apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-07 02:52:40 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

implement the gradient_X for standard_periodic kernel

Browse source
This commit is contained in:
Zhenwen Dai 2016-03-29 14:45:55 +01:00
parent 1b85b45a7e
commit fd2fc557c6
1 changed files with 11 additions and 8 deletions
Download patch file Download diff file Expand all files Collapse all files

19
GPy/kern/src/standard_periodic.py
View file

@ -155,11 +155,14 @@ class StdPeriodic(Kern):
self.period.gradient = 0
self.lengthscale.gradient = 0
# def gradients_X(self, dL_dK, X, X2=None):
# """derivative of the covariance matrix with respect to X."""
#
# raise NotImplemented("Periodic kernel: dK_dX not implemented")
#
# def gradients_X_diag(self, dL_dKdiag, X):
#
# raise NotImplemented("Periodic kernel: dKdiag_dX not implemented")
def gradients_X(self, dL_dK, X, X2=None):
K = self.K(X, X2)
if X2 is None:
dL_dK = dL_dK+dL_dK.T
X2 = X
dX = -np.pi*((dL_dK*K)[:,:,None]*np.sin(2*np.pi/self.period*(X[:,None,:] - X2[None,:,:]))/(2.*np.square(self.lengthscale)*self.period)).sum(1)
return dX
def gradients_X_diag(self, dL_dKdiag, X):
return np.zeros(X.shape)