hmm_states.py 文件源码

def _expected_statistics_from_messages_slow(trans_potential,likelihood_log_potential,alphal,betal):
        expected_states = alphal + betal
        expected_states -= expected_states.max(1)[:,na]
        np.exp(expected_states,out=expected_states)
        expected_states /= expected_states.sum(1)[:,na]

        Al = np.log(trans_potential)
        log_joints = alphal[:-1,:,na] + (betal[1:,na,:] + likelihood_log_potential[1:,na,:]) + Al[na,...]
        log_joints -= log_joints.max((1,2))[:,na,na]
        joints = np.exp(log_joints)
        joints /= joints.sum((1,2))[:,na,na] # NOTE: renormalizing each isnt really necessary
        expected_transcounts = joints.sum(0)

        normalizer = np.logaddexp.reduce(alphal[0] + betal[0])

        return expected_states, expected_transcounts, normalizer

    ### EM