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random 2 bug neutralized... not fixed

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Ricardo 2013-09-17 14:25:59 +01:00
parent 7e4dca7e3a
commit 6f8a1f81c4
2 changed files with 11 additions and 3 deletions
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13
GPy/core/sparse_gp.py
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@ -165,13 +165,17 @@ class SparseGP(GPBase):
raise NotImplementedError, "heteroscedatic derivates with uncertain inputs not implemented"
else:
LBi = chol_inv(self.LB)
Lmi_psi1, nil = dtrtrs(self._Lm, np.asfortranarray(self.psi1.T), lower=1, trans=0)
_LBi_Lmi_psi1, _ = dtrtrs(self.LB, np.asfortranarray(Lmi_psi1), lower=1, trans=0)
_Bi_Lmi_psi1, _ = dtrtrs(self.LB.T, np.asfortranarray(_LBi_Lmi_psi1), lower=1, trans=0)
self.partial_for_likelihood = -0.5 * self.likelihood.precision + 0.5 * self.likelihood.V**2
self.partial_for_likelihood += 0.5 * self.output_dim * (self.psi0 - np.sum(Lmi_psi1**2,0))[:,None] * self.likelihood.precision**2
self.partial_for_likelihood += 0.5*np.sum(_Bi_Lmi_psi1*Lmi_psi1,0)[:,None]*self.likelihood.precision**2 #NOTE this term has numerical issues
self.partial_for_likelihood += 0.5*np.sum(mdot(LBi.T,LBi,Lmi_psi1)*Lmi_psi1,0)[:,None]*self.likelihood.precision**2
self.partial_for_likelihood += -np.dot(self._LBi_Lmi_psi1Vf.T,_LBi_Lmi_psi1).T * self.likelihood.Y * self.likelihood.precision**2
self.partial_for_likelihood += 0.5*np.dot(self._LBi_Lmi_psi1Vf.T,_LBi_Lmi_psi1).T**2 * self.likelihood.precision**2
@ -254,7 +258,10 @@ class SparseGP(GPBase):
"""
The derivative of the bound wrt the inducing inputs Z
"""
dL_dZ = self.kern.dK_dX(self.dL_dKmm, self.Z)
dL_dZ = self.kern.dK_dX(self.dL_dKmm, self.Z)
if hasattr(self,'multioutput'):
dL_dZ = dL_dZ*2 #NOTE Yes, this looks weird... but it works
if self.has_uncertain_inputs:
dL_dZ += self.kern.dpsi1_dZ(self.dL_dpsi1, self.Z, self.X, self.X_variance)
dL_dZ += self.kern.dpsi2_dZ(self.dL_dpsi2, self.Z, self.X, self.X_variance)

1
GPy/kern/parts/coregionalize.py
View file

@ -158,4 +158,5 @@ class Coregionalize(Kernpart):
target += np.hstack([dW.flatten(),dkappa])
def dK_dX(self,dL_dK,X,X2,target):
#NOTE In this case, pass is equivalent to returning zero.
pass