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This commit is contained in:
Max Zwiessele 2013-06-04 17:27:59 +01:00
commit c4cd93cd17
11 changed files with 38 additions and 34 deletions
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4
GPy/models/GPLVM.py
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@ -26,13 +26,13 @@ class GPLVM(GP):
:type init: 'PCA'|'random'
"""
def __init__(self, Y, Q, init='PCA', X = None, kernel=None, normalize_Y=False, **kwargs):
def __init__(self, Y, Q, init='PCA', X = None, kernel=None, normalize_Y=False):
if X is None:
X = self.initialise_latent(init, Q, Y)
if kernel is None:
kernel = kern.rbf(Q, ARD=Q>1) + kern.bias(Q, np.exp(-2)) + kern.white(Q, np.exp(-2))
likelihood = Gaussian(Y, normalize=normalize_Y)
super(GPLVM, self).__init__(self, X, likelihood, kernel, **kwargs)
GP.__init__(self, X, likelihood, kernel, normalize_X=False)
self._set_params(self._get_params())
def initialise_latent(self, init, Q, Y):

2
GPy/models/GP_regression.py
View file

@ -31,5 +31,5 @@ class GP_regression(GP):
likelihood = likelihoods.Gaussian(Y,normalize=normalize_Y)
super(GP_regression, self).__init__(X, likelihood, kernel, normalize_X=normalize_X)
GP.__init__(self, X, likelihood, kernel, normalize_X=normalize_X)
self._set_params(self._get_params())

2
GPy/models/generalized_FITC.py
View file

@ -40,7 +40,7 @@ class generalized_FITC(sparse_GP):
self.M = self.Z.shape[0]
self.true_precision = likelihood.precision
super(generalized_FITC, self).__init__(self, X, likelihood, kernel=kernel, Z=self.Z, X_variance=None, normalize_X=False)
super(generalized_FITC, self).__init__(X, likelihood, kernel=kernel, Z=self.Z, X_variance=X_variance, normalize_X=normalize_X)
self._set_params(self._get_params())
def _set_params(self, p):

4
GPy/models/sparse_GPLVM.py
View file

@ -23,9 +23,9 @@ class sparse_GPLVM(sparse_GP_regression, GPLVM):
:type init: 'PCA'|'random'
"""
def __init__(self, Y, Q, init='PCA', **kwargs):
def __init__(self, Y, Q, kernel=None, init='PCA', M=10):
X = self.initialise_latent(init, Q, Y)
sparse_GP_regression.__init__(self, X, Y, **kwargs)
sparse_GP_regression.__init__(self, X, Y, kernel=kernel,M=M)
def _get_param_names(self):
return (sum([['X_%i_%i'%(n,q) for q in range(self.Q)] for n in range(self.N)],[])

2
GPy/models/sparse_GP_regression.py
View file

@ -43,5 +43,5 @@ class sparse_GP_regression(sparse_GP):
#likelihood defaults to Gaussian
likelihood = likelihoods.Gaussian(Y,normalize=normalize_Y)
super(sparse_GP_regression, self).__init__(self, X, likelihood, kernel, Z, normalize_X=normalize_X)
sparse_GP.__init__(self, X, likelihood, kernel, Z=Z, normalize_X=normalize_X)
self._set_params(self._get_params())

2
GPy/models/warped_GP.py
View file

@ -29,7 +29,7 @@ class warpedGP(GP):
self.predict_in_warped_space = False
likelihood = likelihoods.Gaussian(self.transform_data(), normalize=normalize_Y)
super(warpedGP, self).__init__(self, X, likelihood, kernel, normalize_X=normalize_X)
GP.__init__(self, X, likelihood, kernel, normalize_X=normalize_X)
self._set_params(self._get_params())
def _scale_data(self, Y):