HBLR.py 文件源码

def updateGamma(self):
        task_matrices = np.zeros((self.n_tasks, self.num_feats, self.num_feats))
        for m in range(self.n_tasks):
            rho_vector = rhoFunction(np.array(self.xi[m]))
            rho_vector = rho_vector.reshape((1,-1))             # Make rho vector 2D
            task_X = self.task_dict[m]['X']
            # Note that the transposing doesn't exactly match the paper because our data format is slightly different
            rho_matrix = abs(rho_vector) * task_X.T
            task_matrices[m,:,:] = np.dot(rho_matrix, task_X)  

        for k in range(self.K):
            inner_sum = np.zeros((self.num_feats,self.num_feats))
            for m in range(self.n_tasks):
                inner_sum = inner_sum + self.phi[m,k] * task_matrices[m,:,:]
            self.gamma[k] = la.inv(la.inv(self.sigma) + 2*inner_sum)
            if self.debug: 
                print "gamma computation {0}".format(k), la.det(la.inv(self.sigma) + 2*inner_sum)