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diagonal add kmm

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Max Zwiessele 2014-03-12 12:03:47 +00:00
parent 54239555a1
commit 5027e8e312
1 changed files with 7 additions and 7 deletions
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14
GPy/inference/latent_function_inference/var_dtc.py
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@ -3,6 +3,7 @@
from posterior import Posterior
from ...util.linalg import jitchol, backsub_both_sides, tdot, dtrtrs, dtrtri, dpotri, dpotrs, symmetrify
from ...util import diag
from ...core.parameterization.variational import VariationalPosterior
import numpy as np
from ...util.misc import param_to_array
@ -28,7 +29,7 @@ class VarDTC(object):
def set_limit(self, limit):
self.get_trYYT.limit = limit
self.get_YYTfactor.limit = limit
def _get_trYYT(self, Y):
return param_to_array(np.sum(np.square(Y)))
@ -77,10 +78,10 @@ class VarDTC(object):
num_inducing = Z.shape[0]
num_data = Y.shape[0]
# kernel computations, using BGPLVM notation
Kmm = kern.K(Z) +np.eye(Z.shape[0]) * self.const_jitter
Lm = jitchol(Kmm+np.eye(Z.shape[0])*self.const_jitter)
Kmm = kern.K(Z).copy()
diag.add(Kmm, self.const_jitter)
Lm = jitchol(Kmm)
# The rather complex computations of A
if uncertain_inputs:
@ -169,7 +170,6 @@ class VarDTC(object):
Bi, _ = dpotri(LB, lower=1)
symmetrify(Bi)
Bi = -dpotri(LB, lower=1)[0]
from ...util import diag
diag.add(Bi, 1)
woodbury_inv = backsub_both_sides(Lm, Bi)
@ -238,7 +238,8 @@ class VarDTCMissingData(object):
dL_dKmm = 0
log_marginal = 0
Kmm = kern.K(Z)
Kmm = kern.K(Z).copy()
diag.add(Kmm, self.const_jitter)
#factor Kmm
Lm = jitchol(Kmm)
if uncertain_inputs: LmInv = dtrtri(Lm)
@ -324,7 +325,6 @@ class VarDTCMissingData(object):
Bi, _ = dpotri(LB, lower=1)
symmetrify(Bi)
Bi = -dpotri(LB, lower=1)[0]
from ...util import diag
diag.add(Bi, 1)
woodbury_inv_all[:, :, ind] = backsub_both_sides(Lm, Bi)[:,:,None]