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adding a comment to clarify predictive_gradeints (Thanks AT)

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James Hensman 2015-03-30 13:41:25 +01:00
parent 4cf1f5494f
commit 2c7582516d
2 changed files with 5 additions and 1 deletions
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4
GPy/core/gp.py
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@ -241,12 +241,14 @@ class GP(Model):
def predictive_gradients(self, Xnew): def predictive_gradients(self, Xnew):
""" """
Compute the derivatives of the latent function with respect to X* Compute the derivatives of the predicted latent function with respect to X*
Given a set of points at which to predict X* (size [N*,Q]), compute the Given a set of points at which to predict X* (size [N*,Q]), compute the
derivatives of the mean and variance. Resulting arrays are sized: derivatives of the mean and variance. Resulting arrays are sized:
dmu_dX* -- [N*, Q ,D], where D is the number of output in this GP (usually one). dmu_dX* -- [N*, Q ,D], where D is the number of output in this GP (usually one).
Note that this is not the same as computing the mean and variance of the derivative of the function!
dv_dX* -- [N*, Q], (since all outputs have the same variance) dv_dX* -- [N*, Q], (since all outputs have the same variance)
:param X: The points at which to get the predictive gradients :param X: The points at which to get the predictive gradients
:type X: np.ndarray (Xnew x self.input_dim) :type X: np.ndarray (Xnew x self.input_dim)

2
GPy/kern/_src/stationary.py
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@ -296,6 +296,8 @@ class Exponential(Stationary):
return -0.5*self.K_of_r(r) return -0.5*self.K_of_r(r)
class OU(Stationary): class OU(Stationary):
""" """
OU kernel: OU kernel: