sync

calc_coopr_rate.py

@@ -6,7 +6,7 @@ import json
 
 
 def calcAndSave(mode, network_type=None):
-    MAX_ROUND = 16 # = game_end_at
+    MAX_ROUND = 28 # = game_end_at
     # matches = Matches.from_profile(mode)
     matches = Matches('wos-data-2022-1', network_type=network_type)
     times = np.zeros(MAX_ROUND)

calc_participants.py

@@ -8,10 +8,11 @@ result = 0
 count = 0
 ma,mi=0,1000
 
-# ms = Matches.from_profile('CCCN')
+ms = Matches('wos-data-2022-1')
-ms = Matches.from_profile_expr(lambda r: True)
+# ms = Matches.from_profile_expr(lambda r: True)
 for m in ms.data:
     l = len(m.query('player', 'join').where(lambda x: 'bot' not in x or x['bot'] == False).select('pid').raw_data)
+    print(f"{m.name} => players: {l} game-end-at: {int(m.query('game', 'created').first()['info']['game_end_at'])}")
     ma = max([ma,l])
     mi = min([mi,l])
     result += l

calc_survivals.py

@@ -5,7 +5,7 @@ from island.match import Match
 result = {}
 
 # = game_end_at + 1
-MAX_ROUND = 17
+MAX_ROUND = 29
 
 for f in Path('wos-data-2022-1').iterdir():
     p = Path(f)

fc_plot.py

@@ -76,7 +76,7 @@ if __name__ == '__main__':
     elif argv[1] == 'nb':
         mode = 'NEW'
         network_type = 'BA'
-        MAX_ROUND = 14
+        MAX_ROUND = 28
     else:
         mode = 'NEW'
         network_type = 'WS'

outputs/CRAW_NEW_BA.json

@@ -1 +1 @@
-[[0.9329268292682927, 0.926829268292683, 0.845679012345679, 0.8506493506493507, 0.8287671232876712, 0.8375, 0.7608695652173914, 0.8333333333333334, 0.7954545454545454, 0.7214285714285714, 0.7578125, 0.7622950819672131, 0.6384615384615384, 0.5819672131147541], [0.9038461538461539, 0.831081081081081, 0.8066666666666666, 0.7246376811594203, 0.7578125, 0.7236842105263158, 0.7364864864864865, 0.7121212121212122, 0.7071428571428572, 0.717948717948718, 0.6890243902439024, 0.75, 0.753968253968254]]
+[[0.9329268292682927, 0.926829268292683, 0.845679012345679, 0.8506493506493507, 0.8287671232876712, 0.8375, 0.7608695652173914, 0.8333333333333334, 0.7954545454545454, 0.7214285714285714, 0.7578125, 0.7622950819672131, 0.6384615384615384, 0.5819672131147541], [0.7837837837837838, 0.6785714285714286, 0.76, 0.7727272727272727, 0.7843137254901961, 0.7363636363636363, 0.7653061224489796, 0.7608695652173914, 0.7325581395348837, 0.6794871794871795, 0.7307692307692307], [0.8166666666666667, 0.73, 0.7941176470588235, 0.8292682926829268, 0.75, 0.7159090909090909, 0.7674418604651163, 0.7631578947368421, 0.7, 0.7051282051282052, 0.6219512195121951, 0.6309523809523809, 0.6351351351351351, 0.5697674418604651, 0.48484848484848486, 0.625, 0.6447368421052632, 0.6621621621621622, 0.6125, 0.578125, 0.5714285714285714, 0.5285714285714286, 0.5925925925925926, 0.5833333333333334, 0.5833333333333334, 0.5645161290322581, 0.6212121212121212, 0.65625]]

outputs/CR_G646.csv

@@ -0,0 +1 @@
+0.7837837837837838,0.6785714285714286,0.76,0.7727272727272727,0.7843137254901961,0.7363636363636363,0.7653061224489796,0.7608695652173914,0.7325581395348837,0.6794871794871795,0.7307692307692307

outputs/CR_G903.csv

@@ -0,0 +1 @@
+0.8166666666666667,0.73,0.7941176470588235,0.8292682926829268,0.75,0.7159090909090909,0.7674418604651163,0.7631578947368421,0.7,0.7051282051282052,0.6219512195121951,0.6309523809523809,0.6351351351351351,0.5697674418604651,0.48484848484848486,0.625,0.6447368421052632,0.6621621621621622,0.6125,0.578125,0.5714285714285714,0.5285714285714286,0.5925925925925926,0.5833333333333334,0.5833333333333334,0.5645161290322581,0.6212121212121212,0.65625

outputs/CR_NEW_BA.csv

@@ -1 +1 @@
-0.91875,0.8814102564102564,0.8269230769230769,0.791095890410959,0.7956204379562044,0.782051282051282,0.7482517482517482,0.7753623188405797,0.75,0.7195945945945946,0.7191780821917808,0.7560975609756098,0.6953125,0.5819672131147541,0.0,0.0
+0.8631284916201117,0.800531914893617,0.8076923076923077,0.8208092485549133,0.7946428571428571,0.776536312849162,0.7639751552795031,0.7948717948717948,0.7516778523489933,0.706081081081081,0.7118055555555556,0.7087378640776699,0.6372549019607843,0.5769230769230769,0.48484848484848486,0.625,0.6447368421052632,0.6621621621621622,0.6125,0.578125,0.5714285714285714,0.5285714285714286,0.5925925925925926,0.5833333333333334,0.5833333333333334,0.5645161290322581,0.6212121212121212,0.65625

