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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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8
GPy/models/sparse_gp_regression.py
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@ -30,7 +30,7 @@ class SparseGPRegression(SparseGP):
"""
def __init__(self, X, Y, kernel=None, Z=None, num_inducing=10, X_variance=None):
def __init__(self, X, Y, kernel=None, Z=None, num_inducing=10, X_variance=None, normalizer=None):
num_data, input_dim = X.shape
# kern defaults to rbf (plus white for stability)
@ -49,7 +49,7 @@ class SparseGPRegression(SparseGP):
if not (X_variance is None):
X = NormalPosterior(X,X_variance)
SparseGP.__init__(self, X, Y, Z, kernel, likelihood, inference_method=VarDTC())
SparseGP.__init__(self, X, Y, Z, kernel, likelihood, inference_method=VarDTC(), normalizer=normalizer)
class SparseGPRegressionUncertainInput(SparseGP):
"""
@ -59,7 +59,7 @@ class SparseGPRegressionUncertainInput(SparseGP):
"""
def __init__(self, X, X_variance, Y, kernel=None, Z=None, num_inducing=10):
def __init__(self, X, X_variance, Y, kernel=None, Z=None, num_inducing=10, normalizer=None):
"""
:param X: input observations
:type X: np.ndarray (num_data x input_dim)
@ -91,5 +91,5 @@ class SparseGPRegressionUncertainInput(SparseGP):
likelihood = likelihoods.Gaussian()
SparseGP.__init__(self, X, Y, Z, kernel, likelihood, X_variance=X_variance, inference_method=VarDTC())
SparseGP.__init__(self, X, Y, Z, kernel, likelihood, X_variance=X_variance, inference_method=VarDTC(), normalizer=normalizer)
self.ensure_default_constraints()