.zeros(max_round-2)
-c_req = np.zeros(max_round-2)
-d_req_succ = np.zeros(max_round-2)
-d_req = np.zeros(max_round-2)
+# c_req_succ = np.zeros(max_round-2)
+# c_req = np.zeros(max_round-2)
+# d_req_succ = np.zeros(max_round-2)
+# d_req = np.zeros(max_round-2)
+
+c_req_succ = np.zeros(max_round)
+c_req = np.zeros(max_round)
+d_req_succ = np.zeros(max_round)
+d_req = np.zeros(max_round)
 
 def is_cooperator(rows, pid):
     m = 0
@@ -39,36 +44,39 @@ for i in range(max_round):
                 r = matches.data[j].query('action', 'request').where(lambda x: x['rno'] == i+2 and x['from'] == row['a']).raw_data
                 rs = matches.data[j].query('action', 'approve').where(lambda x: x['rno'] == i+2 and x['to'] == row['a']).raw_data
                 if is_cooperator(rows, row['a']):
-                    c_req_succ[j] += len(rs)
-                    c_req[j] += len(r)
+                    c_req_succ[i] += len(rs)
+                    c_req[i] += len(r)
                 else:
-                    d_req_succ[j] += len(rs)
-                    d_req[j] += len(r)
+                    d_req_succ[i] += len(rs)
+                    d_req[i] += len(r)
                 calced.add(row['a'])
 
             if row['b'] not in calced:
                 r = matches.data[j].query('action', 'request').where(lambda x: x['rno'] == i+2 and x['from'] == row['b']).raw_data
                 rs = matches.data[j].query('action', 'approve').where(lambda x: x['rno'] == i+2 and x['to'] == row['b']).raw_data
                 if is_cooperator(rows, row['b']):
-                    c_req_succ[j] += len(rs)
-                    c_req[j] += len(r)
+                    c_req_succ[i] += len(rs)
+                    c_req[i] += len(r)
                 else:
-                    d_req_succ[j] += len(rs)
-                    d_req[j] += len(r)
+                    d_req_succ[i] += len(rs)
+                    d_req[i] += len(r)
                 calced.add(row['b'])
 
-
-
+for i in range(len(c_req)):
+    if c_req[i] == 0:
+        c_req[i] = 0.1
+    if d_req[i] == 0:
+        d_req[i] = 0.1
 
 c_req_succ_fr = c_req_succ / c_req
 d_req_succ_fr = d_req_succ / d_req
 
-# print(c_req_succ)
-# print(c_req)
-# print(c_req_succ_fr)
-# print(d_req_succ)
-# print(d_req)
-# print(d_req_succ_fr)
+print(c_req_succ)
+print(c_req)
+print(c_req_succ_fr)
+print(d_req_succ)
+print(d_req)
+print(d_req_succ_fr)
 
 req_succ_fr_mean = [mean(c_req_succ_fr), mean(d_req_succ_fr)]
 req_succ_fr_sem = [std(c_req_succ_fr), std(d_req_succ_fr)]
@@ -115,5 +123,5 @@ ax.set_ylabel('Request Approval Rate')
 # ax.set_xticklabels(index+2)
 # ax.legend()
 fig.tight_layout()
-# plt.show()
-plt.savefig('graph/request_success.eps')
+plt.show()
+# plt.savefig('graph/request_success.eps')

rewiring_rate.py

@@ -12,11 +12,11 @@ def error(f,x,y):
 
 if __name__ == '__main__':
 
-    matches = Matches('wos-data-new')
+    matches = Matches('wos-data-new-2')
     max_round = 15
 
     survivals = {}
-    with open('survivals.json', 'r') as f:
+    with open('survivals-2.json', 'r') as f:
         survivals = json.load(f)
 
     neighbors = {}
@@ -41,7 +41,7 @@ if __name__ == '__main__':
                 n[r['b']] = [r['a']]    
         neighbors[matches.names[i]] = n
 
-    for i in range(max_round):
+    for i in range(max_round-1):
         re = []
         for j in range(len(matches.data)):
             rewire = 0
@@ -95,47 +95,47 @@ if __name__ == '__main__':
     red = '#d63031'
 
     # p1折线图
-    # fig = plt.figure(figsize=(6.4, 3.6))
-    # ax = fig.gca()
-    # ax.plot(x, rewires, color=green, linewidth=3)
-    # ax.set_ylim(0, 0.5)
-    # ax2 = ax.twinx()
-    # ax2.plot(x, tau, color=red, linewidth=3)
-    # ax2.set_ylim(0,1440)
-    # ax.set_xlim(1,14)
-    # ax.set_xlabel("Rounds")
-    # ax.set_ylabel("Rewiring Rate", color=green)
-    # ax.tick_params(axis='y', labelcolor=green)
-    # ax2.set_ylabel("$\\tau_{p}$", family='sans-serif', color=red)
-    # ax2.tick_params(axis='y', labelcolor=red)
+    fig = plt.figure(figsize=(6.4, 3.6))
+    ax = fig.gca()
+    ax.plot(x, rewires, color=green, linewidth=3)
+    ax.set_ylim(0, 0.5)
+    ax2 = ax.twinx()
+    ax2.plot(x, tau, color=red, linewidth=3)
+    ax2.set_ylim(0,1440)
+    ax.set_xlim(1,14)
+    ax.set_xlabel("Rounds")
+    ax.set_ylabel("Rewiring Rate", color=green)
+    ax.tick_params(axis='y', labelcolor=green)
+    ax2.set_ylabel("$\\tau_{p}$", family='sans-serif', color=red)
+    ax2.tick_params(axis='y', labelcolor=red)
 
