From 4f532216ad5fd8aa4e00c197f1fd456834b4ab38 Mon Sep 17 00:00:00 2001 From: Siivola Eero Date: Wed, 24 Jan 2018 13:40:34 +0200 Subject: [PATCH] Changed two function names so that they follow the python naming convention --- GPy/kern/src/multioutput_kern.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/GPy/kern/src/multioutput_kern.py b/GPy/kern/src/multioutput_kern.py index 7c499092..b7feaadb 100644 --- a/GPy/kern/src/multioutput_kern.py +++ b/GPy/kern/src/multioutput_kern.py @@ -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])