outputs/CR_NEW_WS.csv

@@ -1 +1 @@
-0.918918918918919,0.907563025210084,0.9012875536480687,0.8951219512195122,0.8853658536585366,0.8729729729729729,0.8532608695652174,0.8285714285714286,0.7774390243902439,0.7774566473988439,0.7212121212121212,0.6488095238095238,0.5911949685534591,0.4873417721518987,0.29411764705882354,0.23026315789473684
+0.918918918918919,0.907563025210084,0.9012875536480687,0.8951219512195122,0.8853658536585366,0.8729729729729729,0.8532608695652174,0.8285714285714286,0.7774390243902439,0.7774566473988439,0.7212121212121212,0.6488095238095238,0.5911949685534591,0.4873417721518987,0.29411764705882354,0.23026315789473684,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0

outputs/THETA_G646.csv

@@ -0,0 +1 @@
+1256.84,1210.5,1221.24,1081.78,946.94,1072.76,1051.78,1124.18,919.48,1169.78,917.66

outputs/THETA_G903.csv

@@ -0,0 +1 @@
+1104.9318181818182,1153.1818181818182,1088.3181818181818,997.8636363636364,1011.9318181818181,866.6136363636364,1082.7954545454545,1114.75,1043.1818181818182,981.8409090909091,1134.8863636363637,1091.8181818181818,1047.2727272727273,1127.9545454545455,1099.0227272727273,1085.3181818181818,977.1136363636364,1156.5227272727273,1065.25,1256.8181818181818,1096.3636363636363,1034.9772727272727,1101.2727272727273,1100.1136363636363,1210.4318181818182,1113.5681818181818,1254.5,1219.5227272727273

outputs/THETA_NEW_BA.csv

@@ -1 +1 @@
-1191.0056818181818,1216.3522727272727,1152.0625,1174.596590909091,1138.0397727272727,1154.2386363636363,1136.653409090909,1043.6306818181818,1175.3125,1062.5568181818182,1109.375,1223.6420454545455,1146.8693181818182,1195.0235294117647,0.0,0.0
+1135.877094972067,1121.2011173184358,1117.3519553072626,1060.5865921787708,995.4860335195531,1028.1061452513966,1058.0279329608938,994.8324022346369,1045.441340782123,1021.1899441340782,1048.703910614525,1178.108527131783,1034.5271317829458,1172.1472868217054,1099.0227272727273,1085.3181818181818,977.1136363636364,1156.5227272727273,1065.25,1256.8181818181818,1096.3636363636363,1034.9772727272727,1101.2727272727273,1100.1136363636363,1210.4318181818182,1113.5681818181818,1254.5,1219.5227272727273

outputs/THETA_NEW_WS.csv

@@ -1 +1 @@
-1283.093023255814,1227.2209302325582,1192.5116279069769,1209.8488372093022,1267.5523255813953,1283.5232558139535,1284.0813953488373,1305.1744186046512,1294.1976744186047,1322.5232558139535,1335.6802325581396,1326.1627906976744,1371.8081395348838,1350.3023255813953,1401.5747126436781,1405.2413793103449
+1283.093023255814,1227.2209302325582,1192.5116279069769,1209.8488372093022,1267.5523255813953,1283.5232558139535,1284.0813953488373,1305.1744186046512,1294.1976744186047,1322.5232558139535,1335.6802325581396,1326.1627906976744,1371.8081395348838,1350.3023255813953,1401.5747126436781,1405.2413793103449,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0

theta_plot.py

@@ -5,15 +5,15 @@ from matplotlib import markers
 blue = '#0984e3'
 red = '#d63031'
 
-MAX_ROUND = 16 # = game_end_at + 1
+MAX_ROUND = 28 # = game_end_at
 x = np.arange(1, MAX_ROUND+1)
 tc = np.loadtxt("outputs/THETA_NEW_BA.csv", delimiter=',')
 ts = np.loadtxt("outputs/THETA_NEW_WS.csv", delimiter=',')
 
 fig = plt.figure(figsize=(6,4.5))
 ax = fig.gca()
-ax.plot(x[:-2], tc[:-2], 'o--', color='limegreen', linewidth=2, label=r"BA")
+ax.plot(x, tc, 'o--', color='limegreen', linewidth=2, label=r"BA")
-ax.plot(x, ts, 'o-', color='darkorange', linewidth=2, label=r"WS")
+ax.plot(x[:15], ts[:15], 'o-', color='darkorange', linewidth=2, label=r"WS")
 
 # ax.set_ylim(-1500, 500)
 # ax.set_yticks(sp.linspace(-1500, 500, 6))

theta_r.py

@@ -22,7 +22,7 @@ import numpy as np
 from island.match import Match
 from island.matches import Matches
 
-MAX_ROUND = 16 # game_end_at
+MAX_ROUND = 28 # game_end_at
 
 class theta_r_i:
     def __init__(self):