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fixed bug in sparse GP plotting

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This commit is contained in:
Nicolo Fusi 2013-05-21 16:36:12 +01:00
parent b59253fe01
commit 17a82f99bd
3 changed files with 2 additions and 33 deletions
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2
GPy/models/GP.py
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@ -173,7 +173,7 @@ class GP(model):
"""
# normalize X values
Xnew = (Xnew.copy() - self._Xmean) / self._Xstd
mu, var = self._raw_predict(Xnew, which_parts, full_cov)
mu, var = self._raw_predict(Xnew, which_parts=which_parts, full_cov=full_cov)
# now push through likelihood
mean, var, _025pm, _975pm = self.likelihood.predictive_values(mu, var, full_cov)

2
GPy/models/sparse_GP.py
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@ -234,7 +234,7 @@ class sparse_GP(GP):
Kxx = self.kern.Kdiag(Xnew, which_parts=which_parts)
var = Kxx - np.sum(Kx * np.dot(Kmmi_LmiBLmi, Kx), 0)
else:
assert which_parts=='all', "swithching out parts of variational kernels is not implemented"
# assert which_parts=='all', "swithching out parts of variational kernels is not implemented"
Kx = self.kern.psi1(self.Z, Xnew, X_variance_new)#, which_parts=which_parts) TODO: which_parts
mu = np.dot(Kx, self.Cpsi1V)
if full_cov: