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Changed two function names so that they follow the python naming convention

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Siivola Eero 2018-01-24 13:40:34 +02:00
parent 3bb905be85
commit 4f532216ad
1 changed files with 5 additions and 5 deletions
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10
GPy/kern/src/multioutput_kern.py
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@ -93,12 +93,12 @@ class MultioutputKern(CombinationKernel):
[[np.copyto(target[s], kern.Kdiag(X[s])) for s in slices_i] for kern, slices_i in zip(kerns, slices)]
return target
def update_gradients_full_wrapper(self, cov_struct, dL_dK, X, X2):
def _update_gradients_full_wrapper(self, cov_struct, dL_dK, X, X2):
gradient = cov_struct['kern'].gradient.copy()
cov_struct['update_gradients_full'](dL_dK, X, X2)
cov_struct['kern'].gradient += gradient
def update_gradients_diag_wrapper(self, kern, dL_dKdiag, X):
def _update_gradients_diag_wrapper(self, kern, dL_dKdiag, X):
gradient = kern.gradient.copy()
kern.update_gradients_diag(dL_dKdiag, X)
kern.gradient += gradient
@ -111,14 +111,14 @@ class MultioutputKern(CombinationKernel):
slices = index_to_slices(X[:,self.index_dim])
if X2 is not None:
slices2 = index_to_slices(X2[:,self.index_dim])
[[[[ self.update_gradients_full_wrapper(self.covariance[i][j], dL_dK[slices[i][k],slices2[j][l]], X[slices[i][k],:], X2[slices2[j][l],:]) for k in range(len(slices[i]))] for l in range(len(slices2[j]))] for i in range(len(slices))] for j in range(len(slices2))]
[[[[ self._update_gradients_full_wrapper(self.covariance[i][j], dL_dK[slices[i][k],slices2[j][l]], X[slices[i][k],:], X2[slices2[j][l],:]) for k in range(len(slices[i]))] for l in range(len(slices2[j]))] for i in range(len(slices))] for j in range(len(slices2))]
else:
[[[[ self.update_gradients_full_wrapper(self.covariance[i][j], dL_dK[slices[i][k],slices[j][l]], X[slices[i][k],:], X[slices[j][l],:]) for k in range(len(slices[i]))] for l in range(len(slices[j]))] for i in range(len(slices))] for j in range(len(slices))]
[[[[ self._update_gradients_full_wrapper(self.covariance[i][j], dL_dK[slices[i][k],slices[j][l]], X[slices[i][k],:], X[slices[j][l],:]) for k in range(len(slices[i]))] for l in range(len(slices[j]))] for i in range(len(slices))] for j in range(len(slices))]
def update_gradients_diag(self, dL_dKdiag, X):
self.reset_gradients()
slices = index_to_slices(X[:,self.index_dim])
[[ self.update_gradients_diag_wrapper(self.covariance[i][i]['kern'], dL_dKdiag[slices[i][k]], X[slices[i][k],:]) for k in range(len(slices[i]))] for i in range(len(slices))]
[[ self._update_gradients_diag_wrapper(self.covariance[i][i]['kern'], dL_dKdiag[slices[i][k]], X[slices[i][k],:]) for k in range(len(slices[i]))] for i in range(len(slices))]
def gradients_X(self,dL_dK, X, X2=None):
slices = index_to_slices(X[:,self.index_dim])