apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-06-11 15:15:15 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

comment linear x linear for testing purposes

Browse source
This commit is contained in:
Max Zwiessele 2013-10-07 07:42:44 +01:00
parent 31c82a74ce
commit 9170067e52
1 changed files with 6 additions and 7 deletions
Download patch file Download diff file Expand all files Collapse all files

13
GPy/kern/kern.py
View file

@ -433,8 +433,8 @@ class kern(Parameterized):
prod = np.multiply(tmp1, tmp2)
crossterms += prod[:, :, None] + prod[:, None, :]
# target += crossterms
return target + crossterms
target += crossterms
return target
def dpsi2_dtheta(self, dL_dpsi2, Z, mu, S):
"""Gradient of the psi2 statistics with respect to the parameters."""
@ -462,8 +462,8 @@ class kern(Parameterized):
# compute the "cross" terms
# TODO: we need input_slices here.
for p1, p2 in itertools.permutations(self.parts, 2):
if p1.name == 'linear' and p2.name == 'linear':
raise NotImplementedError("We don't handle linear/linear cross-terms")
# if p1.name == 'linear' and p2.name == 'linear':
# raise NotImplementedError("We don't handle linear/linear cross-terms")
tmp = np.zeros((mu.shape[0], Z.shape[0]))
p1.psi1(Z, mu, S, tmp)
p2.dpsi1_dZ((tmp[:, None, :] * dL_dpsi2).sum(1), Z, mu, S, target)
@ -477,9 +477,8 @@ class kern(Parameterized):
# compute the "cross" terms
# TODO: we need input_slices here.
for p1, p2 in itertools.permutations(self.parts, 2):
if p1.name == 'linear' and p2.name == 'linear':
raise NotImplementedError("We don't handle linear/linear cross-terms")
# if p1.name == 'linear' and p2.name == 'linear':
# raise NotImplementedError("We don't handle linear/linear cross-terms")
tmp = np.zeros((mu.shape[0], Z.shape[0]))
p1.psi1(Z, mu, S, tmp)
p2.dpsi1_dmuS((tmp[:, None, :] * dL_dpsi2).sum(1) * 2., Z, mu, S, target_mu, target_S)