"""
计算theta_r
theta_r_i=所有邻居的剩余时间

输出：
1. json格式(详细)
{
    "GID": {
        "RID": {
            "PID": theta_r_i,
        }
    }
}
2. CSV格式(按轮平均值, CLASSIC/SURVIVE分别对应一个文件)
"""
import csv
import json
from functools import reduce
from sre_constants import MAX_REPEAT
from tkinter.tix import MAX
import numpy as np
from island.match import Match
from island.matches import Matches

MAX_ROUND = 28

class theta_r_i:
    def __init__(self):
        self.details = {}
        self.survivals = {}
        with open('outputs/survivals_new.json','r') as f:
            self.survivals = json.load(f)
        self.neighbors = {}
        with open('outputs/neighborhood_new.json', 'r') as f:
            self.neighbors = json.load(f)
        self.seasons = [
            dict(season=Matches('wos-data-2022', network_type='BA'), name='NEW_BA'),
            dict(season=Matches('wos-data-2022', network_type='WS'), name='NEW_WS')
        ]
        # self.seasonSurvive = Matches.from_profile('SURVIVE')
        # self.seasonClassic = Matches.from_profile('CLASSIC')


    def getNeighborTR(self, m, r, p, s):
        """
        获取该玩家所有邻居的剩余时间
        
        :param m: Match
        :param r: Round ID
        :param p: PID
        :param s: Survivals list(neighborhood)
        :returns: theta_{r}_{i}
        """
        return 1440*len(s) - reduce(lambda a, b: a + b['tr'], m.query('action', 'done').where(lambda x: x['rno'] == r and ((x['a'] in s)or(x['b']in s))).raw_data, 0)


    def getNeighborhood(self, m, r, p):
        """
        获取该玩家当轮存活邻居
        
        :param m: Match
        :param r: Round ID
        :param p: PID
        :returns: Survivals list(neighborhood)
        """
        if str(p) not in self.neighbors[m.name]:
            print("Alone(%d)!" % p)
            return []
        return [i for i in self.survivals[m.name][str(r)] if i in self.neighbors[m.name][str(p)]]


    def calcRoundData(self, m, r):
        """
        计算某场比赛，某一轮的theta值
        
        :param m: Match
        :param r: Round ID
        :param p: PID
        :returns: an average value and a detail dict
        """
        r += 1
        ans = {}
        sigma = 0.0
        for p in self.survivals[m.name][str(r)]:
            e = max(0, min(144000000, self.getNeighborTR(m, r, p, self.getNeighborhood(m, r, p))))
            ans[p] = e
            sigma += e
        return (sigma, ans)

    def calc_season(self, season, name):
        """
        calc E_i,D
        """
        avg = np.zeros(MAX_ROUND)
        cnt = np.zeros(MAX_ROUND)
        for m in season.data:
            d = {}
            maxr = int(m.query('game', 'created').first()['info']['game_end_at'])
            for r in range(1, maxr):
                sigma, ans = self.calcRoundData(m, r)
                d[r] = ans
                avg[r-1] += sigma
                cnt[r-1] += len(ans)
            self.details[m.name] = d
        print(cnt)
        for i in range(MAX_ROUND): 
            if cnt[i] == 0: 
                cnt[i] = 1
        avg /= cnt
        with open(f'outputs/EID_{name}.csv', 'w') as f:
            csv.writer(f).writerow(avg)
        return avg

    def calc(self):
        for s in self.seasons:
            self.calc_season(s['season'], s['name'])
        with open('outputs/EID_new_detail.json', 'w') as f:
            json.dump(self.details, f)
        
if __name__ == '__main__':
    e = theta_r_i()
    e.calc()