diff --git a/break_tie.py b/break_tie.py
index 73ed3e2..e98bafa 100644
--- a/break_tie.py
+++ b/break_tie.py
@@ -3,7 +3,7 @@ from matplotlib import pyplot as plt
 from island.match import Match
 from island.matches import Matches
 
-mode = 'CLASSIC'
+mode = 'SURVIVE'
 matches = Matches.from_profile_expr(lambda r: mode in r)
 
 labels = ['Stay Connected', 'Break Tie']
diff --git a/break_tie_bar.py b/break_tie_bar.py
index 16915cd..78a9c87 100644
--- a/break_tie_bar.py
+++ b/break_tie_bar.py
@@ -4,18 +4,23 @@ from matplotlib import pyplot as plt
 
 '''
 survive
-'''
+
 break_tie = [13.717872086072923, 86.26126126126125]
 stay_connected = [86.28212791392707, 13.738738738738737]
-'''
+
 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()
 
 index = np.arange(2)
@@ -24,21 +29,22 @@ bar_width = 0.35
 opacity = 1
 error_config = {'ecolor': '0.3'}
 
-rects1 = ax.bar(index, break_tie, bar_width,
-                alpha=opacity, color='#fdcb6e',
-                label='Break Tie')
+rects1 = ax.bar(index, bt_s, bar_width,
+                alpha=opacity, color='#d63031',
+                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',
-                label='Stay Connected')
+                label='Classic')
 
 
-ax.set_ylabel('Frequency of Behavior')
-ax.set_title('Behavior after Moves')
+ax.set_ylabel('Frequency of Breaking Ties')
+# ax.set_title('Behavior after Moves')
 ax.set_xticks(index + bar_width / 2)
 ax.set_xticklabels(('C', 'D'))
+ax.set_xlabel('Previous Move')
 ax.set_ylim(0,100)
-fig.legend(loc='lower center')
+ax.legend(loc='upper left')
 fig.tight_layout()
 # plt.show()
-plt.savefig("graph/break_tie_bar_%s.eps" % (mode))
+plt.savefig("graph/break_tie_bar.eps")
diff --git a/break_tie_chi2.py b/break_tie_chi2.py
index bd75fbc..d29e72a 100644
--- a/break_tie_chi2.py
+++ b/break_tie_chi2.py
@@ -1,15 +1,15 @@
 from scipy.stats import chi2_contingency as chi2
 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)
 print("%f, %e, %f" % (chi, p, dof))
 
 '''
 survive:
-chi = 1189.53, p = 1.149752e-260
+chi = 1189.5306, p = 1.149752e-260
 
 classic:
-chi = 611.59, p = 5.031232e-135
+chi = 600.7032, p = 1.177183e-132
 
 '''
diff --git a/fail_reason.py b/fail_reason.py
index f0f80f8..cea0ca5 100644
--- a/fail_reason.py
+++ b/fail_reason.py
@@ -2,62 +2,127 @@ import json
 from matplotlib import pyplot as plt
 from island.match import Match
 from island.matches import Matches
+import numpy as np
+from scipy.stats import pearsonr
 
-mode = 'SURVIVE'
-matches = Matches.from_profile_expr(lambda r: mode in r)
+class Solution:
+    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):
-    r = m.query('action', 'request').where(lambda x: x['rno'] == i+1 and x['from'] == target).raw_data
-    rs = m.query('action', 'approve').where(lambda x: x['rno'] == i+1 and x['to'] == target).raw_data
-    rsn = [n['from'] for n in rs]
-    for j in r:
-        if j['to'] not in rsn:
-            tr = 1440
-            for k in m.query('action', 'request').where(lambda x: x['rno'] == i+1 and x['from'] == j['to']).raw_data:
-                tr -= k['tr']
-            for k in m.query('action', 'cancel').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+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']
-            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
+    def get_reason(self, m, i, target, ttr):
+        tr = 1440
+        for k in m.query('action', 'request').where(lambda x: x['rno'] == i and x['from'] == target).raw_data:
+            tr -= k['tr']
+        for k in m.query('action', 'cancel').where(lambda x: x['rno'] == i and x['from'] == target).raw_data:
+            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']
+        for k in m.query('action', 'deny').where(lambda x: x['rno'] == i and x['to'] == target).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']
+        for k in m.query('action', 'approve').where(lambda x: x['rno'] == i and x['from'] == target).raw_data:
+            tr -= k['tr']
+        return tr >= ttr
 
