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[normalizer] first commit for normalizer in GPy

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Conflicts:
	GPy/core/sparse_gp.py
	GPy/models/bayesian_gplvm.py
This commit is contained in:
mzwiessele 2014-08-27 12:05:13 -07:00
parent 7ed0e70a46
commit 7ec0e75c0e
6 changed files with 101 additions and 24 deletions
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6
GPy/core/sparse_gp.py
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@ -34,7 +34,7 @@ class SparseGP(GP):
"""
def __init__(self, X, Y, Z, kernel, likelihood, inference_method=None, name='sparse gp', Y_metadata=None):
def __init__(self, X, Y, Z, kernel, likelihood, inference_method=None, name='sparse gp', Y_metadata=None, normalizer=False):
#pick a sensible inference method
if inference_method is None:
@ -48,7 +48,7 @@ class SparseGP(GP):
self.Z = Param('inducing inputs', Z)
self.num_inducing = Z.shape[0]
GP.__init__(self, X, Y, kernel, likelihood, inference_method=inference_method, name=name, Y_metadata=Y_metadata)
GP.__init__(self, X, Y, kernel, likelihood, inference_method=inference_method, name=name, Y_metadata=Y_metadata, normalizer=normalizer)
logger.info("Adding Z as parameter")
self.add_parameter(self.Z, index=0)
@ -56,7 +56,7 @@ class SparseGP(GP):
return isinstance(self.X, VariationalPosterior)
def parameters_changed(self):
self.posterior, self._log_marginal_likelihood, self.grad_dict = self.inference_method.inference(self.kern, self.X, self.Z, self.likelihood, self.Y, self.Y_metadata)
self.posterior, self._log_marginal_likelihood, self.grad_dict = self.inference_method.inference(self.kern, self.X, self.Z, self.likelihood, self.Y_normalized, self.Y_metadata)
self.likelihood.update_gradients(self.grad_dict['dL_dthetaL'])
if isinstance(self.X, VariationalPosterior):
#gradients wrt kernel