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[grads x]

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This commit is contained in:
Max Zwiessele 2016-06-08 14:28:25 +01:00
parent 0c6e3bc88f
commit b1fd7c9aaf
3 changed files with 12 additions and 12 deletions
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2
GPy/core/gp.py
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@ -377,7 +377,7 @@ class GP(Model):
if full_cov:
dK2_dXdX = kern.gradients_XX(one, Xnew)
else:
dK2_dXdX = kern.gradients_XX(one, Xnew).sum(0)
dK2_dXdX = kern.gradients_XX_diag(one, Xnew)
#dK2_dXdX = np.zeros((Xnew.shape[0], Xnew.shape[1], Xnew.shape[1]))
#for i in range(Xnew.shape[0]):
# dK2_dXdX[i:i+1,:,:] = kern.gradients_XX(one, Xnew[i:i+1,:])

2
GPy/kern/src/integral.py
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@ -42,7 +42,7 @@ class Integral(Kern): #todo do I need to inherit from Stationary
#print "V%0.5f" % self.variances.gradient
#print "L%0.5f" % self.lengthscale.gradient
else: #we're finding dK_xf/Dtheta
print "NEED TO HANDLE TODO!"
print("NEED TO HANDLE TODO!")
#useful little function to help calculate the covariances.
def g(self,z):

2
GPy/kern/src/stationary.py
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@ -273,7 +273,7 @@ class Stationary(Kern):
dL2_dXdX: [NxQxQ]
"""
dL_dK_diag = dL_dK_diag.copy().reshape(-1, 1, 1)
assert dL_dK_diag.size == X.shape[0], "dL_dK_diag has to be given as row [N] or column vector [Nx1]"
assert (dL_dK_diag.size == X.shape[0]) or (dL_dK_diag.size == 1), "dL_dK_diag has to be given as row [N] or column vector [Nx1]"
l4 = np.ones(X.shape[1])*self.lengthscale**2
return dL_dK_diag * (np.eye(X.shape[1]) * -self.dK2_drdr_diag()/(l4))[None, :,:]# np.zeros(X.shape+(X.shape[1],))