 
-for m in matches.data:
-    info = m.query('game', 'created').select('info').first()['info']
-    conf = json.loads(info['config'])
-    game_end_at = int(info['game_end_at'])
+    def new_partner_reason(self):
+        re_after = [0] * 2  # [c,d]
+        su_after = [0] * 2
+        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):
-        calced = set()
-        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:
-            if row['act_a'] == op and row['a'] not in calced:
-                get_reason(m, i, row['a'])
-                calced.add(row['a'])
-            if row['act_b'] == op and row['b'] not in calced:
-                get_reason(m, i, row['b'])
-                calced.add(row['b'])
+            for p in m.query('player', 'join').raw_data:
+                pid = p['pid']
+                for i in range(2, game_end_at):
+                    previous_round_partner = []
+                    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:
+                        if r['a'] == pid:
+                            previous_round_partner.append(r['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)
-_all = sum(percents) / 100
-percents[0] /= _all
-percents[1] /= _all
+                    new_partner_requester = {}
+                    for r in m.query('action', 'request').where(lambda x: x['rno'] == i and (x['from'] == pid or x['to'] == pid)).raw_data:
+                        if r['from'] == pid:
+                            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']
-
-plt.figure()
-plt.pie(percents, labels=labels, autopct="%1.2f%%", pctdistance=1.1, labeldistance=2,startangle=90, colors=['#00b894', '#fdcb6e'])
-plt.legend()
-plt.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.
-# plt.show()
-plt.savefig("graph/fail_reason_%s_%s.eps"%(op, mode))
+if __name__ == '__main__':
+    print('CLASSIC')
+    sc = Solution('CLASSIC')
+    npc_after = sc.new_partner_reason()
+    print("reason: ", sc.suff, sc.insuff, sc.insuff / (sc.suff + sc.insuff))
+    print("reason(c): ", sc.detail_suff[0], sc.detail_insuff[0], sc.detail_insuff[0] / (sc.detail_suff[0] + sc.detail_insuff[0]))
+    print("reason(d): ", sc.detail_suff[1], sc.detail_insuff[1], sc.detail_insuff[1] / (sc.detail_suff[1] + sc.detail_insuff[1]))
+    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]))
diff --git a/fail_reason_chi2.py b/fail_reason_chi2.py
index 74c2caf..f94d1b1 100644
--- a/fail_reason_chi2.py
+++ b/fail_reason_chi2.py
@@ -1,7 +1,7 @@
 from scipy.stats import chi2_contingency as chi2
 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)
 print("%f, %e, %f" % (chi, p, dof))
 
diff --git a/food_loss.py b/food_loss.py
index f9f007c..fbd60fe 100644
--- a/food_loss.py
+++ b/food_loss.py
@@ -1,5 +1,6 @@
 import json
 from matplotlib import pyplot as plt
+from matplotlib import patches as pch
 from island.match import Match
 from island.matches import Matches
 import numpy as np
@@ -12,6 +13,9 @@ class Solution:
         self.matches = Matches.from_profile_expr(lambda r: mode in r)
 
     def food_loss(self):
+        survivals = {}
+        with open('survivals.json', 'r') as f:
+            survivals = json.load(f)
         fl = [[],[]]
         payoff = {
             'C': {
@@ -30,46 +34,57 @@ class Solution:
             for p in m.query('player', 'join').raw_data:
                 pid = p['pid']
                 for i in range(2, game_end_at):
+                    if pid not in survivals[m.name][str(i)]: break
                     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:
                         if r['act_a' if r['a'] == pid else 'act_b'] == 'C':
                             c += 1
                         t += 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:
                         if r['a'] == pid:
                             f += payoff[r['act_a']][r['act_b']] * r['tr'] / 1440.0
                         else:
                             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
 
 
 if __name__ == '__main__':
-    mode = 'SURVIVE'
-    s = Solution(mode)
-    f = s.food_loss()
+    sc = Solution('CLASSIC')
+    fc = sc.food_loss()
+    ss = Solution('SURVIVE')
+    fs = ss.food_loss()
     blue = '#0984e3'
     red = '#d63031'
+    green = '#00b894'
     c = [blue, red]
-    labels = ['C', 'D']
-    fig = plt.figure(figsize=(3, 3))
+    labels = ['Dissipative', 'Classic']
+    fig = plt.figure(figsize=(8, 6))
     ax = fig.gca()
-    error_config = {'ecolor': '0.3', 'capsize': 4}
-    bplot = ax.boxplot(f,
-                        vert=True,  # vertical box alignment
-                        patch_artist=True,  # fill with color
-                        notch=True,  # notch shape
-                        labels=labels)  # will be used to label x-ticks
+    index = np.arange(2)
+    widths = 0.3
 
-    for patch, color in zip(bplot['boxes'], c):
-        patch.set_facecolor(color)
-    ax.set_ylabel('Frequency')
+    vp1 = ax.violinplot(fs, positions=index-widths/2, widths=widths, showmeans=True, showmedians=True)
+    vp2 = ax.violinplot(fc, positions=index+widths/2, widths=widths, showmeans=True, showmedians=True)
+    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.legend()
+    ax.set_xticks(index)
+    ax.set_xticklabels(['C', 'D'])
+    ax.set_ylim(-6, 4)
+    ax.set_xlabel("Previous Move")
+    ax.legend([hdl1, hdl2], labels)
 
     fig.tight_layout()
-    plt.show()
-    # plt.savefig("graph/new_partner_bar_%s.eps" % mode)
+    # plt.show()
+    plt.savefig("graph/FoodLoss.svg")
diff --git a/island/match.py b/island/match.py
index ad89b88..d04bee2 100644
--- a/island/match.py
+++ b/island/match.py
@@ -10,6 +10,7 @@ class Match:
         """
         :param json_string: string represents data in json format
         """
+        self.name = ''
         if dtype == 'json':
             self.raw_data = json.loads(raw)
             self.dtype = 'json'
diff --git a/island/matches.py b/island/matches.py
index 0b94d56..3e1ff97 100644
--- a/island/matches.py
+++ b/island/matches.py
@@ -11,11 +11,13 @@ class Matches:
         if from_list:
             for l in source:
                 self.data.append(Match.read_from_json(l))
+                self.data[-1].name = Path(l).stem
                 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.data[-1].name = Path(f).stem
                     self.names.append(Path(f).stem)
 
     @staticmethod
diff --git a/new_partner_bar.py b/new_partner_bar.py
index 3380481..92352a3 100644
--- a/new_partner_bar.py
+++ b/new_partner_bar.py
@@ -75,14 +75,16 @@ class Solution:
                                 new_partner_succ += 1
                     su_after[is_coop] += new_partner_succ
         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
 
 
 if __name__ == '__main__':
-    mode = 'CLASSIC'
-    s = Solution(mode)
-    su_after = s.new_partner_after()
+    sc = Solution('CLASSIC')
+    npc_after = sc.new_partner_after()
+    ss = Solution('SURVIVE')
+    nps_after = ss.new_partner_after()
     index = np.arange(2)
     
     blue = '#0984e3'
@@ -90,20 +92,23 @@ if __name__ == '__main__':
 
     fig = plt.figure(figsize=(3, 3))
     ax = fig.gca()
-    bar_width = 0.5
+    bar_width = 0.35
     opacity = 1
     error_config = {'ecolor': '0.3', 'capsize': 4}
-    rects1 = ax.bar(index, su_after, bar_width,
-                    color=red, label='New Patner')
+    rects1 = ax.bar(index, nps_after, bar_width,
+                    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_title('Scores by group and gender')
-    ax.set_xticks(index)
+    ax.set_ylabel('Rate')
+    # ax.set_title('Rate of Successfully Making New Partner')
+    ax.set_xlabel('Previous Move')
+    ax.set_xticks(index + bar_width / 2)
     ax.set_xticklabels(['C', 'D'])
     ax.set_ylim(0,1)
-    ax.set_xlim(-0.5,1.5)
     ax.legend()
 
     fig.tight_layout()
     # plt.show()
-    plt.savefig("graph/new_partner_bar_%s.eps" % mode)
+    # plt.savefig("graph/new_partner_bar.eps")
diff --git a/rewiring_rate.py b/rewiring_rate.py
index f7acd4a..0289226 100644
--- a/rewiring_rate.py
+++ b/rewiring_rate.py
@@ -18,7 +18,7 @@ def p1(x, rewires, tau, postfix, show):
     ax2 = ax.twinx()
     ax2.plot(x, tau, color=red, linewidth=3)
     ax2.set_ylim(0, 1440)
-    ax.set_xlim(1, 14)
+    ax.set_xlim(2, 15)
     ax.set_xlabel("Rounds")
     ax.set_ylabel("Rewiring Rate", color=green)
     ax.tick_params(axis='y', labelcolor=green)
@@ -31,11 +31,31 @@ def p1(x, rewires, tau, postfix, show):
     else:
         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):
     # # p2散点图
-    fig = plt.figure(figsize=(6.4, 3.6))
+    fig = plt.figure(figsize=(4, 3))
     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)
@@ -51,7 +71,7 @@ def p2(tau, rewires, postfix, show):
     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_xticks(sp.linspace(0, 1440, 7))
     ax.set_ylim(0, 0.6)
     plt.tight_layout()
     if show:
@@ -64,7 +84,7 @@ def p2(tau, rewires, postfix, show):
 
 
 if __name__ == '__main__':
-    mode = 'CLASSIC'
+    mode = 'SURVIVE'
     matches = Matches.from_profile_expr(lambda r: mode in r)
     max_round = 15
 
