def train(self, patterns):
        '''
        Compute weight matrix analytically
        '''
        #print('patterns',type(patterns),patterns)
        self.W = np.zeros((self.dim, self.dim))
        #print('self.W',self.W.shape,self.W)
        # P = len(patterns)
        P = patterns.shape[0]
        for i in range(self.W.shape[0]):
            for j in range(self.W.shape[1]):
                if i != j:
                    sum = 0
                    for p in range(len(patterns)):
                        sum += patterns[p][i]*patterns[p][j]
                    self.W[i,j] = (1/P)*sum
                else:
                    self.W[i,j] = 0