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

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Max Zwiessele 2014-03-12 12:07:15 +00:00
commit 603b70bb6e
2 changed files with 7 additions and 0 deletions
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3
GPy/kern/_src/add.py
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@ -46,6 +46,9 @@ class Add(CombinationKernel):
def update_gradients_diag(self, dL_dK, X): def update_gradients_diag(self, dL_dK, X):
[p.update_gradients_diag(dL_dK, X) for p in self.parts] [p.update_gradients_diag(dL_dK, X) for p in self.parts]
def update_gradients_diag(self, dL_dKdiag, X):
[p.update_gradients_diag(dL_dKdiag, X[:,i_s]) for p, i_s in zip(self._parameters_, self.input_slices)]
def gradients_X(self, dL_dK, X, X2=None): def gradients_X(self, dL_dK, X, X2=None):
"""Compute the gradient of the objective function with respect to X. """Compute the gradient of the objective function with respect to X.

4
GPy/kern/_src/kern.py
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@ -62,6 +62,10 @@ class Kern(Parameterized):
def gradients_X_diag(self, dL_dKdiag, X): def gradients_X_diag(self, dL_dKdiag, X):
raise NotImplementedError raise NotImplementedError
def update_gradients_diag(self, dL_dKdiag, X):
""" update the gradients of all parameters when using only the diagonal elements of the covariance matrix"""
raise NotImplementedError
def update_gradients_full(self, dL_dK, X, X2): def update_gradients_full(self, dL_dK, X, X2):
"""Set the gradients of all parameters when doing full (N) inference.""" """Set the gradients of all parameters when doing full (N) inference."""
raise NotImplementedError raise NotImplementedError