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Merge branch 'devel' of github.com:SheffieldML/GPy into devel

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James Hensman 2013-05-20 16:34:23 +01:00
commit 2569240095
6 changed files with 63 additions and 48 deletions
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25
GPy/models/sparse_GP.py
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@ -8,6 +8,7 @@ from ..util.plot import gpplot
from .. import kern
from GP import GP
from scipy import linalg
from ..likelihoods import Gaussian
class sparse_GP(GP):
"""
@ -172,19 +173,19 @@ class sparse_GP(GP):
For a Gaussian likelihood, no iteration is required:
this function does nothing
"""
if self.has_uncertain_inputs:
Lmi = chol_inv(self.Lm)
Kmmi = tdot(Lmi.T)
diag_tr_psi2Kmmi = np.array([np.trace(psi2_Kmmi) for psi2_Kmmi in np.dot(self.psi2,Kmmi)])
self.likelihood.fit_FITC(self.Kmm,self.psi1,diag_tr_psi2Kmmi) #This uses the fit_FITC code, but does not perfomr a FITC-EP.#TODO solve potential confusion
#raise NotImplementedError, "EP approximation not implemented for uncertain inputs"
else:
self.likelihood.fit_DTC(self.Kmm, self.psi1)
# self.likelihood.fit_FITC(self.Kmm,self.psi1,self.psi0)
self._set_params(self._get_params()) # update the GP
if not isinstance(self.likelihood,Gaussian): #Updates not needed for Gaussian likelihood
self.likelihood.restart() #TODO check consistency with pseudo_EP
if self.has_uncertain_inputs:
Lmi = chol_inv(self.Lm)
Kmmi = tdot(Lmi.T)
diag_tr_psi2Kmmi = np.array([np.trace(psi2_Kmmi) for psi2_Kmmi in np.dot(self.psi2,Kmmi)])
self.likelihood.fit_FITC(self.Kmm,self.psi1,diag_tr_psi2Kmmi) #This uses the fit_FITC code, but does not perfomr a FITC-EP.#TODO solve potential confusion
#raise NotImplementedError, "EP approximation not implemented for uncertain inputs"
else:
self.likelihood.fit_DTC(self.Kmm, self.psi1)
# self.likelihood.fit_FITC(self.Kmm,self.psi1,self.psi0)
self._set_params(self._get_params()) # update the GP
def _log_likelihood_gradients(self):
return np.hstack((self.dL_dZ().flatten(), self.dL_dtheta(), self.likelihood._gradients(partial=self.partial_for_likelihood)))