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kernel adding now takes over constraints

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Max Zwiessele 2014-02-11 15:23:49 +00:00
parent b7312a1b99
commit 4cfc13d5fc
4 changed files with 9 additions and 12 deletions
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6
GPy/core/sparse_gp.py
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@ -7,6 +7,7 @@ from gp import GP
from parameterization.param import Param
from ..inference.latent_function_inference import varDTC
from .. import likelihoods
from GPy.util.misc import param_to_array
class SparseGP(GP):
"""
@ -54,7 +55,10 @@ class SparseGP(GP):
self.add_parameter(self.Z, index=0)
def parameters_changed(self):
self.posterior, self._log_marginal_likelihood, self.grad_dict = self.inference_method.inference(self.kern, self.X, self.X_variance, self.Z, self.likelihood, self.Y)
Xvar = self.X_variance
if self.X_variance is not None:
Xvar = param_to_array(self.X_variance)
self.posterior, self._log_marginal_likelihood, self.grad_dict = self.inference_method.inference(self.kern, param_to_array(self.X), Xvar, param_to_array(self.Z), self.likelihood, self.Y)
#The derivative of the bound wrt the inducing inputs Z
self.Z.gradient = self.kern.gradients_X(self.grad_dict['dL_dKmm'], self.Z)