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minor bugfixes in plotting: quantiles are now computed using predict_kw

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correctly
This commit is contained in:
James Hensman 2015-08-18 08:00:47 +01:00
parent 097b048100
commit ea3bfbb597
4 changed files with 9 additions and 5 deletions
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3
GPy/models/gp_var_gauss.py
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@ -60,7 +60,8 @@ class GPVariationalGaussianApproximation(Model):
var = np.diag(Sigma).reshape(-1,1)
F, dF_dm, dF_dv, dF_dthetaL = self.likelihood.variational_expectations(self.Y, m, var, Y_metadata=self.Y_metadata)
self.likelihood.gradient = dF_dthetaL.sum(1).sum(1)
if dF_dthetaL is not None:
self.likelihood.gradient = dF_dthetaL.sum(1).sum(1)
dF_da = np.dot(K, dF_dm)
SigmaB = Sigma*self.beta
dF_db = -np.diag(Sigma.dot(np.diag(dF_dv.flatten())).dot(SigmaB))*2