apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-06-02 14:45:15 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

Merge branch 'psi1_transpose_fix' into devel

Browse source
This commit is contained in:
James Hensman 2013-06-06 14:39:12 +01:00
commit 2929c69fce
5 changed files with 24 additions and 25 deletions
Download patch file Download diff file Expand all files Collapse all files

6
GPy/kern/kern.py
View file

@ -360,9 +360,7 @@ class kern(Parameterised):
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)
tmp2 = np.zeros_like(target)
p2.dpsi1_dZ((tmp[:, None, :] * dL_dpsi2).sum(1).T, Z, mu, S, tmp2)
target += tmp2
p2.dpsi1_dZ((tmp[:, None, :] * dL_dpsi2).sum(1), Z, mu, S, target)
return target * 2
@ -378,7 +376,7 @@ class kern(Parameterised):
tmp = np.zeros((mu.shape[0], Z.shape[0]))
p1.psi1(Z, mu, S, tmp)
p2.dpsi1_dmuS((tmp[:, None, :] * dL_dpsi2).sum(1).T * 2., Z, mu, S, target_mu, target_S)
p2.dpsi1_dmuS((tmp[:, None, :] * dL_dpsi2).sum(1) * 2., Z, mu, S, target_mu, target_S)
return target_mu, target_S

4
GPy/kern/linear.py
View file

@ -98,7 +98,7 @@ class linear(Kernpart):
target += tmp.sum()
def dK_dX(self, dL_dK, X, X2, target):
target += (((X2[:, None, :] * self.variances)) * dL_dK[:, :, None]).sum(0)
target += (((X2[None,:, :] * self.variances)) * dL_dK[:, :, None]).sum(1)
def dKdiag_dX(self,dL_dKdiag,X,target):
target += 2.*self.variances*dL_dKdiag[:,None]*X
@ -134,7 +134,7 @@ class linear(Kernpart):
def dpsi1_dmuS(self, dL_dpsi1, Z, mu, S, target_mu, target_S):
"""Do nothing for S, it does not affect psi1"""
self._psi_computations(Z, mu, S)
target_mu += (dL_dpsi1.T[:, :, None] * (Z * self.variances)).sum(1)
target_mu += (dL_dpsi1[:, :, None] * (Z * self.variances)).sum(1)
def dpsi1_dZ(self, dL_dpsi1, Z, mu, S, target):
self.dK_dX(dL_dpsi1.T, Z, mu, target)

6
GPy/kern/rbf.py
View file

@ -178,13 +178,13 @@ class rbf(Kernpart):
self._psi_computations(Z, mu, S)
denominator = (self.lengthscale2 * (self._psi1_denom))
dpsi1_dZ = -self._psi1[:, :, None] * ((self._psi1_dist / denominator))
target += np.sum(dL_dpsi1.T[:, :, None] * dpsi1_dZ, 0)
target += np.sum(dL_dpsi1[:, :, None] * dpsi1_dZ, 0)
def dpsi1_dmuS(self, dL_dpsi1, Z, mu, S, target_mu, target_S):
self._psi_computations(Z, mu, S)
tmp = self._psi1[:, :, None] / self.lengthscale2 / self._psi1_denom
target_mu += np.sum(dL_dpsi1.T[:, :, None] * tmp * self._psi1_dist, 1)
target_S += np.sum(dL_dpsi1.T[:, :, None] * 0.5 * tmp * (self._psi1_dist_sq - 1), 1)
target_mu += np.sum(dL_dpsi1[:, :, None] * tmp * self._psi1_dist, 1)
target_S += np.sum(dL_dpsi1[:, :, None] * 0.5 * tmp * (self._psi1_dist_sq - 1), 1)
def psi2(self, Z, mu, S, target):
self._psi_computations(Z, mu, S)