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Added a debug examples

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Alan Saul 2013-05-07 13:35:47 +01:00
parent f95666a8f9
commit a52c20f470
3 changed files with 104 additions and 9 deletions
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6
GPy/models/GP.py
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@ -116,7 +116,6 @@ class GP(model):
"""
return -0.5 * self.D * self.K_logdet + self._model_fit_term() + self.likelihood.Z
def _log_likelihood_gradients(self):
"""
The gradient of all parameters.
@ -132,9 +131,14 @@ class GP(model):
dL_dthetaK_implicit = self.likelihood._Kgradients(self.dL_dK, dK_dthetaK)
dL_dthetaK = dL_dthetaK_explicit + dL_dthetaK_implicit
print "dL_dthetaK_explicit: {dldkx} dL_dthetaK_implicit: {dldki} dL_dthetaK: {dldk}".format(dldkx=dL_dthetaK_explicit, dldki=dL_dthetaK_implicit, dldk=dL_dthetaK)
dL_dthetaL = self.likelihood._gradients(partial=self.dL_dK)
else:
print "dL_dthetaK: ", dL_dthetaK
dL_dthetaL = self.likelihood._gradients(partial=np.diag(self.dL_dK))
print "dL_dthetaL: ", dL_dthetaL
return np.hstack((dL_dthetaK, dL_dthetaL))
#return np.hstack((self.kern.dK_dtheta(dL_dK=self.dL_dK, X=self.X), self.likelihood._gradients(partial=np.diag(self.dL_dK))))