sync

.gitignore

@@ -6,4 +6,5 @@ user*
 *.svg
 __pycache__
 .vscode
-.idea
+.idea
+new-cr

basic_info.py

@@ -0,0 +1,21 @@
+import datetime
+import json
+from island.matches import Matches
+
+
+def basic_info(name):
+    matches = Matches(name)
+    print(name)
+    for m in matches.data:
+        info = m.query(cat="game", act="created").raw_data[0]
+        config = json.loads(info['info']['config'])
+        print(f"{m.name}: network={config['network']['type']}, "
+              f"players={len(m.query('player', 'join').raw_data)}, "
+              f"game_end_at={info['info']['game_end_at']},"
+              f"game_start={datetime.datetime.fromtimestamp(int(info['info']['next_start'])).isoformat()}")
+
+
+if __name__ == '__main__':
+    basic_info("wos-data-no-tr")
+    basic_info("wos-data-2022-pd")
+    basic_info("wos-data-2022-sd")

calc_coopr_rate.py

@@ -4,46 +4,56 @@ import numpy as np
 import csv
 import json
 
+NAME = 'wos-data-2022-sd'
 
-def calcAndSave(mode, network_type=None):
-    MAX_ROUND = 28 # = game_end_at
+
+def calc_and_save(mode, network_type=None):
+    matches = Matches(NAME, network_type=network_type)
+    max_round = 0  # = game_end_at
+    for m in matches.data:
+        max_round = max(max_round, int(m.query('game', 'created').first()['info']['game_end_at']))
     # matches = Matches.from_profile(mode)
-    matches = Matches('wos-data-2022-1', network_type=network_type)
-    times = np.zeros(MAX_ROUND)
-    cs = np.zeros(MAX_ROUND)
+    times = np.zeros(max_round)
+    cs = np.zeros(max_round)
     crs = []
     for m in matches.data:
         maxr = int(m.query('game', 'created').first()['info']['game_end_at'])
-        c = [0]*maxr
-        for r in range(1, maxr+1):
+        c = [0.0] * maxr
+        for r in range(1, maxr + 1):
             rows = m.query('action', 'done').where(lambda x: x['rno'] == r).raw_data
-            coop = 0
+            actors = dict()  # pid -> [C,D]
+            coop_rate = 0.0
             for row in rows:
-                if row['act_a'] == 'C':
-                    coop += 1
-                if row['act_b'] == 'C':
-                    coop += 1
+                for side in ['a', 'b']:
+                    if row[side] not in actors:
+                        actors[row[side]] = [0, 0]
+                    if row[f'act_{side}'] == 'C':
+                        actors[row[side]][0] += 1
+                    else:
+                        actors[row[side]][1] += 1
             if rows:
-                times[r-1] += len(rows) * 2
-                cs[r-1] += coop
-                c[r - 1] = coop / (len(rows) * 2)
+                for v in actors.values():
+                    coop_rate += float(v[0]) / float(v[0] + v[1])
+
+                times[r - 1] += len(actors)
+                cs[r - 1] += coop_rate
+                c[r - 1] = coop_rate / len(actors)
         with open(f"outputs/CR_{m.name}.csv", 'w') as f:
             csv.writer(f).writerow(c)
         crs.append(c)
 
-    for i in range(MAX_ROUND):
-        if(times[i] == 0):
+    for i in range(max_round):
+        if times[i] == 0:
             times[i] = 1
     cs /= times
-    with open("outputs/CR_%s_%s.csv"%(mode, network_type), 'w') as f:
+    with open("outputs/CR_%s_%s.csv" % (mode, network_type), 'w') as f:
         csv.writer(f).writerow(cs)
-    with open("outputs/CRAW_%s_%s.json"%(mode, network_type), 'w') as f:
+    with open("outputs/CRAW_%s_%s.json" % (mode, network_type), 'w') as f:
         json.dump(crs, f)
 
+
 if __name__ == '__main__':
     # calcAndSave('CLASSIC')
     # calcAndSave('SURVIVE')
-    calcAndSave('NEW', 'BA')
-    calcAndSave('NEW', 'WS')
-
-
+    calc_and_save('NEW', 'BA')
+    calc_and_save('NEW', 'WS')

calc_reward2.py

@@ -0,0 +1,36 @@
+import json
+import csv
+from pathlib import Path
+from island.match import Match
+from island.matches import Matches
+
+userdata = {}
+with open('wos-award\\s2.csv', 'r', encoding='utf-8') as c:
+    for row in csv.reader(c):
+        userdata[int(row[0])] = {
+            'uid': row[0],
+            'name': row[1],
+            'email': row[2],
+            'reward': 0,
+            'participate': 0
+        }
+ms = Matches('wos-data-2022-1')
+for m in ms.data:
+    game_end_at = int(m.query('game', 'created').first()['info']['game_end_at'])
+    for r in m.query('user', 'fitness').raw_data:
+
+        if r['user'] in userdata:
+            userdata[r['user']]['reward'] += float(r['fitness'])/game_end_at
+            userdata[r['user']]['participate'] += 1
+total=0
+with open('user.reward.csv', 'w', encoding='utf-8') as out:
+    writer = csv.writer(out, lineterminator='\n')
+    writer.writerow(['uid', 'name', 'email', 'reward', 'participate'])
+    for k,v in userdata.items():
+        if v['reward'] == 0:
+            continue
+        r = round(v['reward'], 2)
+        writer.writerow([k, v['name'], v['email'], r, v['participate']])
+        total += r
+
+print("total: %.2f" % (total))

calc_reward3.py

@@ -0,0 +1,85 @@
+import json
+import csv
+from pathlib import Path
+from island.match import Match
+from island.matches import Matches
+
+user_data = {} # user_id => {m => match_count, s => total_score, w => total_win}
+winners = {} # match_id => [user_id]
+
+ms = Matches('wos-data-no-tr')
+for m in ms.data:
+    print(m.name)
+    if m.name in ['G1196', 'G1214']:
+        game_end_at = int(m.query('game', 'created').first()['info']['game_end_at'])
+        for r in m.query('user', 'fitness').raw_data:
+            if r['user'] not in user_data:
+                user_data[r['user']] = dict(m=0,s=0,w=0)
+            user_data[r['user']]['m'] += 1
+            user_data[r['user']]['s'] += float(r['fitness'])/game_end_at
+        r = m.query('game', 'winner').first()
+        for u in r['data']:
+            user_data[u]['w'] += 1
+        winners[m.name] = r['data']
+
+    else:
+        player_data = {} #player_id => game_count
+        user_data_this_match = {} # user_id => {g => game_count, s => avg_score}
+        for r in m.query('action', 'done').raw_data:
+            for p in [r['a'], r['b']]:
+                if p not in player_data:
+                    player_data[p] = 1
+                else:
+                    player_data[p] += 1
+
+        for r in m.query('player', 'join').raw_data:
+            if r['pid'] in player_data:
+                user_data_this_match[r['uid']] = dict(g=player_data[r['pid']], s=0)
+
+        for r in m.query('user', 'fitness').raw_data:
+            if r['user'] in user_data_this_match:
+                user_data_this_match[r['user']]['s'] = float(r['fitness'])/user_data_this_match[r['user']]['g']
+                if r['user'] not in user_data:
+                    user_data[r['user']] = dict(m=1, s=user_data_this_match[r['user']]['s'], w=0)
+                else:
+                    user_data[r['user']]['m'] += 1
+                    user_data[r['user']]['s'] += user_data_this_match[r['user']]['s']
+
+        top1 = dict(s=0, u=[])
+        top2 = dict(s=0, u=[])
+        top3 = dict(s=0, u=[])
+        for k,v in user_data_this_match.items():
+            if v['s'] > top1['s']:
+                top3 = top2
+                top2 = top1
+                top1 = dict(s=v['s'], u=[k])
+            elif v['s'] == top1['s']:
+                top1['u'].append(k)
+            elif v['s'] > top2['s']:
+                top3 = top2
+                top2 = dict(s=v['s'], u=[k])
+            elif v['s'] == top2['s']:
+                top2['u'].append(k)
+            elif v['s'] > top3['s']:
+                top3 = dict(s=v['s'], u=[k])
+            elif v['s'] == top3['s']:
+                top3['u'].append(k)
+
+        print('Match: ', m.name)
+        print('top1: ', json.dumps(top1))
+        print('top2: ', json.dumps(top2))
+        print('top3: ', json.dumps(top3))
+        winners[m.name] = top1['u']+top2['u']+top3['u']
+        for t in [top1, top2, top3]:
+            for u in t['u']:
+                user_data[u]['w'] += 1
+
+
+with open('user.avg.score.csv', 'w', encoding='utf-8') as f:
+    writer = csv.writer(f, lineterminator='\n')
+    for k,v in user_data.items():
+        avg_score = v['s']/v['m']
+        writer.writerow([k, v['s'], v['w'], avg_score])
+
+with open('winners.json', 'w', encoding='utf-8') as f:
+    json.dump(winners, f)

