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fix the bug in the prediction of full covariance matrix

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This commit is contained in:
Zhenwen Dai 2018-10-29 14:45:36 +00:00
parent 4f3047e035
commit bae67d584e
1 changed files with 2 additions and 1 deletions
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3
GPy/inference/latent_function_inference/posterior.py
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@ -245,6 +245,7 @@ class Posterior(object):
for i in range(var.shape[1]):
var[:, i] = (Kxx - (np.sum(np.dot(woodbury_inv[:, :, i].T, Kx) * Kx, 0)))
var = var
var = np.clip(var, 1e-15, np.inf)
else:
psi0_star = kern.psi0(pred_var, Xnew)
psi1_star = kern.psi1(pred_var, Xnew)
@ -265,7 +266,7 @@ class Posterior(object):
var += -psi2_star.reshape(N, -1).dot(woodbury_inv.flat)[:, None]
else:
var += -psi2_star.reshape(N, -1).dot(woodbury_inv.reshape(-1, D))
var = np.clip(var, 1e-15, np.inf)
var = np.clip(var, 1e-15, np.inf)
return mu, var