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[gradsxx] putting tests in, not complete yet!

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Max Zwiessele 2016-06-07 09:24:38 +01:00
parent 4e833a4f3a
commit a3f458926b
4 changed files with 72 additions and 84 deletions
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11
GPy/core/gp.py
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@ -355,7 +355,7 @@ class GP(Model):
:param X: The points at which to get the predictive gradients.
:type X: np.ndarray (Xnew x self.input_dim)
:param kern: The kernel to compute the jacobian for.
:param boolean full_cov: whether to return the cross-covariance terms between
:param boolean full_cov: whether to return the cross-covariance terms between
the N* Jacobian vectors
:returns: dmu_dX, dv_dX
@ -377,9 +377,10 @@ class GP(Model):
if full_cov:
dK2_dXdX = kern.gradients_XX(one, Xnew)
else:
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,:])
dK2_dXdX = -kern.gradients_XX(one, Xnew).sum(0)
#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,:])
def compute_cov_inner(wi):
if full_cov:
@ -424,7 +425,7 @@ class GP(Model):
Sigma = var_jac.sum(-1)
else:
Sigma = self.output_dim*var_jac
G = 0.
if mean:
G += mumuT