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slicing support for kernel input dimension

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Max Zwiessele 2014-03-07 16:59:41 +00:00
parent 5f3524e7da
commit db5fd17609
10 changed files with 178 additions and 65 deletions
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8
GPy/core/sparse_gp.py
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@ -64,8 +64,8 @@ class SparseGP(GP):
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.Z.gradient[:,self.kern.active_dims] = self.kern.gradients_X(dL_dKmm, self.Z)
self.Z.gradient[:,self.kern.active_dims] += self.kern.gradients_Z_expectations(
self.grad_dict['dL_dpsi1'], self.grad_dict['dL_dpsi2'], Z=self.Z, variational_posterior=self.X)
else:
#gradients wrt kernel
@ -77,8 +77,8 @@ class SparseGP(GP):
self.kern.gradient += target
#gradients wrt Z
self.Z.gradient = self.kern.gradients_X(self.grad_dict['dL_dKmm'], self.Z)
self.Z.gradient += self.kern.gradients_X(self.grad_dict['dL_dKnm'].T, self.Z, self.X)
self.Z.gradient[:,self.kern.active_dims] = self.kern.gradients_X(self.grad_dict['dL_dKmm'], self.Z)
self.Z.gradient[:,self.kern.active_dims] += self.kern.gradients_X(self.grad_dict['dL_dKnm'].T, self.Z, self.X)
def _raw_predict(self, Xnew, full_cov=False):
"""