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added a default kernel option in BGPLVM

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This commit is contained in:
James Hensman 2013-02-13 18:18:29 +00:00
parent 8761f72c59
commit bfd2166469
1 changed files with 4 additions and 3 deletions
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7
GPy/models/BGPLVM.py
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@ -22,7 +22,7 @@ class Bayesian_GPLVM(sparse_GP, GPLVM):
:type init: 'PCA'|'random'
"""
def __init__(self, Y, Q, init='PCA', M=10, Z=None, **kwargs):
def __init__(self, Y, Q, init='PCA', M=10, Z=None, kernel=None, **kwargs):
X = self.initialise_latent(init, Q, Y)
if Z is None:
@ -30,10 +30,11 @@ class Bayesian_GPLVM(sparse_GP, GPLVM):
else:
assert Z.shape[1]==X.shape[1]
kernel = kern.rbf(Q) + kern.white(Q)
if kernel is None:
kernel = kern.rbf(Q) + kern.white(Q)
S = np.ones_like(X) * 1e-2#
sparse_GP.__init__(self, X, Gaussian(Y), X_uncertainty=S, Z=Z,**kwargs)
sparse_GP.__init__(self, X, Gaussian(Y), kernel, Z=Z, X_uncertainty=S, **kwargs)
def _get_param_names(self):
X_names = sum([['X_%i_%i'%(n,q) for n in range(self.N)] for q in range(self.Q)],[])