sync

eid_calc.py

@@ -61,6 +61,10 @@ class Eid:
 
         return reduce(lambda x,y: x + max(0,min(y,1440)), trs.values(), 0)
 
+    def getTR2(self, m, r, p, s, d):
+        truenb = [i for i in s if i not in d]
+        return reduce(lambda a, b: a + b['tr'], m.query('action', 'done').where(lambda x: x['rno'] == r and ((x['a'] in truenb and x['b'] == p)or(x['b']in truenb and x['a'] == p))).raw_data, 0)
+
     def getNeighborhood(self, m, r, p):
         """
         获取该玩家当轮存活邻居
@@ -86,7 +90,7 @@ class Eid:
         """
         victim = []
         ans = 0
-        for d in m.query('action', 'done').where(lambda x: x['rno'] == r and (x['a'] == p or x['b'] == p)).raw_data:
+        for d in m.query('action', 'done').where(lambda x: x['rno'] == r-1 and (x['a'] == p or x['b'] == p)).raw_data:
             if d['a'] == p and d['act_a'] == 'D':
                 victim.append(d['b'])
                 ans += d['tr']
@@ -124,10 +128,11 @@ class Eid:
         ans = {}
         sigma = 0.0
         for p in self.survivals[m.name][str(r)]:
-            u, v = self.getVictims2(m, r+1, p)
-            e = max(0, min(1440, self.getNeighborTR(m, r, p, self.getNeighborhood(m, r, p), v))) - u
-            ans[p] = e
-            sigma += e
+            u, v = self.getVictims(m, r, p)
+            if u > 0:
+                e = max(0, min(1440, self.getTR2(m, r, p, self.getNeighborhood(m, r, p), v))) - u
+                ans[p] = e
+                sigma += e
         return (sigma, ans)
 
     def calc(self):
@@ -144,6 +149,10 @@ class Eid:
                 avgC[r-1] += sigma
                 cnt[r-1] += len(ans)
             detail[m.name] = d
+        print(cnt)
+        for i in range(15): 
+            if cnt[i] == 0: 
+                cnt[i] = 1
         avgC /= cnt
         cnt = np.zeros(15)
         for m in self.seasonSurvive.data:
@@ -155,6 +164,10 @@ class Eid:
                 avgS[r-1] += sigma
                 cnt[r-1] += len(ans)
             detail[m.name] = d
+        print(cnt)
+        for i in range(15): 
+            if cnt[i] == 0: 
+                cnt[i] = 1
         avgS /= cnt
         with open('outputs/EID_CLASSIC.csv', 'w') as f:
             csv.writer(f).writerow(avgC)
@@ -165,4 +178,4 @@ class Eid:
         
 if __name__ == '__main__':
     e = Eid()
-    e.calc()
+    e.calc()

eid_plot.py

@@ -3,6 +3,7 @@ from matplotlib import pyplot as plt
 import scipy as sp
 from scipy.stats import pearsonr
 from matplotlib import markers
+from sys import argv
 blue = '#0984e3'
 red = '#d63031'
 
@@ -15,7 +16,7 @@ def p1(x, coopr, e, postfix, show=True):
     ax.set_ylim(0, 1)
     ax.set_yticks(sp.linspace(0, 1, 5))
     ax2 = ax.twinx()
-    ax2.plot(x, e, color=red, linewidth=2, label=r"$E_{i,D}$")
+    ax2.plot(x[1:], e[1:], color=red, linewidth=2, label=r"$E_{i,D}$")
     # ax2.set_ylim(0, 1440)
     # ax2.set_yticks(sp.linspace(0, 1440, 5))
     ax2.tick_params(labelsize=18)
@@ -33,29 +34,28 @@ def p1(x, coopr, e, postfix, show=True):
     else:
         plt.savefig("graph/eid_co_plot_%s.eps" % postfix)
 
-def p2(e, coopr, postfix, show=True):
+def p2(e, coopr, postfix, show=True, showline=True):
     # p2散点图
     fig = plt.figure(figsize=(4, 3))
     ax = fig.gca()
-    fp1,residuals,rank,sv,rcond = sp.polyfit(e, coopr, 1, full=True)
-    print("残差：",residuals)
-    print('Model parameter:',fp1)
-    print("Other parameters: rank=%s, sv=%s, rcond=%s"%(str(rank), str(sv), str(rcond)))
-    f1 = sp.poly1d(fp1)
-    print("error= %f" % error(f1, e, coopr))
-    fx = sp.linspace(np.min(e), np.max(e), 2)
-
-    plt.plot(fx,f1(fx),linewidth=2,color=red, ls='--', zorder=0)
-
+    if showline:
+        fp1,residuals,rank,sv,rcond = sp.polyfit(e, coopr, 1, full=True)
+        print("残差：",residuals)
+        print('Model parameter:',fp1)
+        print("Other parameters: rank=%s, sv=%s, rcond=%s"%(str(rank), str(sv), str(rcond)))
+        f1 = sp.poly1d(fp1)
+        print("error= %f" % error(f1, e, coopr))
+        fx = sp.linspace(np.min(e), np.max(e), 2)
+        plt.plot(fx,f1(fx),linewidth=2,color=red, ls='--', zorder=0)
 
