if self.gp is None:
// TODO: return from GP prior
return 0.0, 0.0, 0.0
m, s2 = self.gp.predict(np.atleast_2d(x))
return m, s2, np.sqrt(s2)
def eval_mean(self, x):
Returns the GP model mean function at x.
After Change
if self._gp is None:
// TODO: return from GP mean function if given
return np.zeros(len(x), self.input_dim), \
np.ones(len(x), self.input_dim)
// Need to cast as 2d array for gpy