def get_bayes_optimal(self):
        params = np.zeros((3,2))
        p1 = self.balance
        p2 = 1.0 - self.balance
        params[0,0] = (2.0*self.variance1) * np.dot(self.mean1,self.mean1)/-1.0 + np.log(p1)
        params[0,1] = -1.0/(2.0*self.variance2) * np.dot(self.mean2,self.mean2) + np.log(p2)
        params[1,0] = 1.0/self.variance1 * self.mean1[0]
        params[2,0] = 1.0/self.variance1 * self.mean1[1]
        params[1,1] = 1.0/self.variance2 * self.mean2[0]
        params[2,1] = 1.0/self.variance2 * self.mean2[1]
        ##print params
        return params
dataset/ETHPy150Open alvations/pywsd/merlin/simple_data_set.py/SimpleDataSet.get_bayes_optimal/swapped operands of `/`