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improved stability of sparse GP computations

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Specifically in computing dL_dKmm
This commit is contained in:
James Hensman 2013-04-16 11:06:21 +01:00
parent dd27b285d6
commit 403dc42462
1 changed files with 4 additions and 1 deletions
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5
GPy/models/sparse_GP.py
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@ -99,6 +99,7 @@ class sparse_GP(GP):
self.V = (self.likelihood.precision/self.scale_factor)*self.likelihood.Y self.V = (self.likelihood.precision/self.scale_factor)*self.likelihood.Y
#Compute A = L^-1 psi2 beta L^-T #Compute A = L^-1 psi2 beta L^-T
#self. A = mdot(self.Lmi,self.psi2_beta_scaled,self.Lmi.T)
tmp = linalg.lapack.flapack.dtrtrs(self.Lm,self.psi2_beta_scaled.T,lower=1)[0] tmp = linalg.lapack.flapack.dtrtrs(self.Lm,self.psi2_beta_scaled.T,lower=1)[0]
self.A = linalg.lapack.flapack.dtrtrs(self.Lm,np.asarray(tmp.T,order='F'),lower=1)[0] self.A = linalg.lapack.flapack.dtrtrs(self.Lm,np.asarray(tmp.T,order='F'),lower=1)[0]
@ -142,7 +143,9 @@ class sparse_GP(GP):
# Compute dL_dKmm # Compute dL_dKmm
self.dL_dKmm = -0.5 * self.D * mdot(self.Lmi.T, self.A, self.Lmi)*sf2 # dB #self.dL_dKmm_old = -0.5 * self.D * mdot(self.Lmi.T, self.A, self.Lmi)*sf2 # dB
tmp = linalg.lapack.flapack.dtrtrs(self.Lm,np.asfortranarray(self.A),lower=1,trans=1)[0]
self.dL_dKmm = -0.5*self.D*sf2*linalg.lapack.flapack.dtrtrs(self.Lm,np.asfortranarray(tmp.T),lower=1,trans=1)[0]
#self.dL_dKmm += -0.5 * self.D * (- self.C/sf2 - 2.*mdot(self.C, self.psi2_beta_scaled, self.Kmmi) + self.Kmmi) # dC #self.dL_dKmm += -0.5 * self.D * (- self.C/sf2 - 2.*mdot(self.C, self.psi2_beta_scaled, self.Kmmi) + self.Kmmi) # dC
#self.dL_dKmm += np.dot(np.dot(self.E*sf2, self.psi2_beta_scaled) - self.Cpsi1VVpsi1, self.Kmmi) + 0.5*self.E # dD #self.dL_dKmm += np.dot(np.dot(self.E*sf2, self.psi2_beta_scaled) - self.Cpsi1VVpsi1, self.Kmmi) + 0.5*self.E # dD
self.dL_dKmm += 0.5*(self.D*(self.C/sf2 -self.Kmmi) + self.E) + np.dot(np.dot(self.D*self.C + self.E*sf2,self.psi2_beta_scaled) - self.Cpsi1VVpsi1,self.Kmmi) # d(C+D) self.dL_dKmm += 0.5*(self.D*(self.C/sf2 -self.Kmmi) + self.E) + np.dot(np.dot(self.D*self.C + self.E*sf2,self.psi2_beta_scaled) - self.Cpsi1VVpsi1,self.Kmmi) # d(C+D)