-    # plt.tight_layout()
-    # # plt.show()
+    plt.tight_layout()
+    plt.show()
     # plt.savefig('graph/tau_p_rewire_plot.eps')
 
     # # p2散点图
-    fig = plt.figure(figsize=(6.4, 3.6))
-    ax = fig.gca()
-    # ax.set_ylim(0.5, 1)
-    fp1,residuals,rank,sv,rcond = sp.polyfit(tau, rewires, 1, full=True)
-    print("残差：",residuals)
-    print('Model parameter:',fp1)
-    f1 = sp.poly1d(fp1)
-    print("error= %f" % error(f1, tau, rewires))
-    # fx = sp.linspace(0,max(tau2),1000)
-    fx = sp.linspace(0,1440,2)
+    # fig = plt.figure(figsize=(6.4, 3.6))
+    # ax = fig.gca()
+    # # ax.set_ylim(0.5, 1)
+    # fp1,residuals,rank,sv,rcond = sp.polyfit(tau, rewires, 1, full=True)
+    # print("残差：",residuals)
+    # print('Model parameter:',fp1)
+    # f1 = sp.poly1d(fp1)
+    # print("error= %f" % error(f1, tau, rewires))
+    # # fx = sp.linspace(0,max(tau2),1000)
+    # fx = sp.linspace(0,1440,2)
 
-    plt.plot(fx,f1(fx),linewidth=2,color=red, ls='--', zorder=0)
-    plt.scatter(tau, rewires, color=green, linewidths=2, zorder=100)
-    # plt.scatter(tau_r, coopr_r, color='white', edgecolors=green, linewidths=2, zorder=101)
-    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, 13))
-    ax.set_ylim(0, 0.6)
-    plt.tight_layout()
+    # plt.plot(fx,f1(fx),linewidth=2,color=red, ls='--', zorder=0)
+    # plt.scatter(tau, rewires, color=green, linewidths=2, zorder=100)
+    # # plt.scatter(tau_r, coopr_r, color='white', edgecolors=green, linewidths=2, zorder=101)
+    # 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, 13))
+    # ax.set_ylim(0, 0.6)
+    # plt.tight_layout()
     # plt.show()
-    plt.savefig('graph/tau_p_rewire_sca.eps')
+    # plt.savefig('graph/tau_p_rewire_sca.eps')
 
 
 

tau_p_co.py

@@ -12,11 +12,11 @@ def error(f,x,y):
 
 if __name__ == '__main__':
   
-    matches = Matches('wos-data-new')
+    matches = Matches('wos-data-new-3')
     max_round = 15
 
     survivals = {}
-    with open('survivals.json', 'r') as f:
+    with open('survivals-3.json', 'r') as f:
         survivals = json.load(f)
 
     neighbors = {}
@@ -42,7 +42,7 @@ if __name__ == '__main__':
                 n[r['b']] = [r['a']]    
         neighbors[matches.names[i]] = n
 
-    for i in range(max_round):
+    for i in range(max_round-1):
         co = []
         for j in range(len(matches.data)):
             coop = 0
@@ -59,6 +59,8 @@ if __name__ == '__main__':
         bx.append(co)
         if co:
             coopr.append(np.average(co))
+        else:
+            coopr.append(0)
 
 
     for i in range(max_round-1):
@@ -114,17 +116,23 @@ if __name__ == '__main__':
     # ax2.tick_params(axis='y', labelcolor=red)
 
     # plt.tight_layout()
-    # # plt.show()
-    # plt.savefig('graph/tau_p_co_plot.eps')
+    # plt.show()
+    # # plt.savefig('graph/tau_p_co_plot.eps')
 
     tau2 = []
     coopr2 = []
     tau_r = []
     coopr_r = []
+    tau3 = []
+    coopr3 = []
     for i in range(len(tau)):
         if tau[i] <= 720:
             tau2.append(tau[i])
             coopr2.append(coopr[i])
+            if tau[i] - 316 > 0.00001:
+                tau3.append(tau[i])
+                coopr3.append(coopr[i])
+
         else:
             tau_r.append(tau[i])
             coopr_r.append(coopr[i])
@@ -153,7 +161,5 @@ if __name__ == '__main__':
     plt.show()
     # plt.savefig('graph/tau_p_co_sca.eps')
 
-
-
     # 皮尔逊相关系数
     print("pearson: %f, p-value: %f" % pearsonr(tau2, coopr2))

taup_and_new_partner.py

@@ -5,14 +5,14 @@ from island.matches import Matches
 import numpy as np
 from scipy.stats import pearsonr
 
-matches = Matches('wos-data-new')
+matches = Matches('wos-data-new-2')
 
 k = np.arange(0, 1441, 144)
 succ = np.zeros(11)
 total = np.zeros(11)
 
 survivals = {}
-with open('survivals.json', 'r') as f:
+with open('survivals-2.json', 'r') as f:
     survivals = json.load(f)
 
 neighbors = {}