apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-12 13:32:39 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

epsilon and power_ep now are parameters of update_likelihood.

Browse source
This commit is contained in:
Ricardo 2013-09-20 13:22:38 +01:00
parent c8fec98071
commit a51af5b8c4
5 changed files with 62 additions and 30 deletions
Download patch file Download diff file Expand all files Collapse all files

6
GPy/core/sparse_gp.py
View file

@ -215,7 +215,7 @@ class SparseGP(GPBase):
#def _get_print_names(self):
# return self.kern._get_param_names_transformed() + self.likelihood._get_param_names()
def update_likelihood_approximation(self):
def update_likelihood_approximation(self, **kwargs):
"""
Approximates a non-gaussian likelihood using Expectation Propagation
@ -229,10 +229,10 @@ class SparseGP(GPBase):
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.T, diag_tr_psi2Kmmi) # This uses the fit_FITC code, but does not perfomr a FITC-EP.#TODO solve potential confusion
self.likelihood.fit_FITC(self.Kmm, self.psi1.T, diag_tr_psi2Kmmi, **kwargs) # 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.T)
self.likelihood.fit_DTC(self.Kmm, self.psi1.T, **kwargs)
# self.likelihood.fit_FITC(self.Kmm,self.psi1,self.psi0)
self._set_params(self._get_params()) # update the GP