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predict_raw can take arbitary Ys.

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This commit is contained in:
Arno Solin 2013-11-28 14:03:45 +02:00
parent 9fff81b7ce
commit 5fc80202ab
1 changed files with 6 additions and 2 deletions
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8
GPy/models/state_space.py
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@ -77,11 +77,15 @@ class StateSpace(Model):
#return self.kf_likelihood_g(F,L,Qc,self.sigma2,H,Pinf,dF,dQc,dPinf,self.X,self.Y)
return False
def predict_raw(self, Xnew, filteronly=False):
def predict_raw(self, Xnew, Y=None, filteronly=False):
# Set defaults
if Y is None:
Y = self.Y
# Make a single matrix containing training and testing points
X = np.vstack((self.X, Xnew))
Y = np.vstack((self.Y, np.nan*np.zeros(Xnew.shape)))
Y = np.vstack((Y, np.nan*np.zeros(Xnew.shape)))
# Sort the matrix (save the order)
_, return_index, return_inverse = np.unique(X,True,True)