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very basic GP_regression demo is working

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James Hensman 2012-11-30 09:11:46 +00:00
parent 07d793e309
commit 4b4f1da128
10 changed files with 31 additions and 41 deletions
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12
GPy/kern/kern.py
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@ -166,8 +166,8 @@ class kern(parameterised):
slices1, slices2 = self._process_slices(slices1,slices2)
if X2 is None:
X2 = X
target = np.zeros((X.shape[0],X2.shape[0],self.Nparam))
[p.dK_dtheta(X[s1,i_s],X2[s2,i_s],target[s1,s2,ps]) for p,i_s,ps,s1,s2 in zip(self.parts, self.input_slices, self.param_slices, slices1, slices2)]
target = np.zeros(self.Nparam)
[p.dK_dtheta(partial,X[s1,i_s],X2[s2,i_s],target[ps]) for p,i_s,ps,s1,s2 in zip(self.parts, self.input_slices, self.param_slices, slices1, slices2)]
return target
def dK_dX(self,X,X2=None,slices1=None,slices2=None):
@ -185,11 +185,13 @@ class kern(parameterised):
[p.Kdiag(X[s,i_s],target=target[s]) for p,i_s,s in zip(self.parts,self.input_slices,slices)]
return target
def dKdiag_dtheta(self,X,slices=None):
def dKdiag_dtheta(self,partial,X,slices=None):
assert X.shape[1]==self.D
assert len(partial.shape)==1
assert partial.size==X.shape[0]
slices = self._process_slices(slices,False)
target = np.zeros((X.shape[0],self.Nparam))
[p.dKdiag_dtheta(X[s,i_s],target[s,ps]) for p,i_s,s,ps in zip(self.parts,self.input_slices,slices,self.param_slices)]
target = np.zeros(self.Nparam)
[p.dKdiag_dtheta(partial,X[s,i_s],target[ps]) for p,i_s,s,ps in zip(self.parts,self.input_slices,slices,self.param_slices)]
return target
def dKdiag_dX(self, X, slices=None):