apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-11 13:02:38 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

REVERT a53690ab7f, flapack back substitued in

Browse source
This commit is contained in:
Max Zwiessele 2013-05-31 12:09:11 +01:00
parent 43c2f8af87
commit 4eebf99bfb
15 changed files with 96 additions and 101 deletions
Download patch file Download diff file Expand all files Collapse all files

10
GPy/models/mrd.py
View file

@ -65,7 +65,7 @@ class MRD(model):
self._init = True
X = self._init_X(initx, likelihood_or_Y_list)
Z = self._init_Z(initz, X)
self.bgplvms = [Bayesian_GPLVM(l, Q=Q, kernel=k, X=X, Z=Z, M=self.M, _debug=_debug, ** kw) for l, k in zip(likelihood_or_Y_list, kernels)]
self.bgplvms = [Bayesian_GPLVM(l, Q=Q, kernel=k, X=X, Z=Z, M=self.M, **kw) for l, k in zip(likelihood_or_Y_list, kernels)]
del self._init
self.gref = self.bgplvms[0]
@ -143,9 +143,9 @@ class MRD(model):
# S_names = sum([['X_variance_%i_%i' % (n, q) for q in range(self.Q)] for n in range(self.N)], [])
n1 = self.gref._get_param_names()
n1var = n1[:self.NQ * 2 + self.MQ]
map_names = lambda ns, cd48_name: map(lambda x: "{1}_{0}".format(*x),
map_names = lambda ns, name: map(lambda x: "{1}_{0}".format(*x),
itertools.izip(ns,
itertools.repeat(cd48_name)))
itertools.repeat(name)))
return list(itertools.chain(n1var, *(map_names(\
sparse_GP._get_param_names(g)[self.MQ:], n) \
for g, n in zip(self.bgplvms, self.names))))
@ -213,12 +213,12 @@ class MRD(model):
dLdmuS = numpy.hstack((dLdmu.flatten(), dLdS.flatten())).flatten()
dldzt1 = reduce(lambda a, b: a + b, (sparse_GP._log_likelihood_gradients(g)[:self.MQ] for g in self.bgplvms))
return self.gref._clipped(numpy.hstack((dLdmuS,
return numpy.hstack((dLdmuS,
dldzt1,
numpy.hstack([numpy.hstack([g.dL_dtheta(),
g.likelihood._gradients(\
partial=g.partial_for_likelihood)]) \
for g in self.bgplvms]))))
for g in self.bgplvms])))
def _init_X(self, init='PCA', likelihood_list=None):
if likelihood_list is None: