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This commit is contained in:
mzwiessele 2014-06-27 16:18:41 -07:00
parent 8213b5011c
commit 35b778b45f
6 changed files with 27 additions and 27 deletions
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11
GPy/inference/latent_function_inference/var_dtc.py
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@ -9,6 +9,8 @@ import numpy as np
from ...util.misc import param_to_array
from . import LatentFunctionInference
log_2_pi = np.log(2*np.pi)
import logging
logger = logging.getLogger('vardtc')
class VarDTC(LatentFunctionInference):
"""
@ -225,14 +227,18 @@ class VarDTCMissingData(LatentFunctionInference):
from ...util.subarray_and_sorting import common_subarrays
self._subarray_indices = []
csa = common_subarrays(inan, 1)
for v,ind in csa.iteritems():
size = len(csa)
for i, (v,ind) in enumerate(csa.iteritems()):
if not np.all(v):
logger.info('preparing subarrays {:.3%}'.format((i+1.)/size))
v = ~np.array(v, dtype=bool)
ind = np.array(ind, dtype=int)
if ind.size == Y.shape[1]:
ind = slice(None)
self._subarray_indices.append([v,ind])
logger.info('preparing subarrays Y')
Ys = [Y[v, :][:, ind] for v, ind in self._subarray_indices]
logger.info('preparing traces Y')
traces = [(y**2).sum() for y in Ys]
return Ys, traces
else:
@ -280,7 +286,10 @@ class VarDTCMissingData(LatentFunctionInference):
#if not full_VVT_factor:
# psi1V = np.dot(Y.T*beta_all, psi1_all).T
#logger.info('computing dimension-wise likelihood and derivatives')
#size = len(Ys)
for y, trYYT, [v, ind] in itertools.izip(Ys, traces, self._subarray_indices):
#logger.info('{:.3%} dimensions:{}'.format((i+1.)/size, ind))
if het_noise: beta = beta_all[ind]
else: beta = beta_all