def likelihood(self,beta):
		_, F, v = self.model(beta)

		loglik = 0
		for i in xrange(0,self.data.shape[0]):
			loglik += np.linalg.slogdet(F[:,:,i])[1] + np.dot(v[i],np.dot(np.linalg.pinv(F[:,:,i]),v[i]))
		return -(-((self.data.shape[0]/2)*log(2*pi))-0.5*loglik.T[0].sum())
dataset/ETHPy150Open RJT1990/pyflux/pyflux/ssm/llm.py/LLEV.likelihood/original