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stability improvements in sparse_GP

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James Hensman 2013-04-10 11:04:49 +01:00
parent 45403105f9
commit eb1d8f211f
3 changed files with 16 additions and 9 deletions
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16
GPy/models/sparse_GP.py
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@ -7,6 +7,7 @@ from ..util.linalg import mdot, jitchol, chol_inv, pdinv, trace_dot
from ..util.plot import gpplot
from .. import kern
from GP import GP
from scipy import linalg
#Still TODO:
# make use of slices properly (kernel can now do this)
@ -96,21 +97,26 @@ class sparse_GP(GP):
self.Kmmi, self.Lm, self.Lmi, self.Kmm_logdet = pdinv(self.Kmm)
self.V = (self.likelihood.precision/self.scale_factor)*self.likelihood.Y
self.A = mdot(self.Lmi, self.psi2_beta_scaled, self.Lmi.T)
#Compute A = L^-1 psi2 beta L^-T
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.B = np.eye(self.M)/sf2 + self.A
self.Bi, self.LB, self.LBi, self.B_logdet = pdinv(self.B)
self.psi1V = np.dot(self.psi1, self.V)
tmp = np.dot(self.Lmi.T, self.LBi.T)
self.C = np.dot(tmp,tmp.T)
#tmp = np.dot(self.Lmi.T, self.LBi.T)
tmp = linalg.lapack.clapack.dtrtrs(self.Lm.T,np.asarray(self.LBi.T,order='C'),lower=0)[0]
self.C = np.dot(tmp,tmp.T) #TODO: tmp is triangular. replace with dtrmm (blas) when available
self.Cpsi1V = np.dot(self.C,self.psi1V)
self.Cpsi1VVpsi1 = np.dot(self.Cpsi1V,self.psi1V.T)
self.E = np.dot(self.Cpsi1VVpsi1,self.C)/sf2
#self.E = np.dot(self.Cpsi1VVpsi1,self.C)/sf2
self.E = np.dot(self.Cpsi1V/sf,self.Cpsi1V.T/sf)
# Compute dL_dpsi # FIXME: this is untested for the heterscedastic + uncertin inputs case
self.dL_dpsi0 = - 0.5 * self.D * (self.likelihood.precision * np.ones([self.N,1])).flatten()
#self.dL_dpsi1 = mdot(self.V, self.psi1V.T,self.C).T
self.dL_dpsi1 = np.dot(self.Cpsi1V,self.V.T)
if self.likelihood.is_heteroscedastic:
if self.has_uncertain_inputs: