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bug fix w.r.t. var_dtc.py

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This commit is contained in:
Zhenwen Dai 2014-03-18 12:35:28 +00:00
parent 9e64f116d8
commit 5acb66cf78
2 changed files with 25 additions and 4 deletions
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8
GPy/inference/latent_function_inference/var_dtc.py
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@ -134,7 +134,7 @@ class VarDTC(object):
# log marginal likelihood
log_marginal = _compute_log_marginal_likelihood(likelihood, num_data, output_dim, beta, het_noise,
psi0, A, LB, trYYT, data_fit, Y)
psi0, A, LB, trYYT, data_fit, VVT_factor)
#put the gradients in the right places
dL_dR = _compute_dL_dR(likelihood,
@ -208,7 +208,7 @@ class VarDTCMissingData(object):
self._subarray_indices = [[slice(None),slice(None)]]
return [Y], [(Y**2).sum()]
def inference(self, kern, X, Z, likelihood, Y):
def inference(self, kern, X, Z, likelihood, Y, Y_metadata=None):
if isinstance(X, VariationalPosterior):
uncertain_inputs = True
psi0_all = kern.psi0(Z, X)
@ -305,7 +305,7 @@ class VarDTCMissingData(object):
# log marginal likelihood
log_marginal += _compute_log_marginal_likelihood(likelihood, num_data, output_dim, beta, het_noise,
psi0, A, LB, trYYT, data_fit)
psi0, A, LB, trYYT, data_fit,VVT_factor)
#put the gradients in the right places
dL_dR += _compute_dL_dR(likelihood,
@ -420,7 +420,7 @@ def _compute_dL_dR(likelihood, het_noise, uncertain_inputs, LB, _LBi_Lmi_psi1Vf,
def _compute_log_marginal_likelihood(likelihood, num_data, output_dim, beta, het_noise, psi0, A, LB, trYYT, data_fit,Y):
#compute log marginal likelihood
if het_noise:
lik_1 = -0.5 * num_data * output_dim * np.log(2. * np.pi) + 0.5 * np.sum(np.log(beta)) - 0.5 * np.sum(beta * Y**2)
lik_1 = -0.5 * num_data * output_dim * np.log(2. * np.pi) + 0.5 * np.sum(np.log(beta)) - 0.5 * np.sum(beta * np.square(Y).sum(axis=-1))
lik_2 = -0.5 * output_dim * (np.sum(beta.flatten() * psi0) - np.trace(A))
else:
lik_1 = -0.5 * num_data * output_dim * (np.log(2. * np.pi) - np.log(beta)) - 0.5 * beta * trYYT