import numpy as np
class Work :
    """ X - is a matrix of pattern, when x_ is the string,
    that we want to compare with all our pattern
    in our program X.size(0) = 3
    X[i][j] in (0, 1)
    W - is a matrix of weigth
    net - is a helper string for y
    fnet - the result of f(net)
    y - is a string in previous iteration
    We calculate y while it is not one of patterns
    in the begining y = x_"""

    def __init__(self, X, x_):
        self.X = X
        self.x_ = x_
        self.y = x_
        self.fnet = x_
        self.W = self.init_W()
        self.k = 0

    def init_W(self):
        W = np.zeros((self.x_.shape[0],self.x_.shape[0]))
        for i in range (0, self.X.shape[0]):
            for j in range (0,self.X.shape[1]):
                for k in range (0,self.X.shape[1]):
                    if(k!=j):
                        W[j][k]+=X[i][j]*X[i][k]
        return W

    def next_net(self):
        net = np.zeros((self.y.shape[0]))
        for j in range(0, self.y.shape[0]):
            for k in range(0, self.y.shape[0]):
                if (k!=j):
                    net[k]+=self.W[j][k]*self.y[j]
        return net

    def f(self, net, fnet_old):
        fnet = np.zeros((net.shape[0]))
        for i in range(0, net.shape[0]):
            if (net[i] >0):
                fnet[i] = 1
            elif (net[i] == 0):
                fnet[i] = fnet_old[i]
            else:
                fnet[i] = -1
        return fnet



    def solution(self):
        self.k = 0
        while ((not(np.array_equal(self.y, self.X[0]))) and (not(np.array_equal(self.y, self.X[1])))
               and (not(np.array_equal(self.y, self.X[2])))):
            self.k+=1
            net = self.next_net()
            fnet = self.f(net, self.fnet)
            self.fnet = fnet
            self.y = self.fnet

        return self.y