import math

class Glicko2:
    _tau = 0.5

    def getRating(self):
        return (self.__rating * 173.7178) + 1500 

    def setRating(self, rating):
        self.__rating = (rating - 1500) / 173.7178

    rating = property(getRating, setRating)

    def getRd(self):
        return self.__rd * 173.7178

    def setRd(self, rd):
        self.__rd = rd / 173.7178

    rd = property(getRd, setRd)
        
    def __init__(self, rating = 1500, rd = 350, vol = 0.06):

        self.setRating(rating)
        self.setRd(rd)
        self.vol = vol
            
    def _preRatingRD(self):

        self.__rd = math.sqrt(math.pow(self.__rd, 2) + math.pow(self.vol, 2))
        
    def update_player(self, rating_list, RD_list, outcome_list):

        rating_list = [(x - 1500) / 173.7178 for x in rating_list]
        RD_list = [x / 173.7178 for x in RD_list]

        v = self._v(rating_list, RD_list)
        self.vol = self._newVol(rating_list, RD_list, outcome_list, v)
        self._preRatingRD()
        
        self.__rd = 1 / math.sqrt((1 / math.pow(self.__rd, 2)) + (1 / v))
        
        tempSum = 0
        for i in range(len(rating_list)):
            tempSum += self._g(RD_list[i]) * \
                        (outcome_list[i] - self._E(rating_list[i], RD_list[i]))
        self.__rating += math.pow(self.__rd, 2) * tempSum
        
        
    def _newVol(self, rating_list, RD_list, outcome_list, v):

        i = 0
        delta = self._delta(rating_list, RD_list, outcome_list, v)
        a = math.log(math.pow(self.vol, 2))
        tau = self._tau
        x0 = a
        x1 = 0
        
        while x0 != x1:
            # New iteration, so x(i) becomes x(i-1)
            x0 = x1
            d = math.pow(self.__rating, 2) + v + math.exp(x0)
            h1 = -(x0 - a) / math.pow(tau, 2) - 0.5 * math.exp(x0) \
            / d + 0.5 * math.exp(x0) * math.pow(delta / d, 2)
            h2 = -1 / math.pow(tau, 2) - 0.5 * math.exp(x0) * \
            (math.pow(self.__rating, 2) + v) \
            / math.pow(d, 2) + 0.5 * math.pow(delta, 2) * math.exp(x0) \
            * (math.pow(self.__rating, 2) + v - math.exp(x0)) / math.pow(d, 3)
            x1 = x0 - (h1 / h2)

        return math.exp(x1 / 2)
        
    def _delta(self, rating_list, RD_list, outcome_list, v):

        tempSum = 0
        for i in range(len(rating_list)):
            tempSum += self._g(RD_list[i]) * (outcome_list[i] - self._E(rating_list[i], RD_list[i]))
        return v * tempSum
        
    def _v(self, rating_list, RD_list):

        tempSum = 0
        for i in range(len(rating_list)):
            tempE = self._E(rating_list[i], RD_list[i])
            tempSum += math.pow(self._g(RD_list[i]), 2) * tempE * (1 - tempE)
        return 1 / tempSum
        
    def _E(self, p2rating, p2RD):

        return 1 / (1 + math.exp(-1 * self._g(p2RD) * \
                                    (self.__rating - p2rating)))
        
    def _g(self, RD):

        return 1 / math.sqrt(1 + 3 * math.pow(RD, 2) / math.pow(math.pi, 2))
        
    def did_not_compete(self):

        self._preRatingRD()