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kern fix. All tests now pass

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This commit is contained in:
Mike Croucher 2015-03-06 17:07:35 +00:00
parent f627c0b1cd
commit 028fa93d36
2 changed files with 6 additions and 6 deletions
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8
GPy/kern/_src/independent_outputs.py
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@ -94,10 +94,10 @@ class IndependentOutputs(CombinationKernel):
else: else:
slices2 = index_to_slices(X2[:,self.index_dim]) slices2 = index_to_slices(X2[:,self.index_dim])
[[[collate_grads(kern, i, dL_dK[s,s2],X[s],X2[s2]) for s in slices_i] for s2 in slices_j] for i,(kern,slices_i,slices_j) in enumerate(zip(kerns,slices,slices2))] [[[collate_grads(kern, i, dL_dK[s,s2],X[s],X2[s2]) for s in slices_i] for s2 in slices_j] for i,(kern,slices_i,slices_j) in enumerate(zip(kerns,slices,slices2))]
if self.single_kern: if self.single_kern:
kern.gradient = target self.kern.gradient = target
else:[kern.gradient.__setitem__(Ellipsis, target[i]) for i, [kern, _] in enumerate(zip(kerns, slices))] else:
[kern.gradient.__setitem__(Ellipsis, target[i]) for i, [kern, _] in enumerate(zip(kerns, slices))]
def gradients_X(self,dL_dK, X, X2=None): def gradients_X(self,dL_dK, X, X2=None):
target = np.zeros(X.shape) target = np.zeros(X.shape)
@ -144,7 +144,7 @@ class IndependentOutputs(CombinationKernel):
if self.single_kern: target[:] += kern.gradient if self.single_kern: target[:] += kern.gradient
else: target[i][:] += kern.gradient else: target[i][:] += kern.gradient
[[collate_grads(kern, i, dL_dKdiag[s], X[s,:]) for s in slices_i] for i, (kern, slices_i) in enumerate(zip(kerns, slices))] [[collate_grads(kern, i, dL_dKdiag[s], X[s,:]) for s in slices_i] for i, (kern, slices_i) in enumerate(zip(kerns, slices))]
if self.single_kern: kern.gradient = target if self.single_kern: self.kern.gradient = target
else:[kern.gradient.__setitem__(Ellipsis, target[i]) for i, [kern, _] in enumerate(zip(kerns, slices))] else:[kern.gradient.__setitem__(Ellipsis, target[i]) for i, [kern, _] in enumerate(zip(kerns, slices))]
class Hierarchical(CombinationKernel): class Hierarchical(CombinationKernel):

4
GPy/models/mrd.py
View file

@ -329,9 +329,9 @@ class MRD(BayesianGPLVMMiniBatch):
def __getstate__(self): def __getstate__(self):
state = super(MRD, self).__getstate__() state = super(MRD, self).__getstate__()
if state.has_key('kern'): if 'kern' in state:
del state['kern'] del state['kern']
if state.has_key('likelihood'): if 'likelihood' in state:
del state['likelihood'] del state['likelihood']
return state return state