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fixed bug with the bias kernel.
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1 changed files with 5 additions and 3 deletions
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@ -104,9 +104,11 @@ class sparse_GP(GP):
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self.dL_dpsi2 += - 0.5 * self.likelihood.precision[:,None,None]/sf2 * self.D * self.C[None,:,:] # dC
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self.dL_dpsi2 += - 0.5 * self.likelihood.precision[:,None,None]/sf2 * self.D * self.C[None,:,:] # dC
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self.dL_dpsi2 += - 0.5 * self.likelihood.precision[:,None,None]* self.E[None,:,:] # dD
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self.dL_dpsi2 += - 0.5 * self.likelihood.precision[:,None,None]* self.E[None,:,:] # dD
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else:
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else:
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self.dL_dpsi2 = 0.5 * self.likelihood.precision * self.D * self.Kmmi[None,:,:] # dB
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self.dL_dpsi2 = 0.5 * self.likelihood.precision * self.D * self.Kmmi # dB
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self.dL_dpsi2 += - 0.5 * self.likelihood.precision/sf2 * self.D * self.C[None,:,:] # dC
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self.dL_dpsi2 += - 0.5 * self.likelihood.precision/sf2 * self.D * self.C # dC
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self.dL_dpsi2 += - 0.5 * self.likelihood.precision * self.E[None,:,:] # dD
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self.dL_dpsi2 += - 0.5 * self.likelihood.precision * self.E # dD
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#repeat for each of the N psi_2 matrices
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self.dL_dpsi2 = np.repeat(self.dL_dpsi2[None,:,:],self.N,axis=0)
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# Compute dL_dKmm
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# Compute dL_dKmm
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self.dL_dKmm = -0.5 * self.D * mdot(self.Lmi.T, self.A, self.Lmi)*sf2 # dB
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self.dL_dKmm = -0.5 * self.D * mdot(self.Lmi.T, self.A, self.Lmi)*sf2 # dB
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