count_player.py

@@ -0,0 +1,26 @@
+import logging
+from island.matches import Matches
+
+
+def count(name="", network_type=None):
+    # matches = Matches.from_profile(mode)
+    matches = Matches(name, network_type=network_type)
+    players = 0
+    for m in matches.data:
+        c = len(m.query('player', 'join').raw_data)
+        
+        # logging.info("%s: %d", m.name, c)
+        print(f"{m.name}: {c}")
+        players += c
+    # logging.info("%s: %d", network_type, players)
+
+
+if __name__ == '__main__':
+    logging.basicConfig(level=logging.INFO)
+    # calcAndSave('CLASSIC')
+    # calcAndSave('SURVIVE')
+    # logging.info('BA')
+    # count('NEW', 'BA')
+    # logging.info('WS')
+    # count('NEW', 'WS')
+    count("wos-data-2022-sd")

fc_plot.py

@@ -19,7 +19,7 @@ nowak_survive = [0.50017833, 0.26068193, 0.88939394, 0.9595738, 0.99796403, 0.99
 santos_survive = [0.50071587, 0.27929701, 0.9098483, 0.938, 0.99437628, 0.99861352, 0.99877322, 1, 1, 1, 1, 1, 1, None, None]
 santos_classic = [0.49821874, 0.2757036, 0.26718917, 0.26270039, 0.25895974, 0.2562166, 0.25439971, 0.25290346, 0.25187032, 0.25097969, 0.25037406, 0.24983969, 0.24919843, 0.24884218, 0.24862843]
 
-MAX_ROUND = 16
+MAX_ROUND = 10
 
 def p1(x, coopr, crawx, crawy, postfix, show=True):
     fig = plt.figure(figsize=(5, 2))
@@ -39,7 +39,8 @@ def p1(x, coopr, crawx, crawy, postfix, show=True):
     ax.tick_params(labelsize=10)
     ax.tick_params(direction='in')
     ax.set_xlim(0, MAX_ROUND+1)
-    ax.set_xticks([1, 5, 10, 15])
+    # ax.set_xticks([1, 5, 10, 15, 20, 25, 30])
+    ax.set_xticks([1, 5, 10])
     # ax.set_xticklabels([''])
     ax.set_xlabel("Rounds", size=11)
     ax.set_ylabel(r"f$_{\rm c}$", size=11, fontstyle='normal')
@@ -76,7 +77,6 @@ if __name__ == '__main__':
     elif argv[1] == 'nb':
         mode = 'NEW'
         network_type = 'BA'
-        MAX_ROUND = 28
     else:
         mode = 'NEW'
         network_type = 'WS'

is_pd.py

@@ -0,0 +1,13 @@
+import json
+from island.matches import Matches
+
+
+def ispd(name):
+    matches = Matches(name)
+    for m in matches.data:
+        config = json.loads(m.query(cat="game", act="created").raw_data[0]['info']['config'])
+        print(f"{m.name}: {config['payoffs']['DD'] == [1, 1]}")
+
+
+if __name__ == '__main__':
+    ispd("wos-data-no-tr")

winners.json

@@ -0,0 +1 @@
+{"G1196": [450, 476, 458], "G1214": [496, 561, 460], "G1224": [564, 481, 359], "G1228": [467, 54, 489], "G1230": [408, 480, 463], "G1234": [472, 476, 515]}