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chol_inv added somewhere

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Ricardo 2013-05-15 18:12:32 +01:00
parent 95cb52d4a5
commit d0942a7bfd
1 changed files with 5 additions and 4 deletions
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9
GPy/likelihoods/EP.py
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@ -1,6 +1,6 @@
import numpy as np import numpy as np
from scipy import stats, linalg from scipy import stats, linalg
from ..util.linalg import pdinv,mdot,jitchol,DSYR,tdot from ..util.linalg import pdinv,mdot,jitchol,chol_inv,DSYR,tdot
from likelihood import likelihood from likelihood import likelihood
class EP(likelihood): class EP(likelihood):
@ -133,7 +133,6 @@ class EP(likelihood):
return self._compute_GP_variables() return self._compute_GP_variables()
#@profile
def fit_DTC(self, Kmm, Kmn): def fit_DTC(self, Kmm, Kmn):
""" """
The expectation-propagation algorithm with sparse pseudo-input. The expectation-propagation algorithm with sparse pseudo-input.
@ -150,7 +149,7 @@ class EP(likelihood):
""" """
KmnKnm = np.dot(Kmn,Kmn.T) KmnKnm = np.dot(Kmn,Kmn.T)
Lm = jitchol(Kmm) Lm = jitchol(Kmm)
Lmi,info = linalg.lapack.flapack.dtrtrs(Lm,np.asfortranarray(np.eye(M)),lower=1,trans=1) Lmi = chol_inv(Lm)
Kmmi = np.dot(Lmi.T,Lmi) Kmmi = np.dot(Lmi.T,Lmi)
KmmiKmn = np.dot(Kmmi,Kmn) KmmiKmn = np.dot(Kmmi,Kmn)
Qnn_diag = np.sum(Kmn*KmmiKmn,-2) Qnn_diag = np.sum(Kmn*KmmiKmn,-2)
@ -242,7 +241,9 @@ class EP(likelihood):
q(f|X) = int_{df}{N(f|KfuKuu_invu,diag(Kff-Qff)*N(u|0,Kuu)} = N(f|0,Sigma0) q(f|X) = int_{df}{N(f|KfuKuu_invu,diag(Kff-Qff)*N(u|0,Kuu)} = N(f|0,Sigma0)
Sigma0 = diag(Knn-Qnn) + Qnn, Qnn = Knm*Kmmi*Kmn Sigma0 = diag(Knn-Qnn) + Qnn, Qnn = Knm*Kmmi*Kmn
""" """
Kmmi, self.Lm, self.Lmi, Kmm_logdet = pdinv(Kmm) Lm = jitchol(Kmm)
Lmi = chol_inv(Lm)
Kmmi = np.dot(Lmi.T,Lmi)
P0 = Kmn.T P0 = Kmn.T
KmnKnm = np.dot(P0.T, P0) KmnKnm = np.dot(P0.T, P0)
KmmiKmn = np.dot(Kmmi,P0.T) KmmiKmn = np.dot(Kmmi,P0.T)