     plt.scatter(e, coopr, color='white', edgecolors=blue, linewidths=2, zorder=101)
     ax.set_xlabel(r'$E_{i,D}$', family='sans-serif', size=20)
     ax.set_ylabel(r'$f_{c}$', family='sans-serif', size=20)
     # ax.set_xlim(0, 1440)
-    # ax.set_xticks(sp.linspace(0, 1440, 5))
+    # ax.set_xticks(sp.linspace(int(min(e)*0.9), int(max(e)*1.1), 4))
     ax.tick_params(labelsize=14)
-    ax.set_ylim(0.5, 1)
-    ax.set_yticks(sp.linspace(0.5, 1, 5))
+    ax.set_ylim(0.6, 1)
+    ax.set_yticks(sp.linspace(0.6, 1, 5))
     plt.tight_layout()
     if show:
         plt.show()
@@ -65,21 +65,28 @@ def p2(e, coopr, postfix, show=True):
     # 皮尔逊相关系数
     print("pearson: %f, p-value: %f" % pearsonr(e, coopr))
 
-if __name__ == '__main__':
-    mode = 'CLASSIC'
-    mode = 'SURVIVE'
+def p2c(e,c,m,s):
+    p2(e,c,m,s,False)
 
-    show = False
-    show = True
-
-    coopr = np.loadtxt("outputs/CR_%s.csv"%mode, delimiter=',')
+def plot(mode, show, isp1):
+    coopr = np.loadtxt("outputs/CR_%s.csv" % mode, delimiter=',')
     x = np.arange(1, 16)
-    e = np.loadtxt("outputs/EID_%s.csv"%mode, delimiter=',')
+    e = np.loadtxt("outputs/EID_%s.csv" % mode, delimiter=',')
 
-    p1(x,coopr, e, mode, show)
-    # p2(e, coopr, mode, show)
-    
+    if isp1:
+        p1(x, coopr, e, mode, show)
+    else:
+        if mode == 'SURVIVE':
+            p2(e[1:12], coopr[1:12], mode, show)
+        else:
+            p2c(e[1:], coopr[1:], mode, show)
 
+if __name__ == '__main__':
+    # eid_plot c/s 1/2 t/f
+    mode = 'CLASSIC' if argv[1] == 'c' else 'SURVIVE'
+    isp1 = argv[2] == '1'
+    show = argv[3] == 't'
+    plot(mode, show, isp1)
 
     """
 SURVIVE
@@ -96,4 +103,4 @@ Model parameter: [  3.14661037e-05   7.35284315e-01]
 Other parameters: rank=2, sv=[ 1.41231835  0.07319068], rcond=3.33066907388e-15
 error= 0.009927
 pearson: 0.309326, p-value: 0.261915
-    """
+    """

fc_plot.py

@@ -0,0 +1,38 @@
+import numpy as np
+from matplotlib import pyplot as plt
+import scipy as sp
+from scipy.stats import pearsonr
+from matplotlib import markers
+from sys import argv
+blue = '#0984e3'
+red = '#d63031'
+
+def p1(x, coopr, postfix, show=True):
+    fig = plt.figure(figsize=(4.5, 3))
+    ax = fig.gca()
+    ax.plot(x, coopr, 'o-', color=blue, linewidth=2, label="$f_c$")
+    ax.set_ylim(0, 1)
+    ax.set_yticks(sp.linspace(0, 1, 5))
+    ax.tick_params(labelsize=18)
+    ax.set_xlim(0, 16)
+    ax.set_xlabel("Rounds", size=22)
+    ax.set_ylabel(r"$f_c$", family='sans-serif', size=22)
+    ax.yaxis.grid(True, linestyle='--')
+
+    plt.tight_layout()
+    if show:
+        plt.show()
+    else:
+        plt.savefig("graph/fc_plot_%s.eps" % postfix)
+
+
+def plot(mode, show):
+    coopr = np.loadtxt("outputs/CR_%s.csv" % mode, delimiter=',')
+    x = np.arange(1, 16)
+    p1(x, coopr, mode, show)
+
+if __name__ == '__main__':
+    # fc_plot c/s t/f
+    mode = 'CLASSIC' if argv[1] == 'c' else 'SURVIVE'
+    show = argv[2] == 't'
+    plot(mode, show)

outputs/EID_CLASSIC.csv

@@ -1 +1 @@
-180.0,-41.8604651163,-124.186046512,-69.7674418605,-44.6511627907,-164.651162791,-69.7674418605,-92.0930232558,-97.6744186047,-101.860465116,-209.032258065,-213.71024735,-104.939271255,-165.755395683,-649.411764706
+0.0,-965.647058824,-1052.30769231,-1074.92957746,-944.262295082,-884.571428571,-1140.0,-1143.52941176,-1188.57142857,-1249.41176471,-1047.27272727,-1097.14285714,-1200.0,-1260.0,-1440.0

outputs/EID_SURVIVE.csv

@@ -1 +1 @@
--58.293956044,-788.740365112,-833.236533958,-1329.43820225,-1278.73417722,-1369.30909091,-1370.60240964,-1343.59832636,-1427.42358079,-1392.89719626,-1440.0,-1440.0,-1390.34482759,-1440.0,-1152.0
+0.0,-944.835294118,-790.169230769,-551.851851852,-1107.69230769,-1280.0,-960.0,-1440.0,-1440.0,-1440.0,0.0,0.0,0.0,-411.428571429,-1440.0