@@ -74,7 +94,7 @@ if __name__ == '__main__':
 
     neighbors = {}
     rewires = []
-    x = np.arange(1, max_round)
+    x = np.arange(2, max_round+1)
     mwRe = {} # Match-wise frequency of rewiring
     mwTau = {} # Match-wise Tau
     tau = []
@@ -94,7 +114,7 @@ if __name__ == '__main__':
                 n[r['b']] = [r['a']]    
         neighbors[matches.names[i]] = n
 
-    for i in range(max_round-1):
+    for i in range(1, max_round):
         re = []
         for j in range(len(matches.data)):
             rewire = 0
@@ -110,7 +130,7 @@ if __name__ == '__main__':
             rewires.append(np.average(re))
 
 
-    for i in range(max_round-1):
+    for i in range(1, max_round):
         tp = []
         for j in range(len(matches.data)):
             if i == 0:
@@ -148,8 +168,10 @@ if __name__ == '__main__':
     red = '#d63031'
 
     # p1折线图
-    # p1(x, rewires, tau, mode, False)
-    p2(tau, rewires, mode, False)
+    # p1(x, rewires, tau, mode, True)
+    # p2c(tau, rewires, False)
+    p2(tau[:12], rewires[:12], mode, False)
+    
    
 '''
 classic
@@ -157,12 +179,12 @@ classic
 Model parameter: [  9.81549075e-04  -9.87729952e-01]
 error= 0.058738
 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
-残差： [ 0.05788203]
-Model parameter: [ 0.00033232 -0.06283898]
-error= 0.057882
-Other parameters: rank=2, sv=[ 1.3284034   0.48512309], rcond=3.10862446895e-15
-pearson: 0.893237, p-value: 0.000017
+残差： [ 0.00293523]
+Model parameter: [ 0.00016483 -0.02259405]
+error= 0.002935
+Other parameters: rank=2, sv=[ 1.33437859  0.46843758], rcond=2.6645352591e-15
+pearson: 0.947167, p-value: 0.000003
 '''
diff --git a/tau_p_co.py b/tau_p_co.py
index 6a14af5..923a2f9 100644
--- a/tau_p_co.py
+++ b/tau_p_co.py
@@ -15,20 +15,21 @@ def error(f,x,y):
     return sp.sum((f(x)-y)**2)
 
 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.plot(x, coopr, color=blue, linewidth=3)
-    ax.set_ylim(0.5, 1)
+    ax.plot(x, coopr, color=blue, linewidth=2, label="$f_c$")
+    ax.set_ylim(0, 1)
     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)
-    ax.set_xlim(1, 14)
+    ax.set_xlim(1, 15)
     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)
-    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)
 
+    fig.legend()
     plt.tight_layout()
     if show:
         plt.show()
@@ -49,7 +50,7 @@ def p2(tau, coopr, limited, postfix, show=True):
             coopr_r.append(coopr[i])
 
     # p2散点图
-    fig = plt.figure(figsize=(6.4, 3.6))
+    fig = plt.figure(figsize=(4, 3))
     ax = fig.gca()
     # ax.set_ylim(0.5, 1)
     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.scatter(tau2, coopr2, color=blue, linewidths=2, zorder=100)
     plt.scatter(tau_r, coopr_r, color='white', edgecolors=blue, linewidths=2, zorder=101)
-    ax.set_xlabel('$\\tau_{p}$', family='sans-serif')
-    ax.set_ylabel('Frequency of Cooperation')
+    ax.set_xlabel(r'$\tau_{p}$', family='sans-serif')
+    ax.set_ylabel(r'$f_{c}$', family='sans-serif')
     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)
     plt.tight_layout()
     if show:
@@ -88,7 +89,7 @@ if __name__ == '__main__':
 
     neighbors = {}
     coopr = []
-    x = np.arange(1, max_round)
+    x = np.arange(1, max_round+1)
     mwCo = {} # Match-wise frequency of cooperation
     mwTau = {} # Match-wise Tau
     bx = []
@@ -109,7 +110,7 @@ if __name__ == '__main__':
                 n[r['b']] = [r['a']]    
         neighbors[matches.names[i]] = n
 
-    for i in range(max_round-1):
+    for i in range(max_round):
         co = []
         for j in range(len(matches.data)):
             coop = 0
@@ -130,7 +131,7 @@ if __name__ == '__main__':
             coopr.append(0)
 
 
-    for i in range(max_round-1):
+    for i in range(max_round):
         tp = []
         for j in range(len(matches.data)):
             if i == 0:
@@ -168,18 +169,13 @@ if __name__ == '__main__':
     red = '#d63031'
 
     # 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
     残差： [ 0.00548837]
@@ -187,4 +183,12 @@ if __name__ == '__main__':
     Other parameters: rank=2, sv=[ 1.36321571  0.37635479], rcond=1.99840144433e-15
     error= 0.005488
     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
+
     '''