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merge the current devel into psi2

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Zhenwen Dai 2014-08-11 18:01:23 +01:00
commit 785c580032
49 changed files with 1839 additions and 581 deletions
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21
GPy/core/sparse_gp.py
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@ -8,6 +8,9 @@ from ..inference.latent_function_inference import var_dtc
from .. import likelihoods
from parameterization.variational import VariationalPosterior
import logging
logger = logging.getLogger("sparse gp")
class SparseGP(GP):
"""
A general purpose Sparse GP model
@ -46,7 +49,7 @@ class SparseGP(GP):
self.num_inducing = Z.shape[0]
GP.__init__(self, X, Y, kernel, likelihood, inference_method=inference_method, name=name, Y_metadata=Y_metadata)
logger.info("Adding Z as parameter")
self.add_parameter(self.Z, index=0)
def has_uncertain_inputs(self):
@ -57,19 +60,23 @@ class SparseGP(GP):
self.likelihood.update_gradients(self.grad_dict['dL_dthetaL'])
if isinstance(self.X, VariationalPosterior):
#gradients wrt kernel
dL_dKmm = self.grad_dict.pop('dL_dKmm')
dL_dKmm = self.grad_dict['dL_dKmm']
self.kern.update_gradients_full(dL_dKmm, self.Z, None)
target = self.kern.gradient.copy()
self.kern.update_gradients_expectations(variational_posterior=self.X, Z=self.Z, dL_dpsi0=self.grad_dict['dL_dpsi0'], dL_dpsi1=self.grad_dict['dL_dpsi1'], dL_dpsi2=self.grad_dict['dL_dpsi2'])
self.kern.update_gradients_expectations(variational_posterior=self.X,
Z=self.Z,
dL_dpsi0=self.grad_dict['dL_dpsi0'],
dL_dpsi1=self.grad_dict['dL_dpsi1'],
dL_dpsi2=self.grad_dict['dL_dpsi2'])
self.kern.gradient += target
#gradients wrt Z
self.Z.gradient = self.kern.gradients_X(dL_dKmm, self.Z)
self.Z.gradient += self.kern.gradients_Z_expectations(
self.grad_dict['dL_dpsi0'],
self.grad_dict['dL_dpsi1'],
self.grad_dict['dL_dpsi2'],
Z=self.Z,
self.grad_dict['dL_dpsi0'],
self.grad_dict['dL_dpsi1'],
self.grad_dict['dL_dpsi2'],
Z=self.Z,
variational_posterior=self.X)
else:
#gradients wrt kernel