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more stabilisation of sparse GP

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James Hensman 2013-04-29 11:37:08 +01:00
parent 23bde6f3dd
commit 5fca43f980
2 changed files with 10 additions and 6 deletions
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1
GPy/models/__init__.py
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@ -9,7 +9,6 @@ from sparse_GP_regression import sparse_GP_regression
from GPLVM import GPLVM from GPLVM import GPLVM
from warped_GP import warpedGP from warped_GP import warpedGP
from sparse_GPLVM import sparse_GPLVM from sparse_GPLVM import sparse_GPLVM
from uncollapsed_sparse_GP import uncollapsed_sparse_GP
from Bayesian_GPLVM import Bayesian_GPLVM from Bayesian_GPLVM import Bayesian_GPLVM
from mrd import MRD from mrd import MRD
from generalized_FITC import generalized_FITC from generalized_FITC import generalized_FITC

15
GPy/models/sparse_GP.py
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@ -92,7 +92,7 @@ class sparse_GP(GP):
#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) #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.asfortranarray(tmp.T),lower=1)[0]
self.B = np.eye(self.M)/sf2 + self.A self.B = np.eye(self.M)/sf2 + self.A
@ -101,12 +101,17 @@ class sparse_GP(GP):
self.psi1V = np.dot(self.psi1, self.V) self.psi1V = np.dot(self.psi1, self.V)
tmp = linalg.lapack.flapack.dtrtrs(self.Lm,np.asfortranarray(self.Bi),lower=1,trans=1)[0] tmp = linalg.lapack.flapack.dtrtrs(self.Lm,np.asfortranarray(self.Bi),lower=1,trans=1)[0]
self.C = linalg.lapack.flapack.dtrtrs(self.Lm,np.asfortranarray(tmp.T),lower=1,trans=1)[0] self.C = linalg.lapack.flapack.dtrtrs(self.Lm,np.asfortranarray(tmp.T),lower=1,trans=1)[0]
#TODO: can we multiply in C by forwardsubstitution?
self.Cpsi1V = np.dot(self.C,self.psi1V) #self.Cpsi1V = np.dot(self.C,self.psi1V)
self.Cpsi1VVpsi1 = np.dot(self.Cpsi1V,self.psi1V.T) #back substutue C into psi1V
#self.E = np.dot(self.Cpsi1V/sf,self.Cpsi1V.T/sf) tmp,info1 = linalg.lapack.flapack.dtrtrs(self.Lm,np.asfortranarray(self.psi1V),lower=1,trans=0)
tmp,info2 = linalg.lapack.flapack.dpotrs(self.LB,tmp,lower=1)
self.Cpsi1V,info3 = linalg.lapack.flapack.dtrtrs(self.Lm,tmp,lower=1,trans=1)
self.Cpsi1VVpsi1 = np.dot(self.Cpsi1V,self.psi1V.T) #TODO: stabilize?
self.E = tdot(self.Cpsi1V/sf) self.E = tdot(self.Cpsi1V/sf)
# Compute dL_dpsi # FIXME: this is untested for the heterscedastic + uncertin inputs case # 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_dpsi0 = - 0.5 * self.D * (self.likelihood.precision * np.ones([self.N,1])).flatten()
self.dL_dpsi1 = np.dot(self.Cpsi1V,self.V.T) self.dL_dpsi1 = np.dot(self.Cpsi1V,self.V.T)