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[SSGPLVM] support linear kernel with ARD off

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Zhenwen Dai 2014-03-06 10:24:19 +00:00
parent 21ba9663b6
commit a7b1f30c46
1 changed files with 5 additions and 1 deletions
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4
GPy/kern/_src/linear.py
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@ -110,6 +110,7 @@ class Linear(Kern):
gamma = variational_posterior.binary_prob gamma = variational_posterior.binary_prob
mu = variational_posterior.mean mu = variational_posterior.mean
S = variational_posterior.variance S = variational_posterior.variance
return np.einsum('q,nq,nq->n',self.variances,gamma,np.square(mu)+S) return np.einsum('q,nq,nq->n',self.variances,gamma,np.square(mu)+S)
# return (self.variances*gamma*(np.square(mu)+S)).sum(axis=1) # return (self.variances*gamma*(np.square(mu)+S)).sum(axis=1)
else: else:
@ -150,7 +151,10 @@ class Linear(Kern):
_dpsi2_dvariance, _, _, _, _ = linear_psi_comp._psi2computations(self.variances, Z, mu, S, gamma) _dpsi2_dvariance, _, _, _, _ = linear_psi_comp._psi2computations(self.variances, Z, mu, S, gamma)
grad = np.einsum('n,nq,nq->q',dL_dpsi0,gamma,mu2S) + np.einsum('nm,nq,mq,nq->q',dL_dpsi1,gamma,Z,mu) +\ grad = np.einsum('n,nq,nq->q',dL_dpsi0,gamma,mu2S) + np.einsum('nm,nq,mq,nq->q',dL_dpsi1,gamma,Z,mu) +\
np.einsum('nmo,nmoq->q',dL_dpsi2,_dpsi2_dvariance) np.einsum('nmo,nmoq->q',dL_dpsi2,_dpsi2_dvariance)
if self.ARD:
self.variances.gradient = grad self.variances.gradient = grad
else:
self.variances.gradient = grad.sum()
else: else:
#psi1 #psi1
self.update_gradients_full(dL_dpsi1, variational_posterior.mean, Z) self.update_gradients_full(dL_dpsi1, variational_posterior.mean, Z)